METHODS: 99 adult patients at four training and research hospitals who had undergone an abdominal contrast computed tomography scan in the ED with the final diagnosis of splenic abscess from January 2004 to November 2017 were recruited. Evaluation for sarcopenia was performed via calculating the psoas cross-sectional area at the level of the third lumbar vertebra and normalising for height, before checking it against pre-defined values. Univariate analyses were used to evaluate the differences between survivors and non-survivors. Sensitivity, specificity, and predictive values of the presence of sarcopenia in predicting in-hospital mortality were calculated. Kaplan-Meier methods, log-rank test, and Cox proportional hazards model were also performed to examine survival between groups with sarcopenia versus non-sarcopenia.
RESULTS: Splenic abscess patients with sarcopenia were 7.56 times more at risk of in-hospital mortality than those without sarcopenia (multivariate-adjusted HR: 7.56; 95% CI: 1.55-36.93). Presence of sarcopenia was found to have 84.62% sensitivity and 96.49% negative predictive value in predicting mortality.
CONCLUSION: Sarcopenia is associated with poor prognoses of in-hospital mortality in patients with splenic abscess presenting to the ED. We recommend its use in the ED to rapidly risk stratify and predict outcome to guide treatment strategies.
Purpose: To analyze the injury rates, patterns, and risk factors of functional training/CrossFit.
Study Design: Descriptive epidemiology study.
Methods: Electronic questionnaires were distributed to 244 participants from 15 centers in the country. Descriptive data regarding the athletes, injury occurrence within the past 6 months, injury details, and risk factors were collected.
Results: Of the 244 athletes, 112 (46%) developed at least 1 new injury over the previous 6 months. Injury rates were significantly higher in athletes from nonaffiliate training gyms compared with CrossFit-affiliated gyms, in athletes with previous injuries, and in those who perceived themselves as having more than average fitness.
Conclusion: Coaches and athletes need to be more aware of risk factors for injury to enable safer and better training strategies.
AIM: The aim of the study was to determine the influence of various risk factors on ST2 levels in patients with HFpEF and diabetes mellitus type 2 (T2DM).
MATERIALS AND METHODS: A total of one hundred and thirty-four patients (74 females and 60 males, 51 diabetic patients and 83 patients without T2DM with HFpEF were examined. Duration of HF and T2DM, common risk factors, such as smoking, overweight, clinical examination, parameters of carbohydrate and lipid metabolism, glomerular filtration rate (GFR) and M235T polymorphism of ATG have been used. Multivariate backward stepwise cox regression analysis was performed in Statistica 10,0. p<0,05 was considered statistically significant.
RESULTS: ST2 level in patients with HFpEF associated with T2DM exceeded this value in patients with HFpEF without T2DM and was 23.26 ng/ml (18.5: 29.3) vs. 20.39 ng/ml (18.3: 24.6), respectively (p<0,05). To assess the cumulative effect of the studied factors on the ST2 level, we performed the Cox's stepwise multivariate regression analysis. Smoking, HOMA-IR (Homeostatic Model Assessment for Insulin Resistance), glucose, HbA1 and insulin levels were found to be the most significant factors influencing ST2 levels in patients with HF and T2DM, indicating a significant effect of DM type 2 on ST2 concentration.
CONCLUSIONS: Smoking, HOMA-IR, glucose, HbA1, and insulin levels can significantly affect ST2 levels in patients with T2DM and HFpEF.
METHOD: Participants (N = 75) completed a clinical interview, cognitive control tasks, and the Cognitive Emotion Regulation Questionnaire.
RESULTS: Those with suicidal ideation or previous attempts had poorer cognitive control and cognitive emotion regulation than controls. Furthermore, those who had attempted suicide had poorer cognitive control and reported greater use of self-blame, rumination, and catastrophizing, and less use of acceptance, than those with suicidal ideation only. There was an indirect effect of cognitive control deficits on suicidality through cognitive emotion regulation (self-blame, acceptance, rumination, catastrophizing).
CONCLUSIONS: Exploring these cognitive deficits and difficulties can assist in further understanding the risk factors for suicidality and improve targeted interventions. This is of particular relevance in Iran where the need for policies and interventions targeting the prevention of suicide has been identified.
METHODS AND RESULTS: The PeriOperative ISchemic Evaluation (POISE)-1 trial evaluated the effects of metoprolol vs. placebo in 8351 patients, and POISE-2 compared the effect of aspirin vs. placebo, and clonidine vs. placebo in 10 010 patients. These trials included patients with, or at risk of, cardiovascular disease who were undergoing non-cardiac surgery. For the purpose of this study, we combined the POISE datasets, excluding 244 patients who were in atrial fibrillation (AF) at the time of randomization. Perioperative atrial fibrillation was defined as new AF that occurred within 30 days after surgery. Our primary outcome was the incidence of stroke at 1 year of follow-up; secondary outcomes were mortality and myocardial infarction (MI). We compared outcomes among patients with and without POAF using multivariable adjusted Cox proportional hazards models. Among 18 117 patients (mean age 69 years, 57.4% male), 404 had POAF (2.2%). The stroke incidence 1 year after surgery was 5.58 vs. 1.54 per 100 patient-years in patients with and without POAF, adjusted hazard ratio (aHR) 3.43, 95% confidence interval (CI) 2.00-5.90; P risk of death (incidence 31.37 vs. 9.34; aHR 2.51, 95% CI 2.01-3.14; P risk of stroke, MI, and death at 1 year. Intervention studies are needed to evaluate risk reduction strategies in this high-risk population.
METHODS AND RESULTS: After the randomized treatment period (5.6 years), participants were invited to participate in 3.1 further years of observation (total 8.7 years). The first co-primary outcome for the entire length of follow-up was the composite of myocardial infarction, stroke, or CV death [major adverse cardiovascular event (MACE)-1], and the second was MACE-1 plus resuscitated cardiac arrest, heart failure, or coronary revascularization (MACE-2). In total, 9326 (78%) of 11 994 surviving Heart Outcomes Prevention Evaluation (HOPE)-3 subjects consented to participate in extended follow-up. During 3.1 years of post-trial observation (total follow-up of 8.7 years), participants originally randomized to rosuvastatin compared with placebo had a 20% additional reduction in MACE-1 [95% confidence interval (CI), 0.64-0.99] and a 17% additional reduction in MACE-2 (95% CI 0.68-1.01). Therefore, over the 8.7 years of follow-up, there was a 21% reduction in MACE-1 (95% CI 0.69-0.90, P = 0.005) and 21% reduction in MACE-2 (95% CI 0.69-0.89, P = 0.002). There was no benefit of BP lowering in the overall study either during the active or post-trial observation period, however, a 24% reduction in MACE-1 was observed over 8.7 years.
CONCLUSION: The CV benefits of rosuvastatin, and BP lowering in those with elevated systolic BP, compared with placebo continue to accrue for at least 3 years after cessation of randomized treatment in individuals without cardiovascular disease indicating a legacy effect.
TRIAL REGISTRATION NUMBER: NCT00468923.
STUDY DESIGN: A systematic search was performed using the MEDLINE, EMBASE, PsycINFO, CINAHL, and Web of Science databases to identify English-language articles published through June 2018. Articles were included if they were longitudinal studies in community-based populations, the primary exposure occurred during childhood, and the primary outcome was either a measure of subclinical CVD or a clinical CVD event occurring in adulthood. Two independent reviewers screened determined whether eligibility criteria were met.
RESULTS: There were 210 articles that met the predefined criteria. The greatest number of publications examined associations of clinical risk factors, including childhood adiposity, blood pressure, and cholesterol, with the development of adult CVD. Few studies examined childhood lifestyle factors including diet quality, physical activity, and tobacco exposure. Domains of risk beyond "traditional" cardiovascular risk factors, such as childhood psychosocial adversity, seemed to have strong published associations with the development of CVD.
CONCLUSIONS: Although the evidence was fairly consistent in direction and magnitude for exposures such as childhood adiposity, hypertension, and hyperlipidemia, significant gaps remain in the understanding of how childhood health and behaviors translate to the risk of adulthood CVD, particularly in lesser studied exposures like glycemic indicators, physical activity, diet quality, very early life course exposure, and population subgroups.