Background: and Purpose The optimal blood pressure (BP) control after successful endovascular thrombectomy (EVT) in acute ischemic stroke (AIS) with large vessel occlusion (LVO) remains debatable. We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) that evaluate the efficacy and safety of standard BP control (with systolic BP ≤180 mm Hg) versus intensive BP control (systolic BP <140 mm Hg) during the 24 hours after successful EVT in AIS with LVO. Methods: PubMed, Scopus, the Cochrane Central Register of Controlled Trials, and Embase were searched to identify relevant trials. The crude odds ratio (OR) and 95% confidence interval (CI) were calculated and estimates using random-effects models were pooled. This meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (PROSPERO ID: CRD42023450673). Results: Four RCTs involving 1,559 participants were included. Regarding efficacy outcomes, intensive BP control was associated with a lower likelihood of functional independence (OR: 0.68; 95% CI: 0.51–0.91 for modified Rankin Scale [mRS] ≤2) and walking without assistance (OR: 0.65; 95% CI: 0.53–0.81 for mRS ≤3). For safety outcomes, consistent with the efficacy findings, intensive BP control was significantly associated with severe disability or death (mRS 5 or 6) (OR: 1.34; 95% CI: 1.07–1.69). However, there were no significant differences including all-cause mortality, any intracerebral hemorrhage (ICH), symptomatic ICH, parenchymal hematoma type 2, and stroke recurrence. Conclusion While all four RCTs were conducted to demonstrate the superiority of intensive BP control over standard BP control, standard BP control may be beneficial for the outcome after EVT for AIS with LVO without increasing adverse safety outcomes. Caution should be needed with the application of intensive BP control during the 24 hours following successful recanalization after EVT.

Background: We investigated the association between body composition changes and new-onset diabetes mellitus (DM) development according to the body mass index (BMI) in a longitudinal setting in the general Korean population. Methods: From 2010 to 2011 (1st) and 2012 to 2013 (2nd), we included 1,607,508 stratified random sample participants without DM from the National Health Insurance Service-Health Screening dataset of Korean. The predicted appendicular skeletal muscle mass index (pASMMI), body fat mass index (pBFMI), and lean body mass index (pLBMI) were calculated using pre-validated anthropometric prediction equations. A prediction equation was constructed by combining age, weight, height, waist circumference, serum creatinine levels, alcohol consumption status, physical activity, and smoking history as variables affecting body composition. Results: Decreased pASMMI (men: hazard ratio [HR], 0.866; 95% confidence interval [CI], 0.830 to 0.903; P<0.001; women: HR, 0.748; 95% CI, 0.635 to 0.881; P<0.001), decreased pLBMI (men: HR, 0.931; 95% CI, 0.912 to 0.952; P<0.001; women: HR, 0.906; 95% CI, 0.856 to 0.959; P=0.007), and increased pBFMI (men: HR, 1.073; 95% CI, 1.050 to 1.096; P<0.001; women: HR, 1.114; 95% CI, 1.047 to 1.186; P=0.007) correlated with the development of new-onset DM. Notably, only in the overweight and obese BMI categories, decreases in pASMMI and pLBMI and increases in pBFMI associated with new-onset DM, regardless of gender. Conclusion Decreased pASMMI and pLBMI, and increased pBFMI with excess fat accumulation may enhance the risk of newonset DM. Therefore, appropriate changes in body composition can help prevent new-onset DM.

Background: We investigated the association between body composition changes and new-onset diabetes mellitus (DM) development according to the body mass index (BMI) in a longitudinal setting in the general Korean population. Methods: From 2010 to 2011 (1st) and 2012 to 2013 (2nd), we included 1,607,508 stratified random sample participants without DM from the National Health Insurance Service-Health Screening dataset of Korean. The predicted appendicular skeletal muscle mass index (pASMMI), body fat mass index (pBFMI), and lean body mass index (pLBMI) were calculated using pre-validated anthropometric prediction equations. A prediction equation was constructed by combining age, weight, height, waist circumference, serum creatinine levels, alcohol consumption status, physical activity, and smoking history as variables affecting body composition. Results: Decreased pASMMI (men: hazard ratio [HR], 0.866; 95% confidence interval [CI], 0.830 to 0.903; P<0.001; women: HR, 0.748; 95% CI, 0.635 to 0.881; P<0.001), decreased pLBMI (men: HR, 0.931; 95% CI, 0.912 to 0.952; P<0.001; women: HR, 0.906; 95% CI, 0.856 to 0.959; P=0.007), and increased pBFMI (men: HR, 1.073; 95% CI, 1.050 to 1.096; P<0.001; women: HR, 1.114; 95% CI, 1.047 to 1.186; P=0.007) correlated with the development of new-onset DM. Notably, only in the overweight and obese BMI categories, decreases in pASMMI and pLBMI and increases in pBFMI associated with new-onset DM, regardless of gender. Conclusion Decreased pASMMI and pLBMI, and increased pBFMI with excess fat accumulation may enhance the risk of newonset DM. Therefore, appropriate changes in body composition can help prevent new-onset DM.

Background: We investigated the association between body composition changes and new-onset diabetes mellitus (DM) development according to the body mass index (BMI) in a longitudinal setting in the general Korean population. Methods: From 2010 to 2011 (1st) and 2012 to 2013 (2nd), we included 1,607,508 stratified random sample participants without DM from the National Health Insurance Service-Health Screening dataset of Korean. The predicted appendicular skeletal muscle mass index (pASMMI), body fat mass index (pBFMI), and lean body mass index (pLBMI) were calculated using pre-validated anthropometric prediction equations. A prediction equation was constructed by combining age, weight, height, waist circumference, serum creatinine levels, alcohol consumption status, physical activity, and smoking history as variables affecting body composition. Results: Decreased pASMMI (men: hazard ratio [HR], 0.866; 95% confidence interval [CI], 0.830 to 0.903; P<0.001; women: HR, 0.748; 95% CI, 0.635 to 0.881; P<0.001), decreased pLBMI (men: HR, 0.931; 95% CI, 0.912 to 0.952; P<0.001; women: HR, 0.906; 95% CI, 0.856 to 0.959; P=0.007), and increased pBFMI (men: HR, 1.073; 95% CI, 1.050 to 1.096; P<0.001; women: HR, 1.114; 95% CI, 1.047 to 1.186; P=0.007) correlated with the development of new-onset DM. Notably, only in the overweight and obese BMI categories, decreases in pASMMI and pLBMI and increases in pBFMI associated with new-onset DM, regardless of gender. Conclusion Decreased pASMMI and pLBMI, and increased pBFMI with excess fat accumulation may enhance the risk of newonset DM. Therefore, appropriate changes in body composition can help prevent new-onset DM.

Background: We investigated the association between body composition changes and new-onset diabetes mellitus (DM) development according to the body mass index (BMI) in a longitudinal setting in the general Korean population. Methods: From 2010 to 2011 (1st) and 2012 to 2013 (2nd), we included 1,607,508 stratified random sample participants without DM from the National Health Insurance Service-Health Screening dataset of Korean. The predicted appendicular skeletal muscle mass index (pASMMI), body fat mass index (pBFMI), and lean body mass index (pLBMI) were calculated using pre-validated anthropometric prediction equations. A prediction equation was constructed by combining age, weight, height, waist circumference, serum creatinine levels, alcohol consumption status, physical activity, and smoking history as variables affecting body composition. Results: Decreased pASMMI (men: hazard ratio [HR], 0.866; 95% confidence interval [CI], 0.830 to 0.903; P<0.001; women: HR, 0.748; 95% CI, 0.635 to 0.881; P<0.001), decreased pLBMI (men: HR, 0.931; 95% CI, 0.912 to 0.952; P<0.001; women: HR, 0.906; 95% CI, 0.856 to 0.959; P=0.007), and increased pBFMI (men: HR, 1.073; 95% CI, 1.050 to 1.096; P<0.001; women: HR, 1.114; 95% CI, 1.047 to 1.186; P=0.007) correlated with the development of new-onset DM. Notably, only in the overweight and obese BMI categories, decreases in pASMMI and pLBMI and increases in pBFMI associated with new-onset DM, regardless of gender. Conclusion Decreased pASMMI and pLBMI, and increased pBFMI with excess fat accumulation may enhance the risk of newonset DM. Therefore, appropriate changes in body composition can help prevent new-onset DM.