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      A prognostic model predicted deterioration in health-related quality of life in older patients with multimorbidity and polypharmacy

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          A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation

          The objective of this study was to develop a prospectively applicable method for classifying comorbid conditions which might alter the risk of mortality for use in longitudinal studies. A weighted index that takes into account the number and the seriousness of comorbid disease was developed in a cohort of 559 medical patients. The 1-yr mortality rates for the different scores were: "0", 12% (181); "1-2", 26% (225); "3-4", 52% (71); and "greater than or equal to 5", 85% (82). The index was tested for its ability to predict risk of death from comorbid disease in the second cohort of 685 patients during a 10-yr follow-up. The percent of patients who died of comorbid disease for the different scores were: "0", 8% (588); "1", 25% (54); "2", 48% (25); "greater than or equal to 3", 59% (18). With each increased level of the comorbidity index, there were stepwise increases in the cumulative mortality attributable to comorbid disease (log rank chi 2 = 165; p less than 0.0001). In this longer follow-up, age was also a predictor of mortality (p less than 0.001). The new index performed similarly to a previous system devised by Kaplan and Feinstein. The method of classifying comorbidity provides a simple, readily applicable and valid method of estimating risk of death from comorbid disease for use in longitudinal studies. Further work in larger populations is still required to refine the approach because the number of patients with any given condition in this study was relatively small.
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            Regularization Paths for Generalized Linear Models via Coordinate Descent

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              Conducting Meta-Analyses inRwith themetaforPackage

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                Journal
                Journal of Clinical Epidemiology
                Journal of Clinical Epidemiology
                Elsevier BV
                08954356
                February 2021
                February 2021
                : 130
                : 1-12
                Article
                10.1016/j.jclinepi.2020.10.006
                98b2474c-ac7f-47a1-bf2c-07266d8ea6df
                © 2021

                https://www.elsevier.com/tdm/userlicense/1.0/

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