Journal of the American Geriatrics Society最新文献

Background: Rapid increase in cardiometabolic diseases in India may contribute to increased incidence of late-life cognitive impairment. This study focuses on associations between baseline cardiometabolic risk factors and subsequent decline in cognitive function among older adults in India, leveraging data from two waves (Wave 1: 2017-2020, Wave 2: 2022-2024) of the Longitudinal Aging Study in India-Diagnostic Assessment of Dementia (LASI-DAD).

Methods: Analysis included longitudinal data of 1554 study participants. A summary measure of different cognitive functional domains was used. Cognitive decline was defined as annual decline in cognitive score ≥ 0.05 times the standard deviation of the summary score. Cardiometabolic risk was characterized using cardiovascular, metabolic, and inflammatory biomarkers. Multivariate, multinomial logistic regression analysis was used to examine the associations between cardiometabolic risk and cognitive decline.

Results: At baseline, 71.7% of the sample had elevated homocysteine levels, 44.4% had elevated blood pressure, 23% had elevated glycosylated hemoglobin (HbA1c), and 6.7% had elevated uric acid levels. Between the two waves, 34.8% experienced significant cognitive decline, while 35.6% died. Multivariate multinomial logistic regression showed significant cognitive decline was associated with elevated blood pressure [odds ratio (OR): 1.7, 95% confidence interval (CI) 1.3-2.2], elevated HbA1c (OR: 1.1, 95% CI: 1.0-1.2), being overweight (OR: 1.4, 95% CI: 1.0-2.0), and elevated uric acid level (OR: 1.2, 95% CI: 1.0-1.3). Those with hypertension had 1.5 times higher odds of mortality (95% confidence interval: 1.2-2.0), while those with diabetes mellitus or elevated pro-brain natriuretic peptide had 1.2 times (95% CI: 1.1-1.4), and 1.8 times (95% CI: 1.1-1.4) higher odds of mortality.

Conclusion: Cardiometabolic risk factors play a significant role in late-life cognitive decline and death among older Indians. These longitudinal relationships from LASI-DAD highlight potentially modifiable risk factors and inform potential prevention policies.

Background: Nursing home residents (NHRs) remain at high risk for severe outcomes following SARS-CoV-2 infection. Omicron descendants have dominated circulating strains, with XBB in 2023 and KP.2 strain by mid-2024, leading to immune escape and increased transmissibility. We aimed to assess the immunogenicity of one versus two prior doses of the XBB.1.5 vaccines and potential differences in the subsequent response to the KP.2 booster.

Methods: We conducted a longitudinal immunologic evaluation of 131 NHRs in Ohio and Rhode Island. Samples were collected 2-6 weeks after the first and second XBB.1.5 vaccination doses, 60 days before KP.2 vaccination, and 2-6 weeks after the KP.2 booster. We measured anti-spike and neutralizing antibody titers to both XBB.1.5 and KP.2.

Results: NHRs who received two booster doses of the XBB.1.5 vaccine developed higher peak anti-spike antibody levels (29,777 AU/mL) and neutralizing titers (7082) compared to those with only one dose (13,788 AU/mL and 1293, respectively). Over time, anti-spike antibody and neutralizing titers declined, but both remained higher in the two-dose group before receiving the KP.2 vaccine. After vaccination with XBB.1.5, neutralization against KP.2 was significantly lower than against XBB.1.5, suggesting reduced cross-reactivity and highlighting the potential for immune escape. However, KP.2 vaccination markedly boosted neutralizing titers in all participants, regardless of their prior XBB.1.5 dose history.

Conclusion: NHRs who received a two-dose regimen of the XBB.1.5 vaccine demonstrated stronger immune responses and higher pre-KP.2 titers than those who received a single dose. However, the diminished cross-protective neutralization of KP.2 highlights the variant's immune evasiveness. The KP.2 booster effectively elicited anti-KP.2 levels, supporting the continued use of updated, variant-matched boosters to protect high-risk populations such as NHRs.

A New Era for Menopause Hormone Therapy: Key Considerations for Geriatricians After FDA Boxed Warning Removal.

Background: To avoid potential harms from hypoglycemia, guidelines for diabetes management in nursing home residents recommend less intensive glycemic control. However, it is unknown how often hypoglycemia and hyperglycemia co-occur in the same resident, which may present challenges for deintensification of diabetes treatment.

Methods: We conducted a cross-sectional study of insulin-treated Veterans Affairs nursing home residents with diabetes aged ≥ 65 years from 1/1/2016 to 9/30/2019 with a nursing home stay ≥ 7 days. Residents missing fingerstick glucose measurements during the first 7 days were excluded. We classified insulin use as basal insulin only, bolus insulin only, or a combination of basal and bolus insulin. We examined the prevalence of fingerstick-detected hypoglycemia (< 54 mg/dL, 54-69 mg/dL) and hyperglycemia (250-299, 300-349, 350-399, ≥ 400 mg/dL) overall and stratified by type of insulin.

Results: Among 12,031 insulin-treated residents, the mean age was 74.4 years, 98% were male, and 22% were non-White. Most residents (n = 7176, 59.6%) were treated with a combination of basal and bolus insulin, 31.8% (n = 3829) used bolus insulin alone and 8.5% (n = 1026) used basal insulin alone. During the first 7 days of the nursing home stay, 5730 (48%) had hyperglycemia ≥ 250 mg/dL alone, 862 (7%) had hypoglycemia < 70 mg/dL alone, 1488 (12%) had both hyperglycemia and hypoglycemia, and 3951 (33%) had neither hypoglycemia nor hyperglycemia. Residents on a combination of basal and bolus insulin were more likely to have hyperglycemia ≥ 400 mg/dL (10.2% vs. 3.6% for bolus insulin alone and 1.6% for basal insulin alone, p < 0.001) and to have hypoglycemia < 54 mg/dL (8.4% vs. 2.9% for bolus alone vs. 5.9% for basal alone, p < 0.001).

Conclusion: Nearly two-thirds of nursing home residents with hypoglycemia also had hyperglycemia. Efforts to de-intensify diabetes treatment in nursing homes will need to address the high burden of hyperglycemia by tailoring the timing and type of insulin to minimize hypoglycemia while also not worsening hyperglycemia.

DXA Utilization Among Veterans Aged ≥ 50 years by Facility-Reported DXA Capacity.

Receiver Operating Characteristic Curve for the Modified Caregiver Strain Index predicting high Zarit-Burden Interview, showing excellent discrimination.

Background: Cannabis use is rising among adults, yet few users receive structured medical supervision. Older users face unique risks necessitating specialized oversight. Given their longitudinal relationships and detailed understanding of patients' health and goals, primary care providers are well-positioned to guide decisions and education about medical cannabis (MC). Further, because of their expertise in managing complex considerations of aging, geriatricians in particular are uniquely qualified to offer safe, evidence-informed guidance to older adults using MC. This led us to develop and implement a physician-led MC clinic embedded in a geriatric primary care practice.

Methods: A monthly, physician-led MC certification clinic was established to provide individualized evaluation, safety assessment, medication review, and counseling, with support from pharmacy and nursing. The clinic was shaped by the legal, regulatory, and clinical context. The demographic characteristics, medical and qualifying conditions, and medication profiles of patients with a MC clinic visit between Jan 1, 2022, and July 1, 2024, were evaluated retrospectively. Data was analyzed descriptively.

Results: In 30 months, 144 visits were completed. The population had a mean age of 65 years (SD 13.8), was 59.7% female, and diverse. There was high clinical complexity (mean 20.9 comorbid conditions, 14.7 medications). Pain was the predominant qualifying condition (88.9%), with anxiety (13.9%) and insomnia (11.8%) also common. Drug utilization reviews revealed a mean of 4.6 interactions per patient. Common medications included CNS depressants (66.0%), pain medications (59.0%), and psychiatric medications (56.9%).

Conclusions: This model demonstrates a feasible approach to integrating MC care into primary care for medically complex older adults. This integration prevents MC care fragmentation, provides thorough drug interaction screening, and supports informed MC risk-benefit assessment.