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Introduction: Oncoplastic surgery (OPS) is a form of breast conservation surgery involving partial mastectomy followed by volume displacement or replacement surgery. As the field of OPS is growing, we sought to determine if there was a learning curve to this surgery.
Methods: A retrospective chart review was conducted of all patients who underwent OPS over a 6-year period with a single surgeon formally trained in both Plastic Surgery and Breast Oncology. Cumulative summation analysis (CUSUM) was performed on mean operative time to generate the learning curve and learning curve phases. Outcomes were compared between phases to determine significance.
Results: Mean operative time decreased significantly across the 6-year period, generating three distinct learning curve phases: Learner phase (cases 1-23), Competence phase (24-73), and Mastery phase (74 and greater). The overall positive margin rate was 10.9% and there was no significant difference in rates between phases (p = 0.49). Overall complication rates, reoperation rates, and locoregional recurrence remained the same across all phases (p = 0.16; p = 0.65; p = 0.41). The rate of partial nipple loss decreased between phases (p = 0.02).
Conclusion: As with many complex operations, there does appear to be a learning curve with OPS, as the operative time and the rates of partial nipple loss decreased over time.
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http://dx.doi.org/10.1002/jso.27294 | DOI Listing |
Knee Surg Relat Res
September 2025
Florida Orthopaedic Institute, Gainesville, FL, 32607, USA.
Background: A clear understanding of minimal clinically important difference (MCID) and substantial clinical benefit (SCB) is essential for effectively implementing patient-reported outcome measurements (PROMs) as a performance measure for total knee arthroplasty (TKA). Since not achieving MCID and SCB may reflect suboptimal surgical benefit, the primary aim of this study was to use machine learning to predict patients who may not achieve the threshold-based outcomes (i.e.
View Article and Find Full Text PDFGeroscience
September 2025
Department of Urology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
This study aims to investigate the predictive value of combined phenotypic age and phenotypic age acceleration (PhenoAgeAccel) for benign prostatic hyperplasia (BPH) and develop a machine learning-based risk prediction model to inform precision prevention and clinical management strategies. The study analyzed data from 784 male participants in the US National Health and Nutrition Examination Survey (NHANES, 2001-2008). Phenotypic age was derived from chronological age and nine serum biomarkers.
View Article and Find Full Text PDFImmunol Res
September 2025
Department of Immunology and Allergy, Faculty of Medicine, Necmettin Erbakan University, Konya, Türkiye.
Background: Variants of uncertain significance (VUS) represent a major diagnostic challenge in the interpretation of genetic testing results, particularly in the context of inborn errors of immunity such as severe combined immunodeficiency (SCID). The inconsistency among computational prediction tools often necessitates expensive and time-consuming wet-lab analyses.
Objective: This study aimed to develop disease-specific, multi-class machine learning models using in silico scores to classify SCID-associated genetic variants and improve the interpretation of VUS.
Ren Fail
December 2025
Department of Critical Care Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, China.
This study aimed to develop a predictive model and construct a graded nomogram to estimate the risk of severe acute kidney injury (AKI) in patients without preexisting kidney dysfunction undergoing liver transplantation (LT). Patients undergoing LT between January 2022 and June 2023 were prospectively screened. Severe AKI was defined as Kidney Disease: Improving Global Outcomes stage 3.
View Article and Find Full Text PDFJMIR Med Educ
September 2025
Institute for General Practice and Interprofessional Care, University Hospital Tübingen, Osianderstraße 5, Tübingen, 72076, Germany, 49 70712985285.
Background: The increasing prevalence of dermatological diseases will pose a growing challenge to the health care system and, in particular, to general practitioners (GPs) as the first point of contact for these patients. In many countries, primary care physicians are supported by teledermatology services.
Objective: The aim of this study was to detect learning effects and gains among GPs through teledermatology consultations (TCs) in daily practice.