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Record W4381598806 · doi:10.1097/mrr.0000000000000592

Characteristics and healthcare utilization of COVID-19 rehabilitation patients during the first and second waves of the pandemic in Toronto, Canada

2023· article· en· W4381598806 on OpenAlexaffabout
Marina B. Wasilewski, Zara Szigeti, Robert Simpson, Jacqueline Minezes, Amanda L. Mayo, Lawrence R. Robinson, Maria Lung, Sander L. Hitzig

Bibliographic record

VenueInternational Journal of Rehabilitation Research · 2023
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsSt. John's Rehab HospitalHealth Sciences CentreToronto Rehabilitation InstituteUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineInterquartile rangePandemicRehabilitationRetrospective cohort studyCoronavirus disease 2019 (COVID-19)CohortCohort studyHealth carePhysical therapyEmergency medicineDiseaseInternal medicine

Abstract

fetched live from OpenAlex

The objective of this study is to describe the healthcare utilization, and clinical and sociodemographic features of a cohort of 74 coronavirus disease 2019 (COVID-19) patients admitted to a tertiary rehabilitation hospital in Toronto, Canada. A retrospective chart review was performed using 74 charts from patients admitted to a COVID-19 rehabilitation unit between 11 April 2020 and 30 April 2021. Measures of central tendency, SDs, interquartile ranges, frequencies, and proportions were calculated to analyze clinical and sociodemographic data. A total of 74 patients were included in this study, including 33 males and 41 females. The mean age was 72.8 years, with Wave 1 patients being younger than Wave 2 patients. Sixty-six percent of total patients experienced hypertension. Mean functional independence measure score across both waves was 78 at admission and 100 at discharge. Mean length of stay was 14.6 days in Wave 1 and 18.8 days in Wave 2. This study represents some of the first data on the characteristics and outcomes of COVID-19 patients admitted to inpatient rehabilitation in Toronto, Canada across the initial waves of the COVID-19 pandemic.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.398
Teacher spread0.369 · 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 teacher head, not a consensus.

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
Published2023
Admission routes2
Has abstractyes

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