MP31-10 SYSTEMATIC REVIEW AND META-ANALYSIS OF FRAILTY INDICES IN UROLOGIC SURGERY: RISK PREDICTION OF POSTOPERATIVE COMPLICATIONS
Notice bibliographique
Résumé
You have accessJournal of UrologyCME1 May 2022MP31-10 SYSTEMATIC REVIEW AND META-ANALYSIS OF FRAILTY INDICES IN UROLOGIC SURGERY: RISK PREDICTION OF POSTOPERATIVE COMPLICATIONS Jane Kurtzman, Preston Kerr, Rashed Kosber, and Steven Brandes Jane KurtzmanJane Kurtzman More articles by this author , Preston KerrPreston Kerr More articles by this author , Rashed KosberRashed Kosber More articles by this author , and Steven BrandesSteven Brandes More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002580.10AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Contemporary surgical planning rarely involves formally assessing patient frailty, especially among urology (GU) patients. Our aim was to systematically review the literature to assess the ability of frailty indices to predict the risk of postoperative complications after GU surgery. METHODS: We systematically reviewed EMBASE, PubMed and SCOPUS according to PRISMA criteria in June 2021. Studies that utilized a validated frailty index (FI) to assess risk of major postoperative complication (Clavien-Dindo ≥3), following GU surgery were eligible for inclusion. Charlson Comorbity Index and Eastern Cooperative Oncology Group were not considered FIs. Administrative studies, those without odds ratios (OR) and/or raw data were excluded. The pooled effect size was calculated as OR and corresponding 95% CI through a random effect model using inverse variance weighing. RESULTS: Of 1,265 unique articles initially identified, 9 studies - from 6 different countries, published from 2019-2021, were eligible for inclusion (4 prospective; 5 retrospective). 8/9 studies assessed only GU oncologic surgery. The Modified Frailty Index (mFI) was the most commonly used index (n=3), followed by the Fried Phenotype Criteria (n=2), the Canadian Study of Health and Aging (CSHA) Index (n=2) and the Rockwood Frailty Index (n=2). Data from a total of 2,153 patients was included. Based on pooled OR from both univariable and multivariable analyses, frailty was associated with a significantly higher odds of postoperative complication at 30 days (OR 2.7, 95% CI: 1.8-4.0, p <0.001 and OR 2.1, 95% CI: 1.5-3.0, p <0.001, Fig 1A-B), but may not be at 90 days (OR 2.0, p=0.11 and OR 1.6, p=0.35, Fig 1C-D). Stratified by FI, higher Rockwood and CSHA scores were associated with an increased odds of 30 d complication (OR 1.8, p <0.001 and OR 2.6, p=0.002), but mFI ≥2 was not (OR 5.0, p=0.11). CONCLUSIONS: Frailty indices are a relatively new addition to the urologist’s toolkit. Preoperative assessment of frailty can help predict risk of early (30 d) major postoperative complications but may be less useful for later complications, though significant additional studies are needed. Further work is also needed to evaluate the impact of frailty on non-oncologic urology patients who undergo major GU surgery. Source of Funding: None © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e525 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Jane Kurtzman More articles by this author Preston Kerr More articles by this author Rashed Kosber More articles by this author Steven Brandes More articles by this author Expand All Advertisement PDF DownloadLoading ...
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,042 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,010 | 0,016 |
| Bibliométrie | 0,009 | 0,009 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».