Background: The integration of artificial intelligence (AI) into clinical workflows holds promise for enhancing outpatient decision-making and patient education. ChatGPT, a large language model developed by OpenAI, has gained attention for its potential to support both clinicians and patients. However, its performance in the outpatient setting of general surgery remains underexplored. Objective: This study aimed to evaluate whether ChatGPT-4 can function as a virtual outpatient assistant in the management of puerperal mastitis by assessing the accuracy, clarity, and clinical safety of its responses to frequently asked patient questions in Turkish. Methods: Fifteen questions about puerperal mastitis were sourced from public health care websites and online forums. These questions were categorized into general information (n=2), symptoms and diagnosis (n=6), treatment (n=2), and prognosis (n=5). Each question was entered into ChatGPT-4 (September 3, 2024), and a single Turkish-language response was obtained. The responses were evaluated by a panel consisting of 3 board-certified general surgeons and 2 general surgery residents, using five criteria: sufficient length, patient-understandable language, accuracy, adherence to current guidelines, and patient safety. Quantitative metrics included the DISCERN score, Flesch-Kincaid readability score, and inter-rater reliability assessed using the intraclass correlation coefficient (ICC). Results: A total of 15 questions were evaluated. ChatGPT’s responses were rated as “excellent” overall by the evaluators, with higher scores observed for treatment- and prognosis-related questions. A statistically significant difference was found in DISCERN scores across question types (P=.01), with treatment and prognosis questions receiving higher ratings. In contrast, no significant differences were detected in evaluator-based ratings (sufficient length, understandability, accuracy, guideline compliance, and patient safety), JAMA benchmark scores, or Flesch-Kincaid readability levels (P>.05 for all). Interrater agreement was good across all evaluation parameters (ICC=0.772); however, agreement varied when assessed by individual criteria. Correlation analyses revealed no significant overall associations between subjective ratings and objective quality measures, although a strong positive correlation between literature compliance and patient safety was identified for one question (r=0.968, P<.001). Conclusions: ChatGPT demonstrated adequate capability in providing information on puerperal mastitis, particularly for treatment and prognosis. However, evaluator variability and the subjective nature of assessments highlight the need for further optimization of AI tools. Future research should emphasize iterative questioning and dynamic updates to AI knowledge bases to enhance reliability and accessibility.

Breast abscesses are common in surgical practice, with significant recurrence rates. Identifying factors associated with recurrence is crucial for guiding management and improving outcomes. This study aimed to evaluate the clinical, pathological, radiological, and laboratory factors associated with recurrence in patients who underwent surgical treatment for breast abscesses. This retrospective observational study included female patients who were managed surgically for breast abscesses between January 2018 and June 2024. The data included demographic, surgical, pathological, and laboratory parameters. Statistical analyses were performed to compare the recurrence and non-recurrence groups and identify significant predictors of recurrence. Logistic regression analysis was applied to determine independent predictors of recurrence. A total of 55 patients who underwent surgical treatment for breast abscesses were included in the study. Recurrence was observed in 30.9% of the patients (n = 17). In intergroup comparisons, lower hemoglobin levels were associated with recurrence (mean: 12.1 vs 13.09 g/dL; P = .057; mean difference: −0.994; 95% CI: −2.018 to 0.030), and recurrence was more frequent among Syrian-immigrant patients (17.6% vs 2.6%; χ² = 3.927; P = .048). Logistic regression identified granulomatous mastitis as a significant predictor, increasing the risk of recurrence (OR: 62.7; 95% CI: 1.98–1981.4; P = .031). This study highlights the high recurrence rate of surgically treated breast abscesses and the heterogeneity of the condition, which includes diverse etiologies. Preoperative patient counseling regarding recurrence risk is essential to strengthen the patient–physician relationship.

This study aimed to identify independent predictors of sentinel lymph node (SLN) metastasis in clinically node-negative (cN0) breast cancer and evaluate the diagnostic accuracy of intraoperative frozen section (FS). A retrospective analysis was conducted on 72 female patients with early-stage (cT1-2 cN0) invasive breast cancer who underwent SLN biopsy. Clinical, pathological, and radiological parameters were evaluated. Univariate and multivariate logistic regression analyses were performed to determine independent predictors of metastasis. Intraoperative FS results were compared with definitive paraffin pathology. Definitive permanent paraffin section analysis confirmed SLN metastasis in 41.7% (n = 30) of patients. The false negative rate for intraoperative FS was 23.3%. Multivariate analysis identified lymphovascular invasion (LVI; OR = 8.22, P = .001) and elevated continuous progesterone receptor expression (OR = 1.02, P = .008) as significant independent predictors of initial SLN metastasis. Conversely, human epidermal growth factor receptor 2 positivity demonstrated a significant inverse relationship with nodal involvement (OR = 0.20, P = .010). Other clinicopathological parameters, including Ki-67, were not significantly associated. Our findings suggest that initial SLN metastasis may be primarily associated with the presence of LVI, elevated progesterone receptor expression, and human epidermal growth factor receptor 2 status. Preoperative identification of these specific markers could optimize risk stratification and support the strategic consideration of neoadjuvant systemic therapy to mitigate the diagnostic limitations of intraoperative staging.

Background: Achalasia is a rare esophageal motility disorder that causes dysphagia owing to impaired lower esophageal sphincter (LES) relaxation. This study aimed to evaluate a modified dissection and radial myotomy technique during peroral endoscopic myotomy (POEM) and to compare its outcomes with those of the standard approach. Methods: This prospective, single-center study was conducted between February 2022 and December 2022. Eighty total with 80 achalasia patients undergoing POEM were divided into 2 groups: Group A (n=40), treated with the novel technique, and Group B (n=40), treated with the standard approach. Demographics, Eckardt score (ES), submucosal tunnel (ST), myotomy length, intervention duration, and adverse events were recorded. The follow-up period ranged from 3 to 20 months. Results: Patients who underwent the novel radial myotomy technique (Group A) had significantly longer myotomy lengths (11.8±2.4 vs. 8.1±2.0 cm, P <0.001), greater myotomy extension beyond the esophagogastric junction (4.2±0.8 vs. 2.7±0.6 cm, P <0.001), and improved postoperative Eckardt scores (median 1 [0–1] vs. 2, ^1–3 P =0.006) compared with the conventional POEM group (Group B). Subgroup analysis revealed that in Type III achalasia patients, the novel approach yielded longer submucosal tunnel lengths (15.6±0.8 cm, P =0.038) and favorable symptom relief. Despite extended dissection, there was no increase in gastroesophageal reflux disease (GERD)-related symptoms. Conclusion: The novel dissection and radial myotomy technique demonstrated superior outcomes in reducing dysphagia symptoms and LES resistance compared with the standard approach. Tailoring ST and myotomy lengths based on the achalasia type and EGJ involvement may optimize outcomes without increasing the risk of GERD.

BACKGROUND Puerperal mastitis, affecting up to 30% of breastfeeding women, is a common condition managed in general surgery outpatient clinics. The increasing integration of artificial intelligence (AI) into healthcare presents opportunities for enhancing decision-making processes. OBJECTIVE This study evaluates ChatGPT’s responses to frequently asked questions about puerperal mastitis, focusing on their quality, adherence to clinical guidelines, and patient safety. METHODS Fifteen questions were categorized into general information (n=2), symptoms and diagnosis (n=6), treatment (n=2), and prognosis (n=5). These questions, written in Turkish to reflect the target population, were input into ChatGPT 4.0. Responses were evaluated by five raters using criteria including sufficient length, understandability, accuracy, adherence to literature, and patient safety. DISCERN and Flesch-Kincaid readability scores were also calculated. Statistical analyses compared ratings across question categories and criteria. RESULTS ChatGPT’s responses were rated as “excellent” overall, with higher scores for treatment and prognosis-related questions. DISCERN scores showed significant differences between question categories (p=0.014), with treatment questions receiving the highest ratings. Flesch-Kincaid scores indicated readability at a university graduate level. While strong correlations were observed between adherence to literature and patient safety in certain questions, evaluator consistency varied, with significant differences in accuracy (p<0.001). CONCLUSIONS ChatGPT demonstrated adequate capability in providing information on puerperal mastitis, particularly for treatment and prognosis. However, evaluator variability and the subjective nature of assessments highlight the need for further optimization of AI tools. Future research should emphasize iterative questioning and dynamic updates to AI knowledge bases to enhance reliability and accessibility