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Record W4402613834 · doi:10.1017/s0714980824000199

Emergency Department Boarding Time Is Associated with Functional Decline in Older Adults Six Months Post Discharge

2024· article· en· W4402613834 on OpenAlexafffund
Caroline L Duquette, Melissa K. Andrew, George A. Kuchel, Jo‐Anne Clarke, Robert Ohle, Chris P. Verschoor

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2024
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsDalhousie UniversityNOSM UniversityHealth Sciences North
FundersNational Institute on AgingNorthern Ontario Academic Medicine Association
KeywordsEmergency departmentMedicineBarthel indexGerontologyPsychological interventionBalance (ability)Frailty IndexActivities of daily livingEmergency medicinePhysical therapyNursing

Abstract

fetched live from OpenAlex

Functional decline following hospitalization remains an important problem in health care, especially for frail older adults. Modifiable factors related to reduction in harms of hospitalization are not well described. One particularly pervasive factor is emergency department (ED) boarding time; time waiting from decision to admit, until transfer to an in-patient medical unit. We sought to investigate how the functional status of frail older adults correlated with the length of time spent boarded in the ED. We found that patients who waited for 24 hours or more exhibited functional decline in both the Barthel Index and Hierarchical Assessment of Balance and Mobility and an increase in the Clinical Frailty Scale from discharge to 6 months post discharge. In conclusion, there is a need for additional investigation into ED focused interventions to reduce ED boarding time for this population or to improve access to specialized geriatric services within the ED.

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)0.001
metaresearch head score (Gemma)0.008
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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.220
Teacher spread0.212 · 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

Citations6
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissement→Same topicFrailty in Older Adults→French-language works237,207→