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Record W4406937559 · doi:10.1136/bmjopen-2023-082602

Descriptive retrospective cross-sectional study of rehabilitation care for poststroke users in Québec during the COVID-19 pandemic

2025· article· en· W4406937559 on OpenAlexafffundabout
Palak Vakil, Perrine Ferré, Johanne Higgins, Louis‐David Beaulieu, Marie-Hélène Milot, Marie‐Hélène Boudrias

Bibliographic record

VenueBMJ Open · 2025
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsUniversité de SherbrookeUniversité du Québec à ChicoutimiJewish Rehabilitation HospitalCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanMcGill UniversityUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalCentre for Interdisciplinary Research in RehabilitationCentre Hospitalier Universitaire de SherbrookeMcGill University Health Centre
FundersFonds de Recherche du Québec - Santé
KeywordsMedicinePandemicCross-sectional studyCoronavirus disease 2019 (COVID-19)Rehabilitation2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)EpidemiologyRetrospective cohort studyFamily medicineMedical emergencyPhysical therapyDiseaseVirologyInfectious disease (medical specialty)Internal medicineOutbreakPathology

Abstract

fetched live from OpenAlex

OBJECTIVES: During the COVID-19 pandemic, designated rehabilitation centres were established in the province of Québec, where strict sociosanitary measures such as isolation and mandatory personal protection equipment requirements were followed. This study aimed to describe the impact of the pandemic on rehabilitation care indicators for poststroke users with (COV+) and without (COV-) COVID-19 infection in designated rehabilitation centres compared with those admitted in the previous year (pre-COV). METHOD: A retrospective analysis of 292 medical files was performed in 3 rehabilitation centres. Demographic characteristics were collected, as well as indicators routinely collected in acute care and rehabilitation such as length of stay (LOS), the Functional Independence Measure and a number of physical/occupational therapy (PT/OT) sessions. Non-parametric statistical tests were used to compare variables among the three groups. RESULTS: COV+ users were older than COV- and pre-COV ones (p<0.01) and were more disabled on admission to a rehabilitation centre (p<0.01). They also exhibited longer LOS in acute care prior to rehabilitation (p<0.001) and were more often rehospitalised (p<0.002) during the course of their stay in the rehabilitation centre. Despite longer rehabilitation stays (p<0.001) and more PT/OT sessions, COV+ users remained more disabled at discharge (p<0.002). COV- users showed rehabilitation care indicators resembling the ones of pre-COV despite spending less time in rehabilitation. CONCLUSIONS: Patients who had a stroke infected with COVID-19 exhibited greater vulnerability on admission to rehabilitation. They required more care and services during their rehabilitation period. However, this additional support did not enable them to achieve the same level of recovery as COV- and pre-COV users. This underscores the added impact of the disease on already impaired patients and highlights the specific needs of COV+ users undergoing rehabilitation.

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 score0.140
Threshold uncertainty score0.281

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.051
GPT teacher head0.435
Teacher spread0.384 · 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

Citations1
Published2025
Admission routes3
Has abstractyes

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