A predictive model of computed tomography and clinical features of EGFR gene mutation in lung adenocarcinoma.

This study aims to develop a predictive model for epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma by integrating computed tomography (CT) imaging features with clinical characteristics. A retrospective analysis was conducted using electronic medical records from 194 patients diagnosed with lung adenocarcinoma between January 2016 and December 2020, with approval from the institutional review board. Features were selected using LASSO regression, and predictive models were built using logistic regression, support vector machine, and random forest methods.

A network meta-analysis comparative the efficacy of angiotensin-converting enzyme inhibitors and calcium channel blockers in hypertension.

Background: Currently, most studies primarily focus on directly comparing the efficacy and safety of angiotensin-converting enzyme inhibitors (ACEIs) and calcium channel blockers (CCBs), the two major classes of antihypertensive drugs. Moreover, the majority of studies are based on randomized controlled trials and traditional meta-analyses, with few exploring the efficacy and safety comparisons among various members of ACEIs and CCBs.

Methods: ACEIs and CCB were searched for in randomized controlled trials in CNKI, Wanfang, VIP, China Biology Medicine Disc (Si-noMed), PubMed, EMbase, and Cochrane Library databases.