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This study aimed to develop and validate a novel nomogram to predict the risk of non-infectious fever (NIF) in patients following laparoscopic myomectomy. A retrospective analysis was conducted on data from patients who underwent laparoscopic myomectomy between 2019 and 2023. Pertinent variables before, during, and after surgery were collected. Multivariate logistic regression analysis identified independent risk factors for postoperative NIF, from which a nomogram was constructed. The study included 576 patients, among whom 64 (11.1%) developed postoperative NIF. Multivariate analysis identified leiomyoma size, number of leiomyomas, preoperative hemoglobin levels, operative time, and estimated blood loss as independent risk factors for postoperative NIF. A predictive nomogram model incorporating these factors demonstrated good accuracy following internal validation. The developed nomogram represents the first tool tailored for predicting NIF after laparoscopic myomectomy. Its implementation can assist clinicians in early identification of high-risk patients, facilitating timely preventive and management strategies.
This study aimed to develop and validate a novel nomogram to predict the risk of non-infectious fever (NIF) in patients following laparoscopic myomectomy. A retrospective analysis was conducted on data from patients who underwent laparoscopic myomectomy between 2019 and 2023. Pertinent variables before, during, and after surgery were collected. Multivariate logistic regression analysis identified independent risk factors for postoperative NIF, from which a nomogram was constructed. The study included 576 patients, among whom 64 (11.1%) developed postoperative NIF. Multivariate analysis identified leiomyoma size, number of leiomyomas, preoperative hemoglobin levels, operative time, and estimated blood loss as independent risk factors for postoperative NIF. A predictive nomogram model incorporating these factors demonstrated good accuracy following internal validation. The developed nomogram represents the first tool tailored for predicting NIF after laparoscopic myomectomy. Its implementation can assist clinicians in early identification of high-risk patients, facilitating timely preventive and management strategies.
Background Parasitic leiomyoma (PL) consists of uterine fibroids separate from the uterus that grow in extrauterine tissues such as the peritoneum and mesenterium. The diagnosis of PL requires a thorough medical history of laparoscopic myomectomies using a morcellator and the identification of typical magnetic resonance imaging (MRI) findings as uterine fibroids. Imaging diagnosis of PL is occasionally difficult when PL degenerates in various ways, owing to atypical findings on computed tomography (CT) and MRI. Case presentation A 29-year-old woman with a history of laparoscopic myomectomy visited a local hospital with lower abdominal pain. A mesenteric tumor on the sigmoid mesentery was suspected on MRI, and she was referred to our hospital. CT scan showed strong early contrast uptake in the center of the tumor, and MRI T2-weighted images showed high signals at the tumor margins and low signals in the center, suggesting a schwannoma. PL was also part of the differential diagnosis because of the patient’s history of laparoscopic myomectomy. With a preoperative diagnosis of a sigmoid colon mesenteric tumor undeniably of malignant origin, laparoscopic resection of the sigmoid mesenteric tumor was performed. Histopathological examination revealed it to be a PL. Conclusions We report a case of PL of the sigmoid mesentery with schwannoma-like findings on imaging that was treated laparoscopically. PL is sometimes difficult to distinguish from schwannomas because of the variety of imaging findings, such as uterine fibroids. PL should be considered in the differential diagnosis of mesenteric tumors following laparoscopic myomectomies, even if it does not show typical imaging findings, such as uterine fibroids.
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