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Record W2171951598 · doi:10.3109/09638288.2010.486468

Joint contractures in the intensive care unit: association with resource utilization and ambulatory status at discharge

2010· article· en· W2171951598 on OpenAlexafffundabout
Heidi Clavet, Paul C. Hébert, Dean Fergusson, Steve Doucette, Guy Trudel

Bibliographic record

VenueDisability and Rehabilitation · 2010
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsMedicineJoint ContractureMuscle contractureAmbulatoryContractureIntensive care unitPhysical therapyRange of motionEmergency medicineSurgeryIntensive care medicine

Abstract

fetched live from OpenAlex

PURPOSE: The objectives of our study were (1) to explore the link between joint contractures acquired in the ICU and the ambulatory status of patients at discharge home, to determine (2) when and how many patients received physiotherapy services in ICU and on the hospital ward, and (3) the differences in the use of hospital resources in the presence or absence of joint contractures. METHOD: Data on ICU joint contractures were extracted from an existing contracture database containing information on 155 Canadian patients with a tertiary ICU stay of 14 days or more. RESULTS: Of 155 patients, 115 (74.2%) received a range of motion assessment in the ICU. The assessment took place a median of 7 days (IQR 0-36) after ICU admission. Significantly fewer patients with joint contractures than without joint contractures were mobilized on the hospital ward (21/38 [55.3%] vs. 27/34 [79.4%], P = 0.03). At discharge home, more patients with joint contractures had a low ambulatory status (38 [64.4%]) compared with patients without joint contractures (26 [51.0%]; P = 0.002). CONCLUSION: The median delay of 7 days before musculoskeletal assessment in the ICU together with failure to assess 26% of patients may have allowed the development of contractures, which affected the patients' ambulatory status at discharge from hospital.

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)0.000
metaresearch head score (Gemma)0.016
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 score0.147
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.014
GPT teacher head0.278
Teacher spread0.264 · 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

Citations25
Published2010
Admission routes3
Has abstractyes

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