Rationale: An objective and simple prognostic model for patients with pulmonary embolism could be helpful in guiding initial intensity of treatment. Objectives: To develop a clinical prediction rule that accurately classifies patients with pulmonary embolism into categories of increasing risk of mortality and other adverse medical outcomes. Methods: We randomly allocated 15,531 inpatient discharges with pulmonary embolism from 186 Pennsylvania hospitals to derivation (67%) and internal validation (33%) samples. We derived our prediction rule using logistic regression with 30-day mortality as the primary outcome, and patient demographic and clinical data routinely available at presentation as potential predictor variables. We externally validated the rule in 221 inpatients with pulmonary embolism from Switzerland and France. Measurements: We compared mortality and nonfatal adverse medical outcomes across the derivation and two validation samples. Main Results: The prediction rule is based on 11 simple patient characteristics that were independently associated with mortality and stratifies patients with pulmonary embolism into five severity classes, with 30-day mortality rates of 0-1.6% in class I, 1.7-3.5% in class II, 3.2-7.1% in class III, 4.0-11.4% in class IV, and 10.0-24.5% in class V across the derivation and validation samples. Inpatient death and nonfatal complications were р 1.1% among patients in class I and р 1.9% among patients in class II. Conclusions: Our rule accurately classifies patients with pulmonary embolism into classes of increasing risk of mortality and other adverse medical outcomes. Further validation of the rule is important before its implementation as a decision aid to guide the initial management of patients with pulmonary embolism.
for the Thyroid Studies Collaboration C ONTROVERSY PERSISTS ON THEindications for screening and threshold levels of thyroidstimulating hormone (TSH) for treatment of subclinical hypothyroidism, 1-3 defined as elevated serum TSH levels with normal thyroxine (T 4 ) concentrations. Because subclinical hypothyroidism has been associated with hypercholesterolemia 4 and atherosclerosis, 5 screening and treatment have been advocated to prevent cardiovascular disease. 3 However, data on the associations with coronary heart disease (CHD) events and mortality are conflicting among several large prospective cohorts. [6][7][8][9] Three recent study-level metaanalyses 10-12 found modestly increased risks for CHD and mortality, but with heterogeneity among individual studies that used different TSH cutoffs, dif-See also Patient Page. CME available online at www.jamaarchivescme.com and questions on p 1392.
Our aim was to critically evaluate the relations among smoking, body weight, body fat distribution, and insulin resistance as reported in the literature. In the short term, nicotine increases energy expenditure and could reduce appetite, which may explain why smokers tend to have lower body weight than do nonsmokers and why smoking cessation is frequently followed by weight gain. In contrast, heavy smokers tend to have greater body weight than do light smokers or nonsmokers, which likely reflects a clustering of risky behaviors (eg, low degree of physical activity, poor diet, and smoking) that is conducive to weight gain. Other factors, such as weight cycling, could also be involved. In addition, smoking increases insulin resistance and is associated with central fat accumulation. As a result, smoking increases the risk of metabolic syndrome and diabetes, and these factors increase risk of cardiovascular disease. In the context of the worldwide obesity epidemic and a high prevalence of smoking, the greater risk of (central) obesity and insulin resistance among smokers is a matter of major concern.
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