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Record W4286500586 · doi:10.1007/s11739-022-03042-5

Frailty assessment in emergency medicine using the Clinical Frailty Scale: a scoping review

2022· review· en· W4286500586 on OpenAlexafffund
Christophe A. Fehlmann, Christian H. Nickel, Emily Cino, Zinnia Al-Najjar, Nigèle Langlois, Debra Eagles

Bibliographic record

VenueInternal and Emergency Medicine · 2022
Typereview
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsUniversity of OttawaOttawa Public HealthOttawa Hospital
FundersUniversité de GenèveUniversity of Ottawa
KeywordsMedicineEmergency departmentMEDLINEEmergency medicineScale (ratio)Medical emergencyFamily medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Frailty is a common condition present in older Emergency Department (ED) patients that is associated with poor health outcomes. The Clinical Frailty Scale (CFS) is a tool that measures frailty on a scale from 1 (very fit) to 9 (terminally ill). The goal of this scoping review was to describe current use of the CFS in emergency medicine and to identify gaps in research. METHODS: We performed a systemic literature search to identify original research that used the CFS in emergency medicine. Several databases were searched from January 2005 to July 2021. Two independent reviewers completed screening, full text review and data abstraction, with a focus on study characteristics, CFS assessment (evaluators, timing and purpose), study outcomes and statistical methods. RESULTS: A total of 4818 unique citations were identified; 34 studies were included in the final analysis. Among them, 76% were published after 2018, mainly in Europe or North America (79%). Only two assessed CFS in the pre-hospital setting. The nine-point scale was used in 74% of the studies, and patient consent was required in 69% of them. The main reason to use CFS was as a main exposure (44%), a potential predictor (15%) or an outcome (15%). The most frequently studied outcomes were mortality and hospital admission. CONCLUSION: The use of CFS in emergency medicine research is drastically increasing. However, the reporting is not optimal and should be more standardized. Studies evaluating the impact of frailty assessment in the ED are needed. REGISTRATION: https://doi.org/10.17605/OSF.IO/W2F8N.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.712
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0750.000

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 head0.350
GPT teacher head0.545
Teacher spread0.195 · 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 designOther design
Domainnot available
GenreReview

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

Citations90
Published2022
Admission routes2
Has abstractyes

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