Identification of Low-Risk Patients with Acute Symptomatic Pulmonary Embolism for Outpatient Therapy.

RATIONALE: Patients with acute symptomatic pulmonary embolism (PE) deemed to be at low risk for early complications might be candidates for partial or complete outpatient treatment. OBJECTIVES: To develop and validate a clinical prediction rule that accurately identifies patients with PE and low risk of short-term complications and to compare its prognostic ability with two previously validated models (i.e., the Pulmonary Embolism Severity Index [PESI] and the Simplified PESI [sPESI]) METHODS: Multivariable logistic regression of a large international cohort of patients with PE prospectively enrolled in the RIETE (Registro Informatizado de la Enfermedad TromboEmbólica) registry. MEASUREMENTS AND MAIN RESULTS: All-cause mortality, recurrent PE, and major bleeding up to 10 days after PE diagnosis were determined. Of 18,707 eligible patients with acute symptomatic PE, 46 (0.25%) developed recurrent PE, 203 (1.09%) bled, and 471 (2.51%) died. Predictors included in the final model were chronic heart failure, recent immobilization, recent major bleeding, cancer, hypotension, tachycardia, hypoxemia, renal insufficiency, and abnormal platelet count. The area under receiver-operating characteristic curve was 0.77 (95% confidence interval [CI], 0.75-0.78) for the RIETE score, 0.72 (95% CI, 0.70-0.73) for PESI (P < 0.05), and 0.71 (95% CI, 0.69-0.73) for sPESI (P < 0.05). Our RIETE score outperformed the prognostic value of PESI in terms of net reclassification improvement (P < 0.001), integrated discrimination improvement (P < 0.001), and sPESI (net reclassification improvement, P < 0.001; integrated discrimination improvement, P < 0.001). CONCLUSIONS: We built a new score, based on widely available variables, that can be used to identify patients with PE at low risk of short-term complications, assisting in triage and potentially shortening duration of hospital stay.

Modelling body mass index and endometrial cancer risk in a pooled-analysis of three case-control studies.

OBJECTIVE: To quantify the relation between body mass index (BMI) and endometrial cancer risk, and to describe the shape of such a relation. DESIGN: Pooled analysis of three hospital-based case-control studies. SETTING: Italy and Switzerland. POPULATION: A total of 1449 women with endometrial cancer and 3811 controls. METHODS: Multivariate odds ratios (OR) and 95% confidence intervals (95% CI) were obtained from logistic regression models. The shape of the relation was determined using a class of flexible regression models. MAIN OUTCOME MEASURE: The relation of BMI with endometrial cancer. RESULTS: Compared with women with BMI 18.5 to <25 kg/m(2) , the odds ratio was 5.73 (95% CI 4.28-7.68) for women with a BMI ≥35 kg/m(2) . The odds ratios were 1.10 (95% CI 1.09-1.12) and 1.63 (95% CI 1.52-1.75) respectively for an increment of BMI of 1 and 5 units. The relation was stronger in never-users of oral contraceptives (OR 3.35, 95% CI 2.78-4.03, for BMI ≥30 versus <25 kg/m(2) ) than in users (OR 1.22, 95% CI 0.56-2.67), and in women with diabetes (OR 8.10, 95% CI 4.10-16.01, for BMI ≥30 versus <25 kg/m(2) ) than in those without diabetes (OR 2.95, 95% CI 2.44-3.56). The relation was best fitted by a cubic model, although after the exclusion of the 5% upper and lower tails, it was best fitted by a linear model. CONCLUSIONS: The results of this study confirm a role of elevated BMI in the aetiology of endometrial cancer and suggest that the risk in obese women increases in a cubic nonlinear fashion. The relation was stronger in never-users of oral contraceptives and in women with diabetes. TWEETABLE ABSTRACT: Risk of endometrial cancer increases with elevated body weight in a cubic nonlinear fashion.