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Objectives To develop a prediction model of spontaneous ureteral stone passage (SSP) using machine learning and logistic regression and compare the performance of the two models. Indications for management of ureteral stones are unclear, and the clinician determines whether to wait for SSP or perform active treatment, especially in well-controlled patients, to avoid unwanted complications. Therefore, suggesting the possibility of SSP would help make a clinical decision regarding ureteral stones. Methods Patients diagnosed with unilateral ureteral stones at our emergency department between August 2014 and September 2018 were included and underwent non-contrast-enhanced computed tomography 4 weeks from the first stone episode. Predictors of SSP were applied to build and validate the prediction model using multilayer perceptron (MLP) with the Keras framework. Results Of 833 patients, SSP was observed in 606 (72.7%). SSP rates were 68.2% and 75.6% for stone sizes 5–10 mm and <5 mm, respectively. Stone opacity, location, and whether it was the first ureteral stone episode were significant predictors of SSP. Areas under the curve (AUCs) for receiver operating characteristic (ROC) curves for MLP, and logistic regression were 0.859 and 0.847, respectively, for stones <5 mm, and 0.881 and 0.817, respectively, for 5–10 mm stones. Conclusion SSP prediction models were developed in patients with well-controlled unilateral ureteral stones; the performance of the models was good, especially in identifying SSP for 5–10-mm ureteral stones without definite treatment guidelines. To further improve the performance of these models, future studies should focus on using machine learning techniques in image analysis.

Background: The number, location, and pattern of perforators in anterolateral thigh(ALT) flap vary and predicting them preoperatively will aid in reconstructing complex head and neck defects. This article suggests guidelines for utilizing CTA imagery to predict perforators of ALT-free flaps. Methods: We retrospectively analyzed 53 Korean patients who underwent reconstruction with ALT flap in our department from March 2021 to July 2022. The location, course, origin, and pedicle lengths predicted in CTA and confirmed in the operation field were recorded and compared. Results: Among the 85 intraoperatively-found perforators, 79 were also identified in CTA. Six perforators unidentified in CTA were newly found intraoperatively. The positive predictive value of CTA for the perforator was 100%, with a sensitivity of 79/85 = 92.9%. Of the 79 perforators depicted by the CTA for the flap, CTA and intraoperative findings for the course were consistent in 52 cases, a 9.6 mm median discrepancy being noted between the actual location and CTA. Conclusions: The overall pattern or location of perforation was not significantly different between the two, although some differences were observed. It is suggested that the addition of Doppler imaging, in conjunction with CTA, can aid in perforator detection and help minimize such discrepancies.

Although some surgeons prefer anterolateral thigh and latissimus dorsi ap for soft tissue reconstruction in head and neck area because it minimizes donor site complications, radial forearm ap remains the workhorse for soft tissue reconstruction due to its reliability. To reduce donor site morbidity, the authors developed a novel technique for radial forearm ap harvesting using a robotic device. 42 radial forearm free ap reconstruction cases were studied, consisting of 31 conventional and 11 robotassisted cases. 1:1 propensity score matching was done according to age, sex, previous and postoperative radiation therapy history and method used for vein anastomosis.There were no signi cant difference was in ap outcome, which was 100% vitality in the robot-assisted group and 90.9% vitality in the conventional group. The robot-assisted group showed signi cantly longer mean harvesting time than did the conventional group, being 107.2 minutes and 67.0 minutes respectively.Robot-assisted radial forearm ap harvesting can reduce donor site complications by minimizing incision. When more surgical experience is gained under appropriate case selection, we expect our robotassisted method will yield a harvesting time similar to that of the conventional method and thus become more reliable and feasible.

Background Noma is a rare disease that occurs mainly in malnourished patients in developing countries. Noma starts as facial swelling and gingival necrosis that eventually necrotizes underlying tissues including the jaw bone, leaving severe disfigurement. It is reported extremely rarely in patients with severe immunosuppression or blood dyscrasia. Case presentation The gingivitis that occurred in a 12-year-old Asian female patient with acute myeloid leukemia was getting increasingly worse. Although the proper treatment was done, the patient’s condition did not improve, and eventually, a large full-thickness defect was left in the maxillofacial part. Conclusions Early diagnosis and management is the only way to prevent the progression, which leads to facial disfigurement. We present a case of noma in a pediatric acute myeloid leukemia patient, in which oral function was restored through surgical intervention.