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Record W4393269114 · doi:10.29400/tjgeri.2024.384

Comparison of Clinical Frailty Scale and Edmonton Frail Scale in older adults presenting to the emergency department

2024· article· en· W4393269114 on OpenAlexaboutno aff
Mustafa YÜCEL, Yusuf Ali Altuncı, Enver Özçete, Aslı Kilavuz, Funda Karbek Akarca

Bibliographic record

VenueThe Turkish Journal of Geriatrics · 2024
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsEmergency departmentScale (ratio)GerontologyMedicineMedical emergencyGeographyNursingCartography

Abstract

fetched live from OpenAlex

Introduction: This study aimed to compare the prognostic values of Edmonton Frail Scale and Clinical Frailty Scale in the emergency department and determine their suitability for patient management. Materials and Method: This study was conducted as a single-center prospective observational study. Patients aged 65 and older who presented to the emergency department were included. Clinical Frailty Scale and Edmonton Frail Scale scores, the emergency department outcomes, length of stay in the emergency department, 30-day mortality, and 30-day readmission data of the patients were recorded. ROC analysis was performed to examine the predictive values on outcomes. DeLong Test was used to compare the predictive values. Results: This study included 400 patients. Intensive care unit admission was significantly more frequent in the frail group according to both Edmonton Frail Scale and Clinical Frailty Scale. The length of stay in the emergency department was significantly longer in the frail group in both classifications. The mortality rate was significantly higher in the frail group in both classifications. The optimal cut off value for predicting mortality was found to be 9 for Edmonton Frail Scale and 7 for Clinical Frailty Scale. There was no significant difference between the predictive values of two scales. Conclusion: We found that two frail scales have good predictive values for adverse outcomes, such as mortality and the need for Intensive care unit admission in the emergency department. We believe that both scores would be valuable in guiding decisions for the emergency department usage due to their similar predictive values. Keywords: Geriatrics; Emergency Service; Hospital; Frailty; Frail Elderly; Mortality.

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)0.001
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 score0.199
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.044
GPT teacher head0.389
Teacher spread0.344 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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