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APACHE II: a severity of disease classification system

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This paper presents the form and validation results of APACHE II, a severity of disease classification system. APACHE II uses a point score based upon initial values of 12 routine physiologic measurements, age, and previous health status to provide a general measure of severity of disease. An increasing score (range 0 to 71) was closely correlated with the subsequent risk of hospital death for 5815 intensive care admissions from 13 hospitals. This relationship was also found for many common diseases. When APACHE II scores are combined with an accurate description of disease, they can prognostically stratify acutely ill patients and assist investigators comparing the success of new or differing forms of therapy. This scoring index can be used to evaluate the use of hospital resources and compare the efficacy of intensive care in different hospitals or over time.
... e APACHEII was designed to measure of disease severity developed by Knaus et al. [23]. e tool consists of 12 routine physiological points, age points, and chronic health points measured within the first 24 hours of ICU admission [23]. ...
... e APACHEII was designed to measure of disease severity developed by Knaus et al. [23]. e tool consists of 12 routine physiological points, age points, and chronic health points measured within the first 24 hours of ICU admission [23]. e minimum score of 0 and a maximum score of 71 can be obtained by for patients, each item was scored from 0 to 4 (Zero means most normal and 4 means most abnormal) [23]. ...
... e tool consists of 12 routine physiological points, age points, and chronic health points measured within the first 24 hours of ICU admission [23]. e minimum score of 0 and a maximum score of 71 can be obtained by for patients, each item was scored from 0 to 4 (Zero means most normal and 4 means most abnormal) [23]. e sensitivity and the specificity of the tool was of 87.5% and 79.0%, respectively [24]. ...
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Background. Delirium is a common disorder among patients admitted to intensive care units. Identification of the predicators of delirium is very important to improve the patient’s quality of life. Methods. This study was conducted in a prospective observational design to build a predictive model for delirium among ICU patients in Oman. A sample of 153 adult ICU patients from two main hospitals participated in the study. The Intensive Care Delirium Screening Checklist (ICDSC) was used to assess the participants for delirium twice daily. Result. The results showed that the incidence of delirium was 26.1%. Multiple logistic regression analysis showed that sepsis (odds ratio (OR) = 9.77; 95% confidence interval (CI) = 1.91–49.92; P < 0.006 ), metabolic acidosis (odds ratio (OR) = 3.45; 95% confidence interval [CI] = 1.18–10.09; P = 0.024 ), nasogastric tube use (odds ratio (OR) 9.74; 95% confidence interval (CI) = 3.48–27.30; P ≤ 0.001 ), and APACHEII score (OR = 1.22; 95% CI = 1.09–1.37; P ≤ 0.001 ) were predictors of delirium among ICU patients in Oman (R2=0.519, adjusted R2=0.519, P ≤ 0.001 ). Conclusion. To prevent delirium in Omani hospitals, it is necessary to work on correcting those predictors and identifying other factors that had effects on delirium development. Designing of a prediction model may help on early delirium detection and implementation of preventative measures.
... 2,3 Abnormal white blood cell counts (WBCs) are common in critically ill patients with infection, and correlate with disease severity in patients admitted to an intensive care unit (ICU). 5 The WBC integrates many parameters that are pertinent to the host response to infection. 6 Although derangements in the WBC are associated with increased mortality in septic shock, the impact of individual variation in the WBC over time has not been well described. ...
... For the entire cohort, unadjusted ICU mortality was 27% and 30-day mortality was 26%. The median [IQR] ICU length of stay for the entire cohort was 8 days [4][5][6][7][8][9][10][11][12][13][14]. Mechanical ventilation was required by 84% of patients (771/917) and 20% (186/917) required acute renal replacement therapy. ...
... Prognosis in critical care is customarily founded on baseline characteristics, such as the APACHE II score. 5 More recently, the importance of temporal trends in predicting prognosis has been recognized, as reflected by the change in Sequential Organ Failure Assessment (SOFA) score. 26 Nevertheless, studies evaluating temporal trends typically fail to assess differences between patient subgroups, and instead assess the entire group in aggregate, such as the evaluation of the mean platelet count over time in critical illness 27 and septic shock. ...
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Purpose: Septic shock is associated with a mortality of 20-40%. The white blood cell count (WBC) at hospital admission correlates with prognosis in septic shock. Here, we explore whether the trajectory of WBC after admission provides further information about outcomes. We aimed to identify groups of patients with different WBC trajectories and the association of WBC trajectory with mortality. Methods: We included adult patients with septic shock in two academic intensive care units (ICU) in Winnipeg, MB, Canada between 2006 and 2012. We used group-based trajectory analysis to group patients according to their WBC patterns over the first seven days in the ICU. Our primary analysis was the association of WBC trajectory group on 30-day mortality using multivariable Cox proportional hazards regression. Results: We included 917 patients with septic shock. The final model identified seven distinct WBC trajectories. The rising WBC trajectory was independently associated with increased mortality (hazard ratio, 3.41; 95% confidence interval, 1.86 to 6.26; P < 0.001) compared with the stable WBC trajectory. Conclusion: In patients with septic shock, distinct and clinically relevant groups can be identified by analyzing WBC trajectories. A rising WBC trajectory was associated with higher mortality.
... We recorded patient demographics and clinical characteristics, including acute physiology and chronic health evaluation II (APACHE II) scores evaluated with the worst values during the first 24-h in the ICU [13], vital signs, and ventilatory parameters evaluated at the time of EtCO2 measurement, as shown in Tables 1 and 2. All patients were followed up until hospital discharge, and hospital outcomes were recorded. ...
... We believe that such a severe patient is not a good candidate for the HMEF circuit. Second, the median time from HMEF placement to EtCO 2 measurement was 16 h (IQR, [11][12][13][14][15][16][17][18][19]. We could not refer to the accuracy of EtCO 2 under conditions with prolonged use of HMEF, although a study showed that 120-h use of HMEFs did not increase their resistance [28]. ...
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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.
... Tocilizumab required approval from our Infectious Diseases service and a weight-based dose was used, consistent with the Infectious Diseases Society of America Guidelines [18]. Charlson Comorbidity Index Score and Acute Physiology and Chronic Health Evaluation (APACHE) II were calculated as previously described [19,20]. ...
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Background Pneumothorax has been increasingly observed among patients with coronavirus disease-2019 (COVID-19) pneumonia, specifically in those patients who develop acute respiratory distress syndrome (ARDS). In this study, we sought to determine the incidence and potential risk factors of pneumothorax in critically ill adults with COVID-19. Method This retrospective cohort study included adult patients with laboratory-confirmed SARS-CoV-2 infection admitted to one of the adult intensive care units of a tertiary, academic teaching hospital from May 2020 through May 2021. Results Among 334 COVID-19 cases requiring ICU admission, the incidence of pneumothorax was 10% (33 patients). Patients who experienced pneumothorax more frequently required vasopressor support (28/33 [84%] vs. 191/301 [63%] P = 0.04), were more likely to be proned (25/33 [75%] vs. 111/301 [36%], P<0.001), and the presence of pneumothorax was associated with prolonged duration of mechanical ventilation; 21 (1–97) versus 7 (1–79) days, p<0.001 as well as prolonged hospital length of stay (29 [9–133] vs. 15 [1–90] days, P<0.001), but mortality was not significantly different between groups. Importantly, when we performed a Cox proportional hazard ratio (HR) model of multivariate parameters, we found that administration of tocilizumab significantly increased the risk of developing pneumothorax (HR = 10.7; CI [3.6–32], P<0.001). Conclusion Among 334 critically ill patients with COVID-19, the incidence of pneumothorax was 10%. Presence of pneumothorax was associated with prolonged duration of mechanical ventilation and length of hospital stay. Strikingly, receipt of tocilizumab was associated with an increased risk of developing pneumothorax.
... The Charlson comorbidity index (CCI) 18 was used to assess the degree of comorbidity, and the Acute Physiologic and Chronic Health Evaluation II (APACHE II) score was used to evaluate the severity of disease. 19 The Sepsis-related Organ Failure Assessment (SOFA) score was used to evaluate the degree of dysfunction or organ failure caused by infection. 20 Variables including P/F ratio, positive endexpiratory pressure (PEEP) level, tidal volume per predicted body weight (Vt/PBW), static compliance of the respiratory system (Crs), plateau pressure (Pplt), driving pressure (Pdrive) were measured at baseline, at the first hour, fourth hour, first day, second day of the PP, and after resuming the supine position. ...
... Acute physiological assessment and chronic health evaluation (APACHE) score APACHE score [14] is an illness severity score commonly used in critical care medicine to predict mortality upon admission to an intensive care unit. ...
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Introduction Enterococcus is a gram-positive, non-sporing, facultative anaerobe. It is a common cause of nosocomial infections in the United States. Enterococcal bacteremia is primarily a nosocomial infection in the medical intensive care unit (ICU), with a preference for elderly patients with multiple comorbidities. Material and methods This is a retrospective cohort study using the publicly accessible National (Nationwide) Inpatient Sample (NIS) database from October 2015 to December 2017. We examined data from 75,430 patients aged 18 years and older in the NIS who developed enterococcal bacteremia, as identified from the ICD-10 CM codes (B95), to discuss the epidemiologic effects and outcomes of enterococcal bacteremia. Patients were classified based on demographics, and comorbidities were identified. Three primary outcomes were studied: in-hospital mortality, length of stay, and healthcare cost. The secondary outcome was identifying any comorbidities associated with enterococcal bacteremia. Length of stay was defined as days from admission to discharge or death. Healthcare costs were estimated from the hospital perspective from hospital-level ratios of costs-tocharges. SAS 9.4 (2013; SAS Institute Inc., Cary, North Carolina, United States) was used for univariate and multivariate analyses. For data analysis, mortality was modeled using logistic regression. Length of stay and costs were modeled using linear regression, controlling for patient and hospital characteristics. Statistical analyses were performed using SAS. Statistical significance was defined as P<0.05. Results A total of 75,430 patients with enterococcal bacteremia were included in the study. Of this, 44,270 were males and 31,160 females. A total of 50,270 (68.67%) were Caucasians, 11,210 (15.31%) were African Americans, 6,445 (8.80%) were Hispanic and 2,025 (2.77%) were native Americans. Important comorbidities were congestive heart failure (25.91%), valvular disease (8.08%), neurological complications (11.87%), diabetes mellitus with complications (18.89%), renal failure (28.52%), and obesity (11.61%). In-hospital mortality was 11.07%, length of stay was 13.8 days, and a healthcare cost of 41,232.6 USD. Conclusions Enterococcal bacteremia is a nosocomial infection with a preference for the elderly with renal failure, cardiac failure, cardiac valvular diseases, stroke, obesity, and diabetes with complications. Further studies are needed to see whether the mortality caused by enterococcal bacteremia is attributable to comorbidities or to the bacteremia. It is associated with a more extended hospital stay and higher healthcare expenditure. Implementing contact precautions to contain the spread of methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus (VRE) has also checked the spread of enterococci. Further prospective studies can be planned using chart-based data.
... Demographic and clinical data, including age, gender, comorbidities, suspected infection source, organ failure, and blood culture were collected for each participants. The Sequential Organ Failure Assessment (SOFA) score and acute physiology and chronic health evaluation (APACHE IV) were calculated at the ICU admission 43,44 . Initial serum lactate levels were measured at shock recognition and we followed the lactate level at 6, 12 and 24 h from initial measurement. ...
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The aim of this study was to evaluate the prognostic value of the Lactate to Albumin (L/A) ratio compared to that of lactate and lactate clearance in predicting outcomes in patients with septic shock. This was a multi-center observational study of adult patients with septic shock, who admitted to intensive care units (ICUs) at Shohada and Imam Reza Hospitals, Tabriz, Iran, between Sept 2018 and Jan 2021. The area under the curve (AUC) of receiver operating characteristic (ROC) curve and multivariate logistic regression analyses were used to explore associations of the L/A ratio, lactate and lactate clearance on the primary (mortality) and secondary outcomes [ICU length of stay (LOS), duration of mechanical ventilation (MV), need of renal replacement therapy (RRT) and duration of using vasopressors] at baseline, 6 h and 24 h of septic shock recognition. Best performing predictive value for mortality were related to lactate clearance at 24 h, L/A ratio at 6 h and lactate levels at 24 h with (AUC 0.963, 95% CI 0.918–0.987, P < 0.001), (AUC 0.917, 95% CI 0.861–0.956, P < 0.001), and (AUC 0.904, 95% CI 0.845–0.946, P < 0.001), respectively. Generally, the lactate clearance at 24 h had better prognostic performance for mortality and duration of using vasopressor. However, the L/A ratio had better prognostic performance than serum lactate and lactate clearance for RRT, ICU LOS and MV duration.
... Outlier data were discarded in preprocessing, and the 60 variables included in the experiments were derived from patient information, laboratory results within 24 h of ICU stay, vital signs within 24 h of ICU stay, and net fluid balance over 24 h. These clinical variables were chosen based on previous studies [4,20,39], and the analysis intervals were set based on assessments of the typical severity of the disease [16,40]. In this study, we evaluated the performance of our proposed model using one timestamp fixed-length data and multiple timestamp series data. ...
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In the development of predictive models, the problem of missing data is a critical issue that traditionally requires a two-step analysis. Data scientists analyze the patterns of missing values, select variables, impute missing values on the basis of domain knowledge, and then train a model. Models typically have their input sizes hardcoded, and have limitations in handling data with high missing rates or changes in available variables. We propose an attention-based neural network combined with a novel real number representation, which requires little work on manually selecting variables, and in which missing data can be overlooked, making imputation unnecessary. In this proposed model, data analysis can be one step, omitting the first step of imputing missing values. The study included data on 32,709 intensive care unit (ICU) admissions and 60 healthcare variables from the Medical Information Mart for Intensive Care (MIMIC)-IV. The proposed algorithm yielded an area under the receiver operating characteristic curve (AUC) of 0.842 (95% CIs: 0.828-0.856) when predicting prolonged length of stay in the ICU, outperforming current approaches using imputation methods. The proposed algorithm can be applied to a range of problems in data science, as it addresses the issue of incomplete data with automatic variable selection.
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Optimal time for ICU diary delivery and impact on mental health (MH), anxiety-depression, post-traumatic stress symptoms (PTSS), quality of life (QOL), and memories is unclear. We evaluated the effect of ICU diaries, dispatched at different time points, on outcomes in an Indian cohort. Design: Double-blind randomized controlled trial. Setting: A 1,000-bedded teaching hospital in East India. Patients: Mechanically ventilated (>24 hr) adults were recruited, excluding those dead or incapable of meaningful-communication at discharge or follow-up. Eighty-three patients, aged 46.2 ± 17.2 years, Acute Physiology and Chronic Health Evaluation II scores 13.7 ± 4.9 were assessed. Length of ICU stay was 8.2 ± 7.1 days with 3.7 ± 3.2 ventilator days. Intervention: Of 820 screened, 164 had diaries created. Including photographs, diaries were comaintained by healthcare workers and family members. Ninety patients were randomized at 1-month follow-up: diary sent to 45 at 1 month (group ID1) and to 45 at 3 months (ID3). Measurements and main results: Anxiety-depression, memory, and QOL were assessed telephonically or home visits by a psychologist using the Hospital Anxiety-Depression Scale (HADS) and other tools at ICU discharge, 1-month (prerandomization), and 3 months of discharge. ID3 was reassessed after receiving diaries at 3.5 months. Primary outcome was anxiety-depression; secondary outcomes included PTSS, QOL, and memories. There was 100% follow-up. At 3 months, ID1 patients had a significant (p < 0.001) reduction in HADS from baseline when compared with ID3 that had not received diaries (4.16 ± 2.9 vs 2.15 ± 1.8; 95% CI, 2.8-1.2). PTSS scores were likewise better (p < 0.001). ID3 patients demonstrated significant improvement (p < 0.01) in QOL and memories along with HADS and PTSS when assessed at 3.5 months. Conclusions: ICU diaries improve MH but not QOL when delivered at 1 month and assessed 2 months thereafter. Assessed after 15 days, delayed exposure at 3 months significantly improved QOL and memories in addition to MH.
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