1536 TIME TRENDS IN THE SURGICAL MANAGEMENT OF KIDNEY STONE DISEASE
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Résumé
You have accessJournal of UrologyStone Disease: New Technology/SWL, Ureteroscopic or Percutaneous Stone Removal I1 Apr 20121536 TIME TRENDS IN THE SURGICAL MANAGEMENT OF KIDNEY STONE DISEASE Michael Ordon, Refik Saskin, Muhammad Mamdani, David Urbach, R. John D'A. Honey, and Kenneth T. Pace Michael OrdonMichael Ordon Toronto, Canada More articles by this author , Refik SaskinRefik Saskin Toronto, Canada More articles by this author , Muhammad MamdaniMuhammad Mamdani Toronto, Canada More articles by this author , David UrbachDavid Urbach Toronto, Canada More articles by this author , R. John D'A. HoneyR. John D'A. Honey Toronto, Canada More articles by this author , and Kenneth T. PaceKenneth T. Pace Toronto, Canada More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2012.02.1305AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES The management of kidney stone disease has changed dramatically over the past 30 years as a result of significant new technologic and treatment advances. In particular, ureteroscopy (URS) has become a much safer and efficacious procedure with less morbidity. As a result, based on physician surveys and reports from single center series the rate of URS appears to have increased over time. However, large population-based evaluations to assess the changes over time in the surgical treatment of kidney stone disease have not been conducted. Our objective was to evaluate population-based trends in the use of extracorporeal shockwave lithotripsy (SWL), URS and percutaneous nephrolithotomy (PCNL) over the past 20 years, in the province of Ontario, Canada. METHODS Using the Ontario Health Insurance Plan (OHIP) physician claims database we conducted a population-based cross-section time series analysis by identifying all kidney stone treatments performed between July 1, 1991 and Dec. 31, 2010 in the province of Ontario. Ontario has a universal insurance program that covers all 13 million residents and billing outside of the program is not permitted. As such, the data can be considered population based. The primary endpoint was the proportion of all stone treatments represented by each modality, which was calculated for every 3-month block over the study period. Exponential smoothing models were utilized to assess for trends over time in the percent utilization of each of SWL, URS and PCNL. RESULTS We identified 194,781 kidney stone treatments between July 1, 1991 and Dec. 31, 2010. A total of 96,807 SWL treatments, 83,923 URS treatments and 14,051 PCNL treatments were performed. We observed a significant trend over time for decreased utilization of SWL (68.5% to 33.7%, p<0.0001) and an increase in URS utilization (24.6% to 59.5%, p=0.0002), while no change over time was found for PCNL (6.88% to 6.85%, p=0.97) (Figure 1). By the end of 2004, URS had become the most widely used procedure. CONCLUSIONS Our population-based study confirms the increased use of URS over time suggested by physician survey and single centre retrospective series. Accordingly, the utilization of SWL has decreased in a reciprocal fashion. © 2012 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 187Issue 4SApril 2012Page: e621-e622 Advertisement Copyright & Permissions© 2012 by American Urological Association Education and Research, Inc.MetricsAuthor Information Michael Ordon Toronto, Canada More articles by this author Refik Saskin Toronto, Canada More articles by this author Muhammad Mamdani Toronto, Canada More articles by this author David Urbach Toronto, Canada More articles by this author R. John D'A. Honey Toronto, Canada More articles by this author Kenneth T. Pace Toronto, Canada 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 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,005 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,003 |
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 ».