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CANCOV-Canadian Prospective Cohort of 5-year Outcomes in Critically Ill Patients With COVID-19 Critical Illness and Family Caregivers – Long Term Functional Outcomes After Protective Mechanical Ventilation

2025· article· en· W4410157899 on OpenAlexaffabout
E Santangelo, Priscila Robles, Shehroz S. Khan, W. Radovanovic, Kathleen S. Matthews, Laura Dragoi, Hannah Wozniak, Tiffany L. Weir, Elias Fares, Qixuan Li, Ella Huszti, Margaret S. Herridge

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsDalhousie UniversityUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineCritically illCritical illnessMechanical ventilationCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Intensive care medicineProspective cohort studyCohort studyIntensive careTerm (time)VirologyInternal medicineDiseaseInfectious disease (medical specialty)Outbreak

Abstract

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Abstract Rationale: Lung protective mechanical ventilation (PMV) decreases ICU mortality in acute respiratory failure but its impact on long-term function in survivors is unclear. We hypothesized that PMV, defined as a static driving pressure<14 cmH2O for the first seven days in ICU, is associated with functional outcome. Methods: This Canadian, multi-center cohort study recruited patients (≥16y) across the COVID-19 illness spectrum. Standardized multidimensional follow-up was performed up to 12 months and every 6 months to 5 years after ICU discharge. This analysis was limited to patients who required mechanical ventilation (MV) within the first seven days of ICU admission. Ventilatory variables were recorded daily during the first week in ICU then twice per week until discharge or death. Using linear regression modelling including a priori variables (age, Charlson Comorbidity Index (CCI), Slope of MODS during first 7 ICU days, ICU length of stay (LOS)), we evaluated the association between the proportion of time spent within PMV parameters during the first 7 days of ICU admission and the Total FIM score at 6-months in survivors. Results: Study sample included ECMO (n=112) and MV (n=190) (n=302). Baseline characteristics (median [IQR]): age 53 [46,61], male [179, 70%], MODS score 10 [8,11], PaO2/FiO2 82 [63,109]. Respiratory variables at ICU admission for ECMO (median [IQR]) and MV only (median [IQR]) respectively: MVdays 43[15,51]; 16[8,26], p<0.001. Tidal volume per predicted body weight (Vt/PBW) 5.0 [4.2,5.7]; 5.9 [5.2,6.4], p<0.001. Respiratory rate 28 [25,34.] 28 [22,30], p=0.010. PEEP 14[10,16.]; 14 [10,16], p=0.887. Plateau Pressure 29 [27,32]; 28 [24,30] p=0.002. Driving Pressure 16 [13,19]; 14[11,16] p<0.001, Respiratory System Compliance 20 [13,27]; 28 [21,37] p<0.001. Volume Assisted-Control Mode 55 (49.1%); 80(42.6%), p=0.325, Pressure Assisted-Control Mode 46 (41%); 39 (21%), p<0.001. Days of continuous sedation 21 [12,31]; 12[6,19]. Days of Continuous Narcotic 26[14,36]; 14[6,23]. Days of Continuous Paralytic 6 [2,18];5.5 [2,12]. In univariable analysis, the proportion of days patients received PMV was not significantly associated with the total FIM at 6 months (-0.226, 95% CI -1.408,0.955, p=0.708). After adjusting for age, ICU LOS, CCI and 7d MODS slope, PMV was not significantly associated with total FIM at 6 months [-0.351, 95% CI -1.972,1.271, p=0.673). Conclusion: In this multi-center study of critically ill COVID-19 survivors, there was no significant association between the proportion of time patients were exposed to PMV during the first seven days in the ICU and the FIM score at 6 months after ICU discharge.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.292
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes2
Has abstractyes

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