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Record W3173862151 · doi:10.1097/mrr.0000000000000483

Cognitive impairment and functional change in COVID-19 patients undergoing inpatient rehabilitation

2021· article· en· W3173862151 on OpenAlexaboutno aff
Ruchi Patel, Irene Savrides, Christine Cahalan, Gargi Doulatani, Michael W. O’Dell, Joan Toglia, Abhishek Jaywant

Bibliographic record

VenueInternational Journal of Rehabilitation Research · 2021
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentDeliriumMedicineRehabilitationSequelaCognitionPhysical therapyCognitive impairmentCoronavirus disease 2019 (COVID-19)Quality of life (healthcare)Physical medicine and rehabilitationInternal medicinePsychiatryDisease

Abstract

fetched live from OpenAlex

Cognitive impairment is increasingly recognized as a sequela of COVID-19. It is unknown how cognition changes and relates to functional gain during inpatient rehabilitation. We administered the Montreal Cognitive Assessment (MoCA) at admission to 77 patients undergoing inpatient rehabilitation for COVID-19 in a large US academic medical center. Forty-five patients were administered the MoCA at discharge. Functional gain was assessed by change in the quality indicator for self-care (QI-SC). In the full sample, 80.5% of patients exhibited cognitive impairment on admission, which was associated with prior delirium. Among 45 patients with retest data, there were significant improvements in MoCA and QI-SC. QI-SC score gain was higher in patients who made clinically meaningful changes on the MoCA, an association that persisted after accounting for age and delirium history. Cognitive impairment is frequent among COVID-19 patients, but improves over time and is associated with functional gain during inpatient 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 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)0.102
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 score0.101
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.102
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.061
GPT teacher head0.420
Teacher spread0.358 · 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

Citations29
Published2021
Admission routes1
Has abstractyes

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