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Background Despite significant support system disruptions during the coronavirus 2019 (COVID-19) pandemic, little is known about the relationship between social support and symptom burden among older adults following COVID-19 hospitalization. Methods From a prospective cohort of 341 community-living persons aged ≥60 years hospitalized with COVID-19 between June 2020 and June 2021 who underwent follow-up at 1, 3, and 6 months after discharge, we identified 311 participants with ≥1 follow-up assessment. Social support prehospitalization was ascertained using a 5-item version of the Medical Outcomes Study Social Support Survey (range, 5–25), with low social support defined as a score ≤15. At hospitalization and each follow-up assessment, 14 physical symptoms were assessed using a modified Edmonton Symptom Assessment System inclusive of COVID-19-relevant symptoms. Mental health symptoms were assessed using Patient Health Questionnaire-4. Longitudinal associations between social support and physical and mental health symptoms, respectively, were evaluated through multivariable regression. Results Participants' mean age was 71.3 years (standard deviation, 8.5), 52.4% were female, and 34.2% were of Black race or Hispanic ethnicity. 11.8% reported low social support. Over the 6-month follow-up period, low social support was independently associated with higher burden of physical symptoms (adjusted rate ratio [aRR], 1.26; 95% confidence interval [CI], 1.05–1.52), but not mental health symptoms (aRR, 1.14; 95% CI, 0.85–1.53). Conclusions Low social support is associated with greater physical, but not mental health, symptom burden among older survivors of COVID-19 hospitalization. Our findings suggest a potential need for social support screening and interventions to improve post-COVID-19 symptom management in this vulnerable group. [ABSTRACT FROM AUTHOR]

Background: Older adults with acute myocardial infarction (AMI) have higher prevalence of functional impairments, including deficits in cognition, strength, and sensory domains, than their younger counterparts.Objective: To develop and evaluate the prognostic utility of a risk model for 6-month post-AMI mortality in older adults that incorporates information about functional impairments.Design: Prospective cohort study. (ClinicalTrials.gov: NCT01755052).Setting: 94 hospitals throughout the United States.Participants: 3006 persons aged 75 years or older who were hospitalized with AMI and discharged alive.Measurements: Functional impairments were assessed during hospitalization via direct measurement (cognition, mobility, muscle strength) or self-report (vision, hearing). Clinical variables associated with mortality in prior risk models were ascertained by chart review. Seventy-two candidate variables were selected for inclusion, and backward selection and Bayesian model averaging were used to derive (n = 2004 participants) and validate (n = 1002 participants) a model for 6-month mortality.Results: Participants' mean age was 81.5 years, 44.4% were women, and 10.5% were nonwhite. There were 266 deaths (8.8%) within 6 months. The final risk model included 15 variables, 4 of which were not included in prior risk models: hearing impairment, mobility impairment, weight loss, and lower patient-reported health status. The model was well calibrated (Hosmer-Lemeshow P > 0.05) and showed good discrimination (area under the curve for the validation cohort = 0.84). Adding functional impairments significantly improved model performance, as evidenced by category-free net reclassification improvement indices of 0.21 (P = 0.008) for hearing impairment and 0.26 (P < 0.001) for mobility impairment.Limitation: The model was not externally validated.Conclusion: A newly developed model for 6-month post-AMI mortality in older adults was well calibrated and had good discriminatory ability. This model may be useful in decision making at hospital discharge.Primary Funding Source: National Heart, Lung, and Blood Institute of the National Institutes of Health. [ABSTRACT FROM AUTHOR]

Objectives: While patients’ health priorities should inform healthcare, strategies for doing so are lacking for patients with multiple conditions. We describe challenges to, and strategies that support, patients’ priorities-aligned decision-making. Design: Participant observation qualitative study. Setting: Primary care and cardiology practices in Connecticut. Participants: Ten primary care clinicians, five cardiologists, and the Patient Priorities implementation team (four geriatricians, physician expert in clinician training, behavioral medicine expert). The patients discussed were ≥ 66 years with >3 chronic conditions and ≥10 medications or saw ≥ two specialists. Exposure: Following initial training and experience in providing Patient Priorities Care, the clinicians and Patient Priorities implementation team participated in 21 case-based, group discussions (10 face-to-face;11 telephonic). Using emergent learning (i.e. learning which arises from interactions among the participants), participants discussed challenges, posed solutions, and worked together to determine how to align care options with the health priorities of 35 patients participating in the Patient Priorities Care pilot. Main outcomes: Challenges to, and strategies for, aligning decision-making with patient’s health priorities. Results: Categories of challenges discussed among participants included uncertainty, complexity, and multiplicity of problems and treatments; difficulty switching to patients’ priorities as the focus of decision-making; and differing perspectives between patients and clinicians, and among clinicians. Strategies identified to support patient priorities-aligned decision-making included starting with one thing that matters most to each patient; conducting serial trials of starting, stopping, or continuing interventions; focusing on function (i.e. achieving patient’s desired activities) rather than eliminating symptoms; basing communications, decision-making, and effectiveness on patients’ priorities not solely on diseases; and negotiating shared decisions when there are differences in perspectives. Conclusions: The discrete set of challenges encountered and the implementable strategies identified suggest that patient priorities-aligned decision-making in the care of patients with multiple chronic conditions is feasible, albeit complicated. Findings require replication in additional settings and determination of their effect on patient outcomes. [ABSTRACT FROM AUTHOR]

Background: While survival after acute myocardial infarction has improved substantially, older adults remain at heightened risk for hospital readmissions and death. Evidence for the role of cognitive impairment in older myocardial infarction survivors' risk for these outcomes is limited.Methods: 3041 patients aged ≥75 years hospitalized with acute myocardial infarction (mean age 82 ± 5 years, 56% male) recruited from 94 US hospitals. Cognition was assessed using the Telephone Interview for Cognitive Status; scores of <27 and <22 indicated mild and moderate/severe impairment, respectively. Readmissions and death at 6 months post-discharge were ascertained via participant report and medical record review. Associations between cognition and outcomes were evaluated with multivariable-adjusted logistic regression.Results: Mild and moderate/severe cognitive impairment were present in 11% and 6% of the cohort, respectively. Readmission and death at 6 months occurred in 41% and 9% of participants, respectively. Mild and moderate/severe cognitive impairment were associated with increased risk of readmission (odds ratio [OR] 1.36; 95% confidence interval [CI], 1.08-1.72 and OR 1.58; 95% CI, 1.18-2.12, respectively) and death (OR 2.19; 95% CI, 1.54-3.11 and OR 3.82; 95% CI, 2.63-5.56, respectively) in unadjusted analyses. Significant associations between moderate/severe cognitive impairment and death (OR 1.69; 95% CI, 1.10-2.59) persisted after adjustment for demographics, myocardial infarction characteristics, comorbidity burden, functional status, and depression, but not for readmissions.Conclusions: Moderate-to-severe cognitive impairment is associated with heightened risk of death in older acute myocardial infarction patients in the months after hospitalization, but not with readmission. Routine cognitive screening may identify older myocardial infarction survivors at risk for poor outcomes who may benefit from closer oversight and support in the post-discharge period. [ABSTRACT FROM AUTHOR]

Background: Among older adults hospitalized for acute myocardial infarction (AMI) undergoing cardiac catheterization, acute kidney injury (AKI) is common and associated with poor long-term outcomes. Our aim was to identify risk factors for AKI, using both traditional clinical variables and aging-related functional impairments unmeasured in prior studies. Methods: We analyzed data from the SILVER-AMI cohort, which enrolled patients age ≥75 with AMI across 94 U.S. hospitals. Our sample included the 2212 participants who underwent cardiac catheterization. AKI was defined based on KDIGO criteria (increase in serum Cr ≥0.3 mg/dL from baseline or ≥1.5 times baseline) and severity was divided into Stage 1 (1.5-1.9x baseline), Stage 2 (≥2.0-2.9x baseline), and stage 3 (≥3.0x baseline, or dialysis). We analyzed the association of both traditional AKI risk factors and functional impairments (Table) with AKI. We subsequently performed logistic regression with backwards selection to identify independent predictors of AKI. Results: Mean age was 81.3 years, 45.2% were female, 9.5% were nonwhite, and 77.2% underwent PCI. AKI occurred among 421 participants (19.0%); most AKI (88.4%) was Stage 1. After multivariable regression, 10 risk factors remained independent predictors of AKI (Table). The strongest predictors (adjusted) were history of heart failure (OR 1.63, 95% CI 1.23-2.17), nonwhite race (OR 1.53, 95% CI 1.08-2.16), and atrial fibrillation (OR 1.49, 95% CI 1.05-2.10). Among functional impairments analyzed, impaired mobility was the only factor independently associated with AKI (OR 1.39, 95% CI 1.24-1.56). At 6 months, AKI was associated with both mortality (14.5% vs. 5.4%, P<0.001) and hospital readmission (53.3% vs. 36.1%, P<0.001). Conclusions: AKI is common among older adults with AMI undergoing cardiac catheterization; most cases are mild. While traditional risk factors are strong predictors of AKI, mobility is also independently predictive, potentially due to its close association with the frailty syndrome. This suggests the potential utility of mobility in risk stratification among older adults. [ABSTRACT FROM AUTHOR]

Background: Readmissions among older adults hospitalized for acute myocardial infarction (AMI) are costly, disruptive, and difficult to predict. Aging-related functional impairments may improve risk prediction, but have not been measured in most studies. Our objective was therefore to develop a readmission risk model for older adults hospitalized for AMI that considered functional impairments. Methods: SILVER-AMI is a prospective cohort study of 3006 patients age ≥75 hospitalized with AMI at 96 U.S. hospitals. Participants underwent in-hospital assessment of functional impairments including cognition, vision, hearing, and mobility. Clinical variables traditionally associated with readmission risk, as well as patient reported health status, were also collected. The outcome was all-cause readmission at 30 days. We used backward selection and Bayesian model averaging to derive (N=2004) a risk model that was subsequently validated in a separate sample (N=1002). Model discrimination and calibration were respectively evaluated with the C-statistic and the Hosmer-Lemeshow test. Results: Mean age was 81.5 years, 44.4% were women, and 10.5% were nonwhite. Within 30 days, 547 participants (18.2%) experienced readmission (61.0% cardiac cause). Participants who were readmitted were older, had more comorbidities, and had a higher prevalence of functional impairments including activity of daily living disability (17.0% vs. 13.0%, P=0.01), weak grip strength (64.4% vs. 59.2%, P<0.01), and impaired mobility measured by Timed Up and Go (TUG) (72.5% vs. 53.6%, P<0.001). The final readmission risk model contained 8 variables; mobility was the only functional impairment retained, but was the strongest predictor (Figure). The model was well calibrated (P value >0.05 for Hosmer-Lemeshow statistic) and had moderate discrimination (C-statistic: 0.65 derivation cohort, 0.63 validation cohort) across all multiply imputed datasets. Conclusion: In our final risk model, functional mobility was the strongest predictor of 30-day readmission among older adults after AMI. The modest C-statistic indicates that much of the variability in readmission among this older adult population remains unexplained by patient-level factors. [ABSTRACT FROM AUTHOR]