Relationship Between Insurance Status and Receipt of Cardiac Tests and Procedures During Hospitalization: A Cross-Sectional Study.

BACKGROUND: Prior analyses of the relationship between insurance status and receipt of tests and procedures have yielded conflicting findings and have focused on outpatient care. We sought to characterize the relationship between primary payer and diagnostic and procedural intensity, comparing rates of cardiac tests and procedures in matched hospitalized Medicaid and commercially insured patients. METHODS AND RESULTS: We created a propensity score-matched sample of Medicaid and commercially insured adults hospitalized at all acute care hospitals in Kentucky, Maryland, New Jersey, and North Carolina from 2016 to 2018. The main outcome was receipt of a cardiac test or procedure: echocardiogram, stress test, cardiac catheterization (elective, in acute coronary syndrome, in ST-segment-elevation myocardial infarction), and pacemaker and subcutaneous cardiac rhythm monitor implantation. Generalized linear models with a hospital-specific indicator variable were estimated to calculate the adjusted odds of a commercially insured patient receiving a given test or procedure relative to a Medicaid patient. Models controlled for race, ethnicity, and zip code income quartile. Commercially insured patients were more likely to receive each cardiac test or procedure, with adjusted odds ratios ranging from 1.16 (95% CI, 1.00-1.34) for cardiac catheterization in ST-segment-elevation myocardial infarction to 1.40 (95% CI, 1.27-1.54) for pacemaker implantation. CONCLUSIONS: Hospitalized commercially insured patients were more likely to undergo a range of cardiac tests and procedures, some of which may represent low-value care. This may be driven by a combination of physician and patient preference, financial incentives, and social determinants of health. Our findings support the need for hospital payment models focused on increasing value and reducing inequities.

Agreement Between Apple Watch and Actical Step Counts in a Community Setting: Cross-Sectional Investigation From the Framingham Heart Study.

BACKGROUND: Step counting is comparable among many research-grade and consumer-grade accelerometers in laboratory settings. OBJECTIVE: The purpose of this study was to compare the agreement between Actical and Apple Watch step-counting in a community setting. METHODS: Among Third Generation Framingham Heart Study participants (N=3486), we examined the agreement of step-counting between those who wore a consumer-grade accelerometer (Apple Watch Series 0) and a research-grade accelerometer (Actical) on the same days. Secondarily, we examined the agreement during each hour when both devices were worn to account for differences in wear time between devices. RESULTS: We studied 523 participants (n=3223 person-days, mean age 51.7, SD 8.9 years; women: n=298, 57.0%). Between devices, we observed modest correlation (intraclass correlation [ICC] 0.56, 95% CI 0.54-0.59), poor continuous agreement (29.7%, n=957 of days having steps counts with ≤15% difference), a mean difference of 499 steps per day higher count by Actical, and wide limits of agreement, roughly ±9000 steps per day. However, devices showed stronger agreement in identifying who meets various steps per day thresholds (eg, at 8000 steps per day, kappa coefficient=0.49), for which devices were concordant for 74.8% (n=391) of participants. In secondary analyses, in the hours during which both devices were worn (n=456 participants, n=18,760 person-hours), the correlation was much stronger (ICC 0.86, 95% CI 0.85-0.86), but continuous agreement remained poor (27.3%, n=5115 of hours having step counts with ≤15% difference) between devices and was slightly worse for those with mobility limitations or obesity. CONCLUSIONS: Our investigation suggests poor overall agreement between steps counted by the Actical device and those counted by the Apple Watch device, with stronger agreement in discriminating who meets certain step thresholds. The impact of these challenges may be minimized if accelerometers are used by individuals to determine whether they are meeting physical activity guidelines or tracking step counts. It is also possible that some of the limitations of these older accelerometers may be improved in newer devices.

Association of Smartwatch-Based Heart Rate and Physical Activity With Cardiorespiratory Fitness Measures in the Community: Cohort Study.

BACKGROUND: Resting heart rate (HR) and routine physical activity are associated with cardiorespiratory fitness levels. Commercial smartwatches permit remote HR monitoring and step count recording in real-world settings over long periods of time, but the relationship between smartwatch-measured HR and daily steps to cardiorespiratory fitness remains incompletely characterized in the community. OBJECTIVE: This study aimed to examine the association of nonactive HR and daily steps measured by a smartwatch with a multidimensional fitness assessment via cardiopulmonary exercise testing (CPET) among participants in the electronic Framingham Heart Study. METHODS: Electronic Framingham Heart Study participants were enrolled in a research examination (2016-2019) and provided with a study smartwatch that collected longitudinal HR and physical activity data for up to 3 years. At the same examination, the participants underwent CPET on a cycle ergometer. Multivariable linear models were used to test the association of CPET indices with nonactive HR and daily steps from the smartwatch. RESULTS: We included 662 participants (mean age 53, SD 9 years; n=391, 59% women, n=599, 91% White; mean nonactive HR 73, SD 6 beats per minute) with a median of 1836 (IQR 889-3559) HR records and a median of 128 (IQR 65-227) watch-wearing days for each individual. In multivariable-adjusted models, lower nonactive HR and higher daily steps were associated with higher peak oxygen uptake (VO2), % predicted peak VO2, and VO2 at the ventilatory anaerobic threshold, with false discovery rate (FDR)-adjusted P values <.001 for all. Reductions of 2.4 beats per minute in nonactive HR, or increases of nearly 1000 daily steps, corresponded to a 1.3 mL/kg/min higher peak VO2. In addition, ventilatory efficiency (VE/VCO2; FDR-adjusted P=.009), % predicted maximum HR (FDR-adjusted P<.001), and systolic blood pressure-to-workload slope (FDR-adjusted P=.01) were associated with nonactive HR but not associated with daily steps. CONCLUSIONS: Our findings suggest that smartwatch-based assessments are associated with a broad array of cardiorespiratory fitness responses in the community, including measures of global fitness (peak VO2), ventilatory efficiency, and blood pressure response to exercise. Metrics captured by wearable devices offer a valuable opportunity to use extensive data on health factors and behaviors to provide a window into individual cardiovascular fitness levels.

Depressive symptoms are not associated with clinically important levels of digital home blood pressure in the electronic Framingham Heart Study.

Background: Depressive symptoms are common and share many biopsychosocial mechanisms with hypertension. Association studies between depressive symptoms and blood pressure (BP) have been inconsistent. Home BP monitoring may provide insight. Objective: To investigate the association between depressive symptoms and digital home BP. Methods: Electronic Framingham Heart Study (eFHS) participants were invited to obtain a smartphone app and digital BP cuff at research exam 3 (2016-2019). Participants with ≥3 weeks of home BP measurements within 1 year were included. Depressive symptoms were measured using the Center for Epidemiological Studies Depression Scale (CES-D). Multivariable linear mixed models were used to test the associations of continuous CES-D score and dichotomous depressive symptoms (CES-D ≥16) (independent) with home BP (dependent), adjusting for age, sex, cohort, number of weeks since baseline, lifestyle factors, diabetes, and cardiovascular disease. Results: Among 883 participants (mean age 54 years, 59% women, 91% White), the median CES-D score was 4. Depressive symptom prevalence was 7.6%. Mean systolic and diastolic BP at exam 3 were 119 and 76 mm Hg; hypertension prevalence was 48%. A 1 SD higher CES-D score was associated with 0.9 (95% CI: 0.18-1.56, P = .01) and 0.6 (95% CI: 0.06-1.07, P = .03) mm Hg higher home systolic BP and diastolic BP, respectively. Dichotomous depressive symptoms were not significantly associated with home BP (P > .2). Conclusion: Depressive symptoms were not associated with clinically substantive levels of home BP. The association between depression and cardiovascular disease risk factors warrants more data, which may be supported by mobile health measures.

Association of Arterial Stiffness With Mid- to Long-Term Home Blood Pressure Variability in the Electronic Framingham Heart Study: Cohort Study.

BACKGROUND: Short-term blood pressure variability (BPV) is associated with arterial stiffness in patients with hypertension. Few studies have examined associations between arterial stiffness and digital home BPV over a mid- to long-term time span, irrespective of underlying hypertension. OBJECTIVE: This study aims to investigate if arterial stiffness traits were associated with subsequent mid- to long-term home BPV in the electronic Framingham Heart Study (eFHS). We hypothesized that higher arterial stiffness was associated with higher home BPV over up to 1-year follow-up. METHODS: At a Framingham Heart Study research examination (2016-2019), participants underwent arterial tonometry to acquire measures of arterial stiffness (carotid-femoral pulse wave velocity [CFPWV]; forward pressure wave amplitude [FWA]) and wave reflection (reflection coefficient [RC]). Participants who agreed to enroll in eFHS were provided with a digital blood pressure (BP) cuff to measure home BP weekly over up to 1-year follow-up. Participants with less than 3 weeks of BP readings were excluded. Linear regression models were used to examine associations of arterial measures with average real variability (ARV) of week-to-week home systolic (SBP) and diastolic (DBP) BP adjusting for important covariates. We obtained ARV as an average of the absolute differences of consecutive home BP measurements. ARV considers not only the dispersion of the BP readings around the mean but also the order of BP readings. In addition, ARV is more sensitive to measurement-to-measurement BPV compared with traditional BPV measures. RESULTS: Among 857 eFHS participants (mean age 54, SD 9 years; 508/857, 59% women; mean SBP/DBP 119/76 mm Hg; 405/857, 47% hypertension), 1 SD increment in FWA was associated with 0.16 (95% CI 0.09-0.23) SD increments in ARV of home SBP and 0.08 (95% CI 0.01-0.15) SD increments in ARV of home DBP; 1 SD increment in RC was associated with 0.14 (95% CI 0.07-0.22) SD increments in ARV of home SBP and 0.11 (95% CI 0.04-0.19) SD increments in ARV of home DBP. After adjusting for important covariates, there was no significant association between CFPWV and ARV of home SBP, and similarly, no significant association existed between CFPWV and ARV of home DBP (P>.05). CONCLUSIONS: In eFHS, higher FWA and RC were associated with higher mid- to long-term ARV of week-to-week home SBP and DBP over 1-year follow-up in individuals across the BP spectrum. Our findings suggest that higher aortic stiffness and wave reflection are associated with higher week-to-week variation of BP in a home-based setting over a mid- to long-term time span.

How low can we go? A randomized controlled trial of low-quantity initial opioid prescriptions for shoulder surgery.

BACKGROUND: Orthopedic surgeons are the third most frequent prescribers of opioid medications. Given the current opioid addiction crisis, it is critical to limit opioid prescriptions to the lowest effective dose. In this study, we investigated how the initial opioid prescription after shoulder surgery affects maximum possible opioid consumption. We hypothesized that fewer pills in the initial opioid prescription would lead to less opioid consumption, a lower refill request rate, and fewer post-surgery office contacts for pain. METHODS: In this single-center, prospective, randomized controlled clinical trial, 74 adults who underwent shoulder arthroplasty, rotator cuff repair, or other arthroscopic shoulder procedures were enrolled from December 2020 to July 2022. Follow-up was completed by February 2023. Participants were randomly assigned to receive postoperative prescriptions of seven 5-mg oxycodone pills (n = 20), 15 pills (n = 29), or 23 pills (n = 25). The primary outcome was maximum possible opioid consumption within 2 weeks after surgery, calculated by assuming consumption of all pills in the initial prescription, as well as any refills. Secondary outcomes were the opioid prescription refill request rates, post-surgery pain-related telephone calls or messages to the provider's office ("office contacts") within 2 weeks after surgery, and American Shoulder and Elbow Surgeons pain scores 2 weeks after surgery. Baseline characteristics did not differ among groups except for mean age, which was younger in the 7-pill group (P = .047). RESULTS: Maximum possible opioid consumption increased with the number of pills initially prescribed, with means of 78 morphine milligram equivalents (MME) for the 7-pill group, 118 MME for the 15-pill group, and 199 MME for the 23-pill group (P < .001). None of the secondary outcome measures differed among groups. Refill request rates were 20% for the 7-pill group, 3.4% for the 15-pill group, and 12% for the 23-pill group (P = .20). The proportions of patients with at least 1 office contact were 35% in the 7-pill group, 45% in the 15-pill group, and 28% in the 23-pill group (P = .43). Mean American Shoulder and Elbow Surgeons pain scores were 49 in the 7-pill group, 44 in the 15-pill group, and 40 in the 23-pill group (P = .20). CONCLUSION: After shoulder surgery, an initial prescription of fewer opioid pills was associated with less maximum possible opioid consumption without an increase in the percentage of patients requesting opioid refills or contacting the provider's office for pain-related concerns. An initial postoperative prescription of fewer 5-mg oxycodone pills may be equally or more effective compared with larger quantities for most patients.

Association of Depressive Symptom Trajectory With Physical Activity Collected by mHealth Devices in the Electronic Framingham Heart Study: Cohort Study.

BACKGROUND: Few studies have examined the association between depressive symptom trajectories and physical activity collected by mobile health (mHealth) devices. OBJECTIVE: We aimed to investigate if antecedent depressive symptom trajectories predict subsequent physical activity among participants in the electronic Framingham Heart Study (eFHS). METHODS: We performed group-based multi-trajectory modeling to construct depressive symptom trajectory groups using both depressive symptoms (Center for Epidemiological Studies-Depression [CES-D] scores) and antidepressant medication use in eFHS participants who attended 3 Framingham Heart Study research exams over 14 years. At the third exam, eFHS participants were instructed to use a smartphone app for submitting physical activity index (PAI) surveys. In addition, they were provided with a study smartwatch to track their daily step counts. We performed linear mixed models to examine the association between depressive symptom trajectories and physical activity including app-based PAI and smartwatch-collected step counts over a 1-year follow-up adjusting for age, sex, wear hour, BMI, smoking status, and other health variables. RESULTS: We identified 3 depressive symptom trajectory groups from 722 eFHS participants (mean age 53, SD 8.5 years; n=432, 60% women). The low symptom group (n=570; mean follow-up 287, SD 109 days) consisted of participants with consistently low CES-D scores, and a small proportion reported antidepressant use. The moderate symptom group (n=71; mean follow-up 280, SD 118 days) included participants with intermediate CES-D scores, who showed the highest and increasing likelihood of reporting antidepressant use across 3 exams. The high symptom group (n=81; mean follow-up 252, SD 116 days) comprised participants with the highest CES-D scores, and the proportion of antidepressant use fell between the other 2 groups. Compared to the low symptom group, the high symptom group had decreased PAI (mean difference -1.09, 95% CI -2.16 to -0.01) and the moderate symptom group walked fewer daily steps (823 fewer, 95% CI -1421 to -226) during the 1-year follow-up. CONCLUSIONS: Antecedent depressive symptoms or antidepressant medication use was associated with lower subsequent physical activity collected by mHealth devices in eFHS. Future investigation of interventions to improve mood including via mHealth technologies to help promote people's daily physical activity is needed.

Step Count, Self-reported Physical Activity, and Predicted 5-Year Risk of Atrial Fibrillation: Cross-sectional Analysis.

BACKGROUND: Physical inactivity is a known risk factor for atrial fibrillation (AF). Wearable devices, such as smartwatches, present an opportunity to investigate the relation between daily step count and AF risk. OBJECTIVE: The objective of this study was to investigate the association between daily step count and the predicted 5-year risk of AF. METHODS: Participants from the electronic Framingham Heart Study used an Apple smartwatch. Individuals with diagnosed AF were excluded. Daily step count, watch wear time (hours and days), and self-reported physical activity data were collected. Individuals' 5-year risk of AF was estimated, using the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)-AF score. The relation between daily step count and predicted 5-year AF risk was examined via linear regression, adjusting for age, sex, and wear time. Secondary analyses examined effect modification by sex and obesity (BMI≥30 kg/m2), as well as the relation between self-reported physical activity and predicted 5-year AF risk. RESULTS: We examined 923 electronic Framingham Heart Study participants (age: mean 53, SD 9 years; female: n=563, 61%) who had a median daily step count of 7227 (IQR 5699-8970). Most participants (n=823, 89.2%) had a <2.5% CHARGE-AF risk. Every 1000 steps were associated with a 0.08% lower CHARGE-AF risk (P<.001). A stronger association was observed in men and individuals with obesity. In contrast, self-reported physical activity was not associated with CHARGE-AF risk. CONCLUSIONS: Higher daily step counts were associated with a lower predicted 5-year risk of AF, and this relation was stronger in men and participants with obesity. The utility of a wearable daily step counter for AF risk reduction merits further investigation.

Factors associated with long-term use of digital devices in the electronic Framingham Heart Study.

Long-term use of digital devices is critical for successful clinical or research use, but digital health studies are challenged by a rapid drop-off in participation. A nested e-cohort (eFHS) is embedded in the Framingham Heart Study and uses three system components: a new smartphone app, a digital blood pressure (BP) cuff, and a smartwatch. This study aims to identify factors associated with the use of individual eFHS system components over 1-year. Among 1948 eFHS enrollees, we examine participants who returned surveys within 90 days (n = 1918), and those who chose to use the smartwatch (n = 1243) and BP cuff (n = 1115). For each component, we investigate the same set of candidate predictors for usage and use generalized linear mixed models to select predictors (P < 0.1, P value from Z test statistic), adjusting for age, sex, and time (app use: 3-month period, device use: weekly). A multivariable model with the predictors selected from initial testing is used to identify factors associated with use of components (P < 0.05, P value from Z test statistic) adjusting for age, sex, and time. In multivariable models, older age is associated with higher use of all system components. Female sex and higher education levels are associated with higher completion of app-based surveys whereas higher scores for depressive symptoms, and lower than excellent self-rated health are associated with lower use of the smartwatch over the 12-month follow-up. Our findings show that sociodemographic and health related factors are significantly associated with long-term use of digital devices. Future research is needed to test interventional strategies focusing on these factors to evaluate improvement in long-term engagement.

Relations Between BMI Trajectories and Habitual Physical Activity Measured by a Smartwatch in the Electronic Cohort of the Framingham Heart Study: Cohort Study.

BACKGROUND: The prevalence of obesity is rising. Most previous studies that examined the relations between BMI and physical activity (PA) measured BMI at a single timepoint. The association between BMI trajectories and habitual PA remains unclear. OBJECTIVE: This study assesses the relations between BMI trajectories and habitual step-based PA among participants enrolled in the electronic cohort of the Framingham Heart Study (eFHS). METHODS: We used a semiparametric group-based modeling to identify BMI trajectories from eFHS participants who attended research examinations at the Framingham Research Center over 14 years. Daily steps were recorded from the smartwatch provided at examination 3. We excluded participants with <30 days or <5 hours of smartwatch wear data. We used generalized linear models to examine the association between BMI trajectories and daily step counts. RESULTS: We identified 3 trajectory groups for the 837 eFHS participants (mean age 53 years; 57.8% [484/837] female). Group 1 included 292 participants whose BMI was stable (slope 0.005; P=.75), group 2 included 468 participants whose BMI increased slightly (slope 0.123; P<.001), and group 3 included 77 participants whose BMI increased greatly (slope 0.318; P<.001). The median follow-up period for step count was 516 days. Adjusting for age, sex, wear time, and cohort, participants in groups 2 and 3 took 422 (95% CI -823 to -21) and 1437 (95% CI -2084 to -790) fewer average daily steps, compared with participants in group 1. After adjusting for metabolic and social risk factors, group 2 took 382 (95% CI -773 to 10) and group 3 took 1120 (95% CI -1766 to -475) fewer steps, compared with group 1. CONCLUSIONS: In this community-based eFHS, participants whose BMI trajectory increased greatly over time took significantly fewer steps, compared with participants with stable BMI trajectories. Our findings suggest that greater weight gain may correlate with lower levels of step-based physical activity.