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Objective: Gynecological malignancies are significant causes of mortality and morbidity in women worldwide. Although surgery is an important treatment method, both the extent of the surgery and the factors related to the patient affect postoperative processes. The National Early Warning Score 2 (NEWS2) is a simple, inexpensive, and safe early warning score developed in 2012 and updated in 2017. Although it is not commonly used in surgical patients, its use in patients who will undergo major surgery may provide insights about the postoperative process. This study investigates the importance of NEWS2 and its relationship in patients with for major gynecologic oncology surgery. Materials and Methods: Forty-four patients with gynecologic malignancies scheduled for major abdominal surgery were included in this study. Patients with a NEWS-2 score of <3 were included in group 1, and patients with a NEWS-2 score of more than 3 were included in groups 2. NEWS2 Score, Sequential Organ Failure Assessment (SOFA), and Acute Physiology and Chronic Health Evaluation 2 scores (APACHE 2) were calculated. In addition, postoperative routine clinical and laboratory parameters were evaluated. Operation time, duration of intubation in the intensive care unit (ICU), the length of the intensive care stay, and length of hospitalization were recorded. Results: Duration of intubation in the ICU in group 1 with a NEWS2 <3 [8.2 (0-18) vs 16.2 (3-39), respectively; p<0.01], ICU length of stay [21.6 (4-27) vs 47.3 (4-113), respectively; p<0.01], length of hospitalization [11.6 (5-56) vs 18.6 (8-67), respectively; p<0.01]. NEWS2 >3 was significantly higher compared to group 2. The SOFA score was significantly higher in group 2 compared with group 1 [1.2±0.5 vs 4.1±1.9; respectively; p<0.01]. In the correlation analysis, the NEWS2 score level was positively correlated with the SOFA score (p<0.001, r=0.81) and hospitalization time (p<0.001, r=0.60) and neutrophil lymphocyte ratio (NLR) (p<0.001, r=0.47). Conclusion: These findings suggest that the NEWS2 score may be correlated with the length of intensive care intubation, length of intensive care stay, and length of hospitalization. NEWS2 is an effective and simple scoring system that provides information about postoperative outcomes in gynecologic oncology patients scheduled for major surgery.
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BACKGROUND: The current approach to endometrial cancer screening requires that all patients be able to recognize symptoms, report them, and carry out appropriate interventions. The current approach to endometrial cancer screening could become a problem in the future, especially for Black women and women from minority groups, and could lead to disparities in receiving proper care. Moreover, there is a lack of literature on artificial intelligence in the prediction and diagnosis of endometrial intraepithelial neoplasia and endometrial cancer. OBJECTIVE: This study analyzed different artificial intelligence methods to help in clinical decision-making and the prediction of endometrial intraepithelial neoplasia and endometrial cancer risks in pre- and postmenopausal women. This study aimed to investigate whether artificial intelligence may help to overcome the challenges that statistical and diagnostic tests could not. STUDY DESIGN: This study included 564 patients. The features that were collected included age, menopause status, premenopausal abnormal bleeding and postmenopausal bleeding, obesity, hypertension, diabetes mellitus, smoking, endometrial thickness, and history of breast cancer. Endometrial sampling was performed on all women with postmenopausal bleeding and asymptomatic postmenopausal women with an endometrial thickness of at least 3 mm. Endometrial biopsy was performed on premenopausal women with abnormal uterine bleeding and asymptomatic premenopausal women with suspected endometrial lesions. Python was used to model machine learning algorithms. Random forest, logistic regression, multilayer perceptron, Catboost, Xgboost, and Naive Bayes methods were used for classification. The synthetic minority oversampling technique was used to correct the class imbalance in the training sets. In addition, tuning and boosting were used to increase the performance of the models with a 5-fold cross-validation approach using a training set. Accuracy, sensitivity, specificity, positive predictive value, and F1 score were calculated. RESULTS: The prevalence of endometrial or preuterine cancer was 7.9%. Data from 451 patients were randomly assigned to the training group, and data from another 113 patients were used for internal validation. Of note, 3 of 9 features were selected by the Boruta algorithm for use in the final modeling. Age, body mass index, and endometrial thickness were all associated with a high risk of developing precancerous and cancerous diseases, after fine-tuning for the multilayer computer to have the highest area below the receiver operating characteristic curve (area under the curve, 0.938) to predict a precancerous disease. The accuracy was 0.94 for predicting a precancerous disease. Precision, recall, and F1 scores for the test group were 0.71, 0.50, and 0.59, respectively. CONCLUSION: Our study found that artificial intelligence can be used to identify women at risk of endometrial intraepithelial neoplasia and endometrial cancer. The model is not contingent on menopausal status or symptoms. This may be an advantage over the traditional methodology because many women, especially Black women and women from minority groups, could not recognize them. We have proposed to include patients to provide age and body mass index, and measurement of endometrial thickness by either sonography or artificial intelligence may help improve healthcare for women in rural or minority communities.
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STUDY OBJECTIVE: To present technique of vaginally assisted laparoscopic urethrolysis and mesh excision after tension-free vaginal tape. DESIGN: Demonstration video. SETTING: Despite the Food and Drug Administration's warning to limit the use of mesh, midurethral sling surgery (MUS) has not significantly decreased, but operations for complications have increased 3 times [1]. Urethral obstruction after MUS has an incidence of 2.7% to 11% [2] that requires resurgery, which ranges from pull-down, mesh excision to urethrolysis and is chosen by the surgeon's experience. Retropubic urethrolysis and mesh excision are reported to be more successful [3]. Urethrolysis can be performed by a retropubic, transvaginal, or suprameatal approach. Transvaginal mesh excision and urethrolysis are not satisfactory in all cases, and it might be difficult to identify the mesh if it is dislocated proximally or buried in dense fibrosis, which may increase urethral/bladder injuries. Although vaginal urethrolysis and mesh removal are usually preferred as the primary approach, there is no randomized controlled trial comparing retropubic and vaginal urethrolysis with/without mesh removal. Gynecologists should master each technique to provide individualized treatment. Laparoscopic urethrolysis has the advantage of the identification of neighboring structures and provides a safer operation (Fig. 1). Combined vaginal and laparoscopic approaches can be used to totally remove the mesh and for difficult surgeries at the junction of the retropubic urethra and the midurethra (Fig. 2). INTERVENTIONS: (1) Timing of urethrolysis is controversial. Although urethral loosening or pulling down in the first few days and mesh excision in the first 15 days can be useful, urethrolysis can be chosen for delayed cases with marked fibrosis. Preoperative diagnostic cystoscopy to exclude urethral mesh erosion is essential. Intermittent catheterization until surgery should be done. (2) The technique is described in 5 steps. The arcus tendineus is an important landmark [4] (Fig. 3). CONCLUSION: Laparoscopic urethrolysis for urinary obstruction after MUS can be a safe and successful procedure after failed vaginal approach or can be considered as a primary approach in select cases.