RESUMO
Aim: Hypothermia is associated with poor prognosis in patients with sepsis. However, no studies have explored the correlation between the severity of hypothermia and prognosis. Methods: Using data from the Japanese accidental hypothermia network registry (J-Point registry), we examined adult patients aged ≥18 years with infectious diseases whose initial body temperature was ≤35°C from April 1, 2011 to March 31, 2016, in 12 centers. Patients were divided into three groups according to their body temperature: Tertile 1 (T1) (32.0-35.0°C), Tertile 2 (T2) (28.0-31.9°C), and Tertile 3 (T3) (<28.0°C). In-hospital mortality was employed as a metric to assess outcomes. We conducted a multivariate logistic regression analysis to investigate the relationship between the three categories and the occurrence of in-hospital mortality. Results: A total of 572 patients were registered, and 170 eligible patients were identified. Of these patients, 55 were in T1 (32.0-35.0°C), 76 in T2 (28.0-31.9°C), and 39 in T3 (<28.0°C) groups. The overall in-hospital mortality rate in accidental hypothermia (AH) patients with infectious diseases was 34.1%. The in-hospital mortality rates in the T1, T2, and T3 groups were 34.5%, 36.8%, and 28.2%, respectively. The multivariable analysis demonstrated no significant differences regarding in-hospital mortality among the three groups (T2 vs. T1, adjusted odds ratio [OR]: 1.29; 95% confidence interval [CI]: 0.58-2.89 and T3 vs. T1, adjusted OR: 0.83; 95% CI: 0.30-2.31). Conclusion: In this multicenter retrospective observational study, hypothermia severity was not associated with in-hospital mortality in AH patients with infectious diseases.
RESUMO
Objective: This study aimed to identify the amount of weight loss needed in patients with obesity to improve metabolic syndrome (MetS), a risk factor for cardiovascular disease (CVD), over a long period of time. Methods: A total of 576 patients with obesity were enrolled in this study. Effects of continuous physician-supervised weight loss on the cumulative MetS components excluding abdominal circumference (defined as obesity-related CVD risk score) were investigated during a 5-year follow-up period. The extent of weight loss required to reduce the obesity-related CVD risk components was assessed using receiver operating characteristic (ROC) curve analyses. Results: Of the 576 participants, 266 completed 5-year follow-up, with 39.1% and 24.1% of them achieving ≥5.0% and ≥7.5% weight loss at the 5-year follow-up, respectively. The area under the ROC curve for reducing the obesity-related CVD risk components was 0.719 [0.662-0.777] at 1 year and 0.694 [0.613-0.775] at 5 years. The optimal cut-off value for weight loss was 5.0% (0.66 sensitivity and 0.69 specificity) and the value with 0.80 specificity was 7.5% (0.45 sensitivity) at 5 years. Greater reductions in weight were associated with greater improvements in the obesity-related CVD risk score at all follow-up periods (P-trend <0.001). Obesity-related CVD risk score was significantly improved by 5.0-7.5% and ≥7.5% weight loss at 1 year (P = 0.029 and P < 0.001, respectively) and ≥7.5% weight loss at 5 years (P = 0.034). Conclusions: A weight loss of ≥5.0% at 1 year and ≥7.5% at 5 years could reduce the number of obesity-related CVD risk components in patients with obesity.