Background And Study Aims: Although peroral endoscopic myotomy (POEM) is being performed more frequently, the learning curve for gastroenterologists performing the procedure has not been well studied. The aims of this study were to define the learning curve for POEM and determine which preoperative and intraoperative factors predict the time that will be taken to complete the procedure and its different steps.
Patients And Methods: Consecutive patients who underwent POEM performed by a single expert gastroenterologist for the treatment of achalasia or spastic esophageal disorders were included. The POEM procedure was divided into four steps: mucosal entry, submucosal tunneling, myotomy, and closure. Nonlinear regression was used to determine the POEM learning plateau and calculate the learning rate.
Results: A total of 60 consecutive patients underwent POEM in an endoscopy suite. The median length of procedure (LOP) was 88 minutes (range 36 - 210), and the mean (± standard deviation [SD]) LOP per centimeter of myotomy was 9 ± 5 minutes. The total operative time decreased significantly as experience increased (P < 0.001), with a "learning plateau" at 102 minutes and a "learning rate" of 13 cases. The mucosal entry, tunneling, and closure times decreased significantly with experience (P < 0.001). The myotomy time showed no significant decrease with experience (P = 0.35). When the mean (± SD) total procedure times for the learning phase and the corresponding comparator groups were compared, a statistically significant difference was observed between procedures 11 - 15 and procedures 16 - 20 (15.5 ± 2.4 min/cm and 10.1 ± 2.7 min/cm, P = 0.01) but not thereafter. A higher case number was significantly associated with a decreased LOP (P < 0.001).
Conclusion: In this single-center retrospective study, the minimum threshold number of cases required for an expert interventional endoscopist performing POEM to reach a plateau approached 13.
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http://dx.doi.org/10.1055/s-0042-104113 | DOI Listing |
JMIR Med Inform
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Department of Science and Education, Shenzhen Baoan Women's and Children's Hospital, Shenzhen, China.
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View Article and Find Full Text PDFJ Occup Health
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Panasonic Corporation, Department Electric Works Company/Engineering Division, Osaka, Japan.
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Esophagus
January 2025
Department of Surgery, Tohoku University Graduate School of Medicine, 1-1 Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8574, Japan.
Background: Neoadjuvant chemotherapy is standard for advanced esophageal squamous cell carcinoma, though often ineffective. Therefore, predicting the response to chemotherapy before treatment is desirable. However, there is currently no established method for predicting response to neoadjuvant chemotherapy.
View Article and Find Full Text PDFInsights Imaging
January 2025
Department of Orthopaedics, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China.
Introduction: A large number of middle-aged and elderly patients have an insufficient understanding of osteoporosis and its harm. This study aimed to establish and validate a convolutional neural network (CNN) model based on unenhanced chest computed tomography (CT) images of the vertebral body and skeletal muscle for opportunistic screening in patients with osteoporosis.
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J Robot Surg
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Department of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China.
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