2249 PREVALENCE OF UROLITHIASIS AND METABOLIC ABNORMALITIES OF PATIENTS WITH SURGICALLY CONFIRMED PRIMARY HYPERPARATHYROIDISM
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Résumé
You have accessJournal of UrologyStone Disease: Evaluation & Medical Management (II)1 Apr 20132249 PREVALENCE OF UROLITHIASIS AND METABOLIC ABNORMALITIES OF PATIENTS WITH SURGICALLY CONFIRMED PRIMARY HYPERPARATHYROIDISM Mohamed Elkoushy, Alice Yu, Roger Tabah, Richard Payne, and Sero Andonian Mohamed ElkoushyMohamed Elkoushy Montreal, Canada More articles by this author , Alice YuAlice Yu Montreal, Canada More articles by this author , Roger TabahRoger Tabah Montreal, Canada More articles by this author , Richard PayneRichard Payne Montreal, Canada More articles by this author , and Sero AndonianSero Andonian Montreal, Canada More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2013.02.2158AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Primary hyperparathyroidism (PHPT) is well-known to cause nephrolithiasis and nephrocalcinosis which may ultimately result in impaired renal function. The reported prevalence of stone formation in patients with PHPT varies widely among different studies. Moreover, there is sparse data comparing metabolic stone parameters before and following successful Parathyroidectomy (PTX). Therefore, the aim of the present study was to determine the prevalence of urolithiasis in patients with PHPT and to evaluate their metabolic stone work-up before and after PTX. METHODS Institutional Research Ethics approval was obtained. A retrospective review of prospectively collected data was performed for patients presenting with PHPT to the stone, surgical oncology, and otolaryngology clinics at two tertiary centers from January 2006 until November 2011. Data was collected regarding patient characteristics, operative records, pathology (hyperplasia vs. adenoma), and presence of urolithiasis together with 24-hour urine collections before and after PTX, when available. RESULTS Of 333 patients undergoing PTX, 255 patients had surgically-confirmed PHPT and were included in this study. Mean (range) age was 60.3 (18-91) years and 68.2% were females. Preoperative renal calcification was detected in 51 (20%) patients; urolithiasis in 48(18.8%) and nephrocalcinosis in 3 (1.2%) patients. Compared with PHPT patients without urolithiasis, PHPT patients with urolithiasis were significantly younger (61.3 vs. 55.9 years, p=0.02), less likely to be female (71.5% vs. 54.2%, p=0.025) and had significantly lower levels of 25-hydroxyl vitamin D (23.9 vs. 19.7 ng/ml, p=0.03). Nine patients (3.5%) developed recurrent urolithiasis post-PTX and were found to have significantly higher post-PTX total serum calcium levels when compared with patients without recurrent urolithiasis (12.6 vs. 10.9 mg/dl, p=0.01). Similarly, there were significantly more males in the post-PTX recurrent urolithiasis cohort (66.7% vs. 30.5%, p=0.03). Whereas 62% of stone-former were hypercalciuric pre-PTX, no patient had hypercalciuria post-PTX (p<0.001). On multivariate regression, male gender (aOR (95%CI): 6.8 (5.3-7.2), p=0.01) and post-PTX total serum calcium level independently predicted stone recurrence post-PTX (aOR (95%CI): 1.48 (1.33?2.12, p = 0.02). CONCLUSIONS A high prevalence of urolithiasis was detected in patients presenting with PHPT. Male gender and post-PTX total serum calcium level independently predicted stone recurrence. © 2013 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 189Issue 4SApril 2013Page: e922-e923 Advertisement Copyright & Permissions© 2013 by American Urological Association Education and Research, Inc.Metrics Author Information Mohamed Elkoushy Montreal, Canada More articles by this author Alice Yu Montreal, Canada More articles by this author Roger Tabah Montreal, Canada More articles by this author Richard Payne Montreal, Canada More articles by this author Sero Andonian Montreal, 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 | 0,000 | 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 | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».