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Objectives: There is a lack of data on the number of surgeries required for endoscopic combined intrarenal surgery (ECIRS). Accordingly, we aimed to identify the learning curve for ECIRS performed by multiple surgeons.
Methods: We included 296 patients who underwent ECIRS at our university hospital between 2016 and 2021. A learning curve for percutaneous nephrolithotomy side was calculated considering urology-resident surgeons. The learning curve was retrospectively analyzed for surgical time, renal puncture time, stone-free rate, and complications and corrected for age, body mass index, stone size, computed tomography value, cumulative number of surgeries, and stone location.
Results: This study included cases performed by 32 surgeons, including 30 residents and 2 attending surgeons. The median number of surgeries performed by the residents and attending surgeons prior to this study was 4.5 and 90, respectively. The median number of surgical procedures performed during the training period was seven. The surgical time of the residents decreased as the number of cases increased, reaching a median surgical time of 111 min for the attending surgeons after 16.4 cases. Renal puncture time was achieved in 20.1 cases. Complications related to renal access were observed in 13.0% (34 patients), Clavien-Dindo grade II in 1.9% (5 patients), and grade III or higher in 0.8% (2 patients). Comparing the first to fifth cases with the 21st and subsequent cases, the complication rate improved from 35% to 13%.
Conclusion: Our study demonstrated that ECIRS training provided 16-20 cases with a learning curve to achieve acceptable surgical outcomes.
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http://dx.doi.org/10.1111/iju.15520 | DOI Listing |
Int J Surg
September 2025
Department of Anesthesiology, Qingdao Municipal Hospital, Qingdao, Shandong Province, China.
Background: As a common postoperative neurological complication, postoperative delirium (POD) can lead to poor postoperative recovery in patients, prolonged hospitalization, and even increased mortality. However, POD's mechanism remains undefined and there are no reliable molecular markers of POD to date. The present work examined the associations of cerebrospinal fluid (CSF) sTREM2 with CSF POD biomarkers, and investigated whether the effects of CSF sTREM2 on POD were modulated by the core pathological indexes of POD (Aβ42, tau, and ptau).
View Article and Find Full Text PDFInt J Surg
September 2025
Department of Respiratory and Critical Care Medicine, Hubei Province Clinical Research Center for Major Respiratory Diseases, Key Laboratory of Pulmonary Diseases of National Health Commission, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
Background: Precise preoperative discrimination of invasive lung adenocarcinoma (IA) from preinvasive lesions (adenocarcinoma in situ [AIS]/minimally invasive adenocarcinoma [MIA]) and prediction of high-risk histopathological features are critical for optimizing resection strategies in early-stage lung adenocarcinoma (LUAD).
Methods: In this multicenter study, 813 LUAD patients (tumors ≤3 cm) formed the training cohort. A total of 1,709 radiomic features were extracted from the PET/CT images.
Biomed Environ Sci
August 2025
School of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Objective: To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance.
Methods: A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument.
Clin Nurs Res
September 2025
Chonnam National University College of Nursing, Donggu, Gwangju, South Korea.
The increasing prevalence of diabetes mellitus (DM) and patients' lack of self-management awareness have led to a decline in health-related quality of life (HRQoL). Studies identifying potential risk factors for HRQoL in DM patients and presenting generalized models are relatively scarce. The study aimed to develop and evaluate a machine learning (ML)-based model to predict the HRQoL in adult diabetic patients and to examine the important factors affecting HRQoL.
View Article and Find Full Text PDFClin Nurs Res
September 2025
Xuzhou Medical University, Jiangsu Province, China.
This study aimed to develop and validate a machine learning-based predictive model for assessing the risk of fear of childbirth in pregnant women during late pregnancy. A cross-sectional observational study was conducted from November 2022 to July 2023, involving 406 pregnant women. Six machine learning algorithms, including Lasso-assisted logistic regression (LR), random forest (RF), eXtreme Gradient Boosting (XGB), support vector machine (SVM), Bayesian network (BN), and k-nearest neighbors (KNN), were used to construct the models with 10-fold cross-validation.
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