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CANCOV – Canadian Prospective Cohort of 5-year Outcomes in Critically Ill Patients With COVID-19 Critical Illness and Family Caregivers

2025· article· en· W4410270972 on OpenAlexaffabout
Margaret S. Herridge

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineCritical illnessCoronavirus disease 2019 (COVID-19)Critically ill2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Prospective cohort studyIntensive careIntensive care medicineBetacoronavirusCohort studyMEDLINESeverity of illnessInternal medicineVirologyDiseaseOutbreakInfectious disease (medical specialty)

Abstract

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Abstract Rationale: COVID-19 is a novel multisystem disease with unknown long-term morbidity and mortality. Objective: To create a granular dataset of Canadian COVID-19 patients and family caregivers through multidimensional 5-year outcomes and their risk determinants. For COVID ICU survivors, we hypothesize that age, comorbid disease, course in ICU will determine functional/ neuropsychological outcome and healthcare use. Methods: This Canadian, multi-center, ambidirectional cohort study recruited patients and caregivers across the illness spectrum(n=2171). We report on ICU COVID patients ≥ 16y (n=381). Standardized multidimensional follow-up was performed at 3,6,12 and every 6 months to 5 years after ICU discharge. Results: Two-year follow-up was completed in April 2024 and three-year follow-up is ongoing. Baseline characteristics: Hypertension 95%; Obesity: 77%; Diabetes 75%; Dyslipidemia 50%; COPD 44%; mental illness 41%. Median LIS 3.3[3,4]; MODS 10[7, 11] on admission. Median ICU LOS 16d [8, 36] and median hospital LOS 22d[13, 45]. Improving LIS during first 7d of ICU was associated with ICU survival(p<0.007). Overall ICU mortality was 46%. ECMO patients had higher ICU and one-year mortality compared to MV(52% vs 36%; 60% vs 47% respectively).Cohort retention at 12, 24-months; 83%, 86% respectively. Two-year follow-up results: ECMO patients were young (mean 48 y; SD 10), had the fewest comorbidities (median Charlson 1.0 (0.5,1.5), highest prevalence of dialysis 36%;longest duration of continuous sedation(d) (median 21(12,31); narcotics(d)(median 26(14,36); paralytics (d)(median 6(2,18); antibiotics(d)(median 23 (12,35); deep coma (GCS 3)(d) (median18(8,27), MV days (30(15,51), ICU LOS (38 (16,52) and hospital LOS (38(20,66) compared to MV, HFNC and NIV/O2. At 24-months: ECMO/MV and HFNC groups continued to have at least one persistent symptom in > 90%; NIV/O2 was less at 75%. Multidimensional disability (FIM/PCS SF-36, MRC, 6MWD) at 12 -months was unchanged at 24 months. Restrictive PFTs were most marked in the ECMO cohort (TLC, FEV1, FVC % pred median 70,67,68 respectively) and stable. Of 21 patients discharged on home O2, 15/21 remained on home O2 at 24 months. Having any mood disorder decreased between 12 and 24 months for ECMO (36% to 20%), HFNC (28% to 18%) and NIV/O2(0%), but increased for the MV group (33%-52%). Cognitive dysfunction persisted; Stigma remained high and resilience was poor. Healthcare utilization from 12 to 24 months decreased but remained substantial. Comment: In this multi-center sample of severely ill COVID ICU survivors from a Canadian national study, there was important and persistent multidimensional disability to two-year follow-up. ICU survivors of COVID critical illness represent ongoing high-needs healthcare users.

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)0.002
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 score0.070
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.023
GPT teacher head0.371
Teacher spread0.347 · 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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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Same venueAmerican Journal of Respiratory and Critical Care Medicine→Same topicFamily and Patient Care in Intensive Care Units→French-language works237,207→