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Prediction of postoperative mortality in older surgical patients by clinical frailty scale: A systematic review and meta-analysis

2024· review· en· W4401660049 on OpenAlexaboutno aff
Hong-Tao Zhang, Ning Tan, Yue Gao, Keyi She, Qin Luo, Ke-ru Yao, Xi Tang, Lu Li, Lu Zhao, Zhihan Wang, Xinjun Yang, Xinhong Yin

Bibliographic record

VenueGeriatric Nursing · 2024
Typereview
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
FundersNatural Science Foundation of Hunan ProvinceHunan Provincial Science and Technology DepartmentHealth Commission of Hunan Province
KeywordsMeta-analysisMedicineFrailty IndexScale (ratio)MEDLINEGerontologyIntensive care medicineInternal medicineGeographyBiology

Abstract

fetched live from OpenAlex

• The prediction of frailty on postoperative adverse outcomes has been confirmed, but there are various assessment tools for frailty. This study only studied the prediction of clinical frailty scale on postoperative adverse outcomes. At the same time, we further analyzed different death time, literature types, surgical types, etc., to verify the effect of clinical frailty scale on postoperative mortality. To systematically evaluate the predictive efficacy of clinical frailty scale (CFS) for postoperative mortality older surgical patients, and to evaluate the prevalence of frailty in the included studies. A systematic review and meta-analysis of observational studies was conducted, utilizing the MOOSE guidelines for the evaluation of both. Quality assessment of the articles was also performed. The protocol was registered (CRD42023423552). Relevant English and Chinese language studies published until October 20th, 2023 were retrieved from PubMed, Web of Science, Embase, Medline, CINAHL,Cochrane, WAN FANG DATA, VIP Information, CNKI, and SinoMed databases. Study were included in which frailty was measured by the CFS and postoperative mortality was reported for older surgery patients. A meta-analysis to predict postoperative mortality and frailty prevalence was performed using STATA 17.0 software. Sixteen cohort studies were included (5,864 participants) from 1,513 records. All studies' Newcastle-Ottawa Scale (NOS) scores were above 6 points. It was found that the prevalence of surgical frailty in the older was 0.36(CI 0.20–0.52). Patients assessed as frail by the CFS were associated with higher all-cause mortality (OR:4.01; CI 2.59–6.23). Subgroup analysis shows that frailty was associated with1-month mortality (OR:3.85; CI 1.11–13.45) and 1-year mortality (OR:4.43; CI 2.18–8.99). The prevalence of frailty is high in older surgical patients, and CFS can effectively predict the mortality of older surgical patients with frailty.

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)0.011
metaresearch head score (Gemma)0.025
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 score0.015
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.025
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0150.034
Bibliometrics0.0070.007
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 head0.122
GPT teacher head0.429
Teacher spread0.306 · 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

Citations10
Published2024
Admission routes1
Has abstractyes

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