Development and internal validation of an artificial intelligence-assisted bowel sounds auscultation system to predict early enteral nutrition-associated diarrhoea in acute pancreatitis: a prospective observational study.

Aims/Background An artificial intelligence-assisted prediction model for enteral nutrition-associated diarrhoea (ENAD) in acute pancreatitis (AP) was developed utilising data obtained from bowel sounds auscultation. This model underwent validation through a single-centre, prospective observational study. The primary objective of the model was to enhance clinical decision-making by providing a more precise assessment of ENAD risk. Methods The study enrolled patients with AP who underwent early enteral nutrition (EN). Real-time collection and analysis of bowel sounds were conducted using an artificial intelligence bowel sounds auscultation system. Univariate analysis, multicollinearity analysis, and logistic regression analysis were employed to identify risk factors associated with ENAD. The random forest algorithm was utilised to establish the prediction model, and partial dependence plots were generated to analyse the impact of risk factors on ENAD risk. Validation of the model was performed using the optimal model Bootstrap resampling method. Predictive performance was assessed using accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and an area under the receiver operating characteristic (ROC) curve. Results Among the 133 patients included in the study, the incidence of ENAD was 44.4%. Six risk factors were identified, and the model's accuracy was validated through Bootstrap iterations. The prediction accuracy of the model was 81.10%, with a sensitivity of 84.30% and a specificity of 77.80%. The positive predictive value was 82.60%, and the negative predictive value was 80.10%. The area under the ROC curve was 0.904 (95% confidence interval: 0.817-0.997). Conclusion The artificial intelligence bowel sounds auscultation system enhances the assessment of gastrointestinal function in AP patients undergoing EN and facilitates the construction of an ENAD predictive model. The model demonstrates good predictive efficacy, offering an objective basis for precise intervention timing in ENAD management.

Clinical and Animal Studies of Waist and Knee Scraping Therapy for Knee Osteoarthritis.

BACKGROUND: Knee osteoarthritis (KOA) is a degenerative condition with knee pain as the main clinical manifestation. Scraping is one of the commonly used traditional Chinese medicine treatment methods, which activates blood circulation, removes blood stasis, reduces inflammation, and so on. Although scholars have proposed that the synergistic treatment of the waist and knee for KOA is superior to simple knee treatment, there is no relevant reference literature on the application of scraping therapy. Therefore, this study aims to explore the effectiveness and potential mechanisms of waist and knee scraping therapy for treating KOA through clinical and animal studies in order to promote its clinical application. OBJECTIVE: To explore the clinical efficacy of waist and knee scraping therapy in the treatment of KOA from clinical study and increase animal study on this basis to preliminarily explore its mechanism, providing an objective basis for better treatment of KOA. METHODS: The clinical study recruited 90 KOA patients and divided them into a control group, a knee scraping group, and a waist and knee scraping group using a random number table method. All patients were evaluated for clinical efficacy, the Western Ontario McMaster Universities Osteoarthritis Index (WOMAC), and Traditional Chinese Medicine Syndrome Score. The KOA rat model was established using the Hulth method. The rats were randomly divided into a control group, KOA group, waist scraping group, knee scraping group, and waist and knee scraping group. During the intervention process of rats, the pain sensitivity threshold was measured, and HE staining was performed on the synovium and cartilage. The protein and mRNA expression levels of TNF-α, IL- 1ß, IL-6, PGP9.5, SP and TRPA1, TRPV4, SP, and NGF were measured by Western blot and real-time PCR. RESULTS: In the clinical study, the clinical efficacy of the 2 scraping groups was significantly higher than that of the control group. The clinical efficacy of the waist and knee scraping group on the 60th day of treatment was significantly higher than that of the knee scraping group. In terms of improving WOMAC scores, all 3 groups had significance; The function and total score of the waist and knee scraping group on the 28th day of treatment, as well as the pain, function, and total score on the 60th day, were lower than those of the knee scraping group. In terms of improving pain while standing, pain when walking on flat ground, and total score, the scraping group had significant differences. The score of heavy limbs in the waist and knee scraping group was lower than that in the knee scraping group. In an animal study, during the 4th week after modeling, there were differences in the pain sensitivity threshold between the KOA group and the waist scraping group compared to the control group, while there were differences in the pain sensitivity threshold between the knee scraping group and the waist and knee scraping group compared to the KOA group. The expression levels of various proteins and genes in the KOA group and waist scraping group increased compared to the control group; The knee scraping group and the waist and knee scraping group were lower than those in the KOA group. CONCLUSION: Scraping therapy can significantly alleviate knee joint pain and stiffness, improve joint function, and improve clinical efficacy, and the short-term and long-term effects of waist and knee scraping therapy are more significant. The scraping therapy has a definite therapeutic effect on KOA rats, which can improve the threshold of cold hyperalgesia and mechanical hyperalgesia, and the waist and knee scraping therapy is more obvious. This may be related to reducing inflammatory reactions in synovial and ganglion tissues.