MP14-03 SIMPLIFIED FRAILTY INDEX PREDICTS ADVERSE SURGICAL OUTCOMES AND INCREASED LENGTH OF STAY IN RADICAL PROSTATECTOMY PATIENTS: AN ANALYSIS OF THE ACS-NSQIP DATABASE
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Résumé
You have accessJournal of UrologyProstate Cancer: Epidemiology & Natural History III1 Apr 2015MP14-03 SIMPLIFIED FRAILTY INDEX PREDICTS ADVERSE SURGICAL OUTCOMES AND INCREASED LENGTH OF STAY IN RADICAL PROSTATECTOMY PATIENTS: AN ANALYSIS OF THE ACS-NSQIP DATABASE Danny Lascano, Jamie S. Pak, Alexander C. Small, Mark V. Silva, James M. McKiernan, G. Joel DeCastro, Sven Wenske, and Mitchell C. Benson Danny LascanoDanny Lascano More articles by this author , Jamie S. PakJamie S. Pak More articles by this author , Alexander C. SmallAlexander C. Small More articles by this author , Mark V. SilvaMark V. Silva More articles by this author , James M. McKiernanJames M. McKiernan More articles by this author , G. Joel DeCastroG. Joel DeCastro More articles by this author , Sven WenskeSven Wenske More articles by this author , and Mitchell C. BensonMitchell C. Benson More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2015.02.865AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Frailty is usually assessed in a non-standardized manner with descriptions of patients such as appearing “older than stated age”. Currently, no suitable measure exists to qualify this parameter, despite its potentially large impact on surgical outcomes. Therefore, a modified frailty index (FI) was applied to the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) data to evaluate whether it predicts adverse post-surgical outcomes. METHODS The ACS-NSQIP Participant Utilization File was queried for the years 2005–2012 for inpatient radical prostatectomy (RP) patients (n=16848). Employing the Canadian Study of Health and Aging frailty index, 11 variables were matched to NSQIP to create a modified frailty index (FI) using including diabetes mellitus, functional status, CHF, MI, prior cardiac surgery, hypertension, peripheral vascular disease, impaired sensorium, and TIA or CVA with neurological sequela. Four variables specific to cancer were also including: chemotherapy or radiation, weight loss, renal failure, and metastasis. Outcomes assessed included 30-day mortality, surgical site infection (SSI), MI, DVT/PE, Clavien IV complications, length of stay (LOS), and combined adverse events. Chi-square analysis was used for comparing categorical variables, Kruskal-Wallis for non-parametric continuous variables, and logistic regression for comparing different clinical tests. RESULTS Increasing FI was significantly associated with Clavien IV complications, number of SSI and all combined adverse events (p<0.05 for all). A Kruskal-Wallis H test demonstrated a statistically significant difference in LOS between those with different FI (χ2 = 88.02, p<0.01) with a mean rank of 3, 4, 6, 5, 2 and 1 day(s) for FI of 1, 2, 3, 4, 5 and 6 respectively. Multivariate analysis indicated that FI was significantly correlated with Clavien IV complications (OR 1.368, p< 0.01), MI (OR 2.745, p < 0.01), and adverse events including SSI, UTIs and DVT/PE (OR 1.371, p <0.01). CONCLUSIONS Using a large national database, a modified frailty index was shown to significantly correlate with 30-day morbidity and length of stay after RP but not with mortality. This simple tool may be useful for both risk assessment and surgical planning, especially in elderly patients with multiple comorbidities. © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 4SApril 2015Page: e151-e152 Peer Review Report Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.MetricsAuthor Information Danny Lascano More articles by this author Jamie S. Pak More articles by this author Alexander C. Small More articles by this author Mark V. Silva More articles by this author James M. McKiernan More articles by this author G. Joel DeCastro More articles by this author Sven Wenske More articles by this author Mitchell C. Benson 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 | 0,002 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».