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Record W4315929233 · doi:10.1213/ane.0000000000006272

Association Between the FRAIL Scale and Postoperative Complications in Older Surgical Patients: A Systematic Review and Meta-Analysis

2022· review· en· W4315929233 on OpenAlexaff
Selena Gong, Dorothy Qian, Sheila Riazi, Frances Chung, Marina Englesakis, Qixuan Li, Ella Huszti, Jean Wong

Bibliographic record

VenueAnesthesia & Analgesia · 2022
Typereview
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsToronto Western HospitalUniversity Health NetworkWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineMeta-analysisMEDLINEAssociation (psychology)Scale (ratio)Intensive care medicineGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Several frailty screening tools have been shown to predict mortality and complications after surgery. However, these tools were developed for in-person evaluation and cannot be used during virtual assessments before surgery. The FRAIL (fatigue, resistance, ambulation, illness, and loss of weight) scale is a brief assessment that can potentially be conducted virtually or self-administered, but its association with postoperative outcomes in older surgical patients is unknown. The objective of this systematic review and meta-analysis (SRMA) was to determine whether the FRAIL scale is associated with mortality and postoperative outcomes in older surgical patients. METHODS: Systematic searches were conducted of multiple literature databases from January 1, 2008, to December 17, 2022, to identify English language studies using the FRAIL scale in surgical patients and reporting mortality and postoperative outcomes, including postoperative complications, postoperative delirium, length of stay, and functional recovery. These databases included Medline, Medline ePubs/In-process citations, Embase, APA (American Psychological Association) PsycInfo, Ovid Emcare Nursing, (all via the Ovid platform), Cumulative Index to Nursing and Allied Health Literature (CINAHL) EbscoHost, the Web of Science (Clarivate Analytics), and Scopus (Elsevier). The risk of bias was assessed using the quality in prognosis studies tool. RESULTS: A total of 18 studies with 4479 patients were included. Eleven studies reported mortality at varying time points. Eight studies were included in the meta-analysis of mortality. The pooled odds ratio (OR) of 30-day, 6-month, and 1-year mortality for frail patients was 6.62 (95% confidence interval [CI], 2.80-15.61; P < .01), 2.97 (95% CI, 1.54-5.72; P < .01), and 1.54 (95% CI, 0.91-2.58; P = .11), respectively. Frailty was associated with postoperative complications and postoperative delirium, with an OR of 3.11 (95% CI, 2.06-4.68; P < .01) and 2.65 (95% CI, 1.85-3.80; P < .01), respectively. The risk of bias was low in 16 of 18 studies. CONCLUSIONS: As measured by the FRAIL scale, frailty was associated with 30-day mortality, 6-month mortality, postoperative complications, and postoperative delirium.

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)0.014
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.038
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0170.032
Bibliometrics0.0080.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.001
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 head0.053
GPT teacher head0.331
Teacher spread0.278 · 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 designMeta-analysis
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

Citations75
Published2022
Admission routes1
Has abstractyes

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