ABSTRACT
PURPOSE: To investigate the effectiveness of problem-based learning (PBL) and case-based learning (CBL) teaching methods in clinical practical teaching in transarterial chemoembolization (TACE) treatment in China. MATERIALS AND METHODS: A comprehensive search of PubMed, the Chinese National Knowledge Infrastructure (CNKI) database, the Weipu database and the Wanfang database up to June 2023 was performed to collect studies that evaluate the effectiveness of problem-based learning and case-based learning teaching methods in clinical practical teaching in TACE treatment in China. Statistical analysis was performed by R software (4.2.1) calling JAGS software (4.3.1) in a Bayesian framework using the Markov chain-Monte Carlo method for direct and indirect comparisons. The R packages "gemtc", "rjags", "openxlsx", and "ggplot2" were used for statistical analysis and data output. RESULTS: Finally, 7 studies (five RCTs and two observational studies) were included in the meta-analysis. The combination of PBL and CBL showed more effectiveness in clinical thinking capacity, clinical practice capacity, knowledge understanding degree, literature reading ability, method satisfaction degree, learning efficiency, learning interest, practical skills examination scores and theoretical knowledge examination scores. CONCLUSIONS: Network meta-analysis revealed that the application of PBL combined with the CBL teaching mode in the teaching of liver cancer intervention therapy significantly improves the teaching effect and significantly improves the theoretical and surgical operations, meeting the requirements of clinical education.
Subject(s)
Bayes Theorem , Carcinoma, Hepatocellular , Chemoembolization, Therapeutic , Liver Neoplasms , Problem-Based Learning , Humans , Carcinoma, Hepatocellular/therapy , Liver Neoplasms/therapy , China , Network Meta-Analysis , Teaching , Clinical CompetenceABSTRACT
OBJECTIVE: To evaluate the short-term clinical outcomes of radiofrequency ablation (RFA) using a radiofrequency (RF) needle device for varicose ulcers. METHODS: From September 2020 to September 2021, a total of 80 patients with varicose ulcers were included in this study. Based on the different surgical methods, the patients were divided into RF group and control groups, with 40 cases in each group. In the RF group, RFA was performed using an RF needle device and foam sclerotherapy was used for superficial veins. The control group was treated with conventional high-ligation stripping. The surgical data, hospitalization data, clinical efficacy, and postoperative complications of two groups were compared. Meanwhile, the correlation between RBC, HB, HCT, and ulcer healing time was analyzed. RESULTS: Compared to the control group, RF group had shorter surgery time, duration in the hospital, and less intraoperative bleeding (p < .05). The VCSS and CIVIQ scores in RF group were significantly higher than that in control group (p < .05). The healing time of ulcers was shorter in the RF group (x2 = 19.766, p = .000). The RF group had fewer postoperative complications. There was a positive correlation between RBC, HB, and HCT, and ulcer healing time (p < .05). CONCLUSION: The use of the RF needle device for RFA to treat patients with varicose ulcers showed acceptable short-term clinical outcomes with less incidence of trauma, faster recovery, and fewer complications.
ABSTRACT
BACKGROUND: Human cystic echinococcosis (CE) is a life-threatening zoonosis caused by the Echinococcus granulosus (sensu lato). Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality in the world. The coexistence of CE and HCC is exceedingly rare, and only several well-documented cases have been reported. In addition to this coexistence, there is no report of the coexistence of CE, HCC, and liver abscess to date. Herein, we aimed to report a case of coexistence of liver abscess, hepatic CE, and HCC. CASE SUMMARY: A 65-year-old herdsman presented to the department of interventional therapy with jaundice, right upper abdominal distension and pain for 10 d. Laboratory test showed that he had positive results for HBsAg, HBeAb, HBcAb, and echinococcosis IgG antibody. The test also showed an increased level of alpha fetoprotein of 3400 ng/mL. An abdominal computed tomography (CT) scan revealed an uneven enhanced lesion of the liver at the arterial phase with enhancement and was located S4/8 segment of the liver. In addition, CT scan also revealed a mass in the S6 segment of the liver with a thick calcified wall and according to current guideline and medical images, the diagnoses of hepatic CE (CE4 subtype) and HCC were established. Initially, transarterial chemoembolization was performed for HCC. In the follow-up, liver abscess occurred in addition to CE and HCC; thus, percutaneous liver puncture drainage was performed. In the next follow-up, CE and HCC were stable. The liver abscess was completely resolved, and the patient was discharged with no evidence of recurrence. CONCLUSION: This is the first reported case on the coexistence of liver abscess, hepatic CE, and HCC. Individualized treatment and multidisciplinary discussions should be performed in this setting. Therefore, treatment and diagnosis should be based on the characteristics of liver abscess, hepatic CE, and HCC, and in future clinical work, it is necessary to be aware of the possibility of this complex composition of liver diseases.
ABSTRACT
In unsupervised learning, clustering is a common starting point for data processing. The convex or concave fusion clustering method is a novel approach that is more stable and accurate than traditional methods such as k-means and hierarchical clustering. However, the optimization algorithm used with this method can be slowed down significantly by the complexity of the fusion penalty, which increases the computational burden. This paper introduces a random projection ADMM algorithm based on the Bernoulli distribution and develops a double random projection ADMM method for high-dimensional fusion clustering. These new approaches significantly outperform the classical ADMM algorithm due to their ability to significantly increase computational speed by reducing complexity and improving clustering accuracy by using multiple random projections under a new evaluation criterion. We also demonstrate the convergence of our new algorithm and test its performance on both simulated and real data examples.