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Record W4220676397 · doi:10.1177/01945998221086852

Evaluation of Agreement Among Frailty Assessment Tools in Head and Neck Surgery

2022· article· en· W4220676397 on OpenAlexaboutno aff
Yash Pandey, Brianna Pandey, Sarah Aurit, Oleg Militsakh, William M. Lydiatt, Daniel D. Lydiatt, Andrew Coughlin, Robert Lindau, Angela Osmolak, Aru Panwar

Bibliographic record

VenueOtolaryngology · 2022
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineProspective cohort studyFrailty IndexGrip strengthPhysical therapyHead and neckBody mass indexObservational studyCohort studyCohortSurgeryGerontologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate intertest agreement among hand grip strength (HGS), the modified Frailty Index (mFI), and the Edmonton Frail Scale (EFS) in patients presenting for presurgical assessment in a head and neck surgery clinic. STUDY DESIGN: Prospective observational study. SETTING: Academic tertiary medical center. METHODS: Prospective data relating to 3 frailty measurements were collected for 96 consecutive adults presenting for presurgical counseling at a single high-volume head and neck surgical oncology clinic. Frailty was determined with previously validated thresholds for the mFI (≥3) and EFS (>7). The highest of 2 HGS measurements performed for the dominant hand was used to determine frail status based on previously validated sex- and body mass index-specific thresholds. Baseline characteristics were identified to determine the association of such variables to each tool. Agreement among frailty assessment tools was examined. RESULTS: The frequency of frailty in the cohort varied among tools, ranging from 29.2% (28/96) for HGS to 12.5% (12/96) for the mFI and 4.2% (4/96) for the EFS. The overall agreement among the 3 frailty tools via the Fleiss index was poor (kappa, 0.088; 95% CI, -0.028 to 0.203). CONCLUSION: Assessment of frailty is complex, and established frailty assessment tools may not agree on which patients are frail. When assessing a patient as frail, clinicians must be vigilant to the influence of frailty assessment tools on such determinations, which may contribute critical input during shared decision making for patients considering head and neck surgery or nonsurgical alternatives.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.082
GPT teacher head0.355
Teacher spread0.274 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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