Weakness Thresholds Are Differentially Linked to Cognitive Function by Obesity Status in Older Americans.

Background: Weakness can be operationalized with several thresholds, which in turn, could impact associations with cognitive impairment when considering obesity status. Objective: We examined the associations of absolute, normalized, and collective weakness thresholds on future cognitive impairment by obesity status in older adults. Methods: We performed a secondary data analysis on the 2006-2018 waves of the Health and Retirement Study. A spring-type dynamometer collected handgrip strength (HGS). Males were categorized weak if their HGS was <35.5-kg (absolute), <0.45-kg/kg (body mass normalized), or <1.05-kg/kg/m2 (body mass index (BMI) normalized), while females were defined as weak if their HGS was <20.0-kg, <0.337-kg/kg, or <0.79-kg/kg/m2. The modified Telephone Interview of Cognitive Status examined cognitive function. Persons scoring ≤10 had a cognitive impairment. Obesity was categorized as BMI ≥30 kg/m2. Results: We included 7,532 and 3,584 persons aged ≥65-years living without and with obesity, respectively. Those without obesity but beneath the absolute weakness threshold had 1.54 (95% confidence interval (CI): 1.24-1.91) greater odds for future cognitive impairment. Persons with obesity and beneath each threshold also had greater odds for future cognitive impairment: 1.89 (95% CI: 1.28-2.78) for absolute, 2.17 (95% CI: 1.02-4.62) for body mass normalized, and 1.75 (95% CI: 1.10-2.80) for BMI normalized. Older Americans without obesity but underneath all the weakness thresholds had 1.32 (95% CI: 1.00-1.74) greater odds for impairment in cognitive function, while persons with obesity had 2.76 (95% CI: 1.29-5.93) greater odds. Conclusions: There should be consideration for how body size and different weakness thresholds may influence future cognitive outcomes.

Collective Weakness Is Associated With Time to Mortality in Americans.

ABSTRACT: McGrath, R, McGrath, BM, Jurivich, D, Knutson, P, Mastrud, M, Singh, B, and Tomkinson, GR. Collective weakness is associated with time to mortality in Americans. J Strength Cond Res XX(X): 000-000, 2024-Using new weakness cutpoints individually may help estimate time to mortality, but their collective use could improve value. We sought to determine the associations of (a) each absolute and body size normalized cut point and (b) collective weakness on time to mortality in Americans. The analytic sample included 14,178 subjects aged ≥50 years from the 2006-2018 waves of the Health and Retirement Study. Date of death was confirmed from the National Death Index. Handgrip dynamometry measured handgrip strength (HGS). Men were categorized as weak if their HGS was <35.5 kg (absolute), <0.45 kg·kg-1 (body mass normalized), or <1.05 kg·kg-1·m-2 (body mass index [BMI] normalized). Women were classified as weak if their HGS was <20.0 kg, <0.337 kg·kg-1, or <0.79 kg·kg-1·m-2. Collective weakness categorized persons as below 1, 2, or all 3 cutpoints. Cox proportional hazard regression models were used for analyses. Subject values below each absolute and normalized cutpoint for the 3 weakness parameters had a higher hazard ratio for early all-cause mortality: 1.45 (95% confidence interval [CI]: 1.36-1.55) for absolute weakness, 1.39 (CI: 1.30-1.49) for BMI normalized weakness, and 1.33 (CI: 1.24-1.43) for body mass normalized weakness. Those below 1, 2, or all 3 weakness cut points had a 1.37 (CI: 1.26-1.50), 1.47 (CI: 1.35-1.61), and 1.69 (CI: 1.55-1.84) higher hazard for mortality, respectively. Weakness determined by a composite measure of absolute and body size adjusted strength capacity provides robust prediction of time to mortality, thus potentially informing sports medicine and health practitioner discussions about the importance of muscle strength during aging.

Variation in multimorbidity by sociodemographics and social drivers of health among patients seen at community-based health centers.

Purpose: Understanding variation in multimorbidity across sociodemographics and social drivers of health is critical to reducing health inequities. Methods: From the multi-state OCHIN network of community-based health centers (CBHCs), we identified a cross-sectional cohort of adult (> 25 years old) patients who had a visit between 2019-2021. We used generalized linear models to examine the relationship between the Multimorbidity Weighted Index (MWI) and sociodemographics and social drivers of health (Area Deprivation Index [ADI] and social risks [e.g., food insecurity]). Each model included an interaction term between the primary predictor and age to examine if certain groups had a higher MWI at younger ages. Results: Among 642,730 patients, 28.2% were Hispanic/Latino, 42.8% were male, and the median age was 48. The median MWI was 2.05 (IQR: 0.34, 4.87) and was higher for adults over the age of 40 and American Indians and Alaska Natives. The regression model revealed a higher MWI at younger ages for patients living in areas of higher deprivation. Additionally, patients with social risks had a higher MWI (3.16; IQR: 1.33, 6.65) than those without (2.13; IQR: 0.34, 4.89) and the interaction between age and social risk suggested a higher MWI at younger ages. Conclusions: Greater multimorbidity at younger ages and among those with social risks and living in areas of deprivation shows possible mechanisms for the premature aging and disability often seen in community-based health centers and highlights the need for comprehensive approaches to improving the health of vulnerable populations.

Pandemic-related practice changes and CVD risk management in community clinics.

OBJECTIVES: Understanding how the COVID-19 pandemic affected cardiovascular disease (CVD) risk monitoring in primary care may inform new approaches for addressing modifiable CVD risks. This study examined how pandemic-driven changes in primary care delivery affected CVD risk management processes. STUDY DESIGN: This retrospective study used electronic health record data from patients at 70 primary care community clinics with scheduled appointments from September 1, 2018, to September 30, 2021. METHODS: Analyses examined associations between appointment type and select care process measures: appointment completion rates, time to appointment, and up-to-date documentation for blood pressure (BP) and hemoglobin A1c (HbA1c). RESULTS: Of 1,179,542 eligible scheduled primary care appointments, completion rates were higher for virtual care (VC) vs in-person appointments (10.7 percentage points [PP]; 95% CI, 10.5-11.0; P < .001). Time to appointment was shorter for VC vs in-person appointments (-3.9 days; 95% CI, -4.1 to -3.7; P < .001). BP documentation was higher for appointments completed pre- vs post pandemic onset (16.2 PP; 95% CI, 16.0-16.5; P < .001) and for appointments completed in person vs VC (54.9 PP; 95% CI, 54.6-55.2; P < .001). HbA1c documentation was higher for completed appointments after pandemic onset vs before (5.9 PP; 95% CI, 5.1-6.7; P < .001) and for completed VC appointments vs in-person appointments (3.9 PP; 95% CI, 3.0-4.7; P < .001). CONCLUSIONS: After pandemic onset, appointment completion rates were higher, time to appointment was shorter, HbA1c documentation increased, and BP documentation decreased. Future research should explore the advantages of using VC for CVD risk management while continuing to monitor for unintended consequences.

Cardiovascular disease risk management during COVID-19: in-person vs virtual visits.

OBJECTIVES: Limited research has assessed how virtual care (VC) affects cardiovascular disease (CVD) risk management, especially in community clinic settings. This study assessed change in community clinic patients' CVD risk management during the COVID-19 pandemic and CVD risk factor control among patients who had primarily in-person or primarily VC visits. STUDY DESIGN: Retrospective interrupted time-series analysis. METHODS: Data came from an electronic health record shared by 52 community clinics for index (March 1, 2019, to February 29, 2020) and follow-up (July 1, 2020, to February 28, 2022) periods. Analyses compared follow-up period changes in slope and level of population monthly means of 10-year reversible CVD risk score, blood pressure (BP), and hemoglobin A1c (HbA1c) among patients whose completed follow-up period visits were primarily in person vs primarily VC. Propensity score weighting minimized confounding. RESULTS: There were 10,028 in-person and 6593 VC patients in CVD risk analyses, 9874 in-person and 5390 VC patients in BP analyses, and 8221 in-person and 4937 VC patients in HbA1c analyses. The VC group was more commonly younger, female, White, and urban. Mean reversible CVD risk, mean systolic BP, and percentage of BP measurements that were 140/90 mm Hg or higher increased significantly from index to follow-up periods in both groups. Rate of change between these periods was the same for all outcomes in both groups, regardless of care modality. CONCLUSIONS: Among community clinic patients with CVD risk, receiving a majority of care in person vs a majority of care via VC was not significantly associated with longitudinal trends in reversible CVD risk score or key CVD risk factors.

Unwinding of Continuous Medicaid Coverage Among Patients at Community Health Centers.

This retrospective cohort study uses data from the Accelerating Data Value Across a National Community Health Center Network to assess patterns of Medicaid disenrollment during the first 6 months after the end of continuous enrollment.

Care Delivery in Community Health Centers Before, During, and After the COVID-19 Pandemic (2019-2022).

INTRODUCTION: Health centers provide primary and behavioral health care to the nation's safety net population. Many health centers served on the frontlines of the COVID-19 pandemic, which brought major changes to health center care delivery. OBJECTIVE: To elucidate primary care and behavioral health service delivery patterns in health centers before and during the COVID-19 public health emergency (PHE). METHODS: We compared annual and monthly patients from 2019 to 2022 for new and established patients by visit type (primary care, behavioral health) and encounter visits by modality (in-person, telehealth) across 218 health centers in 13 states. RESULTS: There were 1581,744 unique patients in the sample, most from health disparate populations. Review of primary care data over 4 years show that health centers served fewer pediatric patients over time, while retaining the capacity to provide to patients 65+. Monthly data on encounters highlights that the initial shift in March/April 2020 to telehealth was not sustained and that in-person visits rose steadily after November/December 2020 to return as the predominant care delivery mode. With regards to behavioral health, health centers continued to provide care to established patients throughout the PHE, while serving fewer new patients over time. In contrast to primary care, after initial uptake of telehealth in March/April 2020, telehealth encounters remained the predominant care delivery mode through 2022. CONCLUSION: Four years of data demonstrate how COVID-19 impacted delivery of primary care and behavioral health care for patients, highlighting gaps in pediatric care delivery and trends in telehealth over time.

Impact of Reducing Time-to-Antibiotics on Sepsis Mortality, Antibiotic Use, and Adverse Events.

Rationale: Shorter time-to-antibiotics is lifesaving in sepsis, but programs to hasten antibiotic delivery may increase unnecessary antibiotic use and adverse events. Objectives: We sought to estimate both the benefits and harms of shortening time-to-antibiotics for sepsis. Methods: We conducted a simulation study using a cohort of 1,559,523 hospitalized patients admitted through the emergency department with meeting two or more systemic inflammatory response syndrome criteria (2013-2018). Reasons for hospitalization were classified as septic shock, sepsis, infection, antibiotics stopped early, and never treated (no antibiotics within 48 h). We simulated the impact of a 50% reduction in time-to-antibiotics for sepsis across 12 hospital scenarios defined by sepsis prevalence (low, medium, or high) and magnitude of "spillover" antibiotic prescribing to patients without infection (low, medium, high, or very high). Outcomes included mortality and adverse events potentially attributable to antibiotics (e.g., allergy, organ dysfunction, Clostridiodes difficile infection, and culture with multidrug-resistant organism). Results: A total of 933,458 (59.9%) hospitalized patients received antimicrobial therapy within 48 hours of presentation, including 38,572 (2.5%) with septic shock, 276,082 (17.7%) with sepsis, 370,705 (23.8%) with infection, and 248,099 (15.9%) with antibiotics stopped early. A total of 199,937 (12.8%) hospitalized patients experienced an adverse event; most commonly, acute liver injury (5.6%), new MDRO (3.5%), and Clostridiodes difficile infection (1.7%). Across the scenarios, a 50% reduction in time-to-antibiotics for sepsis was associated with a median of 1 to 180 additional antibiotic-treated patients and zero to seven additional adverse events per death averted from sepsis. Conclusions: The impacts of faster time-to-antibiotics for sepsis vary markedly across simulated hospital types. However, even in the worst-case scenario, new antibiotic-associated adverse events were rare.

Area-level social determinants of health and individual-level social risks: Assessing predictive ability and biases in social risk screening.

Introduction: Area-level social determinants of health (SDoH) and individual-level social risks are different, yet area-level measures are frequently used as proxies for individual-level social risks. This study assessed whether demographic factors were associated with patients being screened for individual-level social risks, the percentage who screened positive for social risks, and the association between SDoH and patient-reported social risks in a nationwide network of community-based health centers. Methods: Electronic health record data from 1,330,201 patients with health center visits in 2021 were analyzed using multilevel logistic regression. Associations between patient characteristics, screening receipt, and screening positive for social risks (e.g., food insecurity, housing instability, transportation insecurity) were assessed. The predictive ability of three commonly used SDoH measures (Area Deprivation Index, Social Deprivation Index, Material Community Deprivation Index) in identifying individual-level social risks was also evaluated. Results: Of 244,155 (18%) patients screened for social risks, 61,414 (25.2%) screened positive. Sex, race/ethnicity, language preference, and payer were associated with both social risk screening and positivity. Significant health system-level variation in both screening and positivity was observed, with an intraclass correlation coefficient of 0.55 for social risk screening and 0.38 for positivity. The three area-level SDoH measures had low accuracy, sensitivity, and area under the curve when used to predict individual social needs. Conclusion: Area-level SDoH measures may provide valuable information about the communities where patients live. However, policymakers, healthcare administrators, and researchers should exercise caution when using area-level adverse SDoH measures to identify individual-level social risks.

Antibiotic Prescribing Practices for Upper Respiratory Tract Infections Among Primary Care Providers: A Descriptive Study.

Background: Most antibiotics are prescribed in the ambulatory setting with estimates that up to 50% of use is inappropriate. Understanding factors associated with antibiotic misuse is essential to advancing better stewardship in this setting. We sought to assess the frequency of unnecessary antibiotic use for upper respiratory infections (URIs) among primary care providers and identify patient and provider characteristics associated with misuse. Methods: Unnecessary antibiotic prescribing was assessed in a descriptive study by using adults ≥18 years seen for common URIs in a large, Upper Midwest, integrated health system, electronic medical records from June 2017 through May 2018. Individual provider rates of unnecessary prescribing were compared for primary care providers practicing in the departments of internal medicine, family medicine, or urgent care. Patient and provider characteristics associated with unnecessary prescribing were identified with a logistic regression model. Results: A total of 49 463 patient encounters were included. Overall, antibiotics were prescribed unnecessarily for 42.2% (95% confidence interval [CI], 41.7-42.6) of the encounters. Patients with acute bronchitis received unnecessary antibiotics most frequently (74.2%; 95% CI, 73.4-75.0). Males and older patients were more likely to have an unnecessary antibiotic prescription. Provider characteristics associated with higher rates of unnecessary prescribing included being in a rural practice, having more years in practice, and being in higher volume practices such as an urgent care setting. Fifteen percent of providers accounted for half of all unnecessary antibiotic prescriptions. Conclusions: Although higher-volume practices, a rural setting, or longer time in practice were predictors, unnecessary prescribing was common among all providers.

Interpretability, credibility, and usability of hospital-specific template matching versus regression-based hospital performance assessments; a multiple methods study.

BACKGROUND: Hospital-specific template matching (HS-TM) is a newer method of hospital performance assessment. OBJECTIVE: To assess the interpretability, credibility, and usability of HS-TM-based vs. regression-based performance assessments. RESEARCH DESIGN: We surveyed hospital leaders (January-May 2021) and completed follow-up semi-structured interviews. Surveys included four hypothetical performance assessment vignettes, with method (HS-TM, regression) and hospital mortality randomized. SUBJECTS: Nationwide Veterans Affairs Chiefs of Staff, Medicine, and Hospital Medicine. MEASURES: Correct interpretation; self-rated confidence in interpretation; and self-rated trust in assessment (via survey). Concerns about credibility and main uses (via thematic analysis of interview transcripts). RESULTS: In total, 84 participants completed 295 survey vignettes. Respondents correctly interpreted 81.8% HS-TM vs. 56.5% regression assessments, p < 0.001. Respondents "trusted the results" for 70.9% HS-TM vs. 58.2% regression assessments, p = 0.03. Nine concerns about credibility were identified: inadequate capture of case-mix and/or illness severity; inability to account for specialized programs (e.g., transplant center); comparison to geographically disparate hospitals; equating mortality with quality; lack of criterion standards; low power; comparison to dissimilar hospitals; generation of rankings; and lack of transparency. Five concerns were equally relevant to both methods, one more pertinent to HS-TM, and three more pertinent to regression. Assessments were mainly used to trigger further quality evaluation (a "check oil light") and motivate behavior change. CONCLUSIONS: HS-TM-based performance assessments were more interpretable and more credible to VA hospital leaders than regression-based assessments. However, leaders had a similar set of concerns related to credibility for both methods and felt both were best used as a screen for further evaluation.

A Matched Cohort Analysis for Examining the Association Between Slow Gait Speed and Shortened Longevity in Older Americans.

This investigation examined the association between slow gait speed, as defined with newly established cut-points, and all-cause mortality in older Americans with a matched cohort analysis. The analytic sample included 10,259 Americans aged ≥65 years from the 2006-2014 waves of the Health and Retirement Study. Walking speed was measured in participant residences. Slow gait speed cut-points of <0.60 and <0.75 m/s were used separately for classifying participants as having slow walking speed. Nearest-neighbor propensity score matching was used to match the slow to the not-slow cohorts separately using both cut-points using relevant covariates. Persons with gait speed <0.60 m/s had a 1.42 higher hazard for mortality (95% CI: 1.28-1.57). Older Americans with gait speed <0.75 m/s had a 1.36 higher hazard for mortality (95% CI: 1.23-1.50). Slow gait speed may represent failing health and addressing how slow gait speed could be improved may help with referrals to appropriate interventions.