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ObjectivesTo determine whether glycosylated hemoglobin (HbA1c) levels predict functional decline in older adults.DesignLongitudinal cohort study.ParticipantsCommunity-dwelling, nursing home (NH)-eligible individuals with diabetes mellitus enrolled at On Lok between October 2002 and December 2008 (367 participants, 1,579 HbA1c measurements).SettingOn Lok Lifeways, the original model for Programs of All-Inclusive Care for the Elderly.MeasurementsThe outcomes were functional decline or death at 2 years. The primary predictor was HbA1c. Age, sex, race and ethnicity, baseline function, comorbid conditions, length of time enrolled at On Lok, insulin use, and clustering of HbA1c within participants were adjusted for with mixed-effects Poisson regression.ResultsMean age was 80, and 185 participants (50%) were taking insulin. Sixty-three percent of participants experienced functional decline, and 75% experienced death or functional decline during the study period. At 2 years, higher HbA1c was associated with less functional decline or death (P for trend = .006). Accounting for clustering and confounding factors, HbA1c of 8.0% to 8.9% was associated with a lower likelihood (relative risk = 0.88, 95% confidence interval = 0.79-0.99) of functional decline or death than HbA1c of 7.0% to 7.9%.ConclusionIn community-dwelling, NH-eligible individuals with diabetes mellitus, HbA1c of 8.0% to 8.9% is associated with better functional outcomes at 2 years than HbA1c of 7.0% to 7.9%, suggesting that the current American Geriatrics Society guideline recommending a HbA1c target of 8.0% or less for older adults with limited life expectancy may be lower than necessary to maintain function.

Because the pathologic processes that underlie Alzheimer's disease (AD) appear to start 10 to 20 years before symptoms develop, there is currently intense interest in developing techniques to accurately predict which individuals are most likely to become symptomatic. Several AD risk prediction strategies - including identification of biomarkers and neuroimaging techniques and development of risk indices that combine traditional and non-traditional risk factors - are being explored. Most AD risk prediction strategies developed to date have had moderate prognostic accuracy but are limited by two key issues. First, they do not explicitly model mortality along with AD risk and, therefore, do not differentiate individuals who are likely to develop symptomatic AD prior to death from those who are likely to die of other causes. This is critically important so that any preventive treatments can be targeted to maximize the potential benefit and minimize the potential harm. Second, AD risk prediction strategies developed to date have not explored the full range of predictive variables (biomarkers, imaging, and traditional and non-traditional risk factors) over the full preclinical period (10 to 20 years). Sophisticated modeling techniques such as hidden Markov models may enable the development of a more comprehensive AD risk prediction algorithm by combining data from multiple cohorts. As the field moves forward, it will be critically important to develop techniques that simultaneously model the risk of mortality as well as the risk of AD over the full preclinical spectrum and to consider the potential harm as well as the benefit of identifying and treating high-risk older patients.

Older adults comprise an increasing proportion of the prison and homeless populations. While older age is associated with adverse post-release health events and incarceration is a risk factor for homelessness, the health status and homelessness risk of older pre-release prisoners are unknown. Moreover, most post-release services are geared towards veterans; it is unknown whether the needs of non-veterans differ from those of veterans.To assess health status and risk of homelessness of older pre-release prisoners, and to compare veterans with non-veterans.Cross-sectional study of 360 prisoners (≥55 years of age) within 2 years of release from prison using data from the 2004 Survey of Inmates in State and Federal Correctional Facilities.Veteran status, health status (based on self-report), and risk of homelessness (homelessness before arrest).Mean age was 61 years; 93.8% were men and 56.5% were white. Nearly 40% were veterans, of whom 77.2% reported likely VA service eligibility. Veterans were more likely to be white and to have obtained a high school diploma or GED. Overall, 79.1% reported a medical condition and 13.6% reported a serious mental illness. There was little difference in health status between veterans and non-veterans. Although 1 in 12 prisoners reported a risk factor for homelessness, the risk factors did not differ according to veteran status.Older pre-release prisoners had a high burden of medical and mental illness and were at risk for post-release homelessness regardless of veteran status. Reentry programs linking pre-release older prisoners to medical and psychiatric services and to homelessness prevention programs are needed for both veterans and non-veterans.

Context: Primary aldosteronism (PA) is one of the most common causes of secondary hypertension, but the comparative outcomes of targeted treatment remain unclear. Objective: To compare the clinical outcomes in patients treated for primary aldosteronism over time. Methods: Medline and EMBASE were searched. Original studies reporting the incidence of mortality, major adverse cardiovascular outcomes (MACE), progression to chronic kidney disease, or diabetes following adrenalectomy vs medical therapy were selected. Two reviewers independently abstracted data and assessed study quality. Standard meta-analyses were conducted using random-effects models to estimate relative differences. Time to benefit meta-analyses were conducted by fitting Weibull survival curves to estimate absolute risk differences and pooled using random-effects models. Results: 15 541 patients (16 studies) with PA were included. Surgery was consistently associated with an overall lower risk of death (hazard ratio [HR] 0.34, 95% CI 0.22-0.54) and MACE (HR 0.55, 95% CI 0.36-0.84) compared with medical therapy. Surgery was associated with a significantly lower risk of hospitalization for heart failure (HR 0.48 95% CI 0.34-0.70) and progression to chronic kidney disease (HR 0.62 95% CI 0.39-0.98), and nonsignificant reductions in myocardial infarction and stroke. In absolute terms, 200 patients would need to be treated with surgery instead of medical therapy to prevent 1 death after 12.3 (95% CI 3.1-48.7) months. Conclusion: Surgery is associated with lower all-cause mortality and MACE than medical therapy for PA. For most patients, the long-term surgical benefits outweigh the short-term perioperative risks. [ABSTRACT FROM AUTHOR]

Background: Fifty percent of people living with dementia are undiagnosed. The electronic health record (EHR) Risk of Alzheimer's and Dementia Assessment Rule (eRADAR) was developed to identify older adults at risk of having undiagnosed dementia using routinely collected clinical data. Objective: To externally validate eRADAR in two real-world healthcare systems, including examining performance over time and by race/ethnicity. Design: Retrospective cohort study Participants: 129,315 members of Kaiser Permanente Washington (KPWA), an integrated health system providing insurance coverage and medical care, and 13,444 primary care patients at University of California San Francisco Health (UCSF), an academic medical system, aged 65 years or older without prior EHR documentation of dementia diagnosis or medication. Main Measures: Performance of eRADAR scores, calculated annually from EHR data (including vital signs, diagnoses, medications, and utilization in the prior 2 years), for predicting EHR documentation of incident dementia diagnosis within 12 months. Key Results: A total of 7631 dementia diagnoses were observed at KPWA (11.1 per 1000 person-years) and 216 at UCSF (4.6 per 1000 person-years). The area under the curve was 0.84 (95% confidence interval: 0.84–0.85) at KPWA and 0.79 (0.76–0.82) at UCSF. Using the 90th percentile as the cut point for identifying high-risk patients, sensitivity was 54% (53–56%) at KPWA and 44% (38–51%) at UCSF. Performance was similar over time, including across the transition from International Classification of Diseases, version 9 (ICD-9) to ICD-10 codes, and across racial/ethnic groups (though small samples limited precision in some groups). Conclusions: eRADAR showed strong external validity for detecting undiagnosed dementia in two health systems with different patient populations and differential availability of external healthcare data for risk calculations. In this study, eRADAR demonstrated generalizability from a research sample to real-world clinical populations, transportability across health systems, robustness to temporal changes in healthcare, and similar performance across larger racial/ethnic groups. [ABSTRACT FROM AUTHOR]

Background: Measuring multimorbidity in claims data is used for risk adjustment and identifying populations at high risk for adverse events. Multimorbidity indices such as Charlson and Elixhauser scores have important limitations. We sought to create a better method of measuring multimorbidity using claims data by incorporating geriatric conditions, markers of disease severity, and disease‐disease interactions, and by tailoring measures to different outcomes. Methods: Health conditions were assessed using Medicare inpatient and outpatient claims from subjects age 67 and older in the Health and Retirement Study. Separate indices were developed for ADL decline, IADL decline, hospitalization, and death, each over 2 years of follow‐up. We validated these indices using data from Medicare claims linked to the National Health and Aging Trends Study. Results: The development cohort included 5012 subjects with median age 76 years; 58% were female. Claims‐based markers of disease severity and disease‐disease interactions yielded minimal gains in predictive power and were not included in the final indices. In the validation cohort, after adjusting for age and sex, c‐statistics for the new multimorbidity indices were 0.72 for ADL decline, 0.69 for IADL decline, 0.72 for hospitalization, and 0.77 for death. These c‐statistics were 0.02–0.03 higher than c‐statistics from Charlson and Elixhauser indices for predicting ADL decline, IADL decline, and hospitalization, and <0.01 higher for death (p < 0.05 for each outcome except death), and were similar to those from the CMS‐HCC model. On decision curve analysis, the new indices provided minimal benefit compared with legacy approaches. C‐statistics for both new and legacy indices varied substantially across derivation and validation cohorts. Conclusions: A new series of claims‐based multimorbidity measures were modestly better at predicting hospitalization and functional decline than several legacy indices, and no better at predicting death. There may be limited opportunity in claims data to measure multimorbidity better than older methods. [ABSTRACT FROM AUTHOR]