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Record W4390445929 · doi:10.15584/ejcem.2023.4.21

Fall risk and frailty level in older adults admitted to the emergency department with a complaint of falling

2023· article· en· W4390445929 on OpenAlexaboutno aff
Sevim Çelik, Neşe Uğur, Elif Karahan, İlknur Dolu

Bibliographic record

VenueEuropean Journal of Clinical and Experimental Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEmergency departmentFalling (accident)Fear of fallingInjury preventionPoison controlGerontologyEmergency medicineMedical emergencyEnvironmental healthPsychiatry

Abstract

fetched live from OpenAlex

Introduction and aim. Falls are the second leading cause of unintentional death in the world. The study was conducted to examine the risk of falls and levels of frailty in older adult patients admitted to the emergency department due to fractures, as well as to identify the factors that influence fall risk and frailty levels. Material and methods. This cross-sectional and correlational study conducted with 155 older patients. Data collected by the patient information form, Itaki Fall Risk Scale and Edmonton Frail Scale. Results. Patients diagnosed with fracture in the emergency department had a high risk of falling with a mean score of 9.55±3.84.70.3% of the patients were frail. The one-third (30.3%) had severe frailty. There was a moderate positive correlation between the risk of falling and the mean frailty score of the older adult patients (p<0.001). Conclusion. The study showed that older adults admitted to the emergency department due to falls are at high risk of falling and the majority of them are frail. Early determination of fall risk and frailty levels in the older adults with a history of falling, prevention of falls and fractures due to falls will be beneficial in increasing the quality of life of the older adults.

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 score0.130
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.093
GPT teacher head0.381
Teacher spread0.288 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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