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Sex-specific outcome disparities in very old patients admitted to intensive care medicine: a propensity matched analysis

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Female and male very elderly intensive patients (VIPs) might differ in characteristics and outcomes. We aimed to compare female versus male VIPs in a large, multinational collective of VIPs with regards to outcome and predictors of mortality. In total, 7555 patients were included in this analysis, 3973 (53%) male and 3582 (47%) female patients. The primary endpoint was 30-day-mortality. Baseline characteristics, data on management and geriatric scores including frailty assessed by Clinical Frailty Scale (CFS) were documented. Two propensity scores (for being male) were obtained for consecutive matching, score 1 for baseline characteristics and score 2 for baseline characteristics and ICU management. Male VIPs were younger (83 ± 5 vs. 84 ± 5; p < 0.001), less often frail (CFS > 4; 38% versus 49%; p < 0.001) but evidenced higher SOFA (7 ± 6 versus 6 ± 6 points; p < 0.001) scores. After propensity score matching, no differences in baseline characteristics could be observed. In the paired analysis, the mortality in male VIPs was higher (mean difference 3.34% 95%CI 0.92–5.76%; p = 0.007) compared to females. In both multivariable logistic regression models correcting for propensity score 1 (aOR 1.15 95%CI 1.03–1.27; p = 0.007) and propensity score 2 (aOR 1.15 95%CI 1.04–1.27; p = 0.007) male sex was independently associated with higher odds for 30-day-mortality. Of note, male gender was not associated with ICU mortality (OR 1.08 95%CI 0.98–1.19; p = 0.14). Outcomes of elderly intensive care patients evidenced independent sex differences. Male sex was associated with adverse 30-day-mortality but not ICU-mortality. Further research to identify potential sex-specific risk factors after ICU discharge is warranted. Trial registration : NCT03134807 and NCT03370692; Registered on May 1, 2017 https://clinicaltrials.gov/ct2/show/NCT03370692 .
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Sex‑specic outcome disparities
in very old patients admitted
to intensive care medicine:
a propensity matched analysis
Bernhard Wernly1,2, Raphael Romano Bruno3, Malte Kelm3, Ariane Boumendil4,
Alessandro Morandi5,6, Finn H. Andersen7,8, Antonio Artigas9,10, Stefano Finazzi11,
Maurizio Cecconi12, Steen Christensen13, Loredana Faraldi14, Michael Lichtenauer1,
Johanna M. Muessig3, Brian Marsh15, Rui Moreno16, Sandra Oeyen17,
Christina Agvald Öhman18, Bernado Bollen Pinto19, Ivo W. Soliman20, Wojciech Szczeklik21,
David Niederseer22, Andreas Valentin23, Ximena Watson24, Susannah Leaver25,
Carole Boulanger26, Sten Walther27, Joerg C. Schefold28, Michael Joannidis29, Yuriy Nalapko30,
Muhammed Elhadi31, Jesper Fjølner32, Tilemachos Zafeiridis33, Dylan W. De Lange20,
Bertrand Guidet4,34,35, Hans Flaatten36,37 & Christian Jung3*
Female and male very elderly intensive patients (VIPs) might dier in characteristics and outcomes.
We aimed to compare female versus male VIPs in a large, multinational collective of VIPs with regards
OPEN
1Department of Cardiology, Paracelsus Medical University, Salzburg, Austria. 2Division of Cardiology, Department
of Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden. 3Department of Cardiology,
Pulmonology and Angiology, University Hospital, Moorenstraße 5, 40225 Duesseldorf, Germany. 4Service de
Réanimation Médicale, Publique-Hôpital de Paris, Hôpital Saint-Antoine, 75012 Paris, France. 5Department of
Rehabilitation, Hospital Ancelle Di Cremona, Cremona, Italy. 6Geriatric Research Group, Brescia, Italy. 7Department
of Anaesthesia and Intensive Care, Ålesund Hospital, Ålesund, Norway. 8Department of Circulation and
Medical Imaging, NTNU, Trondheim, Norway. 9Department of Intensive Care Medecine, CIBER Enfermedades
Respiratorias, Corporacion Sanitaria Universitaria Parc Tauli, Autonomous University of Barcelona, Sabadell,
Spain. 10Department of Intensive Care Medecine, University Hospitals Sagrado Corazón and General de Catalunya,
Quirón Salud, Barcelona-Sant Cugat, Spain. 11Dipartimento Di Epidemiologia Clinica, IRCCS Istituto Di Ricerche
Farmacologiche “Mario Negri”, Ranica, BG, Italy. 12Department of Anaesthesia IRCCS, Instituto Clínico Humanitas,
Humanitas University, Milan, Italy. 13Department of Anaesthesia and Intensive Care Medicine, Aarhus University
Hospital, Aarhus, Denmark. 14Grande Ospedale Metropolitano Niguarda, Milan, Italy. 15Misericordiae University
Hospital, Dublin, Ireland. 16Centro Hospitalar Universitário de Lisboa Central, Nova Médical School, Faculdade
de Ciências Médicas de Lisboa, Unidade de Cuidados Intensivos Neurocríticos E Trauma, Hospital de São José,
Lisbon, Portugal. 17Department of Intensive Care 1K12IC, Ghent University Hospital, Ghent, Belgium. 18Karolinska
University Hospital, Stockholm, Sweden. 19Geneva University Hospitals, Geneva, Switzerland. 20Department of
Intensive Care Medicine, University Medical Center, University Utrecht, Utrecht, The Netherlands. 21Intensive
Care and Perioperative Medicine Division, Jagiellonian University Medical College, Kraków, Poland. 22Department
of Cardiology, University Heart Center Zurich, University Hospital Zurich, University of Zurich, Zurich,
Switzerland. 23Kardinal Schwarzenberg Hospital, Schwarzach, Austria. 24St George’s University Hospital, London,
UK. 25Research Lead Critical Care Directorate St George’s Hospital, London, UK. 26NAHP Section ESICM,Intensive
Care Unit, Royal Devon & Exeter NHS Foundation Trust, Exeter, UK. 27Linkoping University Hospital, Linkoping,
Sweden. 28Inselspital, Bern University Hospital, Bern, Switzerland. 29Division of Intensive Care and Emergency
Medicine, Department of Internal Medicine, Medical University Innsbruck, Innsbruck, Austria. 30European Wellness
International, ICU, Luhansk, Ukraine. 31Alkhums Hospital, ICU, Tripoli, Libya. 32Department of Intensive Care,
Aarhus University Hospital, Aarhus, Denmark. 33Intensive Care Unit General Hospital of Larissa Tsakalof Larissa,
Larissa, Greece. 34Service de Réanimation, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique,
AP-HP, Sorbonne Universités, 75013 Paris, France. 35UMR_S 1136, Institut Pierre Louis D’Epidémiologie Et de
Santé Publique, INSERM, 75013 Paris, France. 36Department of Clinical Medecine, University of Bergen, Bergen,
Norway. 37Department of Anaestesia and Intensive Care, Haukeland University Hospital, Bergen, Norway. *email:
christian.jung@med.uni-duesseldorf.de
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to outcome and predictors of mortality. In total, 7555 patients were included in this analysis, 3973
(53%) male and 3582 (47%) female patients. The primary endpoint was 30‑day‑mortality. Baseline
characteristics, data on management and geriatric scores including frailty assessed by Clinical Frailty
Scale (CFS) were documented. Two propensity scores (for being male) were obtained for consecutive
matching, score 1 for baseline characteristics and score 2 for baseline characteristics and ICU
management. Male VIPs were younger (83 ± 5 vs. 84 ± 5; p < 0.001), less often frail (CFS > 4; 38% versus
49%; p < 0.001) but evidenced higher SOFA (7 ± 6 versus 6 ± 6 points; p < 0.001) scores. After propensity
score matching, no dierences in baseline characteristics could be observed. In the paired analysis,
the mortality in male VIPs was higher (mean dierence 3.34% 95%CI 0.92–5.76%; p = 0.007) compared
to females. In both multivariable logistic regression models correcting for propensity score 1 (aOR
1.15 95%CI 1.03–1.27; p = 0.007) and propensity score 2 (aOR 1.15 95%CI 1.04–1.27; p = 0.007) male
sex was independently associated with higher odds for 30‑day‑mortality. Of note, male gender was
not associated with ICU mortality (OR 1.08 95%CI 0.98–1.19; p = 0.14). Outcomes of elderly intensive
care patients evidenced independent sex dierences. Male sex was associated with adverse 30‑day‑
mortality but not ICU‑mortality. Further research to identify potential sex‑specic risk factors after
ICU discharge is warranted.
Trial registration: NCT03134807 and NCT03370692; Registered on May 1, 2017 https:// clini caltr ials.
gov/ ct2/ show/ NCT03 370692.
Patients 80years of age and older, who are admitted to the intensive care unit (ICU) consume a large propor-
tion of health care resources and yet continue to suer from high mortality13. Detailed knowledge of these very
elderly intensive patients (VIPs) could help to perform better risk stratication and ultimately guide clinicians
in whom to admit or whom not to admit to the ICU. e Clinical Frailty Scale (CFS), evaluating frailty through
a simple clinical assessment, has been shown to adequately risk-stratify such elderly patients4,5.
For several medical conditions, including acute myocardial infarction, gender outcome disparities have
been reported6. However, some studies investigated gender dierences in ICU patients, and have found distinct
dierences7,8. Male and female intensive care patients dier with regards to baseline characteristics, risk distribu-
tion and admission diagnoses and these dierences may inuence outcomes9,10. Male sex was linked to adverse
outcomes in a sub-set of VIPs with sepsis10,11. On the other hand, female sex was reported to be independently
associated with the decision to withdraw or withhold intensive care12. Recently, the FROG-ICU evaluated sur-
vival in critically ill patients and reported a trend towards higher survival in elderly women compared to male
patients13.
We, therefore, aimed to compare male versus female VIPs with regards to the distribution of risk factors,
potential dierences in management, and outcome as well as predictors of mortality with special emphasis on
frailty. e main goal with this study using data from two recent large, multinational studies of VIPs was to
compare male and female patients with regards to crude unadjusted und adjusted baseline characteristics and
outcomes4,14,15.
Methods
Study subjects. VIP1 and VIP2 were prospective, multicenter studies, registered on ClinicalTrials.gov
(ID: NTC03134807, NCT03370692). Both studies included very old intensive care patients (VIPs), dened as
patients admitted to an ICU and being aged 80years or older. ese patients have been analyzed in other con-
texts and methods and results have been published previously4,5,16. In summary, for VIP1, each participating ICU
could include either consecutive patients during three months or the rst 20 consecutive patients fullling the
inclusion criteria (all patients 80 of age or older). Data were collected between October 2016 and February 2017.
For VIP2, VIPs were included from May 2018 to May 2019. All methods were carried out in accordance with
relevant guidelines and regulations. All experimental protocols were approved by the local institutional and/or
licensing committees. Informed consent was obtained from all subjects if not omitted by the ethics vote.
In this post-hoc analysis of these two prospective trials, all patients admitted acutely (non-electively) with
complete data on age, gender, clinical frailty score (CFS) frailty score and sequential organ failure assessment
(SOFA) score and 30-day-mortality were included (Supplemental Fig.1). Elective patients from VIP1 were spe-
cically excluded as they signicantly dier from acutely admitted patients in risk distribution and outcomes
as previously shown17. e primary endpoint of this study was 30-day-mortality. Frailty was assessed by CFS
and the respective visual and simple description which were used with permission1820. For the patients of the
VIP2 trial Katz activities of daily living (Katz ADL) with ADL score 4 dening disability and Short form of
Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE), with IQCODE ≥ 3.5 dening cogni-
tive decline were assessed1820.
Statistical analysis. Continuous data points are expressed as mean ± standard deviation (SD) or
median ± interquartile range depending on distribution. Dierences between independent groups were calcu-
lated using student’s T-test or Mann Whitney U-test accordingly. Categorical data are expressed as numbers
(percentage). Chi-square test was applied to calculate dierences between groups and McNemar’s test for paired
survival data.
Two propensity scores for being male were calculated (Fig.1). Propensity score 1 included age (per year),
CFS score (per point), SOFA score (per point), location (Western Europe, Eastern Europe, Non-European) and
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admission diagnosis (respiratory failure, circulatory failure, combined respiratory and circulatory failure, sepsis,
multi-trauma with and without head injury, isolated head injury, intoxication, cerebral injury without trauma,
emergency surgery, other). Propensity score 2 included all items of propensity score 1 plus the non-baseline
variables use of vasoactive drugs, of renal replacement therapy, of intubation, of non-invasive ventilation (NIV)
as well as the decision to limit life-sustaining treatment (withdrawal and/or withholding). Two matched cohorts,
matching males 1:1 to females, for (1) propensity score 1 and (2) propensity score 2 were obtained using “nearest
neighbor” matching, the maximum allowed distance was a Δ in propensity score 1 or 2 of 0.001. e matching
signicantly reduced dierences in baseline characteristics and management.
Sensitivity analysis, analyzing only patients without treatment restrictions and European patients, was per-
formed. Univariable and multivariable logistic regression analysis was performed to assess associations with
treatment withdrawal and mortality. Odds ratios (OR) and adjusted odds ratios (aOR) with respective 95% con-
dence intervals (CI) were calculated. Two multivariable logistic regression models were built for the total cohort,
(1) using propensity score 1 and (2) using propensity score 2 as covariable. For the sub-group analysis assessing
associations of parameters with 30-day-mortality in male and female patients, variables with a p value < 0.10 in
the univariable analysis were included in the multivariable model, then a backward elimination was performed,
the elimination criterion was 0.10. All tests were two-sided, and a p value of < 0.05 was considered statistically
signicant. SPSS version 23.0 (IBM, USA) and MedCalc Statistical Soware version 19.1.3 (MedCalc Soware
bv, Ostend, Belgium; https:// www. medca lc. org; 2019) were used for all statistical analyses.
Ethics approval and consent to participate. A study protocol was provided to participating centers.
Every participating center obtained ethics approval according to local legislation. A copy of the ethics approval
was sent to the study coordinator before start of the study.
Consent for publication. Written informed consent was obtained of all included subjects, except for
patients from VIP2 of sites where study inclusion was explicitly granted without written informed consent.
Results
Study population. In total, 7555 patients were included in this analysis, 3973 (53%) male and 3582 (47%)
female patients. Admission diagnoses and baseline characteristics are presented in Table1. Male patients were
younger compared to female patients, with fewer male patients being over 90years of age (6% vs. 8%; p < 0.001).
Male patients were less oen frail (CFS > 4; 38% vs. 49%; p < 0.001) and less oen suered from disability
(ADL 4; 25% vs. 31%; p < 0.001), and cognitive decline (IQCODE 3.5; 29% vs. 36%; p < 0.001).
Rates of non-invasive ventilation usage (NIV; 25% vs. 24%; p = 0.29) did not dier between male and female
patients. Rates of intubation (53% vs. 48%; p < 0.001), renal replacement therapy (13% vs. 8%; p < 0.001) and
vasoactive drugs (60% vs. 57%; p = 0.003) were higher in male patients compared to females.
Organ failures as assessed by SOFA score was higher in male patients (7 ± 6 vs. 6 ± 6 points; p < 0.001) and the
length of ICU stay was longer (89 ± 154 vs. 72 ± 131h; p < 0.001).
e rates of life-sustainment limitation were similar (35% vs. 34%; p = 0.53). In multivariable logistic regres-
sion model, aer correction for propensity score 1, male gender was not independently associated with any
treatment limitation (aOR 0.92 95%CI 0.83–1.03; p = 0.14).
Survival analysis in the total cohort. In univariable analysis in the unbalanced total cohort, 30-day-
mortality was higher (43% vs. 39%; OR 1.18 95%CI 1.08–1.30; p < 0.001) in male patients compared to female
patients. In multivariable logistic regression models correcting for propensity score 1 (aOR 1.15 95%CI 1.03–
1.27; p = 0.007) as well as propensity score 2 (aOR 1.15 95%CI 1.04–1.27; p = 0.007) male gender was indepen-
dently associated with higher odds for 30-day-mortality. Also, aer adjustment for propensity score 2 and length
Figure1. Flow chart of the propensity-score matching process.
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of ICU stay, male sex (aOR 1.13 95%CI 1.03–1.24; p = 0.01) remained independently associated with higher odds
for 30-day-mortality.
In sensitivity analysis excluding patients with treatment limitation, aer correction for propensity score 1
male gender was independently associated with mortality (aOR 1.19 95%CI 1.04–1.38; p = 0.02) and remained so
in trend aer correction for propensity score 2 (aOR 1.15 95%CI 0.996–1.326; p = 0.056). In sensitivity analysis
excluding non-European countries, male gender was independently associated with higher rates of 30-day-
mortality aer correction for propensity score 1 (aOR 1.14 95%CI 1.03–1.26; p = 0.01) and propensity score 2
(aOR 1.14 95%CI 1.03–1.27; p = 0.01). Of note, male gender was not associated with ICU mortality (OR 1.08
95%CI 0.98–1.19; p = 0.14).
Matched‑cohort 1. Baseline characteristics of the matched-cohort 1 (matched on propensity score 1,
which included only baseline variables, see Fig.1) are given in Table2. Risk parameters were evenly distributed
between male and female patients, but rates of renal replacement therapy were higher (13% vs. 9%; p < 0.001) in
males as were lengths of ICU stay.
In the paired analysis, the mortality in male VIPs was higher (mean dierence 3.33% 95%CI 0.92–5.74%;
p = 0.007) compared to females. In univariable logistic regression, male gender was associated with higher odds
for 30-day-mortality (42% vs. 38%; OR 1.15 95%CI 1.04–1.27; p = 0.007). Again, male gender was not (OR 1.02
95%CI 0.92–1.14; p = 0.69) associated with intra-ICU mortality in this matched cohort.
Table 1. Baseline characteristics in the total cohort, male versus female VIPs. CFS Clinical Frailty Scale, SOFA
Sequential Organ Failure Assessment, ADL Activity of Daily Life measured with the Katz Index, IQCODE
Informant Questionnaire on COgnitive Decline in the Elderly, ICU intensive care unit, NIV non-invasive
ventilation, SD standard deviation.
Male Female
p valuen = 3973 n = 3582
Age
Median (± IQR) 83 (5) 84 (5) < 0.001
Age > 90 n (%) 227 (5.7%) 288 (8%) < 0.001
Frailty score—CFS
Median (± IQR) 4 (2) 4 (3) < 0.001
Frailty (CFS > 4) n (%) 1519 (38%) 1754 (49%) < 0.001
ADL
Median (± IQR) 6 (1) 6 (2) < 0.001
Disablitiy (ADL ≤ 4) 446 (25%) 489 (31%) < 0.001
IQCODE
Median (± IQR) 3.2 (0.6) 3.3 (0.8) 0.001
Cognitive decline (IQCODE ≥ 3.5) 455 (29%) 486 (36%) < 0.001
median (± IQR) 7 (6) 6 (6) < 0.001
ICU length of stay (hours)
median (± IQR) 89 (154) 72 (131) < 0.001
Treatment withdraw and/or withold (%) 1235 (35) 1342 (34) 0.53
NIV n (%) 933 (25%) 873 (24%) 0.54
Intubation n (%) 2108 (53%) 1728 (48%) < 0.001
Renal replacement therapy n (%) 530 (13%) 296 (8%) < 0.001
Vasoactive drugs n (%) 2397 (60%) 2038 (57%) 0.003
Admission diagnosis
Respiratory failure 928 (23%) 889 (25%)
< 0.001
Circulatory failure 577 (15%) 490 (14%)
Combined circulatory and respiratory failure 493 (12%) 395 (11%)
Sepsis 555 (14%) 451 (13%)
Multitrauma w/o head injury 82 (2%) 58 (2%)
Trauma with head injury 74 (2%) 57 (2%)
Head injury 100 (3%) 83 (2%)
Intoxication 12 (< 1%) 24 (1%)
Cerebral injury (non-traumatic) 231 (6%) 248 (7%)
Emergency surgery 442 (6%) 464 (13%)
Other 479 (12%) 423 (12%)
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Matched‑cohort 2. Table3 shows baseline characteristics of matched-cohort 2 (matched on propensity
score 2, which includes baseline variables and information on organ support as well as treatment limitations, see
Fig.1). Again, male patients evidenced longer ICU stays (p < 0.001).
Again, in the paired analysis, the mortality in male VIPs was higher (mean difference 3.34% 95%CI
0.92–5.76%; p = 0.007) compared to females. In univariable logistic regression, male gender was associated with
higher odds for 30-day-mortality (42% vs. 39%; aOR 1.15 95%CI 1.04–1.27; p = 0.007). Again, gender was not
associated with ICU mortality (OR 1.02 95%CI 0.92–1.14; p = 0.67) in this matched cohort.
Sub‑group analysis of female and male patients. e presence of frailty (CFS > 4) was associated
with increased 30-day-mortality in male patients (OR 1.73 95%CI 1.52–1.97; p < 0.001) and remained so in
multivariable logistic regression (Table4a).
In female patients frailty (CFS > 4) was associated with 30-day mortality in univariable analysis (OR 1.65
95%CI 1.44–1.89; p < 0.001) and remained so aer correction in multivariable logistic regression (Table4b).
Furthermore, one-point increases of CFS, as well as SOFA, were independently associated with increased odds
for 30-day-mortality in multivariable logistic regression in male (Table4a) as well as in female (Table4b) VIPs.
Table 2. Baseline characteristics in the matched cohort 1, male versus female VIPs. CFS Clinical Frailty
Scale, SOFA Sequential Organ Failure Assessment, ADL Activity of Daily Life measured with the Katz Index,
IQCODE Informant Questionnaire on COgnitive Decline in the Elderly, ICU intensive care unit, NIV non-
invasive ventilation, SD standard deviation.
Male Female
p valuen = 3183 n = 3183
Age
Median (± IQR) 84 (6) 84 (6) 0.91
Age > 90 n (%) 207 (7%) 195 (6%) 0.57
Frailty score—CFS
Median (± IQR) 4 (3) 4 (3) 0.94
Frailty (CFS > 4) n (%) 1379 (43%) 1409 (44%) 0.46
ADL
Median (± IQR) 6 (2) 6 (2) 0.40
Disablitiy (ADL ≤ 4) 400 (28%) 375 (27%) 0.56
IQCODE
Median (± IQR) 3.3 (0.7) 3.3 (0.7) 0.92
Cognitive decline (IQCODE ≥ 3.5) 404 (32%) 404 (33%) 0.49
SOFA score
Median (± IQR) 7 (6) 6 (6) 0.19
ICU length of stay (hours)
Median (± IQR) 86 (151) 72 (132) < 0.001
Treatment withdraw and/or withold (%) 1054 (33%) 1111 (35%) 0.15
NIV n (%) 789 (25%) 784 (25%) 0.88
Intubation n (%) 1623 (51%) 1559 (49%) 0.10
Renal replacement therapy n (%) 397 (13%) 277 (9%) < 0.001
Vasoactive drugs n (%) 1846 (58%) 1850 (58%) 0.92
Admission diagnosis
Respiratory failure 783 (25%) 786 (25%)
0.99
Circulatory failure 445 (14%) 449 (14%)
Combined circulatory and respiratory failure 353 (11%) 356 (11%)
Sepsis 413 (13%) 410 (13%)
Multitrauma w/o head injury 63 (2%) 55 (2%)
Trauma with head injury 52 (2%) 55 (2%)
Head Injury 78 (3%) 74 (2%)
Intoxication 8 (< 1%) 14 (< 1%)
Cerebral injury (non-traumatic) 203 (6%) 199 (6%)
Emergency surgery 393 (12%) 391 (12%)
Other 392 (12%) 391 (12%)
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Discussion
In this post-hoc analysis of a large group of VIPs included in two international ICU prospective studies, dif-
ferences in the distribution of baseline characteristics and risk factors between male and female patients could
be found. Further, male sex was associated with increased 30-day-mortality in VIPs and remained so aer
propensity-score adjustments for both baseline characteristics alone and baseline characteristics as well as in-ICU
variables. However, sex was not associated with ICU-mortality, neither in the total cohort nor in the adjusted
matched cohorts.
Frailty assessed by CFS was independently associated with 30-day-mortality both in male and female patients
aer adjustment for baseline risk factors. erefore, CFS could safely be integrated in guiding pre-ICU triage as
well as intra-ICU triage both in male and female patients.
Male and female patients diered with regards to baseline characteristics, management, and outcomes. Male
VIPs in this cohort were younger and evidenced lower rates of frailty, disability and cognitive impairment. On the
other hand, male patients were clinically sicker as expressed by higher SOFA scores. Consequently, unadjusted
30-day-mortality was higher in male compared to female VIPs. Aer adjustment for baseline characteristics,
except for rates of renal replacement therapy, there were no dierences in the management of organ support
between male and female patients. Of note, there are recent data indicating higher susceptibility of kidney to
injury in male epithelial cells as compared to female21. Importantly, the rates of treatment limitation did not
Table 3. Baseline characteristics in the matched cohort 2, male versus female VIPs. CFS Clinical Frailty Scale,
SOFA sequential organ failure assessment, ADL Activity of Daily Life measured with the Katz Index, IQCODE
Informant Questionnaire on COgnitive Decline in the Elderly, ICU intensive care unit, NIV Non-invasive
ventilation, SD standard deviation.
Male Female
p valuen = 3142 n = 3142
Age
Mean (± SD) 84 (5) 84 (6) 0.61
Age > 90 n (%) 213 (7%) 207 (7%) 0.80
Frailty score—CFS
Mean (± SD) 4 (3) 4 (3) 0.60
Frailty (CFS > 4) n (%) 1355 (43%) 1406 (45%) 0.20
ADL
Mean (± SD) 6 (2) 6 (2) 0.40
Disablitiy (ADL ≤ 4) 390 (27%) 366 (27%) 0.73
IQCODE
Mean (± SD) 3.2 (0.7) 3.3 (0.7) 0.41
Cognitive decline (IQCODE ≥ 3.5) 392 (32%) 390 (33%) 0.38
SOFA score
Mean (± SD) 7 (6) 6 (6) 0.48
ICU length of stay (hours)
Mean (± SD) 78 (136) 72 (133) 0.007
Treatment withdraw and/or withold (%) 1077 (34%) 1080 (34%) 0.96
NIV n (%) 779 (25%) 792 (25%) 0.73
Intubation n (%) 1566 (50%) 1548 (49%) 0.67
Renal replacement therapy n (%) 287 (9%) 285 (9%) 0.93
Vasoactive drugs n (%) 1825 (58%) 1819 (58%) 0.90
Admission diagnosis
Respiratory failure 766 (24%) 781 (25%)
Circulatory failure 453 (14%) 441 (14%)
Combined circulatory and respiratory failure 361 (12%) 362 (12%)
Sepsis 406 (13%) 418 (13%)
Multitrauma w/o head injury 53 (2%) 57 (2%)
Trauma with head injury 51 (2%) 50 (2%)
Head injury 79 (3%) 80 (3%)
Intoxication 7 (< 1%) 7 (< 1%)
Cerebral injury (non-traumatic) 200 (6%) 195 (6%)
Emergency surgery 397 (13%) 375 (12%)
Other 369 (12%) 376 (12%)
Other 369 (12%) 376 (12%)
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dier between male and female VIPs, nor aer adjustment in multivariable analysis in the total cohort neither
in the propensity-matched cohorts.
However, aer matching and adjustment for both baseline characteristics alone as well as baseline character-
istics plus ICU management, male gender was still independently associated with increased 30-day-mortality
in this analysis. Further, male gender remained independently associated with increased 30-day-mortality in a
sensitivity analysis excluding patients with treatment limitations. Importantly, these results conrm observed
trends in a recent sub-study of the FROG-ICU study: Hollinger etal. reported increased survival rates in mod-
erately elderly women compared to men, whereas in the overall cohort consisting of more than 2000 critically ill
patients no sex-related dierences in outcomes could be found13. ese ndings, relating male gender to adverse
outcomes, are consistent with previous studies reporting adverse outcomes in male septic VIPs10. On the other
hand, this trend in gender dierence was not observed for illness-adjusted mortality in a large Austrian cohort
study on 25,998 patients without age-restriction22. erefore, the observed sex dierences in mortality could
be age-dependent.
Several factors could contribute to this nding. Certainly, bias and lack of data need to be considered,
although extensive adjustment for baseline characteristics as well as treatment management was performed
using propensity scores. However, importantly, only adjustment to available and known covariables is possible.
First, this study lacks extensive data on comorbidities, which probably inuence management and outcome23.
However, adjustments for frailty, which is associated with the amount and extent of comorbidities, were per-
formed. Second, further sensitivity analysis and adjustment on both macro- microcirculatory parameters could
have improved our understanding of this cohort as men have a shorter life expectancy and die at a younger age:
eir bodies are more worn at a same age which could be underestimated in categorical datasets, like SOFA and
CFS: continuous data (like biomarkers) could pick up this dierence24. Especially biomarkers such as lactate con-
centration might help to further explain the ndings—on the other hand, male sex was independently associated
with increased mortality aer correction for baseline variables including SOFA score which integrates clinical
ndings and laboratory values25. Also, other important biomarkers such as serum levels of albumin and blood
urine nitrogen could contribute to the observed sex specic dierences in outcome, but were not available for
this dataset, which is a limitation26. ird, this cohort of VIPs was not designed to evaluate gender-related dier-
ences and, therefore, this analysis remains of retrospective and thesis-generating character per se. Fourth, other
potential confounders, such as smoking status or socioeconomic data are lacking, which is another limitation27.
Fih, we observed a sex-specic dierence in 30-day-mortality, but not in ICU mortality. We speculate, that this
could be due to sex-specic dierences in management and treatment aer discharge from ICU. However, we
do not have any data available to support this notion, which, therefore, remains speculative. As the overall event
rate increases from ICU mortality to the 30-day-mortality increases, sex-specic outcome dierences could be
present at ICU discharge, but our dataset be underpowered to detect these dierences. Still, to our knowledge,
this study constitutes the largest cohort of VIPs reporting gender-related outcomes. erefore, we think that this
strong signal towards adverse outcomes in male VIPs must be taken seriously.
Several biological and non-biological factors could inuence gender-related outcomes. Males and females
are known to dier in genetic, endocrine, and immunological factors13,28. Sex-specic treatment algorithms
and ICU management could contribute to minimizing the observed gender disparities in VIPs. Further, male
Table 4. Associations of relevant factors with 30-day mortality in (a) male patients and (b) female patients.
OR odds ratio, aOR adjusted OR, SOFA Sequential Organ Failure Assessment, CFS Clinical Frailty Scale.
Univariable Multivariable
OR 95%CI p value aOR 95%CI p value
a
Male patients
Age (per year) 1.04 1.02–1.05 < 0.001 1.03 1.01–1.05 0.02
SOFA (per point) 1.18 1.16–1.20 < 0.001 1.11 1.08–1.13 < 0.001
Frailty (per CFS point) 1.21 1.16–1.25 < 0.001 1.13 1.09–1.18 < 0.001
Vasoactive drug (yes vs. no) 2.44 2.13–2.79 < 0.001 0.98 0.81–1.19 0.87
Intubation (yes vs. no) 2.75 2.41–3.14 < 0.001 2.34 1.97–2.78 < 0.001
Renal replacement therapy (yes vs. no) 2.05 1.71–2.47 < 0.001 1.58 1.27–1.98 0.001
Treatment withdrawal or withholding (yes vs. no) 9.02 7.74–10.51 < 0.001 8.99 7.62–10.61 < 0.001
b
Female patients
Age (per year) 1.02 1.002–1.038 0.03 1.02 0.99–1.04 0.17
SOFA (per point) 1.22 1.19–1.14 < 0.001 1.14 1.11–1.17 < 0.001
Frailty (per CFS point) 1.22 1.17–1.27 < 0.001 1.16 1.10–1.21 < 0.001
Vasoactive drug (yes/no) 3.09 2.67–3.57 < 0.001 1.27 1.03–1.55 0.02
Intubation (yes/no) 3.63 3.15–4.18 < 0.001 2.53 2.08–3.07 < 0.001
Renal replacement therapy (yes/no) 3.52 2.73–4.52 < 0.001 3.34 1.74–3.15 < 0.001
Treatment withdrawal or withholding (yes/no) 6.95 5.96–8.10 < 0.001 8.15 6.83–9.72 < 0.001
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and female patients could dier in post-ICU discharge factors. Socioeconomic factors beyond the scope of this
study could inuence outcomes29. Males and females are known to dier in their readiness to assume risk and
especially aer an ICU stay, gender-specic complications such as falls might in part explain observed distinct
outcomes30,31. is notion is supported by the nding that although mortality was consistently higher in males,
ICU-mortality was similar between males and females, both in the unadjusted and adjusted cohorts. e benet
of intensive care in VIP is controversial in general 32. VIPs are known to suer from high mortality aer surviving
the initial ICUstay32. Based on our data, male patients might be particularly prone to die aer ICU discharge as
ICU mortality was similar between genders, but 30-day-mortality independently associated with male gender.
is nding could have several implications. First, male gender could be interpreted as an independent risk
factor and inuence management decisions. Second, if male VIPs are admitted to ICU and survive, post-ICU
management could be particularly important in male patients. Specic geriatric ICUs and discharge to specialist
geriatric wards, as well as close interdisciplinary collaboration with social workers and integration of the patient’s
family, could further improve outcomes in both genders, but especially males. erefore, not only gender-specic
ICU treatment but also post-ICU management could help to improve outcomes in general and reduce observed
gender disparities in VIPs.
Conclusion
Outcomes of elderly intensive care patients evidenced independent sex dierences. Male sex was associated with
adverse 30-day-mortality but not ICU-mortality. Further research to identify potential sex-specic risk factors
aer ICU discharge is warranted.
Data availbility
No additional data available. All data relevant for this study will be given by the authors upon specic request.
Received: 5 June 2020; Accepted: 8 October 2020
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Acknowledgements
e full list of members of the VIP2 study group can be found in the accompanying Supplementary Informa-
tion le.
Author contributions
B.W. and R.R.B and CJ and H.F. and B.G and D.D.L wrote the rst dra of the main manuscript text and prepared
the Figures and Tables. All authors are involved in some work of the manuscript. All authors provided critical
revision of the manuscript..
Funding
Open Access funding enabled and organized by Projekt DEAL. No (industry) sponsorship has been received
for this investigator-initiated study.
Competing interests
e authors declare no competing interests.
Additional information
Supplementary information is available for this paper at https:// doi. org/ 10. 1038/ s41598- 020- 74910-3.
Correspondence and requests for materials should be addressed to C.J.
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... Twelve (n = 12, 20.6) studies exclusively used this approach [2, 18-23, 27, 58-61], without using any additional frailty score. Ten studies [10,30,33,34,37,39,46,47,52,56] only assessed functional status for follow-up, after assessing frailty at the time of hospitalization. ...
... In some studies, the pre-ICU frailty assessment was retrospectively assessed as based on data which were routinely documented for other purposes and not specifically collected for frailty measurement [56-58, 60, 61, 64, 67, 70, 72]. In these studies, the pre-ICU frailty assessment had either been reconstructed from the staff notes from the clinic where the patients were hospitalized [57,64,70] or was based on external datasets containing medical records of inpatients and outpatients, skilled nursing facilities, home health agencies, nursing homes, and permanent medical equipment [58,60,67,72], In one study [61], pre-ICU frailty status was adopted from a national registry, and in two cases [54,56], it was extracted from another study. In the remaining studies, a pre-ICU frailty or functional performance assessment was carried out at the unit where the patient was hospitalized previous to ICU admission, but without specifying exactly the method at the time of triage [2], time of inclusion [22,42], or at time of ICU admission [33,39,45]. ...
Article
Introduction: As new treatments have become established, more frail pre-ICU patients are being admitted to intensive care units (ICUs); this is creating new challenges to provide adequate care and to ensure that resources are allocated in an ethical and economical manner. This systematic review evaluates the current standard for assessing frailty on the ICU, including methods of assessment, time point of measurements, and cut-offs. Methods: A systematic search was conducted on MEDLINE, Clinical Trials, Cochrane Library, and Embase. Randomized and non-randomized controlled studies were included that evaluated diagnostic tools and ICU outcomes for frailty. Exclusion criteria were the following: studies without baseline assessment of frailty on ICU admission, studies in paediatric patients or pregnant women, and studies that targeted very narrow populations of ICU patients. Eligible articles were included until January 31, 2021. Methodological quality was assessed using the Newcastle-Ottawa Scale. No meta-analysis was performed, due to heterogeneity. Results: N = 57 articles (253,376 patients) were included using 19 different methods to assess frailty or a surrogate. Frailty on ICU admission was most frequently detected using the Clinical Frailty Scale (CFS) (n = 35, 60.3%), the Frailty Index (n = 5, 8.6%), and Fried's frailty phenotype (n = 6, 10.3%). N = 22 (37.9%) studies assessed functional status. Cut-offs, time points, and manner of baseline assessment of frailty on ICU admission varied widely. Frailty on ICU admission was associated with short- and long-term mortality, functional and cognitive impairment, increased health care dependency, and impaired quality of life post-ICU discharge. Conclusions: Frailty assessment on the ICU is heterogeneous with respect to methods, cut-offs, and time points. The CFS may best reflect frailty in the ICU. Frailty assessments should be harmonized and performed routinely in the critically ill.
... It also goes hand in hand with a higher risk for infections and sepsis, which is another common clinical challenge associated with high morbidity and mortality [3][4][5]. A better understanding of subgroups at higher risk could therefore contribute to improved patient care [6][7][8][9][10][11]. The pathogenesis and optimal treatment of septic patients is the subject of intensive research, whereas mortality remains high and an often limited functional capacity in surviving patients remains a challenge [6,[12][13][14]. ...
Article
Full-text available
Background Higher survival has been shown for overweight septic patients compared with normal or underweight patients in the past. This study aimed at investigating the management and outcome of septic ICU patients in different body mass index (BMI) categories in a large multicenter database. Methods In total, 16,612 patients of the eICU collaborative research database were included. Baseline characteristics and data on organ support were documented. Multilevel logistic regression analysis was performed to fit three sequential regression models for the binary primary outcome (ICU mortality) to evaluate the impact of the BMI categories: underweight (<18.5 kg/m ² ), normal weight (18.5 to < 25 kg/m ² ), overweight (25 to < 30 kg/m ² ) and obesity (≥ 30 kg/m ² ). Data were adjusted for patient level characteristics (model 2) as well as management strategies (model 3). Results Management strategies were similar across BMI categories. Underweight patients evidenced higher rates of ICU mortality. This finding persisted after adjusting in model 2 (aOR 1.54, 95% CI 1.15–2.06; p = 0.004) and model 3 (aOR 1.57, 95%CI 1.16–2.12; p = 0.003). No differences were found regarding ICU mortality between normal and overweight patients (aOR 0.93, 95%CI 0.81–1.06; p = 0.29). Obese patients evidenced a lower risk of ICU mortality compared to normal weight, a finding which persisted across all models (model 2: aOR 0.83, 95%CI 0.69–0.99; p = 0.04; model 3: aOR 0.82, 95%CI 0.68–0.98; p = 0.03). The protective effect of obesity and the negative effect of underweight were significant in individuals > 65 years only. Conclusion In this cohort, underweight was associated with a worse outcome, whereas obese patients evidenced lower mortality. Our analysis thus supports the thesis of the obesity paradox.
... In very old patients, mortality was higher in female patients and in those who did not receive mechanical ventilation or vasopressors. We are aware of the limitations of subgroup analyses (44), and we demonstrated recently that there were no clinically relevant differences between the sexes in septic patients (45,46). However, the trend toward a higher mortality in patients that did not receive intubation or vasopressors could reflect a more restrictive use of this therapy in very old patients. ...
Article
Purpose: Old (>64 years) and very old (>79 years) intensive care patients with sepsis have a high mortality. In the very old, the value of critical care has been questioned. We aimed to compare the mortality, rates of organ support, and the length of stay in old vs. very old patients with sepsis and septic shock in intensive care. Methods: This analysis included 9,385 patients, from the multi-center eICU Collaborative Research Database, with sepsis; 6184 were old (aged 65–79 years), and 3,201 were very old patients (aged 80 years and older). A multi-level logistic regression analysis was used to fit three sequential regression models for the binary primary outcome of ICU mortality. A sensitivity analysis in septic shock patients ( n = 1054) was also conducted. Results: In the very old patients, the median length of stay was shorter (50 ± 67 vs. 56 ± 72 h; p < 0.001), and the rate of a prolonged ICU stay was lower (>168 h; 9 vs. 12%; p < 0.001) than the old patients. The mortality from sepsis was higher in very old patients (13 vs. 11%; p = 0.005), and after multi-variable adjustment being very old was associated with higher odds for ICU mortality (aOR 1.32, 95% CI 1.09–1.59; p = 0.004). In patients with septic shock, mortality was also higher in the very old patients (38 vs. 36%; aOR 1.50, 95% CI 1.10–2.06; p = 0.01). Conclusion: Very old ICU-patients suffer from a slightly higher ICU mortality compared with old ICU-patients. However, despite the statistically significant differences in mortality, the clinical relevance of such minor differences seems to be negligible.
Chapter
Probably the most frequently reported outcome in healthcare in general, and in intensive care in particular, is survival or its counterpart mortality. Obviously, other patient-centered outcomes are very often connected and even dependent on a patient that survives. It makes no meaning to talk about quality of life in patients not surviving the ICU stay, but for survivors post-hospital discharge, other issues than merely survival become more and more important.
Chapter
Learning objectives of this chapter is to review existent risk score applicable to the very old patient. Problems, challenges and ongoing developments are discussed, with particular emphasis on the importance of previous health status over the presence and degree of physiological derangements in this particular population when developing or applying one of these methods.
Article
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Adverse patient safety events, unintended injuries resulting from medical therapy, were associated with 110,000 deaths in the United States in 2019. A nationwide pandemic (such as COVID-19) further challenges the ability of healthcare systems to ensure safe medication use and the pandemic’s effects on safety events remain poorly understood. Here, we investigate drug safety events across demographic groups before and during a pandemic using a dataset of 1,425,371 reports involving 2,821 drugs and 7,761 adverse events. Among 64 adverse events identified by our analyses, we find 54 increased in frequency during the pandemic, despite a 4.4% decrease in the total number of reports. Out of 53 adverse events with a pre-pandemic gender gap, 33 have seen their gap increase with the pandemic onset. We find that the number of adverse events with an increased reporting ratio is higher in adults (by 16.8%) than in older patients. Our findings have implications for safe medication use and preventable healthcare inequality in public health emergencies.
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En esta colección de artículos nos hemos sumido en el reconocimiento del desconocimiento. Los patrones y protocolos nos sirven de mucho en esta disciplina tan pragmática como es la medicina, siempre y cuando no perdamos de vista que acabaremos teniendo delante una persona, con muchas facetas, sorpresas y que nos habremos de rendir ante lo que la persona desea y espera. Demasiados años generalizando, atribuyendo un determinado peso, raza a nuestros pacientes. Una determinada respuesta frente al infortunio o las malas noticias. El patrón durante mucho tiempo ha sido medicina para hombres, hecha por hombres, hasta el punto de golpearnos indefectiblemente contra el muro si persistimos esta metódica en lugar de mostrar un sano desconocimiento y una más aún sana capacidad de duda. La explosiva y afortunada diversidad nos lleva a reconsiderar el lenguaje, los datos sociodemográficos. Los siguientes artículos, preparados con extremado cuidado y afecto por nuestras compañeras nos enriquecen con dudas y aristas. Aportan conocimiento y también incerteza. Dos aspectos que nos han de permitir avanzar en nuestro servicio a las personas. Como se nos muestran, como esperan ser consideradas.
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Adverse patient safety events were associated with 110 thousand deaths in the U.S. alone in 2019. The COVID-19 pandemic has further challenged the ability of healthcare systems to ensure medication safety, and its effects on patient safety remain unknown. Here, we investigate negative outcomes associated with medication use before and during the pandemic. Using a dataset of 10,443,476 reports involving 3,624 drugs and 19,193 adverse events, we develop an algorithmic approach to analyze the pandemic's impact on incidence of drug safety events by evaluating disproportional reporting relative to the pre-pandemic time, quantifying unexpected trends in clinical outcomes, and adjusting for drug interference. Among 64 adverse events identified by our analyses, we find 54 have increased incidence rates during the pandemic, even though reporting of adverse events has decreased by 4.4% overall. We find clinically relevant differences in drug safety outcomes between demographic groups. Comparing to male patients, women report 47.0% more distinct adverse events whose occurrence significantly increased during the pandemic relative to pre-pandemic levels. Out of 53 adverse events with the pre-pandemic gender gap, 33 have increased gap during the pandemic more than would have been expected had the pandemic not occurred. While musculoskeletal and metabolic side effects are disproportionately enriched in women during the pandemic, immune-related adverse events are enriched only in men. We also find the number of adverse events with a higher reporting ratio during the pandemic in adults is higher (16.8%) than in older patients (adjusted for population size). Our findings have implications for safe medication use and public health policy and highlight the role of variation in adverse events for improving patient safety during a public health emergency.
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Background The average age at which people start smoking has been decreasing in many countries, but insufficient evidence exists on the adult hazards of having started smoking in childhood and, especially, in early childhood. We aimed to investigate the association between smoking habits (focusing on the age when smokers started) and cause-specific premature mortality in a cohort of adults in Cuba. Methods For this prospective study, adults were recruited from five provinces in Cuba. Participants were interviewed (data collected included socioeconomic status, medical history, alcohol consumption, and smoking habits) and had their height, weight, and blood pressure measured. Participants were followed up until Jan 1, 2017 for cause-specific mortality; a subset was resurveyed in 2006–08. We used Cox regression to calculate adjusted rate ratios (RRs) for mortality at ages 30–69 years, comparing never-smokers with current smokers by age they started smoking and number of cigarettes smoked per day and with ex-smokers by the age at which they had quit. Findings Between Jan 1, 1996, and Nov 24, 2002, 146 556 adults were recruited into the study, of whom 118 840 participants aged 30–69 years at recruitment contributed to the main analyses. 27 264 (52%) of 52 524 men and 19 313 (29%) of 66 316 women were current smokers. Most participants reported smoking cigarettes; few smoked only cigars. About a third of current cigarette smokers had started before age 15 years. Compared with never-smokers, the all-cause mortality RR was highest in participants who had started smoking at ages 5–9 years (RR 2·51, 95% CI 2·21–2·85), followed by ages 10–14 years (1·83, 1·72–1·95), 15–19 years (1·56, 1·46–1·65), and ages 20 years or older (1·50, 1·39–1·62). Smoking accounted for a quarter of all premature deaths in this population, but quitting before about age 40 years avoided almost all of the excess mortality due to smoking. Interpretation In this cohort of adults in Cuba, starting to smoke in childhood was common and quitting was not. Starting in childhood approximately doubled the rate of premature death (ie, before age 70 years). If this 2-fold mortality RR continues into old age, about half of participants who start smoking before age 15 years and do not stop will eventually die of complications from their habit. The greatest risks were found among adults who began smoking before age 10 years. Funding UK Medical Research Council, Cancer Research UK, British Heart Foundation, US Centers for Disease Control and Prevention (CDC) Foundation (with support from Amgen).
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Background: Lymphopenic patients with community-acquired pneumonia (CAP) have shown high mortality rates. Corticosteroids have immunomodulatory properties and regulate cytokine storm in CAP. However, it is not known whether their modulatory effect on cytokine secretion differs in lymphopenic and non-lymphopenic patients with CAP. Therefore, we aimed to test whether the presence of lymphopenia may modify the response to corticosteroids (mainly in C reactive protein (CRP)) in patients with severe CAP and high inflammatory status). Methods: A post hoc analysis of a randomized controlled trial [1] (NCT00908713) which evaluated the effect of corticosteroids in patients with severe CAP and high inflammatory response (CRP > 15 mg/dL). Patients were clustered according to the presence of lymphopenia (lymphocyte count below 1000 cell/mm3). Results: At day 1, 35 patients (59%) in the placebo group presented with lymphopenia, compared to 44 patients (73%) in the corticosteroid group. The adjusted mean changes from day 1 showed an increase of 1.19 natural logarithm (ln) cell/mm3 in the corticosteroid group and an increase of 0.67 ln cell/mm3 in the placebo group (LS mean difference of the changes in ln (methylprednisolone minus placebo) 0.51, 95%CI (0.02 to 1.01), p = 0.043). A significant effect was also found for the interaction (p = 0.043) between corticosteroids and lymphopenia in CRP values at day 3, with lower values in patients without lymphopenia receiving corticosteroids after adjustments for potential confounders. Conclusion: In this exploratory post hoc analysis from ramdomized controlled trial (RCT) data, the response to corticosteroids, measured by CRP, may differ according to lymphocyte count. Further larger studies are needed to confirm this data.
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Background: Little is known about risk and prognostic factors in very old patients developing sepsis secondary to community-acquired pneumonia (CAP). Methods: We conducted a retrospective observational study of data prospectively collected at the Hospital Clinic of Barcelona over a 13-year period. Consecutive patients hospitalized with CAP were included if they were very old (≥80 years) and divided into those with and without sepsis for comparison. Sepsis was diagnosed based on the Sepsis-3 criteria. The main clinical outcome was 30-day mortality. Results: Among the 4219 patients hospitalized with CAP during the study period, 1238 (29%) were very old. The prevalence of sepsis in this age group was 71%. Male sex, chronic renal disease, and diabetes mellitus were independent risk factors for sepsis, while antibiotic therapy before admission was independently associated with a lower risk of sepsis. Thirty-day and intensive care unit (ICU) mortality did not differ between patients with and without sepsis. In CAP-sepsis group, chronic renal disease and neurological disease were independent risk factors for 30-day mortality. Conclusion: In very old patients hospitalized with CAP, in-hospital and 1-year mortality rates were increased if they developed sepsis. Antibiotic therapy before hospital admission was associated with a lower risk of sepsis.
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Purpose: Few studies analyzed gender-related outcome differences of critically ill patients and found inconsistent results. This study aimed to test the independent association of gender and long-term survival of ICU patients. Materials and methods: FROG-ICU was a prospective, observational, multi-center cohort designed to investigate the long-term mortality of critically ill adult patients. The primary endpoint of this study was 1-year mortality after ICU admission of women compared to men. Results: The study included 2087 patients, 726 women and 1361 men. Women and men had similar baseline characteristics, clinical presentation, and disease severity. No significant difference in 1-year mortality was found between women and men (34.9% vs. 37.9%, P = 0.18). After multivariable adjustment, no difference in the hazard of death was observed [HR 0.99 (95% CI 0.77-1.28)]. Similar 1-year survival between women and men was found in a propensity score-matched patient cohort of 506 patients [HR 0.79 (95% CI 0.54-1.14)]. Conclusion: Women constituted one-third of the population of critically ill patients and were unexpectedly similar to men regarding demographic characteristics, clinical presentation, and disease severity and had similar risk of death at 1 year after ICU admission. Trial registration ClinicalTrials.gov NCT01367093; registered on June 6, 2011.
Article
Purpose Premorbid conditions affect prognosis of acutely-ill aged patients. Several lines of evidence suggest geriatric syndromes need to be assessed but little is known on their relative effect on the 30-day survival after ICU admission. The primary aim of this study was to describe the prevalence of frailty, cognition decline and activity of daily life in addition to the presence of comorbidity and polypharmacy and to assess their influence on 30-day survival. Methods Prospective cohort study with 242 ICUs from 22 countries. Patients 80 years or above acutely admitted over a six months period to an ICU between May 2018 and May 2019 were included. In addition to common patients’ characteristics and disease severity, we collected information on specific geriatric syndromes as potential predictive factors for 30-day survival, frailty (Clinical Frailty scale) with a CFS > 4 defining frail patients, cognitive impairment (informant questionnaire on cognitive decline in the elderly (IQCODE) with IQCODE ≥ 3.5 defining cognitive decline, and disability (measured the activity of daily life with the Katz index) with ADL ≤ 4 defining disability. A Principal Component Analysis to identify co-linearity between geriatric syndromes was performed and from this a multivariable model was built with all geriatric information or only one: CFS, IQCODE or ADL. Akaike’s information criterion across imputations was used to evaluate the goodness of fit of our models. Results We included 3920 patients with a median age of 84 years (IQR: 81–87), 53.3% males). 80% received at least one organ support. The median ICU length of stay was 3.88 days (IQR: 1.83–8). The ICU and 30-day survival were 72.5% and 61.2% respectively. The geriatric conditions were median (IQR): CFS: 4 (3–6); IQCODE: 3.19 (3–3.69); ADL: 6 (4–6); Comorbidity and Polypharmacy score (CPS): 10 (7–14). CFS, ADL and IQCODE were closely correlated. The multivariable analysis identified predictors of 1-month mortality (HR; 95% CI): Age (per 1 year increase): 1.02 (1.–1.03, p = 0.01), ICU admission diagnosis, sequential organ failure assessment score (SOFA) (per point): 1.15 (1.14–1.17, p < 0.0001) and CFS (per point): 1.1 (1.05–1.15, p < 0.001). CFS remained an independent factor after inclusion of life-sustaining treatment limitation in the model. Conclusion We confirm that frailty assessment using the CFS is able to predict short-term mortality in elderly patients admitted to ICU. Other geriatric syndromes do not add improvement to the prediction model. Since CFS is easy to measure, it should be routinely collected for all elderly ICU patients in particular in connection to advance care plans, and should be used in decision making.
Article
Background Intensive care treat critically ill patients. When intensive care is not considered beneficial for the patient, decisions to withdraw or withhold treatments are made. We aimed to identify independent patient variables that increase the odds for receiving a decision to withdraw or withhold intensive care. Methods Registry study using data from the Swedish Intensive Care Registry (SIR) 2014‐2016. Age, condition at admission, including co‐morbidities (Simplified Acute Physiology Score version 3, SAPS 3), diagnosis, sex, and decisions on treatment limitations were extracted. Patient data were divided into a full care (FC) group, and a withhold or withdraw (WW) treatment group. Results Of all 97 095 cases, 47.1% were 61‐80 years old, 41.9% were women and 58.1% men. 14 996 (15.4%) were allocated to the WW group and 82 149 (84.6%) to the FC group. The WW group, compared with the FC group, was older (P < 0.001), had higher SAPS 3 (P < 0.001) and were predominantly female (P < 0.001). Compared to patients 16‐20 years old, patients >81 years old had 11 times higher odds of being allocated to the WW group. Higher SAPS 3 (continuous) increased the odds of being allocated to the WW group by odds ratio [OR] 1.085, (CI 1.084‐1.087). Female sex increased the odds of being allocated to the WW group by 18% (1.18; CI 1.13‐ 1.23). Conclusion Older age, higher SAPS 3 at admission and female sex were found to be independent variables that increased the odds to receive a decision to withdraw or withhold intensive care.
Article
Purpose of review: Adequate tissue perfusion is of utmost importance to avoid organ failure in patients with cardiogenic shock. Within the recent years, the microcirculation, defined as the perfusion of the smallest vessels, has been identified to play a crucial role. Microcirculatory changes may include capillary flow disturbances as well as changes in the density of perfused vessels. Due to the availability of new technologies to assess the microcirculation, interesting new data came up and it is the purpose of this review to summarize recent studies in the field. Recent findings: Nowadays, an increasing number of studies confirm parameters of the microcirculation, derived by intravital microscopy, to represent strong outcome predictors in cardiogenic shock. In addition, microcirculation as read-out parameter in innovative clinical studies has meanwhile been accepted as serious endpoint. Treatment strategies such as mechanical assist devices, blood pressure regulating agents or fluids use tissue perfusion and microcirculatory network density as targets in addition to clinical perfusion evaluation and decreasing serum lactate levels. Summary: The parameter most frequently used to detect tissue malperfusion is serum lactate. Novel, noninvasive methods to quantify microvascular perfusion have the potential to guide treatment in terms of optimizing organ perfusion and oxygenation probably paving the way for an individualized therapy.
Article
Background: We aimed to evaluate differences in outcome between patients admitted to intensive care unit (ICU) after elective versus acute surgery in a multinational cohort of very old patients (≥80 years; VIP). Predictors of mortality, with special emphasis on frailty, were assessed. Methods: In total, 5063 VIPs were included in this analysis, 922 were admitted after elective surgery or intervention, 4141 acutely, with 402 after acute surgery. Differences were calculated using Mann-Whitney-U test and Wilcoxon test. Univariate and multivariable logistic regression were used to assess associations with mortality. Results: Compared patients admitted after acute surgery, patients admitted after elective surgery suffered less often from frailty as defined as CFS (28% vs 46%; p < 0.001), evidenced lower SOFA scores (4 ± 5 vs 7 ± 7; p < 0.001). Presence of frailty (CFS >4) was associated with significantly increased mortality both in elective surgery patients (7% vs 12%; p = 0.01), in acute surgery (7% vs 12%; p = 0.02). Conclusions: VIPs admitted to ICU after elective surgery evidenced favorable outcome over patients after acute surgery even after correction for relevant confounders. Frailty might be used to guide clinicians in risk stratification in both patients admitted after elective and acute surgery. Trial registration: NCT03134807. Registered 1st May 2017.
Article
Purpose Changes of lactate concentration over time were reported to be associated with survival in septic patients. We aimed to evaluate delta-lactate (ΔLac) 24 h after admission (Δ24Lac) to an intensive care unit (ICU) in critically ill patients for short- and long-term prognostic relevance. Methods In total, 26,285 lactate measurements of 2191 patients admitted to a German ICU were analyzed. Inclusion criterion was a lactate concentration at admission above 2.0 mmol/L. Maximum lactate concentrations of day 1 and day 2 were used to calculate Δ24Lac. Follow-up of patients was performed retrospectively. Association of Δ24Lac and both in-hospital and long-term mortality were investigated. An optimal cut-off was calculated by means of the Youden index. Results Patients with lower Δ24Lac were of similar age, but clinically sicker. As continuous variable, higher Δ24Lac was associated with decreased in-hospital mortality (per 1% Δ24Lac; HR 0.987 95%CI 0.985–0.990; p < 0.001) and an optimal Δ24Lac cut-off was calculated at 19%. Δ24Lac ≤ 19% was associated with both increased in-hospital (15% vs 43%; OR 4.11; 95%CI 3.23–5.21; p < 0.001) and long-term mortality (HR 1.54 95%CI 1.28–1.87; p < 0.001), even after correction for APACHE II, need for catecholamines and intubation. We matched 256 patients with Δ24Lac ≤ 19% to case–controls > 19% corrected for APACHE II scores, baseline lactate level and sex: Δ24Lac ≤ 19% remained associated with lower in-hospital and long-term survival. Conclusions Lower Δ24Lac was robustly associated with adverse outcome in critically ill patients, even after correction for confounders. Δ24Lac might constitute an independent, easily available and important parameter for risk stratification in the critically ill.