Clinical significance of risk factor analysis in pancreatic cancer by using supervised model of machine learning

IntroductionPancreatic cancer (PC) poses a significant global health challenge due to its aggressive nature, late-stage diagnosis, and high mortality despite advancements in treatment. Early detection remains crucial for timely intervention. This study aimed to identify clinically relevant predictors of pancreatic cancer using a supervised machine learning approach and to develop a risk stratification tool with diagnostic capabilities.MethodsA matched case-control study was conducted retrospectively at the Tenth People’s Hospital of Tongji University (2017–2023), involving 353 cases and 370 matched controls. Demographic and hematological data were extracted from medical records. Variables were pre-selected using cluster dendrograms and subsequently refined using logistic regression with backward elimination and Support Vector Machine (SVM) models. A final risk scoring model was developed based on the best-performing model and internally validated.ResultsKey predictors retained in the final logistic regression model included Hemoglobin A1c (HbA1c) (OR 1.28; 95% CI: 1.08–1.52), Alkaline Phosphatase (ALP) (OR 1.02; 95% CI: 1.01–1.03), CA19-9 (OR 1.01; 95% CI: 1.01–1.01), Carcinoembryonic Antigen (CEA) (OR 1.41; 95% CI: 1.20–1.66), and Body Mass Index (BMI) (OR 0.88; 95% CI: 0.81–0.97). The final model demonstrated excellent diagnostic performance (AUC = 0.969, p < 0.001), with high accuracy, sensitivity, and specificity. A nomogram was constructed to facilitate individualized PC risk assessment.ConclusionHbA1c, ALP, CA19-9, CEA, and BMI were independently associated with pancreatic cancer. The machine learning-derived risk scoring model demonstrated high predictive accuracy and may serve as a valuable clinical tool for early detection and screening of pancreatic cancer

Cannabis Use and Abuse in Nepal: A Review of Studies

Nepal is a geographically, ecologically, bio-culturally and ethnically diverse country. Cannabis has been a flora, used in various forms and ways and its effect has been variably a matter of concern in Nepal. Perception to its use has also been changing with time with the dynamics of various factors and trends around and in the world. The views of its proponents at times appear with relatively more powerful influence among people though the views of the opponents seem less, and relatively less influential. Proponents advocate for its legalization with highlights of its different uses and benefits whereas opponents, mainly mental health professionals point out sporadically its adverse consequences, mainly in psychological health. The purpose of this review is to explore the existing literature regarding cannabis use and abuse in Nepal. Search for articles for this review was performed in PubMed, Google Scholar, and Nepal Journal Online. We summarize and discuss about cannabis in various aspects in the Nepalese context. The overarching objective is to reflect upon the ongoing debate regarding its harm and benefits, thereby upon the issue of its legalization in Nepal. </jats:p

A Late Presenting Left-Sided Congenital Diaphragmatic Hernia Repair Complicated by Postoperative Chylothorax: A Case Report

Management of chylothorax after repair of late presenting congenital diaphragmatic hernia is debatable. Conservative management in the form of close monitoring of chylous output with nutritional support appears convincing to surgery