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Record W4362505844 · doi:10.11124/jbies-22-00397

Clinical tools to assess functional capacity before elective non-cardiac surgery: a scoping review protocol

2023· review· en· W4362505844 on OpenAlexafffund
Julian F. Daza, Tyler R. Chesney, Shabbir M.H. Alibhai, Erin Kennedy, Gerald Lebovic, David Lightfoot, Arnaud Romeo Mbadjeu Hondjeu, Juan Morales, Bianca Pivetta, Rachel Jolley, Elizabeth Racz, Luke Wilmshurst, Duminda N. Wijeysundera

Bibliographic record

VenueJBI Evidence Synthesis · 2023
Typereview
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsUniversity of OttawaMount Sinai HospitalUniversity Health NetworkSt. Michael's HospitalUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMedicineMEDLINEProtocol (science)Randomized controlled trialSystematic reviewEvidence-based medicineIntensive care medicineMedical physicsSurgeryAlternative medicinePathology

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this scoping review is to map the evidence on clinical tools to assess functional capacity prior to elective non-cardiac surgery. INTRODUCTION: Functional capacity is a strong prognostic indicator before surgery, which can be used to identify patients at elevated risk of postoperative complications, yet, there is no consensus on which clinical tools should be used to assess functional capacity in patients prior to non-cardiac surgery. INCLUSION CRITERIA: This review will consider any randomized or non-randomized studies that evaluate the performance of a functional capacity assessment tool in adults (≥18 years) prior to non-cardiac surgery. For studies to be included, the tool must be used clinically for risk stratification. We will exclude studies on lung and liver transplant surgery, as well as ambulatory procedures performed under local anesthesia. METHODS: The review will be conducted in line with the JBI methodology for scoping reviews. A peer-reviewed search strategy will be used to query relevant databases (ie, MEDLINE, Embase, EBM Reviews). Additional sources of evidence will include databases of non-peer-reviewed literature and the reference lists of included studies. Two independent reviewers will identify eligible studies in 2 stages: stage 1, based on titles and abstracts; and stage 2, based on full texts. Information on study details, measurement properties, pragmatic qualities, and/or clinical utility metrics will be charted in duplicate onto standardized data collection forms. The results will be presented using descriptive summaries, frequency tables, and visual plots that highlight the extent of evidence and remaining gaps in the validation process of each tool. REVIEW REGISTRATION: Open Science Framework https://osf.io/6nfht.

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)0.012
metaresearch head score (Gemma)0.080
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.688
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.080
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0140.010
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.231
GPT teacher head0.477
Teacher spread0.245 · 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 designSystematic review
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

Citations2
Published2023
Admission routes2
Has abstractyes

Explore more

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