BACKGROUND: Older patients often suffer from multiple comorbid conditions. Few comorbidity indices are valid and reliable in the elderly and were rarely compared. OBJECTIVE: To compare the performance, relevance, and ability of 6 widely used and validated comorbidity indices--Charlson Comorbidity Index, Cumulative Illness Rating Scale-Geriatrics, Index of Coexistent Diseases, Kaplan, Geriatric Index of Comorbidity (GIC), and Chronic Disease Score--to predict adverse outcomes after discharge (1-year risk of rehospitalization, institutionalization, and death). DESIGN, SETTING, AND PARTICIPANTS: Prospective study with 1-year follow-up, between January 2004 and December 2005 in 444 elderly patients (mean age, 85; 74% female) discharged from acute geriatric hospital, Geneva University Hospitals. RESULTS: In univariate analyses, Cumulative Illness Rating Scale?Geriatrics and GIC were the predictors with the largest coefficient of determination for mortality with (R(2) of 9.3%, respectively 8.8%). GIC was also the only significant predictor of institutionalization (R(2) = 6.0%). Higher risk of readmission was significantly associated with GIC (R(2) = 14.0%), Cumulative Illness Rating Scale-Geriatrics (R(2) = 5.6%), Charlson Comorbidity Index (R(2) = 3.1%), and Chronic Disease Score (R(2) = 1.7). CONCLUSIONS: Understanding how to efficiently predict these adverse outcomes in hospitalized elders is important for a variety of clinical and policy reasons. GIC and Cumulative Illness Rating Scale-Geriatrics may improve hospital discharge planning in a geriatric hospital treating very old patients with acute disease. Copyright Â
BACKGROUND: Older patients often suffer from multiple comorbid conditions. Few comorbidity indices are valid and reliable in the elderly and were rarely compared. OBJECTIVE: To compare the performance, relevance, and ability of 6 widely used and validated comorbidity indices--Charlson Comorbidity Index, Cumulative Illness Rating Scale-Geriatrics, Index of Coexistent Diseases, Kaplan, Geriatric Index of Comorbidity (GIC), and Chronic Disease Score--to predict adverse outcomes after discharge (1-year risk of rehospitalization, institutionalization, and death). DESIGN, SETTING, AND PARTICIPANTS: Prospective study with 1-year follow-up, between January 2004 and December 2005 in 444 elderly patients (mean age, 85; 74% female) discharged from acute geriatric hospital, Geneva University Hospitals. RESULTS: In univariate analyses, Cumulative Illness Rating Scale?Geriatrics and GIC were the predictors with the largest coefficient of determination for mortality with (R(2) of 9.3%, respectively 8.8%). GIC was also the only significant predictor of institutionalization (R(2) = 6.0%). Higher risk of readmission was significantly associated with GIC (R(2) = 14.0%), Cumulative Illness Rating Scale-Geriatrics (R(2) = 5.6%), Charlson Comorbidity Index (R(2) = 3.1%), and Chronic Disease Score (R(2) = 1.7). CONCLUSIONS: Understanding how to efficiently predict these adverse outcomes in hospitalized elders is important for a variety of clinical and policy reasons. GIC and Cumulative Illness Rating Scale-Geriatrics may improve hospital discharge planning in a geriatric hospital treating very old patients with acute disease. Copyright Â
Authors: Joseph T Hanlon; Xinhua Zhao; Jennifer G Naples; Sherrie L Aspinall; Subashan Perera; David A Nace; Nicholas G Castle; Susan L Greenspan; Carolyn T Thorpe Journal: J Am Geriatr Soc Date: 2017-02-02 Impact factor: 5.562
Authors: Andrew R Post; Tahsin Kurc; Sharath Cholleti; Jingjing Gao; Xia Lin; William Bornstein; Dedra Cantrell; David Levine; Sam Hohmann; Joel H Saltz Journal: J Biomed Inform Date: 2013-02-09 Impact factor: 6.317
Authors: Amit Kumar; James E Graham; Linda Resnik; Amol M Karmarkar; Alai Tan; Anne Deutsch; Kenneth J Ottenbacher Journal: Am J Phys Med Rehabil Date: 2016-12 Impact factor: 2.159
Authors: Mary Jo V Pugh; Zachary A Marcum; Laurel A Copeland; Eric M Mortensen; John E Zeber; Polly H Noël; Dan R Berlowitz; John R Downs; Chester B Good; Carlos Alvarez; Megan E Amuan; Joseph T Hanlon Journal: Drugs Aging Date: 2013-08 Impact factor: 3.923
Authors: Jeffrey H Silber; Joseph G Reiter; Paul R Rosenbaum; Qingyuan Zhao; Dylan S Small; Bijan A Niknam; Alexander S Hill; Lauren L Hochman; Rachel R Kelz; Lee A Fleisher Journal: Med Care Date: 2018-08 Impact factor: 2.983