Journal of Clinical Monitoring and Computing

Published by Springer Nature
Online ISSN: 1573-2614
Print ISSN: 1387-1307
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Recent publications
  • Mark A BurbridgeMark A Burbridge
  • Ezikiel DacanayEzikiel Dacanay
  • Glenn ShieldsGlenn Shields
  • Richard A JaffeRichard A Jaffe
Purpose: Scalp block is a regional anesthesia technique to reduce the sympathetic response to skull pin application and postoperative pain in patients undergoing craniotomy. These blocks are often performed prior to surgical incision, however, the effect that these blocks have on neuronavigation facial tracing recognition accuracy is unclear because they may distort facial anatomy. Methods: A series of 25 patients undergoing supratentorial craniotomy were administered scalp blocks prior to surgical incision, and their effect on neuronavigation accuracy was assessed. Statistical analysis utilized a two-tailed matched t-test. Results: Bilateral supraorbital and auriculotemporal scalp blocks did not significantly affect the accuracy of facial recognition registration. Conclusion: Scalp block does not interfere with neuronavigation facial recognition accuracy during neurosurgical procedures.
 
The Ultrasound-Guided Cardio-cerebral Resuscitation (UGCeR) protocol
  • Francisco Marcelo TamagnoneFrancisco Marcelo Tamagnone
  • Issac CheongIssac Cheong
  • Ezequiel LunaEzequiel Luna
  • [...]
  • Victoria Otero CastroVictoria Otero Castro
Traumatic brain injury (TBI) is a worldwide public health concern given its significant morbidity and mortality, years of potential life lost, reduced quality of life and elevated healthcare costs. The primary injury occurs at the moment of impact, but secondary injuries might develop as a result of brain hemodynamic abnormalities, hypoxia, and hypotension. The cerebral edema and hemorrhage of the injured tissues causes a decrease in cerebral perfusion pressure (CPP), which leads to higher risk of cerebral ischemia, herniation and death. In this setting, our role as physicians is to minimize damage by the optimization of the CPP and therefore to reduce mortality and improve neurological outcomes. Performing a transcranial doppler ultrasound (TCD) allows to estimate cerebral blood flow velocities and identify states of low flow and high resistance. We propose to include TCD as an initial assessment and further monitoring tool for resuscitation guidance in patients with severe TBI. We present an Ultrasound-Guided Cardio-cerebral Resuscitation (UGCeR) protocol in Patients with Severe TBI.
 
CONSORT flow diagram
Box-and-whisker plots illustrating time to tracheal intubation (in seconds) with a direct laryngoscope, KingVision Channeled blade and KingVision non-channeled blade by MBBS students at times 0 and 1 month. The inner horizontal line within the box represents the median time for tracheal intubation and the cross sign as the mean, and the outer horizontal lines of the box represent the 25th and 75th quartiles. The horizontal lines of the whiskers represent the 95% confidence intervals and circles outside the whisker represent the outliers
Purpose: A videolaryngoscope(VL) with an intubation conduit like KingVision channeled(KVC) blade may provide an added advantage over a non-channeled VL like a KingVision non-channeled (KVNC) blade and direct laryngoscope (DL) for acquiring and retention of intubation skills, especially in novices. Methods: In this prospective two-period randomized crossover trial, one hundred medical students used three laryngoscopes KVC, KVNC and DL for intubation following standardized training with the study devices using a Laerdal Airway Management Trainer. After one month, all participants attempted intubation, in the same manner, using all devices. The duration of intubation, modified Cormack-Lehane (CL) grade, percentage of glottic opening (POGO) score, first-attempt success, number of attempts, ease of intubation and dental trauma was recorded. The retention of intubation skills after 1 month was also assessed on the same parameters. Results: Median intubation times of KVC and DL were comparable and significantly better than KVNC (P < 0.001). The median POGO score was better with both videolaryngoscopes when compared with DL. The ease of intubation (P < 0.0012) and first-attempt success rate (P = 0.001) at the time '0' was significantly better with KVC compared to KVNC and DL. KVC fared better with respect to these intubation parameters during intubation after one month as well. Conclusion: KVC performed better in terms of time to intubation, success rate and ease of procedure as compared to KVNC and DL, both for acquisition and retention of skill. Hence, we advocate that KVC should be the preferred device over KVNC and DL for teaching intubation skills to novices.
 
A) Position of the phased array transducer at the level of the left supraclavicular fossa to measure carotid flow; B) Color Doppler mode of the left common carotid artery that is perfectly aligned with the dotted line representing the incidence of the pulsed doppler signal
A) Measurement of 3 VTI of CSD consecutively. B) Measurement of 3 VTI of CS (up to the dichrote wave) consecutively
Distribution density of LVOT VTI, CS VTI and CSD VTI.
Bland–Altman plot, with regression line for the difference between methods and 95% CI.
Correlation, linear model (red line) and bisector (blue line) between CSD VTI and LVOT VTI (left), and CS VTI and LVOT VTI (right)
Transthoracic echocardiography (TTE) is a fundamental tool for hemodynamic monitoring in critical patients. It allows evaluating the left ventricle’s stroke volume based on the measurement of the velocity-time integral (VTI) of the left ventricle outflow tract (LVOT). However, in the intensive care unit obtaining adequate echocardiographic views may present a challenge. We propose to measure, as a surrogate of the stroke volume, the carotid flow with a novel technique. This is an observational, prospective, and simple blind study, conducted in the intensive care unit of Sanatorio de los Arcos and Hospital Aleman, in Buenos Aires, Argentina. We measured the carotid systodiastolic flow (CSD) VTI and the carotid systolic flow (CS) VTI at the level of the left supraclavicular fossa and we compared it with the LVOT VTI obtained by TTE. We evaluated 43 subjects. Spearman’s correlation coefficient between LVOT VTI and CS VTI was 0.81 (95% CI 0.67–0.89) and between LVOT VTI and CSD VTI was 0.89 (95% CI 0.81–0.94). The Bland–Altman method analysis of the 5-chamber apical window LVOT VTI compared to the CSD VTI showed a bias of − 0.2 (95% CI − 0.82 to 0.43), with a concordance interval between − 4.2 (95% CI − 5.2 to − 3.1) and 3.8 cm (95% CI 2.7 to 4.9). The percentage error was 37.9%. Almost 100% of the values fell within the concordance limits, and no trend was observed in bias across the spectrum of mean variables. Although the CSD VTI could not be interchangeable with the LVOT VTI, it could be considered as its surrogate.
 
Flow chart of the inclusion and exclusion
The reliability of stroke volume variation (SVV) and pulse pressure variation (PPV) in predicting fluid responsiveness during laparoscopic surgery remains unclear. We conducted the present systematic review to summarize the current evidence. We reviewed studies that investigated the reliability of SVV and PPV in laparoscopic surgery. Seven studies were included in the final analysis. Two studies demonstrated that the area under the receiver operating characteristic curve (AUROC) for SVV was less than 0.8, and five studies reported that the AUROC was > 0.8. The pooled AUROC for SVV and PPV was more than 0.8 with high heterogeneities between the included studies. Most individual studies have suggested that SVV and PPV are sufficiently reliable for predicting fluid responsiveness during laparoscopic surgery. However, the limited number of patients, varied apparatus used to define fluid responsiveness, diverse definitions of fluid responsiveness, and different fluids used to perform fluid challenges in the included studies render firm conclusions about SVV’s and PPV’s reliability impossible.
 
Linear correlation between mean intracranial pressure (mICP) values and P2/P1 ratio
P2/P1 values according to mean intracranial pressure (mICP) values, in all patients (n = 72, left side) or after exclusion of those with decompressive craniectomy (n = 51, right side)
Distribution of mean intracranial pressure (mICP), P2/P1 ratio and brain compliance index (BCI), according to early outcomes SB spontaneous breathing, MV mechanical ventilation, ED early death)
Tridimensional graphical depiction of the interaction between mean intracranial pressure (mICP), P2/P1 ratio and short-term outcomes (STO). Higher ICP levels combined with higher P2/P1 ratio results were observed for patients with poorer STO (red zone), whereas even borderline ICP levels, if associated with P2/P1 ratio under 1.2 were compatible often with favorable STO (green zone). Noteworthy, borderline mICP values combined with elevated P2/P1 ratio were frequently found for patients that remained under mechanical ventilation (MV, yellow-orange zone). STO 1- spontaneous breathing, 2- MV and 3- death. Electronic color enhancement is progressive according to the number of events observed for each particular value. Color is from green to red from better to poorer STO
Analysis of intracranial pressure waveforms (ICPW) provides information on intracranial compliance. We aimed to assess the correlation between noninvasive ICPW (NICPW) and invasively measured intracranial pressure (ICP) and to assess the NICPW prognostic value in this population. In this cohort, acute brain-injured (ABI) patients were included within 5 days from admission in six Intensive Care Units. Mean ICP (mICP) values and the P2/P1 ratio derived from NICPW were analyzed and correlated with outcome, which was defined as: (a) early death (ED); survivors on spontaneous breathing (SB) or survivors on mechanical ventilation (MV) at 7 days from inclusion. Intracranial hypertension (IHT) was defined by ICP > 20 mmHg. A total of 72 patients were included (mean age 39, 68% TBI). mICP and P2/P1 values were significantly correlated (r = 0.49, p < 0.001). P2/P1 ratio was significantly higher in patients with IHT and had an area under the receiving operator curve (AUROC) to predict IHT of 0.88 (95% CI 0.78–0.98). mICP and P2/P1 ratio was also significantly higher for ED group (n = 10) than the other groups. The AUROC of P2/P1 to predict ED was 0.71 [95% CI 0.53–0.87], and the threshold P2/P1 > 1.2 showed a sensitivity of 60% [95% CI 31–83%] and a specificity of 69% [95% CI 57–79%]. Similar results were observed when decompressive craniectomy patients were excluded. In this study, P2/P1 derived from noninvasive ICPW assessment was well correlated with IHT. This information seems to be as associated with ABI patients outcomes as ICP. Trial registration: NCT03144219, Registered 01 May 2017 Retrospectively registered, https://www.clinicaltrials.gov/ct2/show/NCT03144219.
 
Massey Scale skin color versus number of subjects for self-identified White (blue tint boxes) and Black (salmon tint boxes) subjects
Scatter plot (SpO2 versus SaO2) along with performance metrics for White subjects (Fig. 2a) vs. Black subjects (Fig. 2b)
Box plots showing accuracy comparison for Black (salmon tint) and White (blue tint) ethnic groups binned by 1% saturation bins, from 89–96%. Figure 3a reproduced (with permission) from the Sjoding et al. study [12], and Fig. 3b similar box-plot configuration using Masimo SET® data pairs from the current laboratory study. Shaded area of SaO2%
Recent publications have suggested that pulse oximeters exhibit reduced accuracy in dark-skinned patients during periods of hypoxemia. Masimo SET® (Signal Extraction Technology®) has been designed, calibrated, and validated using nearly equal numbers of dark and light skinned subjects, with the goal of eliminating differences between pulse oximetry saturation (SpO2) and arterial oxygen saturation (SaO2) values due to skin pigmentation. The accuracy concerns reported in dark-skinned patients led us to perform a retrospective analysis of healthy Black and White volunteers. Seventy-five subjects who self-identified as being racially Black or White underwent a desaturation protocol where SaO2 values were decreased from 100 to 70%, while simultaneous SpO2 values were recorded using Masimo RD SET® sensors. Statistical bias (mean difference) and precision (standard deviation of difference) were − 0.20 ± 1.40% for Black and − 0.05 ± 1.35% for White subjects. Plots of SpO2 versus SaO2 show no significant visible differences between races throughout the saturation range from 70 to 100%. Box plots grouped in 1% saturation bins, from 89–96%, and plotted against concomitant SaO2 values, show that occult hypoxemia (SaO2 < 88% when SpO2 = 92–96%) occurred in only 0.2% of White subject data pairs, but not in any Black subjects. There were no clinically significant differences in bias (mean difference of SpO2-SaO2) found between healthy Black and White subjects. Occult hypoxemia was rare and did not occur in Black subjects. Masimo RD SET® can be used with equal assurance in people with dark or light skin. These laboratory results were obtained in well-controlled experimental conditions in healthy volunteers—not reflecting actual clinical conditions/patients.
 
The sublingual mucosa is a commonly used intraoral location for identifying microcirculatory alterations using handheld vital microscopes (HVMs). The anatomic description of the sublingual cave and its related training have not been adequately introduced. The aim of this study was to introduce anatomy guided sublingual microcirculatory assessment. Measurements were acquired from the floor of the mouth using incident dark-field (IDF) imaging before (T0) and after (T1) sublingual cave anatomy instructed training. Instructions consists of examining a specific region of interested identified through observable anatomical structures adjacent and bilaterally to the lingual frenulum which is next to the sublingual papilla. The anatomical location called the sublingual triangle, was identified as stationed between the lingual frenulum, the sublingual fold and ventrally to the tongue. Small, large, and total vessel density datasets (SVD, LVD and TVD respectively) obtained by non-instructed and instructed measurements (NIN (T0) and IM (T1) respectively) were compared. Microvascular structures were analyzed, and the presence of salivary duct-related microcirculation was identified. A total of 72 video clips were used for analysis in which TVD, but not LVD and SVD, was higher in IM compared to NIM (NIM vs. IM, 25 ± 2 vs. 27 ± 3 mm/mm ² (p = 0.044), LVD NIM vs. IM: 7 ± 1 vs. 8 ± 1mm/mm ² (p = 0.092), SVD NIM vs. IM: 18 ± 2 vs. 20 ± 3 mm/mm ² (p = 0.103)). IM resulted in microcirculatory assessments which included morphological properties such as capillaries, venules and arterioles, without salivary duct-associated microcirculation. The sublingual triangle identified in this study showed consistent network-based microcirculation, without interference from microcirculation associated with specialized anatomic structures. These findings suggest that the sublingual triangle, an anatomy guided location, yielded sublingual based measurements that conforms with international guidelines. IM showed higher TVD values, and future studies are needed with larger sample sizes to prove differences in microcirculatory parameters.
 
Choropleth map of absolute survey answers
Perception of reliability Vs. perception of price of a quantitative neuromuscular monitor
Perception of reliability of a quantitative neuromuscular monitor Vs. training status of the responding anesthesiologist
Purpose: Neuromuscular blocking agents (NMBAs) are routinely administered to patients in a multiplicity of anesthetic settings. Absence of postoperative residual neuromuscular block is widely considered an anesthetic patient safety mandate. Despite the increasing availability of a wider range of commercial quantitative neuromuscular monitors, the availability and use of neuromuscular monitoring devices is deemed to be suboptimal even in countries with above-average health system ratings. The present study aims to more precisely characterize the perceived availability, cost sensitivity and usability of neuromuscular monitoring devices within European anesthesia departments. Methods: A pre-registered internet-based survey assessing the availability, cost sensitivity and usability of neuromuscular monitoring devices was distributed as e-mail newsletter by the European Society of Anaesthesiology and Intensive Care (ESAIC) to all of its active full members. The survey was available online for a total of 120 days. Results: Having targeted a total of 7472 ESAIC members, the survey was completed by a total of 692 anesthesiologists (9.3%) distributed across 37 different European countries. Quantitative monitors were reported to be proportionally more available than qualitative ones (87.6% vs. 62.6%, respectively), as well as in greater monitor-per-operating room ratios. Most anesthesiologists (60.5%) expressed moderate confidence in quantitative monitors, with artifactual recordings and inaccurate measurements being the most frequently encountered issues (25.9%). The commercial pricing of quantitative devices was considered more representative of a device’s true value, when compared to qualitative instruments (average cost of €4.500 and €1.000 per device, respectively). Conclusion: The availability of quantitative NMM in European operating theaters has increased in comparison with that reported in previous decades, potentially indicating increasing monitoring rates. European anesthesiologists express moderate confidence in quantitative neuromuscular monitors, along with a sentiment of adequate pricing when compared to their qualitative counterparts. Trust in quantitative monitors is marked by caution and awareness for artifactual recordings, with a consequent expectation that developments focusing on accuracy, reliability and ergonomics of neuromuscular monitors be prioritized.
 
General block diagram of the proposed system
Schematic diagram of the proposed DRRMNVS
The prototype of the proposed DRRMNVS
Sample pictures showing the measurement output on Blynk app (A) and ThingSpeak (B). ThingSpeak’s graphical output displays the continuous measurement result, allowing caregivers to see the past trend without missing data
Bland-Altman Plot, showing the average values of simultaneous (A) Oxygen Saturation, (B) Temperature, (C) Pulse Rate, and (D) Respiration Rate as measured with DRRMNVS and Standard devices in X-axis versus their difference in Y-axis. The green solid reference line represents the mean error (bias), and the dashed reference lines are the upper and the lower limits of agreement between DRRMNVS and Standard devices
Background Realtime and remote monitoring of neonatal vital signs is a crucial part of providing appropriate care in neonatal intensive care units (NICU) to reduce mortality and morbidity of newborns. In this study, a new approach, a device for remote and real-time monitoring of neonatal vital signs (DRRMNVS) in the neonatal intensive care unit using the internet of things (IoT), was proposed. The system integrates four vital signs: oxygen saturation, pulse rate, body temperature and respiration rate for continuous monitoring using the Blynk app and ThingSpeak IoT platforms. Methods The Wemos D1 mini, a Wi-Fi microcontroller, was used to acquire the four biological biomarkers from sensors, process them and display the result on an OLED display for point of care monitoring and on the Blynk app and ThingSpeak for remote and continuous monitoring of vital signs. The Bland-Altman test was employed to test the agreement of DRRMNVS measurement with reference standards by taking measurements from ten healthy adults. Results The prototype of the proposed device was successfully developed and tested. Bias [limits of agreement] were: Oxygen saturation (SpO2): -0.1 [− 1.546 to + 1.346] %; pulse rate: -0.3 [− 2.159 to + 1.559] bpm; respiratory rate: -0.7 [− 0.247 to + 1.647] breaths/min; temperature: 0.21 [+ 0.015˚C to + 0.405˚C] ˚C. The proof-of-concept prototype was developed for $33.19. Conclusion The developed DRRMNVS device was cheap and had acceptable measurement accuracy of vital signs in a controlled environment. The system has the potential to advance healthcare service delivery for neonates with further development from this proof-of-concept level.
 
Consort diagram
ROC showing the.diagnostic ability of ONSD, LF/HF ratio, CT scoring and combination of ONSD and LF/HF ratio to predict intraoperative brain relaxation. A ONSD ROC, B LF/HF ROC, C CT scoring ROC, D Combination of ONSD and LF/HF ratio ROC. ONSD optic nerve sheath diameter, LF low frequency, HF high frequency, CT computed tomography
Haemodynamic changes with induction and intubation. HR heart rate (/min), MAP mean arterial pressure (mmHg), SBP systolic blood pressure (mmHg), BRS brain relaxation score
Brain relaxation is an important requirement in intracranial neurosurgical procedures and optimal brain relaxation improves the operating conditions. Optic nerve sheath diameter (ONSD) is a non-invasive bedside surrogate marker of intracranial pressure (ICP) status. Elevated ICP is often associated with marked autonomic dysfunction. There is no standard measure to predict intraoperative brain condition non-invasively, considering both anatomical displacement and physiological effects due to raised ICP and brain oedema. This study was aimed to determine the usefulness of heart rate variability (HRV) parameters and ONSD preoperatively in predicting intraoperative brain relaxation in patients with supratentorial tumors undergoing surgery.This prospective observational study was conducted in a tertiary care centre. 58 patients with supratentorial brain tumors undergoing elective surgery were studied. Preoperative clinical presentation, computed tomography (CT) findings, ONSD and HRV parameters were assessed in determining intraoperative brain condition. Intraoperative hemodynamic parameters and brain relaxation score after craniotomy were studied. There was significant difference in CT grade, ONSD and HRV parameters in patients between lax and tight brain. A receiver operating curve was constructed to determine the cut off to predict intraoperative brain bulge. A CT grade more than 2, ONSD of greater than 0.63 cms and ratio of low frequency to high ratio (LF/HF) of more than 1.8 were good predictors of brain bulge. The changes in ONSD and HRV parameters, with the CT findings can be used as surrogate markers of increased ICP to help predict intraoperative brain condition.
 
Box and whisker (5–95 percentile) plot of baseline values and changes in HR, MAP, SV, SVR, CVP and HPI over the different experimental stages. *P < 0.05, **P < 0.01 compared to baseline values. + represents mean and solid line median
Box and whisker (5–95 percentile) plot of baseline values and changes in PA mean, SvO2 and SVV over the different experimental stages. *P < 0.05, **P < 0.01 compared to baseline values. + represents mean and solid line median
Correlation of LVEF, dP/dt and LVSWI
Percentage change from baseline values for LVEF, dP/dt and LVSWI over each experimental stage. *P < 0.05, **P < 0.01, ⋆⋆⋆P < 0.001 compared to baseline values
To investigate if the Hypotension Prediction Index was an early indicator of haemodynamic instability in a negative inotropy porcine model, and to assess the correlation of commonly measured indicators of left ventricular systolic function. Eight anaesthetised pigs were volume resuscitated and then underwent an incremental infusion of esmolol hydrochloride (0-3000 mg/hr), following which it was then reduced in a stepwise manner. Full haemodynamic measurements were taken at each stage and measurements of left ventricular systolic function including left ventricular stroke work index, ejection fraction and peripheral dP/dT were obtained. At an infusion rate of 500 mg/hr of esmolol there were no significant changes in any measured variables. At 1000 mg/hr MAP was on average 11 mmHg lower (95% CI 1 to 11 mmHg, p = 0.027) with a mean of 78 mmHg, HPI increased by 33 units (95% CI 4 to 62, p = 0.026) with a mean value of 63. No other parameters showed significant change from baseline values. Subsequent increases in esmolol showed changes in all parameters except SVV, SVR and PA mean. Correlation between dP/dt and LVSWI was 0.85 (95% CI 0.77 to 0.90, p < 0.001), between LVEF and dP/dt 0.39 (95% CI 0.18 to 0.57, p < 0.001), and between LSWI and LVEF 0.41 (95% CI 0.20 to 0.59, p < 0.001). In this model haemodynamic instability induced by negative inotropy was detected by the HPI algorithm prior to any clinically significant change in commonly measured variables. In addition, the peripheral measure of left ventricular contractility dP/dt correlates well with more established measurements of LV systolic function.
 
Sketch of regions of interest (ROI) in an EIT image. UR: Upper right lung; UL: Upper left lung; LR: Lower right lung; LL: Lower left lung; Ventilation distribution in ventral regions = ROI1% + ROI2%; Ventilation distribution in dorsal regions = ROI3% +ROI4%.
ROC curves of HVVI for ventilated patients. AUC, area under the ROC curve; HVVI, Horizonal ventral ventilation index; ROC, receiver operating characteristic
Early diagnostic process and real-time monitor of PTX in mechanically ventilated ICU patients using EIT
MV = Mechanical ventilation
Purpose This study aimed to evaluate the routine use of electrical impedance tomography (EIT) to diagnose pneumothorax (PTX) in mechanically ventilated patients in the intensive care unit (ICU). Methods A retrospective cohort study was conducted including mechanically ventilated supine patients who received EIT examinations. The EIT-based tidal variation was divided into ventral and dorsal regions of interest (ROIs): upper right (UR, ROI1), upper left (UL, ROI2) lower right (LR, ROI3), and lower left (LL, ROI4), and the ventilation defect score (DS) was calculated in each quadrant. Furthermore, horizontal ventral ventilation index (HVVI) was defined as ROI1% / ROI2% in the two ventral quadrants if ROI1% > ROI2%, otherwise HVVI = ROI2% / ROI1%. Results A total of 203 patients were included, 25 of them with confirmed PTX. In the PTX patients, preceding cardiac surgery was the most common cause of PTX. Compared with the patients without PTX, the PTX patients had a higher DS in the ventral quadrants [median and interquartile range (IQR): 1.00 (0.00, 2.00) vs. 0.00 (0.00, 0.00), P < 0.001] respectively, but similar in the dorsal quadrants [median and IQR: 1.00 (0.00, 1.00) vs. 0.00 (0.00, 1.00), P = 0.722]. Moreover, a higher HVVI was found in the PTX group [median and IQR: 2.51 (1.58, 3.52) vs. 1.36 (1.15, 1.77), P < 0.001]. The area under the receiver operating characteristic curve of the HVVI to differentiate PTX from non-PTX was 0.88, with a sensitivity of 70% and a specificity of 90% when the cut-off value was 2.57. Conclusion The ventilation defect in the ventral regions and a high HVVI on EIT were observed in mechanically ventilated patients with PTX, which should trigger further diagnostics to confirm it.
 
Distribution of hydration status by Bioimpedance Spectroscopy Analysis in the early perioperative period: dehydration (RFO <  − 10%), normohydration (− 10% ≤ RFO ≤  + 15%), overhydration RFO > 15%. RFO relative fluid overload
Relationship between fluid balance, changes in weight, and changes in absolute fluid overload on postoperative day five in acute high-risk abdominal surgery: A Absolute fluid overload and cumulative fluid balance; B Absolute fluid overload and changes in weight; C Cumulative fluid balance and changes in weight
Associations between pre- to 6 h postoperative changes in volume status and net fluid balance in patients undergoing acute high-risk abdominal surgery. Regression equations are as follows: A Change in intra cellular volume; B Change in extra cellular volume; C Change in total body volume; D Change in intra cellular volume and extra cellular volume. Pearson correlation test. R² = coefficient of determination
Association between cumulative fluid balance and Bioimpedance Spectroscopy Analysis measured overhydration, *statistically significant (p < .01): Daily fluid balance was defined as the difference between total input (all fluids, nutrition, blood products, medications) and total output (losses through urinary, gastrointestinal, or other drainage tubes), not including insensible losses). Cumulated fluid balance was calculated as the algebraic sum of daily fluid balance during the observational period; overhydration: Relative fluid overload > 15%
Objective assessment of fluid status in critical surgical care may help optimize perioperative fluid administration and prevent postoperative fluid retention. We evaluated the feasibility of hydration status and fluid distribution assessment by Bioimpedance spectroscopy Analysis (BIA) in patients undergoing acute high-risk abdominal (AHA) surgery. This observational study included 73 patients undergoing AHA surgery. During the observational period (0–120 h), we registered BIA calculated absolute fluid overload (AFO) and relative fluid overload (RFO), defined as AFO/extracellular water ratio, as well as cumulative fluid balance and weight. Based on RFO values, hydration status was classified into three categories: dehydrated (RFO < − 10%), normohydrated (− 10% ≤ RFO ≤ + 15%), overhydrated RFO > 15%. We performed a total of 365 BIA measurements. Preoperative overhydration was found in 16% of patients, increasing to 66% by postoperative day five. The changes in BIA measured AFO correlated with the cumulative fluid balance (r2 = 0.44, p < .001), and change in weight (r2 = 0.55, p < .0001). Perioperative overhydration measured with BIA was associated with worse outcome compared to patients with normo- or dehydration. We have demonstrated the feasibility of obtaining perioperative bedside BIA measurements in patients undergoing AHA surgery. BIA measurements correlated with fluid balance, weight changes, and postoperative clinical complications. BIA-assessed fluid status might add helpful information to guide fluid management in patients undergoing AHA surgery.
 
Mean traintime over all channels in patients with and without a separate intermedius nerve
Koos tumor size in relation to facial nerve outcome. Postoperative and follow-up are pooled
Concordance of clinical HB grades and neural network estimates of the network with inputs yielding the best results (Traintime without clusters, Koos, preoperative HB-grade). Coloring and percentages in each (independent) column give the portion of all randomized results with a specific HB grade. For example, 75.4% of neural estimates in cases with postoperative or follow-up HB 1 also suggest HB 1, while 19.2% suggest HB 2 and thus overestimate facial nerve palsy.
Purpose Facial nerve damage in vestibular schwannoma surgery is associated with A-train patterns in free-running EMG, correlating with the degree of postoperative facial palsy. However, anatomy, preoperative functional status, tumor size and occurrence of A-trains clusters, i.e., sudden A-trains in most channels may further contribute. In the presented study, we examine neural networks to estimate postoperative facial function based on such features. Methods Data from 200 consecutive patients were used to train neural feed-forward networks (NN). Estimated and clinical postoperative House and Brackmann (HB) grades were compared. Different input sets were evaluated. Results Networks based on traintime, preoperative HB grade and tumor size achieved good estimation of postoperative HB grades (chi² = 54.8), compared to using tumor size or mean traintime alone (chi² = 30.6 and 31.9). Separate intermediate nerve or detection of A-train clusters did not improve performance. Removal of A-train cluster traintime improved results (chi² = 54.8 vs. 51.3) in patients without separate intermediate nerve. Conclusion NN based on preoperative HB, traintime and tumor size provide good estimations of postoperative HB. The method is amenable to real-time implementation and supports integration of information from different sources. NN could enable multimodal facial nerve monitoring and improve postoperative outcomes.
 
Schematic illustration of plantar regional oxygen saturation
Surgical draping for saphenectomy in patients with plantar rSO2 monitor
The surgical draping is performed in the following order. (1) Both legs are elevated and placed on the leg rest. (2) Surgical skin is prepared for entire lower extremity except for both feet. (3) Surgical drape is placed under both legs. Additional sterile drape is placed where both feet will be placed. (4) Both legs are placed on the operating table by holding both feet by surgeon with surgical gowns and sterile gloves. (5) Both feet are wrapped with the additional sterile drape
Flow diagram of the study. rSO2, regional oxygen saturation
Plantar regional oxygen saturation (rSO2) thresholds for acute kidney injury (AKI) after cardiac surgery
Univariable and multivariable relationship between absolute and relative lowest plantar rSO2 with AKI.
(a) and (b): Probability of AKI were estimated from univariable moving-window with the width of 10% data
(c) and (d): Probability of AKI were estimated from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for variables consisting of Cleveland clinic score (see the Methods section)
Cerebral regional oxygen saturation (rSO2) and lowest mean arterial blood pressure (MAP) thresholds for acute kidney injury (AKI) after cardiac surgery
Univariable and multivariable relationship between absolute and relative lowest plantar rSO2 with AKI.
(a), (b) and (c): Probability of AKI were estimated from univariable moving-window with the width of 10% data
(d), (e) and (f): Probability of AKI were estimated from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for variables consisting of Cleveland clinic score (see the Methods section)
Acute kidney injury (AKI) is one of the most common complications after cardiac surgery, associated with increased mortality and morbidity. Near-infrared spectroscopy (NIRS) continuously measures regional oxygen saturation(rSO2) in real-time. This exploratory retrospective study aimed to investigate the association between intraoperative plantar rSO2 and postoperative AKI in cardiac surgery patients. Between August 2019 and March 2021, 394 patients were included. Plantar and cerebral rSO2 were monitored using NIRS intraoperatively. The primary outcome was AKI within 7 postoperative days. The nonlinear association between plantar rSO2, cerebral rSO2, and mean arterial blood pressure (MBP) and AKI was assessed, and plantar rSO2<45% was related to an increased risk of AKI. Multivariable logistic regression analyses revealed that longer duration and higher area under the curve below plantar rSO2<45% and MBP<65 mmHg were more likely to be associated with increased odds of AKI. In additional multivariable regression analyses, association between plantar rSO2<45% and AKI was still maintained after adjusting the duration or AUC of MBP<65 mmHg as a covariate. Cerebral rSO2 levels were not associated with AKI. Independent of MAP, intraoperative plantar rSO2 was associated with AKI after cardiac surgery. However, intraoperative cerebral rSO2 was not associated with AKI. Intraoperative plantar rSO2 monitoring may be helpful in preventing AKI.
 
Near infrared spectroscopy (NIRS) technology is frequently used to measure regional cerebral tissue oxygen saturation (rSO2). The measurement of rSO2 has diverse range of clinical application for its easy bed-side applicability, continuous monitoring, interpretation and valuable information on cerebral oxygenation. However, it also has few technical limitations; absorption by skull tissues, presence of hematomas, and other pigments such as melanin, bilirubin can affect the rSO2 measurements and thus interfere with the accuracy of monitoring. We report a case wherein low values of frontal rSO2 normalized after evacuation of bilateral fronto-temporo-parietal (FTP) chronic subdural hematoma (CSDH) in a patient with bilateral internal carotid artery (ICA) stenosis.
 
Flow diagram of cases. BIS bispectral index
Histograms of Fisher transformations of Spearman’s rank correlation coefficients between the BIS value and αF\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{F}$$\end{document}, αO\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{O}$$\end{document}, and αF-αO\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{F}-{\alpha }_{O}$$\end{document}, denoted by Z(ρF)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Z({\rho }_{F})$$\end{document}, Z(ρO)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Z({\rho }_{O})$$\end{document}, and Z(ρFO)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Z({\rho }_{FO})$$\end{document}, respectively. αF\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{F}$$\end{document} frontal alpha power, αO\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{O}$$\end{document} occipital alpha power, BIS bispectral index
Estimation of the median values of αF\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{F}$$\end{document}, αO\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{O}$$\end{document}, and αF-αO\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{F}-{\alpha }_{O}$$\end{document} along with their derivatives with respect to the BIS value ΔαF/ΔBIS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta {\alpha }_{F}/\Delta \text{BIS}$$\end{document}, ΔαO/ΔBIS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta {\alpha }_{O}/\Delta \text{BIS}$$\end{document}, and Δ(αF-αO)/ΔBIS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta {(\alpha }_{F}-{\alpha }_{O})/\Delta \text{BIS}$$\end{document} at each BIS value. The filled area indicates the 95% CI. αF\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{F}$$\end{document} frontal alpha power, αO\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{O}$$\end{document} occipital alpha power, BIS bispectral index, CI confidence interval
Estimation of the median values of αF\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{F}$$\end{document}, αO\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{O}$$\end{document}, and αF-αO\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{F}-{\alpha }_{O}$$\end{document} along with their derivatives with respect to the BIS value ΔαF/ΔBIS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta {\alpha }_{F}/\Delta \text{BIS}$$\end{document}, ΔαO/ΔBIS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta {\alpha }_{O}/\Delta \text{BIS}$$\end{document}, and Δ(αF-αO)/ΔBIS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta {(\alpha }_{F}-{\alpha }_{O})/\Delta \text{BIS}$$\end{document} at each BIS value for the older group (red) and younger group (blue). The filled area indicates the 95% CI. αF\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{F}$$\end{document} frontal alpha power, αO\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{O}$$\end{document} occipital alpha power, BIS bispectral index, CI confidence interval
Estimation of the median values of αF\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{F}$$\end{document}, αO\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{O}$$\end{document}, and αF-αO\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{F}-{\alpha }_{O}$$\end{document} along with their derivatives with respect to the BIS value ΔαF/ΔBIS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta {\alpha }_{F}/\Delta \text{BIS}$$\end{document}, ΔαO/ΔBIS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta {\alpha }_{O}/\Delta \text{BIS}$$\end{document}, and Δ(αF-αO)/ΔBIS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta {(\alpha }_{F}-{\alpha }_{O})/\Delta \text{BIS}$$\end{document} at each BIS value for the inhaled anesthetics group (red) and propofol group (blue). The epochs after propofol bolus administration in the inhaled anesthetics group were excluded for the calculation. The filled area indicates the 95% CI. αF\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{F}$$\end{document} frontal alpha power, αO\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{O}$$\end{document} occipital alpha power, BIS bispectral index, CI confidence interval
A typical electroencephalogram (EEG) change induced by general anesthesia is anteriorization-disappearance of occipital alpha oscillations followed by the development of frontal alpha oscillations. Investigating the quantitative relationship between such a specific EEG change and the level of anesthesia has academic and clinical importance. We quantified the degree of anteriorization and investigated its detailed relationship with the level of anesthesia. We acquired 21-electrode EEG data and bispectral index (BIS) values of 50 patients undergoing surgery from before anesthesia induction until after patient arousal. For each epoch of a 10.24-s window with 1-s offsets, we calculated frontal alpha power [Formula: see text], occipital alpha power [Formula: see text], and their difference [Formula: see text] to quantify anteriorization. We calculated Spearman's rank correlation coefficients between these values and the BIS value. We used locally weighted regression to estimate [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] at each BIS value. Thirty-six patients (26 females and 10 males aged 24-85 years) were analyzed. The 95% confidence intervals for the mean of Fisher transformations of Spearman's rank correlation coefficients between [Formula: see text], [Formula: see text], and [Formula: see text] and BIS value were [- 0.68, - 0.26], [0.02, 0.62], and [- 1.11, - 0.91], respectively. The change in [Formula: see text] and [Formula: see text] with BIS value showed different patterns by the type of anesthetic agent, whereas that in [Formula: see text] was more consistent with smaller individual variance. Anteriorization, quantified by the difference between frontal and occipital alpha powers, continuously developed in conjunction with general anesthesia. Quantifying anteriorization may provide an objective indicator of the level of anesthesia.
 
SaCoVLM™ disposable video laryngeal mask
SaCoVLM™ Glottic exposure grades. Grade 1: visualization of the lateral part of the right aryepiglottic fold and part of the laryngeal inlet, and the ventilation was good; Grade 2: visualization of the bilateral aryepiglottic fold and part of laryngeal inlet, and the ventilation was good; Grade 3: visualization of all laryngeal inlet and posterior glottis; Grade 4: visualization of the whole glottis
To compare the potential influences of blind insertion and up-down optimized glottic exposure manoeuvre on the oropharyngeal leak pressure (OPLP) in using SaCoVLM™ video laryngeal mask (VLM) among patients undergoing general anesthesia. A randomized self-control study controlled was conducted to investigate the effect of two insertion techniques on OPLP. A total of 60 patients (male or female, 18–78 years, BMI 18.0–30.0 kg m⁻² and ASA I–II) receiving selective surgery under general anesthesia were randomly recruited. After induction of anesthesia, the SaCoVLM™ was inserted by blind insertion manoeuvre. The glottic exposure grading(V1) of the SaCoVLM™ visual laryngeal mask and the OPLP(P1) were recorded. And the glottic exposure grading(V2) and OPLP(P2) of SaCoVLM™ were recorded again when the glottic exposure grading was optimal. The glottis exposure grading and OPLP were compared before and after different insertion manoeuver. The glottic exposure grading (V2) obtained by using up-down optimized glottic exposure manoeuvre was better than that obtained by using blind insertion manoeuvre (V1)(P < 0.001). The OPLP was significantly lower in the blind insertion manoeuvre (P1) than in the up-down optimized glottic exposure manoeuvre (P2) (32.4 ± 5.0 cmH2O vs. 36.3 ± 5.2 cmH2O, P < 0.001). In using SaCoVLM™, higher OPLP and better glottic exposure grading were achieved through up-down optimized glottic exposure manoeuvre, protecting the airway while real-time monitoring of conditions around the glottis, which significantly improves airway safety. Our results suggests that up-down optimized glottic exposure manoeuver may be a useful technique for SaCoVLM™ insertion. Trial registration: ChiCTR, ChiCTR2000028802. Registered 4 January 2020, http://www.chictr.org.cn/ChiCTR2000028802.
 
Effects of 3 different extracorporeal blood flows on the intrathoracic blood volume index (A) and the extravascular lung water index (B) measured with transpulmonary thermodilution. Boxes show the interquartile range (25 to 75%), whiskers encompass the range (minimum–maximum), and horizontal lines represent the median of 20 patients with severe ARDS managed with V-V ECMO. Brackets denote statistically significant differences between different ECBF. p values are shown above the brackets
Effects of 3 different extracorporeal blood flows on mean transit time (A) and downslope time (B) measured with transpulmonary thermodilution. Boxes show the interquartile range (25% to 75%), whiskers encompass the range (minimum–maximum), and horizontal lines represent the median of 20 patients with severe ARDS managed with V-V ECMO. Brackets denote statistically significant differences between different ECBF. p values are shown above the brackets
In severe acute respiratory distress syndrome (ARDS), veno-venous extracorporeal membrane oxygenation (V-V ECMO) has been proposed as a therapeutic strategy to possibly reduce mortality. Transpulmonary thermodilution (TPTD) enables monitoring of the extravascular lung water index (EVLWI) and cardiac preload parameters such as intrathoracic blood volume index (ITBVI) in patients with ARDS, but it is not generally recommended during V-V ECMO. We hypothesized that the amount of extracorporeal blood flow (ECBF) influences the calculation of EVLWI and ITBVI due to recirculation of indicator, which affects the measurement of the mean transit time (MTt), the time between injection and passing of half the indicator, as well as downslope time (DSt), the exponential washout of the indicator. EVLWI and ITBVI were measured in 20 patients with severe ARDS managed with V-V ECMO at ECBF rates from 6 to 4 and 2 l/min with TPTD. MTt and DSt significantly decreased when ECBF was reduced, resulting in a decreased EVLWI (26.1 [22.8–33.8] ml/kg at 6 l/min ECBF vs 22.4 [15.3–31.6] ml/kg at 4 l/min ECBF, p < 0.001; and 13.2 [11.8–18.8] ml/kg at 2 l/min ECBF, p < 0.001) and increased ITBVI (840 [753–1062] ml/m ² at 6 l/min ECBF vs 886 [658–979] ml/m ² at 4 l/min ECBF, p < 0.001; and 955 [817–1140] ml/m ² at 2 l/min ECBF, p < 0.001). In patients with severe ARDS managed with V-V ECMO, increasing ECBF alters the thermodilution curve, resulting in unreliable measurements of EVLWI and ITBVI. German Clinical Trials Register (DRKS00021050). Registered 14/08/2018. https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00021050
 
The present case of a patient with several co-morbidities undergoing complex vitrectomy under peribulbar block and sedation with Target Controlled Infusion (TCI of propofol and dexmedetomidine with EEG and Analgesia Nociception Index (ANI) monitoring illustrates the benefits of multimodal monitoring to differentiate the effect of hypnotic and antinociceptive drugs.It is highlighted the delta-alpha electroencephalographic pattern showing adequate sedation, the beta arousal pattern in the EEG concommitant to decrease in the ANI translating insufficient anti-nociception.
 
Correlation plot between CO-CTD and CO-MBA
Bland–Altman plot showing agreement between CO-CTD and CO-MBA. Bold horizontal line indicates bias, and dashed lines indicate 95% limits of agreement
Correlation plot between CO-CTD and CO-MBA, for the arrhythmia subgroup
Bland–Altman plot showing agreement between CO-CTD and CO-MBA, for the arrhythmia subgroup. Bold horizontal line indicates bias, and dashed lines indicate 95% limits of agreement
We sought to assess agreement of cardiac output estimation between continuous pulmonary artery catheter (PAC) guided thermodilution (CO-CTD) and a novel pulse wave analysis (PWA) method that performs an analysis of multiple beats of the arterial blood pressure waveform (CO-MBA) in post-operative cardiac surgery patients. PAC obtained CO-CTD measurements were compared with CO-MBA measurements from the Argos monitor (Retia Medical; Valhalla, NY, USA), in prospectively enrolled adult cardiac surgical intensive care unit patients. Agreement was assessed via Bland-Altman analysis. Subgroup analysis was performed on data segments identified as arrhythmia, or with low CO (less than 5 L/min). 927 hours of monitoring data from 79 patients was analyzed, of which 26 had arrhythmia. Mean CO-CTD was 5.29 ± 1.14 L/min (bias ± precision), whereas mean CO-MBA was 5.36 ± 1.33 L/min, (4.95 ± 0.80 L/min and 5.04 ± 1.07 L/min in the arrhythmia subgroup). Mean of differences was 0.04 ± 1.04 L/min with an error of 38.2%. In the arrhythmia subgroup, mean of differences was 0.14 ± 0.90 L/min with an error of 35.4%. In the low CO subgroup, mean of differences was 0.26 ± 0.89 L/min with an error of 40.4%. In adult patients after cardiac surgery, including those with low cardiac output and arrhythmia CO-MBA is not interchangeable with the continuous thermodilution method via a PAC, when using a 30% error threshold.
 
Pain Scores for electromyography stimulation in the postoperative care unit
NRS: numerical rating scale; SMS: supramaximal stimulation. * indicates P value less than 0.05
Purpose: The supramaximal stimulation (SMS) of the TOF test causes uncomfortable sensations in patients. We aimed to determine whether the submaximal stimulation would be reliable in TOF tests with reduced painful sensation. Methods: The accelomyography (AMG) and electromyography (EMG) monitor was applied at each arm and general anesthesia was induced and maintained by total intravenous anesthesia. At extubation, we conducted TOF test three times at each of four different currents: SMS, 70% SMS, 50% SMS, and 30% SMS. The same procedure was performed in the postanesthesia care unit (PACU) only with EMG, and the pain scores on the numerical rating scale (NRS) during the tests were recorded. Results: A total of 36 patients were enrolled. At extubation, TOF ratios with SMS in AMG and EMG were 112.0 ± 13.1% and 93.7 ± 8.9%, respectively. There were no significant differences in TOF ratios between the SMS and lower stimulation intensities. However, 30% and 50% SMS showed significantly higher rates of the unmeasurable results of tests in the PACU. In terms of the stimulation pain, NRS showed a downward pattern as the current decreased and was significantly lower at 50% and 30% SMS than the NRS at SMS. Conclusion: The TOF test with submaximal stimulation is still reliable and can reduce stimulation pain. Considering the importance of the TOF results in determining extubation, the authors suggest the minimal current for the TOF test as 70% SMS.
 
Study design. Four carbon monoxide (CO)-rebreathings was performed before and after a blood donation and reinfusion of 900 ml whole blood, respectively. During the first CO-rebreathing, blood samples were collected during the procedure to assess CO mixing time
Total hemoglobin mass (tHb) and red blood cell volume (RBCV), plasma volume (PV), and blood volume (BV) before and after phlebotomy and reinfusion. Statistical differences: *** indicate difference (P < 0.001) from baseline, ### indicate difference (P < 0.001) from both ‘after phlebotomy’ and ‘before reinfusion’
Individual changes in blood volume (∆BV) and total hemoglobin mass (tHb) after phlebotomy and reinfusion. Horizontal dashed line indicates 900 ml or 133 g corresponding to the amount of hemoglobin and blood removed and reinfused
Carboxyhemoglobin concentration (ΔHbCO) in arterial and venous blood during the carbon monoxide rebreathing procedure. Statistical differences: *, ***, P < 0.05, P < 0.001, respectively, for comparison between arterial and venous blood. ### indicate difference (P < 0.001) between the different time points when compared to %HbCO at minute 10 in arterial samples. §§§ indicate difference (P < 0.001) between the different time points when compared to %HbCO at minute 10 in venous samples
Bland–Altman plots for individual differences in hemoglobin mass (∆tHb) and blood volume (∆BV) using arterial and venous blood for a CO rebreathing period of 2, 4, 6, 8, and 10 min. Mean difference (horizontal continuous line) with 95% limits of agreement (horizontal dashed lines)
We examined whether a semi-automated carbon monoxide (CO) rebreathing method accurately detect changes in blood volume (BV) and total hemoglobin mass (tHb). Furthermore, we investigated whether a supine position with legs raised reduced systemic CO dilution time, potentially allowing a shorter rebreathing period. Nineteen young healthy males participated. BV and tHb was quantified by a 10-min CO-rebreathing period in a supine position with legs raised before and immediately after a 900 ml phlebotomy and before and after a 900 ml autologous blood reinfusion on the same day in 16 subjects. During the first CO-rebreathing, arterial and venous blood samples were drawn every 2 min during the procedure to determine systemic CO equilibrium in all subjects. Phlebotomy decreased (P < 0.001) tHb and BV by 166 ± 24 g and 931 ± 247 ml, respectively, while reinfusion increased (P < 0.001) tHb and BV by 143 ± 21 g and 862 ± 250 ml compared to before reinfusion. After reinfusion BV did not differ from baseline levels while tHb was decreased (P < 0.001) by 36 ± 21 g. Complete CO mixing was achieved within 6 min in venous and arterial blood, respectively, when compared to the 10-min sample. On an individual level, the relative accuracy after donation for tHb and BV was 102–169% and 55–165%, respectively. The applied CO-rebreathing procedure precisely detect acute BV changes with a clinically insignificant margin of error. The 10-min CO-procedure may be reduced to 6 min with no clinical effects on BV and tHb calculation. Notwithstanding, individual differences may be of concern and should be investigated further.
 
Correlation between computerized cumulative fluid balance and bioelectrical impedance parameters during deresuscitation
Agreement analyses between changes in bioelectrical impedance analysis parameters and computerized cumulative fluid balance during deresuscitation
Bioelectrical impedance analysis (BIA) is a promising tool to evaluate the body composition of critically-ill patients. The present study aimed to assess its value as a fluid management monitoring tool during standardized deresuscitation strategy. A historical cohort of critically-ill adult patients with fluid overload and continuous renal replacement therapy was used to explore both relationship and agreement between changes in cumulative fluid balance and BIA-derived hydration variables within the 5 days following initiation of deresuscitation strategy using net ultrafiltration. Correlations were described using Spearman’s rank correlation coefficient, and agreement using Bland–Altman analysis for repeated measurements. Sixty-one couples of fluid shift measurements from 30 patients were analyzed. The deresuscitation strategy induced a negative mean (± SD) cumulative fluid balance (− 4.2 ± 3.8 L) and a significant decrease in extra- and intracellular water (P < 0.001). Decreases in extra- and intracellular water were independent of weight variations inputted in the BIA device. Total body water (rho = 0.63), extracellular water (rho = 0.68), and intracellular water (rho = 0.67) were significantly correlated with cumulative fluid balance (all P values < 0.001). The limits of agreement did not allow interchangeability for a delta of 2L between cumulative fluid balance and BIA-derived hydration variables (P > 0.05). BIA hydration-derived variables are significantly correlated with cumulative fluid balance but the large limits of agreements exclude interchangeability of the measures.
 
Flow of the patients from the considered studies. FC fluid challenge
Area under the curve (AUC) analysis of cardiac index (CI), stroke volume index (SVI), systolic arterial pressure (SAP), and mean arterial pressure (MAP) calculated during the fluid challenge (FC) administration. Light coloured AUCs are constructed considering the per cent changes of the considered variables in hypotensive patients, while dark coloured AUCs refer to the change in normotensive patients; d5, 5-min after FC end
Individual and averaged mean arterial pressure (MAP) changes during fluid challenge infusion in the overall population (top panel), patients with baseline MAP ≥ 65 mmHg (normotensive, middle panel) and patients baseline MAP < 65 mmHg (hypotensive, bottom panel). Patients are subdivided in fluid responders on the left (green mean values with standard deviations) and fluid non-responders in the right (red mean values with standard deviations). FC fluid challenge
In this study we evaluated the effect of fluid challenge (FC) administration in elective surgical patients with low or normal blood pressure. Secondarily, we appraised the pharmacodynamic effect of FC in normotensive and hypotensive patients. We assessed five merged datasets of patients with a baseline mean arterial pressure (MAP) above or below 65 mmHg and assessed the changes of systolic, diastolic, mean and dicrotic arterial pressures, dynamic indexes of fluid responsiveness and arterial elastance over a 10-min infusion. The hemodynamic effect was assessed by considering the net area under the curve (AUC), the maximal percentage difference from baseline (dmax), the time when the maximal value was observed (tmax) and change from baseline at 5-min (d5) after FC end. A stroke volume index increase > 10% with respect to the baseline value after FC administration indicated fluid response. Two hundred-seventeen patients were analysed [102 (47.0%) fluid responders]. On average, FC restored a MAP \(\ge\) 65 mmHg after 5 min. The AUCs and the dmax of pressure variables and arterial elastance of hypotensive patients were all significantly greater than normotensive patients. Pressure variables and arterial elastance changes in the hypotensive group were all significantly higher at d5 as compared to the normotensive group. In hypotensive patients, FC restores a MAP \(\ge\) 65 mmHg after 5 min from infusion start. The hemodynamic profile of FC in hypotensive and normotensive patients is different; both the magnitude of pressure augmentation and duration is greater in the hypotensive group.
 
Measuring regional cerebral blood flow (rCBF) after revascularization for moyamoya disease, as a type of ischemic cerebrovascular disease, is crucial. This study aims to validate our novel technology that combines near-infrared spectroscopy (NIRS) with a frequency filter to extract the arterial component. We measured rCBF before and after revascularization for moyamoya disease and at the end of the surgery using NIRO-200NX (Hamamatsu Photonics, Japan) and indocyanine green (ICG). rCBF was calculated using Fick’s principle, change in arterial ICG concentrations, and maximum arterial ICG concentration. rCBF measured with NIRS (rCBF_N) was compared with pre- and postoperative rCBF measured with SPECT (rCBF_S). Thirty-four procedures were analyzed. rCBF_N increased from baseline to end of the surgery (mean difference (MD), 2.99 ml/min/100 g; 95% confidence interval (CI), 0.40–5.57 ml/min/100 g on the diseased side; MD, 4.94 ml/min/100 g; 95% CI, 2.35–7.52 ml/min/100 g on the non-diseased side). Similar trends were observed for rCBF_S (MD, 3.98 ml/min/100 g; 95% CI, 2.30–5.67 ml/min/100 g on the diseased side; MD, 2.77 ml/min/100 g; 95% CI, 1.09–4.45 ml/min/100 g on the non-diseased side). Intraclass correlations 3 (ICC3s) between rCBF_N and rCBF_S were weak on the diseased side (ICC3, 0.25; 95% CI, -0.03–0.5; p = 0.07) and the non-diseased side (ICC3, 0.24; 95% CI, -0.05–0.5; p = 0.08). rCBF measurements based on this novel method were weakly correlated with rCBF measurements with SPECT.
 
We recently developed a model-based method for analyzing multiple breath nitrogen washout data that does not require identification of Phase-III. In the present study, we assessed the effect of irregular breathing patterns on the intra-subject variabilities of the model parameters. Nitrogen fraction at the mouth was measured in 18 healthy and 20 asthmatic subjects during triplicate performances of multiple breath nitrogen washout, during controlled (target tidal volume 1 L at 8–12 breaths per minute) and free (unrestricted) breathing. The parameters Scond, Sacin and functional residual capacity (FRC) were obtained by conventional analysis of the slope of Phase-III. Fitting the model to the washout data provided functional residual capacity (FRCM), dead space volume (VD), the coefficient of variation of regional specific ventilation (CV,V˙e), and the model equivalent of Sacin (Sacin-M). Intra-participant coefficients of variation for the model parameters for both health and asthma were FRCM < 5.2%, VD < 5.4%, CV,V˙e < 9.0%, and Sacin-M < 45.6% for controlled breathing, and FRCM < 4.6%, VD < 5.3%, CV,V˙e < 13.2%, and Sacin-M < 103.2% for free breathing. The coefficients of variation limits for conventional parameters were FRC < 6.1%, with Scond < 73.6% and Sacin < 49.2% for controlled breathing and Scond < 35.0% and Sacin < 74.4% for free breathing. The model-fitting approach to multiple breath nitrogen washout analysis provides a measure of regional ventilation heterogeneity in CV,V˙e that is less affected by irregularities in the breathing pattern than its corresponding Phase-III slope analysis parameter Scond.
 
Linear calibration between HovaCal standard concentrations from 0 ppbv to 100 ppbv and EDMON measurements with and without additional humidity
Bland-Altman plot of measured concentrations over 100min with a steady standard concentration of 20 ppbv (A) and 40 ppbv (B) at 100% relative humidity and without additional humidity. Upper and lower reference line are presented as dashed lines
Evaluation of carry-over effects. Measured concentrations over time with 10-minute intervals of 10 ppbv and 0 ppbv standard concentration for measurements with 100% relative humidity and without additional humidity. Concentration changes were evaluated, after changing standard concentration from 10 ppbv to 0 ppbv
Graphical determination of resolution for standard HovaCal concentrations of 5 ppbv in a range of 1–10 ppbv and 40 ppbv in a range of 30–40 ppbv.
Influence of humidity on the EDMON measurement performance
The bedside Exhaled Drug MONitor – EDMON measures exhaled propofol in ppbv every minute based on multi-capillary column – ion mobility spectrometry (MCC-IMS). The MCC pre-separates gas samples, thereby reducing the influence of the high humidity in human breath. However, preliminary analyses identified substantial measurement deviations between dry and humid calibration standards. We therefore performed an analytical validation of the EDMON to evaluate the influence of humidity on measurement performance. A calibration gas generator was used to generate gaseous propofol standards measured by an EDMON device to assess linearity, precision, carry-over, resolution, and the influence of different levels of humidity at 100% and 1.7% (without additional) relative humidity (reference temperature: 37°C). EDMON measurements were roughly half the actual concentration without additional humidity and roughly halved again at 100% relative humidity. Standard concentrations and EDMON values correlated linearly at 100% relative humidity (R²=0.97). The measured values were stable over 100min with a variance ≤ 10% in over 96% of the measurements. Carry-over effects were low with 5% at 100% relative humidity after 5min of equilibration. EDMON measurement resolution at 100% relative humidity was 0.4 and 0.6 ppbv for standard concentrations of 3 ppbv and 41 ppbv. The influence of humidity on measurement performance was best described by a second-order polynomial function (R²≥0.99) with influence reaching a maximum at about 70% relative humidity. We conclude that EDMON measurements are strongly influenced by humidity and should therefore be corrected for sample humidity to obtain accurate estimates of exhaled propofol concentrations.
 
In this article we present the learning from a clinical study of airway device evaluation, conducted under the framework of the Difficult Airway Society (DAS, UK) ‘ADEPT’ (airway device evaluation project team) strategy. We recommend a change in emphasis from small scale randomised controlled trials conducted as research, to larger-scale observational, post-marketing evaluation audits as a way of obtaining more meaningful information.
 
Gastrointestinal endoscopies are often done in the prone position and anesthesiologists are needed to provide sedation. Airway access is limited in the prone position and may make timely airway management difficult in case of airway obstruction during sedation. Specialized laryngeal mask airway devices customized for endoscopy procedures like LMA® Gastro™ can be inserted in the prone position and may help anesthesiologists tide over such crisis situations while simultaneously allowing the endoscopy procedures through the dedicated conduit available for inserting the endoscopes. We have described one such case managed successfully by inserting LMA® Gastro™ in the prone position.
 
LMA® Protector™ (figure provided by courtesy of Teleflex Medical, Co. Westmeath, Ireland)
Baseline characteristics of patients recruited (n = 111)
Details of Surgery
To address the problem of lack of clinical evidence for airway devices introduced to the market, the Difficult Airway Society (UK) developed an approach (termed ADEPT; Airway Device Evaluation Project Team) to standardise the model for device evaluation. Under this framework we assessed th e LMA Protector, a second generation laryngeal mask airway. A total of 111 sequential adult patients were recruited and the LMA Protector inserted after induction of general anaesthesia. Effective insertion was confirmed by resistance to further distal movement, manual ventilation, and listening for gas leakage at the mouth. The breathing circuit was connected to the airway channel and airway patency confirmed with manual test ventilation at 20 cm H 2 0 (water) pressure for 3 s. Data was collected in relation to the time for placement, intraoperative performance and postoperative performance of the airway device. Additionally, investigators rated the ease of insertion and adequacy of lung ventilation on a 5-point scale. The median (interquartile range [range]) time taken to insertion of the device was 31 (26–40[14–780]) s with the ability to ventilate after device insertion 100 (95% CI 96.7- 100)%. Secondary endpoints included one or more manoeuvres 60.3 (95% CI 50.6—69.5)% cases requiring to assist insertion; a median ease of insertion score of 4 (2–5[3–5]), and a median adequacy of ventilation score of 5 (5–5[4–5]). However, the first time insertion rate failure was 9.9% (95% CI 5.1—17.0%). There were no episodes of patient harm recorded, particularly desaturation. The LMA Protector appears suitable for clinical use, but an accompanying article discusses our reflections on the ADEPT approach to studying airway devices from a strategic perspective.
 
Performance versus number of predictors used in the logistic regression models for the feature-sensitivity analysis across the three POR complications in terms of A Brier score and B c-statistic
Guide to using the created POR scoring systems
Accurate estimation of surgical risks is important for informing the process of shared decision making and informed consent. Postoperative reintubation (POR) is a severe complication that is associated with postoperative morbidity. Previous studies have divided POR into early POR (within 72 h of surgery) and late POR (within 30 days of surgery). Using data provided by American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP), machine learning classification models (logistic regression, random forest classification, and gradient boosting classification) were utilized to develop scoring systems for the prediction of combined, early, and late POR. The risk factors included in each scoring system were narrowed down from a set of 37 pre and perioperative factors. The scoring systems developed from the logistic regression models demonstrated strong performance in terms of both accuracy and discrimination across the different POR outcomes (Average Brier score, 0.172; Average c-statistic, 0.852). These results were only marginally worse than prediction using the full set of risk variables (Average Brier score, 0.145; Average c-statistic, 0.870). While more work needs to be done to identify clinically relevant differences between the early and late POR outcomes, the scoring systems provided here can be used by surgeons and patients to improve the quality of care overall.
 
Four recent cases utilizing transabdominal motor-evoked potentials (TaMEPs) are presented as illustrative of the monitoring technique during lumbosacral fusion, sciatic nerve tumor resection, cauda equina tumor resection, and lumbar decompression. Case 1: In a high-grade lumbosacral spondylolisthesis revision fusion, both transcranial motor-evoked potentials (TcMEPs) and TaMEPs detected a transient focal loss of left tibialis anterior response in conjunction with L5 nerve root decompression. Case 2: In a sciatic nerve tumor resection, TcMEPs responses were lost but TaMEPs remained unchanged, the patient was neurologically intact postoperatively. Case 3: TaMEPs were acquired during an L1-L3 intradural extramedullary cauda equina tumor resection utilizing a unique TaMEP stimulation electrode. Case 4: TaMEPs were successfully acquired with little anesthetic fade utilizing an anesthetic regimen of 1.1 MAC Sevoflurane during a lumbar decompression. While the first two cases present TaMEPs and TcMEPs side-by-side, demonstrating TaMEPs correlating to TcMEPs (Case 1) or a more accurate reflection of patient outcome (Case 2), no inference regarding the accuracy of TaMEPs to monitor nerve elements during cauda equina surgery (Cases 3) or the lumbar decompression presented in Case 4 should be made as these are demonstrations of technique, not utility.
 
Study Groups
Boxplots, comparing dosage of rocuronium per minute surgery-time
The level of neuromuscular blockade can be assessed by subjective (qualitative) and objective (quantitative) methods. This study aims to compare the dosage of the neuromuscular blocking agents (NMBA) rocuronium and the need for reversion by sugammadex between those methods. A retrospective, observational analysis was conducted. In the tactile qualitative-neuromuscular monitoring-group (tactile NMM) (n = 244), muscle contractions were assessed tactilely. In the quantitative neuromuscular monitoring-group (n = 295), contractions were accessed using an acceleromyograph. Primary endpoints were dosage of rocuronium per minute operation-time (milligram per kilogram bodyweight per minute (mg/kgBW/min)), count of repeated rocuronium administrations and use of sugammadex. Secondary endpoints were: NMM use before repeated NMBA application or extubation, time to extubation, post-operative oxygen demand. A total of n = 539 patients were included. n = 244 patients were examined with tactile NMM and 295 patients by quantitative NMM. Quantitative NMM use resulted in significantly lower rocuronium dosing (tactile NMM: 0.01 (± 0.007) mg/kgBW/min vs. quantitative NMM: 0.008 (± 0.006) mg/kgBW/min (p < 0.001)). In quantitative NMM use fewer repetitions of rocuronium application were necessary (tactile NMM: 83% (n = 202) vs. quantitative NMM: 71% (n = 208) p = 0.007). Overall, 24% (n = 58) in the tactile NMM-group, and 20% (n = 60) in the quantitative NMM-group received sugammadex ((p = 0.3), OR: 1.21 (0.81-1.82)). Significantly fewer patients in the quantitative NMM-group required oxygen-supply postoperative (quantitative NMM: 43% (n = 120)) vs. tactile NMM: 57% (n = 128)) (p = 0.002). The use of quantitative assessment of NMBA results in a lower overall dosage and requires fewer repetitions of rocuronium application. Therefore, quantitative monitoring systems should be used to monitor NMBA intraoperatively to reduce NMBA dosing, while achieving continuous neuromuscular blockade.
 
The PMD-200 Monitor
Patient flow chart
PACU pain Scores at 90 minutes with breakdown by surgery type
PACU pain score trajectories in the NOL guided and SOC groups
Variables collected during and after surgery
The Nociception Level index (NOL™) is a multiparameter index, based on artificial intelligence for the monitoring of nociception during anesthesia. We studied the influence of NOL-guided analgesia on postoperative pain scores in patients undergoing major abdominal surgery during sevoflurane/fentanyl anesthesia. This study was designed as a single-center, prospective randomized, controlled study. After Institutional Review Board approval and written informed consent, 75 ASA 1–3 adult patients undergoing major abdominal surgery, were randomized to NOL-guided fentanyl dosing (NOL) or standard care (SOC) and completed the study. The sevoflurane target MAC range was 0.8–1.2. In the NOL-guided group (N = 36), when NOL values were > 25 for at least 1 min, a weight adjusted fentanyl bolus was administered. In the control group (N = 39) fentanyl administration was based on hemodynamic indices and clinician judgement. After surgery, pain, was evaluated using the Numerical Rating Scale (NRS) pain scale, ranging from 0 to 10, at 15 min intervals for 180 min or until patient discharge from the PACU. Median postoperative pain scores reported were 3.0 [interquartile range 0.0–5.0] and 5.0 [3.0–6.0] at 90 min in NOL-guided and control groups respectively (Bootstrap corrected actual difference 1.5, 95% confidence interval 0.4–2.6). There was no difference in postoperative morphine consumption or intraoperative fentanyl consumption. Postoperative pain scores were significantly improved in nociception level index-guided patients. We attribute this to more objective fentanyl dosing when timed to actual nociceptive stimuli during anesthesia, contributing to lower levels of sympathetic activation and surgical stress. Clinicaltrials.gov identifier: NCT03970291 date of registration May 31, 2019.
 
Representative lung CT and corresponding LUS images in ventral, intermediate and dorsal lung regions at early and late stages of ARDS, in two opposite cases of aeration improvement (panel A) or worsening (panel B)
Changes in percentage of aerated tissue (A) and changes in normally (B), poorly (C) and not (D) aerated tissue over categorical changes in LUS score. *p < 0.01 VS “Improve” category, #p < 0.01 VS “Equal” category, ##p < 0.05 VS “Equal” category
To evaluate whether lung ultrasound is reliable bedside tool to monitor changes of lung aeration at the early and late stages of ARDS. LUS was performed in ARDS patients that underwent at least two consecutive CT scan at ICU admission and at least 1 week after admission. Twelve fields were evaluated and graded from 0 (normal) to 3 (consolidation). Changes of LUS score in twelve fields (ΔLUS tot ) and in four ventral (ΔLUS V ), intermediate (ΔLUS I ) and dorsal (ΔLUS D ) zones were calculated at each time points. Three categories were described: Improve (ΔLUS < 0), Equal (ΔLUS = 0) or Worse (ΔLUS > 0). LUS scores were correlated with total changes in lung CT aeration (ΔCT air ) and with normally, poorly and not aerated regions (ΔCT norm , ΔCT poor and ΔCT not , respectively). Eleven patients were enrolled. ΔLUS tot had significant correlation with ΔCT air (r = − 0.74, p < 0.01). ΔLUS V , ΔLUS I and ΔLUS D showed significant correlations with ΔCT air (r = − 0.66, r = − 0.69, r = − 0.63, respectively; p < 0.05). Compared to Equal, Improve and Worse categories had significantly higher (p < 0.01) and lower (p < 0.05) ΔCTair values, respectively. Compared to Equal, Improve and Worse categories had lower (p < 0.01) and higher (p < 0.01) ΔCT not values, respectively. LUS score had a good correlation with lung CT in detecting changes of lung aeration.
 
Data warehouse architecture and process. AIMS Anesthesia Information Management System, PMSI Programme de Médicalisation des Systèmes d’Information (hospital discharge reports)
Data model of the data warehouse and the datamarts. Tables of the data warehouse store historical and precise data, at the greatest level of detail, and are linked to each other by foreign key relationships. Tables of the datamarts are constituted of secondary computed data
Challenges encountered over the course of a data warehouse project. Red items represent challenges that will stop the project if they are not fully mastered
Tips for setting up and managing a data warehouse project
This paper describes the development and implementation of an anesthesia data warehouse in the Lille University Hospital. We share the lessons learned from a ten-year project and provide guidance for the implementation of such a project. Our clinical data warehouse is mainly fed with data collected by the anesthesia information management system and hospital discharge reports. The data warehouse stores historical and accurate data with an accuracy level of the day for administrative data, and of the second for monitoring data. Datamarts complete the architecture and provide secondary computed data and indicators, in order to execute queries faster and easily. Between 2010 and 2021, 636 784 anesthesia records were integrated for 353 152 patients. We reported the main concerns and barriers during the development of this project and we provided 8 tips to handle them. We have implemented our data warehouse into the OMOP common data model as a complementary downstream data model. The next step of the project will be to disseminate the use of the OMOP data model for anesthesia and critical care, and drive the trend towards federated learning to enhance collaborations and multicenter studies.
 
Receiver operating characteristics curves for the prediction of moderate to severe postoperative pain. Six different machine-learning algorithms were tested. The logistic regression with elasticnet penalization achieved the best cross-validated area under the Receiver Operating Characteristic curve (CV-AUC)
Variable importance for the prediction of moderate to severe postoperative pain based on SHAP values. The SHAP summary dot plot displays features that influence model predictions of positive outcome (moderate to severe PACU pain) the most. Features are sorted by their mean absolute SHAP value (reflecting their global importance). For every individual, a dot represents the value for each feature from low (blue) to high (red). The features included in the multivariate penalized logistic regression model are displayed. NOL nociception level index, Surg surgery, TWA time weighted average
The relationship between intraoperative nociception and acute postoperative pain is still not well established. The nociception level (NOL) Index (Medasense, Ramat Gan, Israel) uses a multiparametric approach to provide a 0–100 nociception score. The objective of the ancillary analysis of the NOLGYN study was to evaluate the ability of a machine-learning aglorithm to predict moderate to severe acute postoperative pain based on intraoperative NOL values. Our study uses the data from the NOLGYN study, a randomized controlled trial that evaluated the impact of NOL-guided intraoperative administration of fentanyl on overall fentanyl consumption compared to standard of care. Seventy patients (ASA class I–III, aged 18–75 years) scheduled for gynecological laparoscopic surgery were enrolled. Variables included baseline demographics, NOL reaction to incision or intubation, median NOL during surgery, NOL time-weighted average (TWA) above or under manufacturers’ recommended thresholds (10–25), and percentage of surgical time spent with NOL > 25 or < 10. We evaluated different machine learning algorithms to predict postoperative pain. Performance was assessed using cross-validated area under the ROC curve (CV-AUC). Of the 66 patients analyzed, 42 (63.6%) experienced moderate to severe pain. NOL post-intubation (42.8 (31.8–50.6) vs. 34.8 (25.6–41.3), p = 0.05), median NOL during surgery (13 (11–15) vs. 11 (8–13), p = 0.027), percentage of surgical time spent with NOL > 25 (23% (18–18) vs. 20% (15–24), p = 0.036), NOL TWA < 10 (2.54 (2.1–3.0) vs. 2.86 (2.48–3.62), p = 0.044) and percentage of surgical time spent with NOL < 10 (41% (36–47) vs. 47% (40–55), p = 0.022) were associated with moderate to severe PACU pain. Corresponding ROC AUC for the prediction of moderate to severe PACU pain were 0.65 [0.51–0.79], 0.66 [0.52–0.81], 0.66 [0.52–0.79], 0.65 [0.51–0.79] and 0.67 [0.53–0.81]. Penalized logistic regression achieved the best performance with a 0.753 (0.718–0.788) CV-AUC. Our results, even if limited by the small number of patients, suggest that acute postoperative pain is better predicted by a multivariate machine-learning algorithm rather than individual intraoperative nociception variables. Further larger multicentric trials are highly recommended to better understand the relationship between intraoperative nociception and acute postoperative pain. Trial registration Registered on ClinicalTrials.gov in October 2018 (NCT03776838).
 
Examples of a OD quantification by resulted difference on pressure between k2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$k2$$\end{document} and k2end\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$k2end$$\end{document} and b SI identification in a Pt\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P\left(t\right)$$\end{document} curve during inspiration. Identified SI = 1.17, while both (a) and (b) indicate over-distension exists based SI > 1.05 [18]. Plots c and d illustrate curve flattening with OD ≈ 0 cmH2O with no flattening and OD > 0 cmH2O due to nonlinear flattening of the inspiratory P–V loop at end inspiration as stiffness increases due to over-distension. Plots a, b, and d are using same clinical data from Patient 1 at PEEP = 10 cmH2O, while c is using data from Patient 1 at PEEP = 0 cmH2O
Correlation of OD (cmH2O) vs SI (unit-less) is presented in 3 patient groups: a mild, b moderate, and c severe ARDS, including 99, 89, and 8 cases, respectively. Overall correlation among all 19 patients is shown in (d). R² values yield 0.60, 0.79, 0.98, and overall 0.61, respectively. Orange triangles ‘∆’ denote the two abnormal patients, Patient 7 and 12, covering 22 cases totally
Distribution of OD values in SI diagnostic ranges, yielding p < 0.001 (statistically significant) for every pair and three groups together
Plots of a optimal cut point detection yielding least FN + FP cases; b the ROC curve with the three points highlighted. Although point 3 is commonly chosen as the optimal cut point, point 1 is considered as a better choice in this study
Plots for a ROC curve classification outcome presented in scatter plot; and b SI values distributed by proposed OD diagnostic range (p < 0.001 for every pair and three groups together, statistically significant). Dashed lines are validated SI safe range of 0.95–1.05 and proposed OD safe range of 0–0.8 cmH2O
Clinical measurements offer bedside monitoring aiming to minimise unintended over-distension, but have limitations and cannot be predicted for changes in mechanical ventilation (MV) settings and are only available in certain MV modes. This study introduces a non-invasive, real-time over-distension measurement, which is robust, predictable, and more intuitive than current methods. The proposed over-distension measurement, denoted as OD, is compared with the clinically proven stress index (SI). Correlation is analysed via R² and Spearman rs. The OD safe range corresponding to the unit-less SI safe range (0.95–1.05) is calibrated by sensitivity and specificity test. Validation is fulfilled with 19 acute respiratory distress syndrome (ARDS) patients data (196 cases), including assessment across ARDS severity. Overall correlation between OD and SI yielded R² = 0.76 and Spearman rs = 0.89. Correlation is higher considering only moderate and severe ARDS patients. Calibration of OD to SI yields a safe range defined: 0 ≤ OD ≤ 0.8 cmH2O. The proposed OD offers an efficient, general, real-time measurement of patient-specific lung mechanics, which is more intuitive and robust than SI. OD eliminates the limitations of SI in MV mode and its less intuitive lung status value. Finally, OD can be accurately predicted for new ventilator settings via its foundation in a validated predictive personalized lung mechanics model. Therefore, OD offers potential clinical value over current clinical methods.
 
Relative positions of EtCO2 sensor and HMEF in the ventilator circuit. EtCO2, end-tidal carbon dioxide; HMEF, heat and moisture exchanger
Flow of patients of mechanical ventilation. HMEF, heat and moisture exchanger filter
Estimated accuracy difference and the non-inferiority margin. The estimated accuracy difference with two-sided 90% CI was compared to the pre-defined non-inferiority margin of + 1 mm Hg. The blue-tinted region indicated that mainstream EtCO2 on the Y-piece side of HMEF is noninferior to that on the patient side. We defined Δ Y-piece side as the absolute difference between PaCO2 and EtCO2 on the Y-piece side of HMEF, and Δ patient side as the absolute difference between PaCO2 and EtCO2 on the patient side. Accuracy difference was defined as Δ Y-piece side—Δ patient side. EtCO2, end-tidal carbon dioxide; HMEF, heat and moisture exchanger filter
Bland–Altman plots showing the variation of differences between PaCO2 and EtCO2. EtCO2, end-tidal carbon dioxide; LOA, limit of agreement
The purpose of the study was to investigate the accuracy of mainstream EtCO2 measurements on the Y-piece (filtered) side of the heat and moisture exchanger filter (HMEF) in adult critically ill patients, compared to that on the patient (unfiltered) side of HMEF. We conducted a prospective observational method comparison study between July 2019 and December 2019. Critically ill adult patients receiving mechanical ventilation with HMEF were included. We performed a noninferiority comparison of the accuracy of EtCO2 measurements on the two sides of HMEF. The accuracy was measured by the absolute difference between PaCO2 and EtCO2. We set the non-inferiority margin at + 1 mmHg in accuracy difference between the two sides of HMEF. We also assessed the agreement between PaCO2 and EtCO2 using Bland–Altman analysis. Among thirty-seven patients, the accuracy difference was − 0.14 mmHg (two-sided 90% CI − 0.58 to 0.29), and the upper limit of the CI did not exceed the predefined margin of + 1 mmHg, establishing non-inferiority of EtCO2 on the Y-piece side of HMEF (P for non-inferiority < 0.001). In the Bland–Altman analyses, 95% limits of agreement between PaCO2 and EtCO2 were similar on both sides of HMEF (Y-piece side, − 8.67 to + 10.65 mmHg; patient side, − 8.93 to + 10.67 mmHg). The accuracy of mainstream EtCO2 measurements on the Y-piece side of HMEF was noninferior to that on the patient side in critically ill adults. Mechanically ventilated adult patients could be accurately monitored with mainstream EtCO2 on the Y-piece side of the HMEF unless their tidal volume was extremely low.
 
Editorial commenting the article by Idei et al. (PMID: 35661319) and globally addressing the value of the processed EEG monitoring to titrate sedative drugs dosing in the ICU
 
PRISMA flow diagram
Percentage of patients reporting adverse device effects classified by studies
Number of reported adverse device effects classified by devices
Novel technologies allow continuous wireless monitoring systems (CWMS) to measure vital signs and these systems might be favorable compared to intermittent monitoring regarding improving outcomes. However, device safety needs to be validated because uncertain evidence challenges the clinical implementation of CWMS. This review investigates the frequency of device-related adverse events in patients monitored with CWMS in general hospital wards. Systematic literature searches were conducted in PubMed and Embase. We included trials of adult patients in general hospital wards monitored with CWMS. Our primary outcome was the frequency of unanticipated serious adverse device effects (USADEs). Secondary outcomes were adverse device effects (ADEs) and serious adverse device effects (SADE). Data were extracted from eligible studies and descriptive statistics were applied to analyze the data. Seven studies were eligible for inclusion with a total of 1485 patients monitored by CWMS. Of these patients, 54 patients experienced ADEs (3.6%, 95% CI 2.8–4.7%) and no USADEs or SADEs were reported (0%, 95% CI 0–0.31%). The studies of the SensiumVitals® patch, the iThermonitor, and the ViSi Mobile® device reported 28 (9%), 25 (5%), and 1 (3%) ADEs, respectively. No ADEs were reported using the HealthPatch, WARD 24/7 system, or Coviden Alarm Management. Current evidence suggests that CWMS are safe to use but systematic reporting of all adverse device effects is warranted.
 
Head positioning in carotid surgery represents an often overlooked but sensitive period in the surgical plan. A 53-year-old male presented a significant decrement in median nerve somatosensory evoked potential (mSEP) following head and neck positioning for carotid pseudoaneurysm repair before skin incision. Neurophysiological monitoring was performed with mSEP and electroencephalography early during the patient’s preparation and surgery. Within five minutes after rotation and extension of the head to properly expose the surgical field, the contralateral m-SEP significantly decreased in both cortical (N20/P25) and subcortical (P14/N18) components. Partial neck correction led to m-SEP improvement, allowing to proceed with the carotid repair. We discuss possible underlying pathophysiological mechanisms responsible for these changes and highlight the relevance of an early start on monitoring to avoid neurological deficits.
 
PRISMA flow diagram of the study selection process
One of the most significant limitations of oximeters is their performance under poor perfusion conditions. This systematic review examines pulse oximeter model accuracy in adults under poor perfusion conditions. A multiple database search was conducted from inception to December 2020. The inclusion criteria were as follows: (1) adult participants (> 18 years) with explicitly stated conditions that cause poor peripheral perfusion (conditions localized at the oximeter placement site; or systemic conditions, including critical conditions such as hypothermia, hypotension, hypovolemia, and vasoconstricting agents use; or experimental conditions) (2) a comparison of arterial oxygen saturation and arterial blood gas values. A total of 22 studies were included and assessed for reliability and agreement using a modified Guidelines for Reporting Reliability and Agreement Studies tool. We calculated the accuracy root mean square error from bias and precision we extracted from the studies. Most oximeters (75%) were deemed accurate in patients with poor perfusion. Modern oximeters utilizing more complex algorithms were more likely to be accurate than older models. Earlobe placement of oximeters seemed more sensitive, with greater measurement accuracy, than on fingertip placement. Only one study controlled for skin pigmentation, and none strictly followed Food and Drug Association recommendations for experiments to determine oximeter accuracy. Oximeters are accurate in poorly perfused patients, especially newer oximeter models and those placed on earlobes. Further studies are needed that examine multiple oximeter models used on a diverse selection of patients while following FDA recommendations to examine oximeter accuracy.
 
Flowchart depicting handling of records
Heart rate variability (HRV) is a predictor of mortality and morbidity after non-lethal cardiac ischemia, but the relation between preoperatively measured HRV and intra- and postoperative complications is sparsely studied and most recently reviewed in 2007. We, therefore, reviewed the literature regarding HRV as a predictor for intra- and postoperative complications and outcomes. We carried out a systematic review without meta-analysis. A PICO model was set up, and we searched PubMed, EMBASE, and CENTRAL. The screening was done by one author, but all authors performed detailed review of the included studies. We present data from studies on intraoperative and postoperative complications, which were too heterogeneous to warrant formal meta-analysis, and we provide a pragmatic review of HRV indices to facilitate understanding our findings. The review was registered in PROSPERO (CRD42021230641). We screened 2337 records for eligibility. 131 records went on to full-text assessment, 63 were included. In frequency analysis of HRV, low frequency to high frequency ratio could be a predictor for intraoperative hypotension in spinal anesthesia and lower total power could possibly predict intraoperative hypotension under general anesthesia. Detrended fluctuation analysis of HRV is a promising candidate for predicting postoperative atrial fibrillation. This updated review of the relation between preoperative HRV and surgical outcome suggests a clinically relevant role of HRV but calls for high quality studies due to methodological heterogeneity in the current literature. Areas for future research are suggested.
 
Top-cited authors
Thomas W L Scheeren
  • University of Groningen
Patrick Schober
  • Amsterdam University Medical Center
Talakad N Sathyaprabha
  • National Institute of Mental Heath and Neurosciences
Daniel A Reuter
  • University of Rostock
Regis Logier
  • Centre Hospitalier Régional Universitaire de Lille