59 research outputs found

    Mortality Risk Prediction by an Insurance Company and Long-Term Follow-Up of 62,000 Men

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    Background: Insurance companies use medical information to classify the mortality risk of applicants. Adding genetic tests to this assessment is currently being debated. This debate would be more meaningful, if results of present-day risk prediction were known. Therefore, we compared the predicted with the observed mortality of men who applied for life insurance, and determined the prognostic value of the risk assessment. Methods: Long-term follow-up was available for 62,334 male applicants whose mortality risk was predicted with medical evaluation and they were assigned to five groups with increasing risk from 1 to 5. We calculated all cause standardized mortality ratios relative to the Dutch population and compared groups with Cox's regression. We compared the discriminative ability of risk assessments as indicated by a concordance index (c). Results: In 844,815 person years we observed 3,433 deaths. The standardized mortality relative to the Dutch male population was 0.76 (95 percent confidence interval, 0.73 to 0.78). The standardized mortality ratios ranged from 0.54 in risk group 1 to 2.37 in group 5. A large number of risk factors and diseases were significantly associated with increased mortality. The algorithm of prediction was significantly, but only slightly better than summation of the number of disorders and risk factors (c-index, 0.64 versus 0.60, P,0.001). Conclusions: Men applying for insurance clearly had better survival relative to the general population. Readily available medical evaluation enabled accurate prediction of the mortality risk of large groups, but the deceased men could not have been identified with the applied prediction method

    Role of ultrasound, clinical and scintigraphyc parameters to predict malignancy in thyroid nodule

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    Background: This study aimed to evaluate clinical, laboratory, ultrasound (US) and scintigraphyc parameters in thyroid nodule and to develop an auxiliary model for clinical application in the diagnosis of malignancy. Methods: We assessed 143 patients who were surgically treated at a single center, 65% (93) benign vs. 35% (50) malignant lesions at final histology (1998-2008). The clinical, laboratory, scintigraphyc and US features were compared and a prediction model was designed after the multivariate analysis. Results: There were no differences in gender, serum TSH and FT4 levels, thyroid auto-antibodies (TAb), thyroid dysfunction and scintigraphyc results (P = 0.33) between benign and malignant nodule groups. The sonographic study showed differences when the presence of suspected characteristics was found in the nodules of the malignant lesions group, such as: microcalcifications, central flow, border irregularity and hypoechogenicity. After the multivariate analysis the model obtained showed age (>39 years), border irregularity, microcalcifications and nodule size over 2 cm as predictive factors of malignancy, featuring 81.7% of accuracy. Conclusions: This study confirmed a significant increase of risk for malignancy in patients of over 39 years and with suspicious features at US

    Euglycaemic diabetic ketoacidosis

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