MP67-12 THE MODIFIED FRAILTY INDEX AS A MARKER OF ADVERSE OUTCOMES DURING CYSTECTOMY FOR UROTHELIAL CANCER
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Résumé
You have accessJournal of UrologyBladder Cancer: Invasive IV1 Apr 2015MP67-12 THE MODIFIED FRAILTY INDEX AS A MARKER OF ADVERSE OUTCOMES DURING CYSTECTOMY FOR UROTHELIAL CANCER Max Kates, Hiten Patel, Gregory Joice, Jeffrey Tosoian, Nikolai Sopko, Jen-Jane Liu, Phillip Pierorazio, and Trinity Bivalacqua Max KatesMax Kates More articles by this author , Hiten PatelHiten Patel More articles by this author , Gregory JoiceGregory Joice More articles by this author , Jeffrey TosoianJeffrey Tosoian More articles by this author , Nikolai SopkoNikolai Sopko More articles by this author , Jen-Jane LiuJen-Jane Liu More articles by this author , Phillip PierorazioPhillip Pierorazio More articles by this author , and Trinity BivalacquaTrinity Bivalacqua More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2015.02.2495AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Frailty has been identified as a marker of physiologic reserve, and a more accurate predictor of adverse postoperative outcomes compared with age. Although many definitions of frailty exist, recently a clinical predictive rule, the “modified frailty index”(mFI), has been developed utilizing administrative data to predict adverse outcomes in the lung cancer population undergoing lobectomy. Our goal was to validate this clinical rule among patients with bladder cancer undergoing cystectomy. METHODS Patients undergoing cystectomy were identified from the National Surgical Quality Improvement Program (NSQIP) participant use files (2006-2011). The mFI was defined as in prior studies with 11 variables based on mapping the Canadian Study of Health and Aging Frailty Index to NSQIP comorbidities and activities of daily living (ADL)s. These 11 variables each received 1 point, and the sum was divided by 11 for a fraction between 0 and 1. Univariate, χ2, independent sample t-test, and logistic regression analyses were performed where appropriate. RESULTS Of the 1302 cystectomy patients identified, 30% had mFI of 0, 40% had mFI of 0.09, 21% had mFI of 0.18, and 9% had mFI ≥0.27. Overall, 56% of patients experienced a Clavien complication. Patients with mFI ≥0.27 were older ( 72 vs 64 yrs)and more likely to be smokers (54%) compared with mFI of 0 (30%, p<0.01). Mean operative times (342-349 minutes) were similar across mFI indices. Reoperation (5% vs 8.5%) and readmission (20.5% vs 25%) were higher when mFI =0 compared with mFI≥0.27 (P<0.01). Clavien 4 and above complications occurred in 9.1% (36/396), 10.1% (53/526), 12.9 % (35/270) and 13.6% (15/110) among patients with an mFI of 0, 0.09, 0.18, and ≥0.27, respectively (p=0.05). Similarly, the overall mortality rate increased from 2.5% in the lowest frailty index group to 5.4% in the highest. CONCLUSIONS Among patients undergoing cystectomy, the modified frailty index can identify those patients at greater risk for severe complications, readmissions, and mortality. Given that bladder cancer is increasing in prevalence particularly among the elderly, pre-operative risk stratification is crucial to inform decision-making. © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 4SApril 2015Page: e854 Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.MetricsAuthor Information Max Kates More articles by this author Hiten Patel More articles by this author Gregory Joice More articles by this author Jeffrey Tosoian More articles by this author Nikolai Sopko More articles by this author Jen-Jane Liu More articles by this author Phillip Pierorazio More articles by this author Trinity Bivalacqua More articles by this author Expand All Advertisement 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 | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,002 |
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 ».