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Record W6904958190 · doi:10.14288/1.0415827

Investigating patient-reported outcomes among COVID-19 survivors : a longitudinal cohort study

2022· article· en· W6904958190 on OpenAlexaboutno aff

Bibliographic record

VenuecIRcle (University of British Columbia) · 2022
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthPropensity score matchingEmergency departmentCohortCohort studyLongitudinal studyEpidemiology

Abstract

fetched live from OpenAlex

Background: Many Coronavirus Disease 2019 (COVID-19) survivors report long-term sequelae. However, few studies have measured patient-reported outcomes and compared them to those of patients who tested negative for severe acute respiratory syndrome coronavirus-2 (SARS-COV-2). This study compares the long-term physical and mental health outcomes of patients presenting to emergency departments who tested positive for SARS-COV-2 with those who tested negative. Methods: This study enrolled consecutive eligible patients presenting to emergency departments participating in the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN) between March 1st 2020 and July 14th 2021. Patients tested for SARS-COV-2 were eligible. Consecutive SARS-COV-2 positive patients were consented for follow-up, and matched with test-negative controls from the same hospital and date. The outcome measures were the Veterans RAND physical health component score (PCS) and mental health component score (MCS). The PCS and MCS of propensity score matched patients were analyzed using linear mixed effects models. Risk factors for PCS and MCS were modelled using linear regression. Results: Our cohort included 1170 SARS-COV-2 positive patients and 3716 test-negative controls. Comparing the groups, the adjusted mean difference in PCS was 0.50 (95%CI: -0.36, 1.36) and -1.01 (95%CI: -1.91, -0.11) for MCS. A World Health Organization Ordinal Outcome Score of 6-7, representing severe SARS-COV-2 disease, was the strongest predictor of PCS (β=-7.4; 95%CI: -9.8, -5.1). Prior mental health illness was the strongest predictor of MCS (β=-5.4; 95%CI: -6.3, -4.5). Conclusion: The mean PCS was similar among SARS-COV-2 positive and negative participants tested under similar circumstances, while mean MCS was worse among SARS-COV-2 positive participants. The mental health sequelae of COVID-19 should be considered when developing long-term support programs for survivors.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.239
Teacher spread0.222 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

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