MP61-17 CHARACTERIZING CHANGES IN MUSCLE MASS AFTER RADICAL NEPHRECTOMY FOR STAGE II-IV CLEAR CELL RENAL CELL CARCINOMA
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Résumé
You have accessJournal of UrologyKidney Cancer: Epidemiology & Evaluation/Staging/Surveillance III (MP61)1 Sep 2021MP61-17 CHARACTERIZING CHANGES IN MUSCLE MASS AFTER RADICAL NEPHRECTOMY FOR STAGE II-IV CLEAR CELL RENAL CELL CARCINOMA Mouneeb Choudry, Suzanne Lange, Matthew Covington, Jacob Ambrose, Heidi Hanson, Christopher Dechet, Brock O'Neil, Helena Furberg, Adriana Coletta, Jennifer Ose, Jeffrey Yap, Cornelia Ulrich, Jonathan Chipman, and Alejandro Sanchez Mouneeb ChoudryMouneeb Choudry More articles by this author , Suzanne LangeSuzanne Lange More articles by this author , Matthew CovingtonMatthew Covington More articles by this author , Jacob AmbroseJacob Ambrose More articles by this author , Heidi HansonHeidi Hanson More articles by this author , Christopher DechetChristopher Dechet More articles by this author , Brock O'NeilBrock O'Neil More articles by this author , Helena FurbergHelena Furberg More articles by this author , Adriana ColettaAdriana Coletta More articles by this author , Jennifer OseJennifer Ose More articles by this author , Jeffrey YapJeffrey Yap More articles by this author , Cornelia UlrichCornelia Ulrich More articles by this author , Jonathan ChipmanJonathan Chipman More articles by this author , and Alejandro SanchezAlejandro Sanchez More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002101.17AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Sarcopenia (low skeletal muscle mass) is a poor prognostic factor in patients undergoing nephrectomy for localized renal cancer. However, little is known about the trajectory of muscle mass change after surgery. Here, we characterize post-operative changes in muscle mass using a retrospective cohort of patients with clear cell renal cell carcinoma (ccRCC). METHODS: A total of 117 patients with stage II-IV ccRCC who underwent radical nephrectomy from 02/2014-09/2019 at the University of Utah were included. Skeletal muscle (SM) mass area and measures of adiposity (visceral and subcutaneous tissue area) were quantified using standard of care computed tomography (CT) images and Slice-o-matic software (Montreal, Canada). Sarcopenia (yes/no) was classified according to gender-specific international consensus definitions (SMI of <55cm2/m2 for men and <39 cm2/m2 for women). CT images were obtained within 4 months of surgery and at least one scan within 18 months after surgery. RESULTS: Median age 64 (IQR: 56-71), 74% male, 87% White, 69% had stage II-III and 31% had stage IV disease. At baseline, 48% were obese and 54% were considered sarcopenic. Among 80 patients with evaluable skeletal muscle area, 62 patients maintained muscles mass (± 1 SD, 78%) after surgery and 5 had significant muscle deterioration (≥ 2 SD, 6%). CONCLUSIONS: Among patients with stage II-IV clear cell renal cancer undergoing nephrectomy, post-operative muscle loss was present among 22% of patients and significant muscle loss in 6%. Patients with post-operative muscle wasting after surgery may be an ideal group to target with lifestyle interventions. Among a larger cohort of patients, we plan to assess the association of muscle loss with survival outcomes. Source of Funding: The research reported in this publication was supported by Huntsman Cancer Foundation. © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e1090-e1090 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Mouneeb Choudry More articles by this author Suzanne Lange More articles by this author Matthew Covington More articles by this author Jacob Ambrose More articles by this author Heidi Hanson More articles by this author Christopher Dechet More articles by this author Brock O'Neil More articles by this author Helena Furberg More articles by this author Adriana Coletta More articles by this author Jennifer Ose More articles by this author Jeffrey Yap More articles by this author Cornelia Ulrich More articles by this author Jonathan Chipman More articles by this author Alejandro Sanchez More articles by this author Expand All Advertisement Loading ...
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,021 | 0,007 |
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 ».