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Record W2088058139 · doi:10.1310/1qh8-4rcc-me18-g6pv

Recovery Time of Independent Poststroke Life Habits: Part II

2001· article· en· W2088058139 on OpenAlexaff
Lucie Brosseau, Sanraranarayanan Raman, Léonard Fourn, Ginette Coutu-Walkulczyk, Louis E. Tremblay, Mai Pham, Pauline Beaudoin

Bibliographic record

VenueTopics in Stroke Rehabilitation · 2001
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsHôpital Notre-DameUniversité de MontréalCanadian Physiotherapy AssociationUniversity of OttawaMinistry of Health and Long Term Care
Fundersnot available
KeywordsRehabilitationStroke (engine)Physical therapyQuality of life (healthcare)MedicinePhysical medicine and rehabilitationActivities of daily livingProportional hazards modelPsychologySurgery

Abstract

fetched live from OpenAlex

The purposes of this study were to determine the time of the recovery of poststroke life habits and to identify prognostic indicators associated with recovery time among stroke patients in a rehabilitation program. A sample of 421 stroke patients who were admitted to a rehabilitation center was recruited from medical records available from January 1987 to December 1992. The relation between the achievement of independent life habits including bed mobility, transfers and ambulation, bathing activities, dressing activities, eating activities, home activities, sphincter control, and sleep with the potential covariates associated with recovery time was assessed through the analysis of survival data using the Cox maximum-likelihood proportional hazard models. The poststroke life habits obtained generated mean recovery times ranging from 5.51 to 57.60 days from admission to rehabilitation. The survival analysis revealed that the recovery time of the selected poststroke abilities was significantly influenced (p <.05) by one or several indicators; these included physical ability and neuropsychological and life habit characteristics. With this precious information, stroke rehabilitation specialists may be able to reduce the length of time required to recover independent poststroke life habits by treating the specific neuropsychological, physical, and life habit characteristics identified in this study. A faster poststroke recovery would reduce the socioeconomic impact generated by stroke disability and would also ensure a better quality of life to the stroke survivor.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.031
Threshold uncertainty score0.793

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.269
Teacher spread0.257 · 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.

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

Citations4
Published2001
Admission routes1
Has abstractyes

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