Publications by authors named "Jesur Batur"

2 Publications

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A multicenter study to develop a non-invasive radiomic model to identify urinary infection stone in vivo using machine-learning.

Kidney Int 2021 Jun 12. Epub 2021 Jun 12.

Department of Pharmacy, the First People's Hospital of Kashi Prefecture, Affiliated Kashi Hospital of Sun Yat-Sen University, Kashi, People's Republic of China. Electronic address:

Urolithiasis is a common urological disease, and treatment strategy options vary between different stone types. However, accurate detection of stone composition can only be performed in vitro. The management of infection stones is particularly challenging with yet no effective approach to pre-operatively identify infection stones from non-infection stones. Therefore, we aimed to develop a radiomic model for preoperatively identifying infection stones with multicenter validation. In total, 1198 eligible patients with urolithiasis from three centers were divided into a training set, an internal validation set, and two external validation sets. Stone composition was determined by Fourier transform infrared spectroscopy. A total of 1316 radiomic features were extracted from the pre-treatment Computer Tomography images of each patient. Using the least absolute shrinkage and selection operator algorithm, we identified a radiomic signature that achieved favorable discrimination in the training set, which was confirmed in the validation sets. Moreover, we then developed a radiomic model incorporating the radiomic signature, urease-producing bacteria in urine, and urine pH based on multivariate logistic regression analysis. The nomogram showed favorable calibration and discrimination in the training and three validation sets (area under the curve [95% confidence interval], 0.898 [0.840-0.956], 0.832 [0.742-0.923], 0.825 [0.783-0.866], and 0.812 [0.710-0.914], respectively). Decision curve analysis demonstrated the clinical utility of the radiomic model. Thus, our proposed radiomic model can serve as a non-invasive tool to identify urinary infection stones in vivo, which may optimize disease management in urolithiasis and improve patient prognosis.
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June 2021

Prevalence of urolithiasis among the Uyghur children of China: a population-based cross-sectional study.

BJU Int 2019 09 7;124(3):395-400. Epub 2019 May 7.

Department of Urology, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Objectives: To investigate the prevalence and associated factors of urolithiasis amongst Uyghur children.

Subjects And Methods: A cross-sectional survey was conducted of Uyghur children (aged ≤14 years) in the Kashgar Region of China, from July to December 2016. Children were selected by a two-stage random clustered sampling method, evaluated by urinary tract ultrasonography, low-dose computed tomography (CT) examination, blood and urine analysis, and a questionnaire. The prevalence by CT, the prevalence by self-report in the questionnaires, and the lifetime prevalence were evaluated. Binary logistic regression was used to estimate the associated factors.

Results: A total of 5605 children were selected and invited to participate in the study. In all, 4813 Uyghur children (2471 boys and 2342 girls), with an mean (SD; range) age of 75.79 (43.81; 2-177) months, were included in the final analysis, with a response rate of 85.9%. The prevalence of paediatric urolithiasis was 1.8% (95% confidence interval [CI] 1.5-2.2) by CT, 2.3% (95% CI 1.9-2.7) by self-report, and 3.6% (95% CI 3.0-4.1) for the overall life-time. The age-sex adjusted prevalence was 2.0% (95% CI 1.6-2.4) by CT. Binary logistic regression analysis showed that body mass index, urinary tract infection, a family history of urolithiasis, and excessive sweating could increase the risk of stone formation, whilst breast feeding and drinking water at midnight could decrease the risk.

Conclusions: Urolithiasis is a major public health problem amongst Uyghur children, and strategies aimed at the prevention of urolithiasis are needed.
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September 2019