Towards consensus of reported outcomes and a common definition of surgical prehabilitation
Bibliographic record
Abstract
Background.Surgical prehabilitation is a preoperative intervention aiming to better prepare patients to withstand the emotional and physiological stressors of surgery.Despite over two decades of research in this field, the certainty of the evidence for prehabilitation before surgery remains difficult to evaluate in part because of the lack of a universally accepted definition and the heterogeneity of reported outcomes.Objectives.The main objectives of this thesis are to (1) identify how surgical prehabilitation is defined, and (2) systematically map what, when and how outcomes and their specific outcome assessments are reported across primary randomized controlled trials of unimodal (consisting of exercise, nutrition or cognitive/psychological training) and multimodal (two or more modalities) prehabilitation in adult patients undergoing elective surgery. Methods.A scoping review was performed to meet both objectives.The final search was conducted in February 2023 using MEDLINE, EMBASE, PsychInfo, Web of Science, CINAHL, and Cochrane.For objective 1, a qualitative analysis was done using a method and investigator triangulation approach for summative content analysis.For objective 2, data extraction and charting were performed in duplicate and followed the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) framework.Descriptive statistics (counts and frequencies) were used for the analysis of quantitative data. Results.The review included a total of 76 trials, mostly of patients undergoing abdominal (n=26, 34%), orthopedic (n=20, 26%) and thoracic (n=14, 18%) surgeries.We consolidated the following common definition: "Prehabilitation is a process from diagnosis to surgery, consisting of one or more preoperative interventions of exercise, nutrition, anxiety-reducing strategies, and Résumé Contexte.La préhabilitation chirurgicale est une intervention préopératoire visant à mieux préparer les patients à supporter les facteurs de stress émotionnels et physiologiques de la chirurgie.Malgré plus de deux décennies de recherche dans ce domaine, la certitude des preuves en faveur de la préhabilitation avant la chirurgie reste difficile à évaluer en partie en raison du manque d'une définition universellement acceptée et de l'hétérogénéité des résultats rapportés.Objectifs.Les principaux objectifs de cette thèse de maîtrise sont (1) d'identifier comment la préhabilitation chirurgicale est définie, et ( 2) d'identifier systématiquement quels, quand et comment les résultats ainsi que leurs évaluations spécifiques sont rapportés dans les essais contrôlés randomisés primaires portant sur la préhabilitation unimodale (composée d'exercices, de nutrition ou de formation cognitive/psychologique) et multimodale (deux modalités ou plus) chez des patients adultes subissant une chirurgie élective.Méthodes.Une revue de la portée a été réalisée pour atteindre ces deux objectifs.La recherche finale a été effectuée en février 2023 en utilisant MEDLINE, EMBASE, PsychInfo, Web of Science, CINAHL et Cochrane.Pour le premier objectif, une analyse qualitative a été effectuée en utilisant une approche de triangulation des méthodes et une analyse de contenu sommatif.Pour le deuxième objectif, l'extraction et le classement des données ont été réalisés en double et ont suivi le cadre de International Society for Pharmacoeconomics and Outcomes Research (ISPOR).Des statistiques descriptives (dénombrements et fréquences) ont été utilisées pour l'analyse des données quantitatives.Résultats.La revue a inclus un total de 76 essais, principalement chez des patients subissant des chirurgies abdominales (n=26, 34%), orthopédiques (n=20, 26%) et thoraciques (n=14, 18%).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.395 | 0.581 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.016 | 0.009 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.010 | 0.025 |
| Research integrity | 0.007 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".