Automated interpretations of single-lead electrocardiograms predict incident atrial fibrillation: The VITAL-AF Trial.

BACKGROUND: Single-lead electrocardiograms (1L ECG) are increasingly used for atrial fibrillation (AF) detection. Automated 1L ECG interpretation may possess prognostic value for future AF among cases where screening does not result in a short-term AF diagnosis. OBJECTIVE: Investigate the association between automated 1L ECG interpretation and incident AF. METHODS: VITAL-AF was a randomized controlled trial investigating the effectiveness of screening for AF using 1L ECGs. For the present study, participants were divided into four groups based on automated classification of 1L ECGs. Patients with prevalent AF were excluded. Associations between groups and incident AF were assessed using Cox proportional hazards models adjusted for risk factors. The start of follow-up was defined as 60 days after the latest 1L ECG (as some individuals had numerous screening 1L ECGs). RESULTS: The study sample included: Never screened (n=16,306), Normal (n=10,914), Other (n=2,675), Possible AF (n=561). Possible AF had the highest AF incidence (5.91 per 100 person-years, 95% Confidence Interval [CI] 4.24-8.23). Possible AF was associated with greater hazard of incident AF compared to Normal (adjusted Hazard Ratio (2.48, 95% CI 1.66-3.71). Other was associated with greater hazard of incident AF when compared to Normal (1.41, 95% CI 1.04-1.90). CONCLUSIONS: In patients undergoing AF screening with 1L ECGs without prevalent AF or AF within 60 days of screening, presumptive positive and indeterminate 1L ECG interpretations were associated with future AF. Abnormal 1L ECGs may identify individuals at higher risk for future AF.

Predicting post-stroke cognitive impairment using electronic health record data.

BACKGROUND: Secondary prevention interventions to reduce post-stroke cognitive impairment (PSCI) can be aided by the early identification of high-risk individuals who would benefit from risk factor modification. AIMS: To develop and evaluate a predictive model to identify patients at increased risk of PSCI over 5 years using data easily accessible from electronic health records. METHODS: Cohort study that included primary care patients from two academic medical centers. Patients were aged 45 years or older, without prior stroke or prevalent cognitive impairment, with primary care visits and an incident ischemic stroke between 2003 and 2016 (development/internal validation cohort) or 2010 and 2022 (external validation cohort). Predictors of PSCI were ascertained from the electronic health record. The outcome was incident dementia/cognitive impairment within 5 years and beginning 3 months following stroke, ascertained using International Classification of Diseases, Ninth/Tenth Revision (ICD-9/10) codes. For model variable selection, we considered potential predictors of PSCI and constructed 400 bootstrap samples with two-thirds of the model derivation sample. We ran 10-fold cross-validated Cox proportional hazards models using a least absolute shrinkage and selection operator (LASSO) penalty. Variables selected in >25% of samples were included. RESULTS: The analysis included 332 incident diagnoses of PSCI in the development cohort (n = 3741), and 161 and 128 incident diagnoses in the internal (n = 1925) and external (n = 2237) validation cohorts, respectively. The C-statistic for predicting PSCI was 0.731 (95% confidence interval (CI): 0.694-0.768) in the internal validation cohort, and 0.724 (95% CI: 0.681-0.766) in the external validation cohort. A risk score based on the beta coefficients of predictors from the development cohort stratified patients into low (0-7 points), intermediate (8-11 points), and high (12-23 points) risk groups. The hazard ratios (HRs) for incident PSCI were significantly different by risk categories in internal (high, HR: 6.2, 95% CI: 4.1-9.3; Intermediate, HR: 2.7, 95% CI: 1.8-4.1) and external (high, HR: 6.1, 95% CI: 3.9-9.6; Intermediate, HR: 2.8, 95% CI: 1.9-4.3) validation cohorts. CONCLUSION: Five-year risk of PSCI can be accurately predicted using routinely collected data. Model output can be used to risk stratify and identify individuals at increased risk for PSCI for preventive efforts. DATA ACCESS STATEMENT: Mass General Brigham data contain protected health information and cannot be shared publicly. The data processing scripts used to perform analyses will be made available to interested researchers upon reasonable request to the corresponding author.

Predicting post-stroke cognitive impairment using electronic health record data.

Importance: Secondary prevention interventions to reduce post-stroke cognitive impairment (PSCI) can be aided by the early identification of high-risk individuals who would benefit from risk factor modification. Objective: To develop and evaluate a predictive model to identify patients at increased risk of PSCI over 5 years using data easily accessible from electronic health records. Design: Cohort study with patients enrolled between 2003-2016 with follow-up through 2022. Setting: Primary care practices affiliated with two academic medical centers. Participants: Individuals 45 years or older, without prior stroke or prevalent cognitive impairment, with primary care visits and an incident ischemic stroke between 2003-2016 (development/internal validation cohort) or 2010-2022 (external validation cohort). Exposures: Predictors of PSCI were ascertained from the electronic health record. Main Outcome: The outcome was incident dementia/cognitive impairment within 5 years and beginning 3 months following stroke, ascertained using ICD-9/10 codes. For model variable selection, we considered potential predictors of PSCI and constructed 400 bootstrap samples with two-thirds of the model derivation sample. We ran 10-fold cross-validated Cox proportional hazards models using a least absolute shrinkage and selection operator (LASSO) penalty. Variables selected in >25% of samples were included. Results: The analysis included 332 incident diagnoses of PSCI in the development cohort (n=3,741), and 161 and 128 incident diagnoses in the internal (n=1,925) and external (n=2,237) validation cohorts. The c-statistic for predicting PSCI was 0.731 (95% CI: 0.694-0.768) in the internal validation cohort, and 0.724 (95% CI: 0.681-0.766) in the external validation cohort. A risk score based on the beta coefficients of predictors from the development cohort stratified patients into low (0-7 points), intermediate (8-11 points), and high (12-35 points) risk groups. The hazard ratios for incident PSCI were significantly different by risk categories in internal (High, HR: 6.2, 95% CI 4.1-9.3; Intermediate, HR 2.7, 95% CI: 1.8-4.1) and external (High, HR: 6.1, 95% CI: 3.9-9.6; Intermediate, HR 2.8, 95% CI: 1.9-4.3) validation cohorts. Conclusions and Relevance: Five-year risk of PSCI can be accurately predicted using routinely collected data. Model output can be used to risk stratify and identify individuals at increased risk for PSCI for preventive efforts.

Reporting of Facet Joint Inflammation in Lumbar Spine MRI Studies in Patients With Low Back Pain.

STUDY DESIGN: Retrospective. OBJECTIVE: We aimed to assess the frequency of facet joint inflammatory features noted in routine radiology reports of lumbar spine magnetic resonance imaging (MRI) studies among patients with chronic low back pain. SUMMARY OF BACKGROUND DATA: Facet joint arthropathy is one of the most common causes of chronic low back pain. It may encompass various inflammatory imaging characteristics, such as facet joint effusion, bone marrow edema, and soft tissue edema. The extent to which radiology reports mention inflammatory features of the lumbar facet joints and the accuracy of these reports have not been investigated. MATERIALS AND METHODS: The authors performed a chart review on 49 subjects with previous facet-related interventions ( i.e . medial branch blocks or intra-articular facet joint injection) and MRI available in the medical record. One senior musculoskeletal radiologist and a musculoskeletal radiology fellow graded the inflammatory features using a published facet joint inflammation grading system [Gold Standard (GS)]. The authors identified the inflammatory markers mentioned in the radiology reports and calculated the sensitivity and positive predictive value of the radiology reports compared with GS readings. RESULTS: Compared with the GS, the sensitivity of radiology reports for facet joint effusion, bone marrow, and soft tissue edema ranged from 6% to 22%, and the positive predictive value ranged from 25% to 100%. L4/5 had the highest number of cases with inflammatory features noted on the reports. CONCLUSION: Inflammatory findings, such as facet joint effusion, bone marrow edema, and soft tissue edema, are not commonly identified in radiology reports. Further investigations are needed to determine the clinical importance of MRI-detected lumbar facet joint inflammatory features as a potential mechanism of nociception and as a predictor of outcomes following injections or other therapies.

Preoperative Predictors of Arthroscopic Partial Meniscectomy Outcomes: The APM Index Score.

BACKGROUND: Preoperative risk factors contributing to poor outcomes after arthroscopic partial meniscectomy (APM) have not yet been consolidated and codified into an index scoring system used to predict APM success. PURPOSE: To create an index score using available preoperative factors to predict the likelihood of favorable postoperative outcomes after APM. STUDY DESIGN: Case-control study; Level of evidence, 3. METHODS: A consecutive cohort of patients undergoing primary APM were enrolled in this study. Patients completed pre- and postoperative patient-reported outcome measure (PROM) questionnaires that included the Knee injury and Osteoarthritis Outcome Score (KOOS), visual analog scale (VAS) for pain, Veterans RAND 12-Item Health Survey (VR-12 Physical and Mental), and Marx Activity Rating Scale (MARS). Multivariable logistic regression models were performed to evaluate independent predictors of KOOS Pain, Symptoms, and Activities of Daily Living scores and achievement of the minimal clinically important difference (MCID) and substantial clinical benefit (SCB). The authors assigned points to each variable proportional to its odds ratio, rounded to the nearest integer, to generate the index score. RESULTS: In total, 468 patients (mean age, 49 years [SD, 10.4 years; range, 19-81 years]) were included in this study. In the univariate analysis, shorter symptom duration, lower Kellgren-Lawrence (KL) grade, lower preoperative KOOS Pain value, and lower VR-12 Physical score were associated with a higher likelihood of clinical improvement at 1 year. In the multivariable model for clinical improvement with MCID, symptom duration (<3 months: OR, 3.00 [95% CI, 1.45-6.19]; 3-6 months: OR, 2.03 [95% CI, 1.10-3.72], compared with >6 months), KL grade (grade 0: OR, 3.54 [95% CI, 1.66-7.54]; grade 1: OR, 3.04 [95% CI, 1.48-6.26]; grade 2: OR, 2.31 [95% CI, 1.02-5.27], compared with grade 3), and preoperative KOOS Pain value (score <45: OR, 3.00 [95% CI, 1.57-5.76]; score of 45-60: OR, 2.80 [95% CI, 1.47-5.35], compared with score >60) were independent significant predictors for clinical improvement. The scoring algorithm demonstrated that a higher total score predicted a higher likelihood of achieving the MCID: 0 = 40%, 1 = 68%, 2 = 80%, 3 = 89%, and 4 = 96%. CONCLUSION: Using this model, the authors developed an index score that, using preoperative factors, can help identify which patients will achieve clinical improvement after APM. Longer symptom duration and higher KL grade were associated with a decreased likelihood of clinical improvement as measured by KOOS Pain at 1 year postoperatively.

Vulnerability and Colorectal screening during the pandemic.

Objective: Disparities in colorectal cancer (CRC) screening prevalence across United States neighborhoods may reflect social inequities that create barriers to accessing and completing preventive health services. Our objective was to identify whether neighborhood social vulnerability was associated with a change in CRC screening prevalence in Boston neighborhoods during the COVID-19 pandemic. Methods: Adults ages 50-74 years due for CRC screening who received primary care at one of 35 primary care practices affiliated with Massachusetts General Hospital or Brigham and Women's Hospital (Boston, MA), 3/1/2020 to 3/1/2022. The Social Vulnerability Index (SVI) is an aggregate measure of neighborhood social factors often used by public health authorities to examine neighborhood susceptibility to many health outcomes. Results: In 2020, 74.9 % of eligible individuals were up to date with CRC screening and this fell to 67.4 % in 2022 (p < 0.001). In 2020, 36.2 % of eligible patients lived in a neighborhood above the 80th percentile of SVI, consistent with high social vulnerability, while the same value was 35.1 % in 2022. There was no association between the change in screening prevalence and SVI: a decrease of 5.5 % screened in neighborhoods with SVI ≤ 80 compared to a decrease of 3.6 % in neighborhoods with SVI > 80 (p = 0.79). Conclusions: The COVID-19 pandemic equalized the prevalence of CRC screening across Boston-area neighborhoods despite pre-existing geographic disparities in screening prevalence and SVI. Strategies to ensure equitable participation in CRC screening to promote health equity should be considered to promote equitable pandemic recovery.

Nonsteroidal anti-inflammatory drug "allergy" labeling is associated with increased postpartum opioid utilization.

BACKGROUND: Current guidelines recommend a stepwise approach to postpartum pain management, beginning with acetaminophen and nonsteroidal anti-inflammatory drugs (NSAIDs), with opioids added only if needed. Report of a prior NSAID-induced adverse drug reaction (ADR) may preclude use of first-line analgesics, despite evidence that many patients with this allergy label may safely tolerate NSAIDs. OBJECTIVE: We assessed the association between reported NSAID ADRs and postpartum opioid utilization. METHODS: We performed a retrospective cohort study of birthing people who delivered within an integrated health system (January 1, 2017, to December 31, 2020). Study outcomes were postpartum inpatient opioid administrations and opioid prescriptions at discharge. Statistical analysis was performed on a propensity score-matched sample, which was generated with the goal of matching to the covariate distributions from individuals with NSAID ADRs. RESULTS: Of 38,927 eligible participants, there were 883 (2.3%) with an NSAID ADR. Among individuals with reported NSAID ADRs, 49.5% received inpatient opioids in the postpartum period, compared to 34.5% of those with no NSAID ADRs (difference = 15.0%, 95% confidence interval 11.4-18.6%). For patients who received postpartum inpatient opioids, those with NSAID ADRs received a higher total cumulative dose between delivery and hospital discharge (median 30.0 vs 22.5 morphine milligram equivalents [MME] for vaginal deliveries; median 104.4 vs 75.0 MME for cesarean deliveries). The overall proportion of patients receiving an opioid prescription at the time of hospital discharge was higher for patients with NSAID ADRs compared to patients with no NSAID ADRs (39.3% vs 27.2%; difference = 12.1%, 95% confidence interval 8.6-15.6%). CONCLUSION: Patients with reported NSAID ADRs had higher postpartum inpatient opioid utilization and more frequently received opioid prescriptions at hospital discharge compared to those without NSAID ADRs, regardless of mode of delivery.

Comprehensive Grading System of Inflammatory Features of the Lumbar Facet Joints on Magnetic Resonance Imaging.

STUDY DESIGN: Retrospective. OBJECTIVE: We aimed to describe a magnetic resonance imaging (MRI)-based grading system of inflammatory features of the lumbar facet joints using an atlas and assess its reliability. SUMMARY OF BACKGROUND DATA: Chronic low back pain is often caused by facet joint arthropathy. Inflammatory features are often evident on MRI. While several grading systems of facet arthropathy have been described, there is scant data on the reliability of these systems, and none focus exclusively on inflammatory features. MATERIALS AND METHODS: We describe a grading system that assesses facet joint effusion, bone marrow edema, and soft tissue edema. Each feature was graded from 0 to 3 (facet edema) or 0 to 2 (bone marrow edema intensity and extent, soft tissue edema intensity and extent). Four spine experts graded MRIs of 50 subjects at the bilateral L3/4, L4/5, and L5/S1 levels. All subjects had symptomatic facet arthropathy and received therapeutic facet joint injections. We assessed the intra-reader and inter-reader reliability of each feature at each joint and summarized across all six joints. RESULTS: The mean age of subjects was 56 years (SD = 17), and 48% were female. The injections occurred at the L3/4 level in 12% of cases, at L4/5 in 88%, and at L5/S1 in 80% of cases. The intra-reader reliability kappa's for each feature ranged from 0.42 to 0.81. In contrast, the inter-reader reliability kappa values for each feature ranged from 0.37 to 0.54. CONCLUSION: MRI inflammatory features of the lumbar facet joints are often noted in patients with low back pain. The proposed grading system is reliable and could serve as a research tool for studies assessing the clinical relevance and prognostic value of these features.

Characteristics and Attitudes of Wearable Device Users and Nonusers in a Large Health Care System.

BACKGROUND: Consumer wearable devices with health and wellness features are increasingly common and may enhance disease detection and management. Yet studies informing relationships between wearable device use, attitudes toward device data, and comprehensive clinical profiles are lacking. METHODS AND RESULTS: WATCH-IT (Wearable Activity Tracking for Comprehensive Healthcare-Integrated Technology) studied adults receiving longitudinal primary or ambulatory cardiovascular care in the Mass General Brigham health care system from January 2010 to July 2021. Participants completed a 20-question electronic survey about perceptions and use of consumer wearable devices, with responses linked to electronic health records. Multivariable logistic regression was used to identify factors associated with device use. Among 214 992 individuals receiving longitudinal primary or cardiovascular care with an active electronic portal, 11 121 responded (5.2%). Most respondents (55.8%) currently used a wearable device, and most nonusers (95.3%) would use a wearable if provided at no cost. Although most users (70.2%) had not shared device data with their doctor previously, most believed it would be very (20.4%) or moderately (34.4%) important to share device-related health information with providers. In multivariable models, older age (odds ratio [OR], 0.80 per 10-year increase [95% CI, 0.77-0.82]), male sex (OR, 0.87 [95% CI, 0.80-0.95]), and heart failure (OR, 0.75 [95% CI, 0.63-0.89]) were associated with lower odds of wearable device use, whereas higher median income (OR, 1.08 per 1-quartile increase [95% CI, 1.04-1.12]) and care in a cardiovascular medicine clinic (OR, 1.17 [95% CI, 1.05-1.30]) were associated with greater odds of device use. CONCLUSIONS: Among patients in primary and cardiovascular medicine clinics, consumer wearable device use is common, and most users perceive value in wearable health data.

Patient decisions regarding cancer gene panel testing: An exploratory study.

This study examined factors associated with the selection of a specific multi-gene panel test by patients in a cancer genetic counseling clinic. We surveyed patients who received pre-test genetic counseling at the Massachusetts General Hospital Center for Cancer Risk Assessment (CCRA) in 2019 and their genetic counselors to assess demographic and clinical characteristics, patient concerns, and session outcome. Ultimately, 228 eligible participants completed the survey, of whom 85.1% consented to genetic testing. Of those who chose testing, 56.2% selected the largest panel type available, a pan-cancer panel that included both actionable and inactionable genes. White patients were more likely than non-white patients to pursue testing. Among testers, number of testing options offered, participant educational attainment, age, and NCCN Guidelines status were associated with patient choice between four panel options. Some patient concerns, including impact of results on future cancer screening and family dynamics, were also linked to test choice. Several other participant characteristics including income, cancer diagnosis, and family structure did not appear to be predictive of testing choice. Our results confirmed the patient preference for large gene panels and identified a limited number of associations between patient characteristics and concerns and testing choice. We noted however that a significant number of participants did not choose the most commonly selected test, and that test choice is difficult to predict based on clinical and demographic factors. Our results also provide further evidence of well-documented disparities in cancer genetic testing. Study limitations do not allow our findings to be generalized to all cancer genetic counseling patients. Further research is needed to examine how and why patients choose between multiple genetic test options in the cancer setting. This study was one of the first to examine patient choice between a full spectrum of multi-gene panel options.

Public Insurance and Single-Guardian Households Are Associated with Diagnostic Delay in Slipped Capital Femoral Epiphysis.

BACKGROUND: Extensive literature documents the adverse sequelae of delayed diagnosis of slipped capital femoral epiphysis (SCFE), including worsening deformity and surgical complications. Less is known about predictors of delayed diagnosis of SCFE, particularly the effects of social determinants of health. The purpose of this study was to evaluate the impact of insurance type, family structure, and neighborhood-level socioeconomic vulnerability on the delay of SCFE diagnosis. METHODS: We reviewed medical records of patients who underwent surgical fixation for stable SCFE at a tertiary pediatric hospital from 2002 to 2021. We abstracted data on demographic characteristics, insurance status, family structure, home address, and symptom duration. We measured diagnostic delay in weeks from the date of symptom onset to diagnosis. We then geocoded patient addresses to determine their Census tract-level U.S. Centers for Disease Control and Prevention (CDC) and Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index (SVI), using U.S. Census and American Community Survey data. We performed 3 separate logistic regression models to examine the effects of (1) insurance status, (2) family structure, and (3) SVI on a delay of ≥12 weeks (reference, <12 weeks). We adjusted for age, sex, weight status, number of siblings, and calendar year. RESULTS: We identified 351 patients with SCFE; 37% (129) had a diagnostic delay of ≥12 weeks. In multivariable logistic regression models, patients with public insurance were more likely to have a delay of ≥12 weeks than patients with private insurance (adjusted odds ratio [OR], 1.83 [95% confidence interval (CI), 1.12 to 2.97]; p = 0.015) and patients from single-guardian households were more likely to have a delay of ≥12 weeks than patients from multiguardian households (adjusted OR, 1.95 [95% CI, 1.11 to 3.45]; p = 0.021). We did not observe a significant increase in the odds of delay among patients in the highest quartile of overall SVI compared with patients from the lower 3 quartiles, in both the U.S. comparison (adjusted OR, 1.43 [95% CI, 0.79 to 2.58]; p = 0.24) and the Massachusetts comparison (adjusted OR, 1.45 [95% CI, 0.79 to 2.66]; p = 0.23). CONCLUSIONS: The delay in diagnosis of SCFE remains a concern, with 37% of patients with SCFE presenting with delay of ≥12 weeks. Public insurance and single-guardian households emerged as independent risk factors for diagnostic delay. Interventions to reduce delay may consider focusing on publicly insured patients and those from single-guardian households. LEVEL OF EVIDENCE: Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Characteristics and Attitudes of Wearable Device Users and Non-Users in a Large Healthcare System.

Introduction: Consumer wearable devices with health and wellness features are increasingly common and may enhance prevention and management of cardiovascular disease. However, the characteristics and attitudes of wearable device users versus non-users are poorly understood. Methods: Wearable Activity Tracking for Comprehensive Healthcare-Integrated Technology (WATCH-IT) was a prospective study of adults aged ≥18 years receiving longitudinal primary or ambulatory cardiovascular care at one of eleven hospitals within the Mass General Brigham multi-institutional healthcare system between January 2010-July 2021. We invited patients, including wearable users and non-users, to participate via an electronic patient portal. Participants were asked to complete a 20-question survey regarding perceptions and use of consumer wearable devices. Responses were linked to electronic health record data. Multivariable logistic regression was used to identify factors associated with device use. Results: Among 280,834 individuals receiving longitudinal primary or cardiovascular care, 65,842 did not have an active electronic portal or opted out of research contact. Of the 214,992 individuals sent a survey link, 11,121 responded (5.2%), comprising the WATCH-IT patient sample. Most respondents (55.8%) reported current use of a wearable device, and most non-users (95.3%) reported they would use a wearable device if provided at no cost. Although most users (70.2%) had not shared device data with their doctor previously, the majority believed it would be very (20.4%) or moderately (34.4%) important to share device-related health information with providers. In multivariable models, older age (odds ratio [OR] 0.80 per 10-year increase, 95% CI 0.77-0.82), male sex (0.87, 95% CI 0.80-0.95), and heart failure (0.75, 95% CI 0.63-0.89) were associated with lower odds of wearable device use, whereas higher median zip code income (1.08 per 1-quartile increase, 95% CI 1.04-1.12) and care in a cardiovascular medicine clinic (1.17, 95% CI 1.05-1.30) were associated with greater odds of device use. Nearly all respondents (98%) stated they would share device data with researchers studying health outcomes. Conclusions: Within an electronically assembled cohort of patients in primary and cardiovascular medicine clinics with linkage to detailed health records, wearable device use is common. Most users perceive value in wearable data. Our platform may enable future study of the relationships between wearable technology and resource utilization, clinical outcomes, and health disparities.

Effect of clinic-based single-lead electrocardiogram rhythm assessment on oral anticoagulation prescriptions in patients with previously diagnosed atrial fibrillation.

Background: Despite benefits of oral anticoagulation (OAC), many individuals with diagnosed atrial fibrillation (AF) do not receive OAC. Objective: The purpose of this study was to assess whether cardiac rhythm assessment for AF impacted use of OAC in patients with previously diagnosed AF. Methods: VITAL-AF was a cluster randomized controlled trial conducted in 16 primary care practices assessing the efficacy of AF rhythm assessment with single-lead electrocardiogram in routine care. Patients 65 years and older were offered rhythm assessment at visits. In this secondary analysis, we evaluated rhythm assessment uptake and compared initiation and discontinuation of OAC in patients with previously diagnosed AF from intervention and control arms over 1 year. Results: The study included 4593 patients with previously diagnosed AF (2250 intervention; 2343 control). In the intervention arm, 2022 (89.9%) completed rhythm assessment (median 2 visits with rhythm assessment) and 40.1% had ≥1 "Possible AF" result. Initiation of OAC was similar in the intervention (17.7%) and control (19.1%) arms but was influenced by the rhythm assessment result: higher with a "Possible AF" (26.1%; adjusted odds ratio [aOR] 1.62; 95% confidence interval [CI] 1.04-2.51), and lower with a "Normal" result (9.9%; aOR 0.45; 95% CI 0.29-0.71) compared to control. OAC discontinuation was similar in the intervention (6.3%) and control (7.2%) arms, with lower discontinuation with a "Possible AF" result (3.8%; aOR 0.51; 95% CI 0.32-0.81). Conclusions: Including patients with previously diagnosed AF in a point-of-care rhythm assessment strategy did not increase overall OAC use compared to the control arm. However, the rhythm assessment result influenced both initiation and discontinuation of OAC.

A Pilot Randomized Trial of an Advance Care Planning Video Decision Support Tool for Adolescents and Young Adults With Advanced Cancer.

BACKGROUND: Adolescents and young adults (AYAs) with advanced cancer often receive intensive end-of-life care, yet it is unclear if this is goal-concordant. Advance care planning (ACP) video tools may promote identification and communication of AYA preferences. PATIENTS AND METHODS: We conducted a dual-site, 1:1 pilot randomized controlled trial of a novel video-based ACP tool in 50 dyads of AYA patients aged 18 to 39 years with advanced cancer and their caregivers. ACP readiness and knowledge, preferences for future care, and decisional conflict were obtained pre, post, and 3 months after the intervention and compared between groups. RESULTS: Of the 50 AYA/caregiver dyads enrolled, 25 (50%) were randomized to the intervention. Participants primarily identified as female, white, and non-Hispanic. Most AYAs (76%) and caregivers (86%) identified their overall goal as life-prolonging preintervention; less identified this goal postintervention (42% AYAs; 52% caregivers). There was no significant difference in change in proportion of AYAs or caregivers choosing life-prolonging care, CPR, or ventilation between arms postintervention or at 3 months. The change in participant scores for ACP knowledge (AYAs and caregivers) and ACP readiness (AYAs) from preintervention to postintervention was greater in the video arm compared with the control arm; the difference in caregivers' scores for decisional conflict from preintervention to postintervention in the video arm was statistically significant (15 vs 7; P=.005). Feedback from the video participants was overwhelmingly positive; of the 45 intervention participants who provided video feedback, 43 (96%) found the video helpful, 40 (89%) were comfortable viewing the video, and 42 (93%) indicated they would recommend the video to other patients facing similar decisions. CONCLUSIONS: Most AYAs with advanced cancer and their caregivers preferred life-prolonging care in advanced illness, with fewer preferring this type of care postintervention. A brief video-based ACP tool was well-liked by participants and improved caregiver decisional certainty. Videos may be a useful tool to inform AYAs and caregivers about end-of-life care options and promote ACP discussions.

Accuracy and variability of cardiologist interpretation of single lead electrocardiograms for atrial fibrillation: The VITAL-AF trial.

BACKGROUND: Screening for atrial fibrillation (AF) using consumer-based devices capable of producing a single lead electrocardiogram (1L ECG) is increasing. There are limited data on the accuracy of physician interpretation of these tracings. The goal of this study is to assess the sensitivity, specificity, confidence, and variability of cardiologist interpretation of point-of-care 1L ECGs. METHODS: Fifteen cardiologists reviewed point-of-care handheld 1L ECGs collected from patients aged 65 years or older enrolled in the VITAL-AF clinical trial [NCT035115057] who underwent cardiac rhythm assessments with a 1L ECG using an AliveCor KardiaMobile device. Random sampling of 1L ECGs for cardiologist review was stratified by the AliveCor algorithm interpretation. A 12L ECG performed on the same day for clinical purposes was used as the gold standard. Cardiologists each reviewed a common sample of 200 1L ECG tracings and completed a survey associated with each tracing. Cardiologists were blinded to both the AliveCor algorithm and same day 12L ECG interpretation. For each tracing, study cardiologists were asked to assess the rhythm (sinus rhythm, AF, unclassifiable), report their assessment of the quality of the tracing, and rate their confidence in rhythm interpretation. The outcomes included the sensitivity, specificity, variability, and confidence in physician interpretation. Variables associated with each measure were identified using multivariable regression. RESULTS: The average sensitivity for AF was 77.4% (range 50%-90.6%, standard deviation [SD]=11.4%) and the average specificity was 73.0% (range 41.3%-94.6%, SD = 15.4%). The mean variability was 30.8% (range 0%-76.2%, SD = 23.2%). The average reviewer confidence of 1L ECG rhythm assessment was 3.6 out of 5 (range 2.5-4.2, SD = 0.6). Patient and tracing factors associated with sensitivity, specificity, variability, and confidence were identified and included age, body mass index, and presence of artifact. CONCLUSION: Cardiologist interpretation of point-of-care handheld 1L ECGs has modest diagnostic sensitivity and specificity with substantial variability for AF classification despite high confidence. Variability in cardiologist interpretation of 1L ECGs highlights the importance of confirmatory testing for diagnosing AF.

Radiographic Changes Five Years After Treatment of Meniscal Tear and Osteoarthritic Changes.

OBJECTIVE: Meniscal tear in persons aged ≥45 years is typically managed with physical therapy (PT), and arthroscopic partial meniscectomy (APM) is offered to those who do not respond. Prior studies suggest APM may be associated with greater progression of radiographic changes. METHODS: We assessed changes between baseline and 60 months in the Kellgren-Lawrence (KL) grade and OARSI radiographic score (including subscores for joint space narrowing and osteophytes) in subjects aged 45-85 years enrolled into a seven-center randomized trial comparing outcomes of APM with PT for meniscal tear, osteoarthritis changes, and knee pain. The primary analysis classified subjects according to treatment received. To balance APM and PT groups, we developed a propensity score and used inverse probability weighting (IPW). We imputed a 60-month change in the OARSI score for subjects who underwent total knee replacement (TKR). In a sensitivity analysis, we classified subjects by randomization group. RESULTS: We analyzed data from 142 subjects (100 APM, 42 PT). The mean ± SD weighted baseline OARSI radiographic score was 3.8 ± 3.5 in the APM group and 4.0 ± 4.9 in the PT group. OARSI scores increased by a mean of 4.1 (95% confidence interval [95% CI] 3.5-4.7) in the APM group and 2.4 (95% CI 1.7-3.2) in the PT group (P < 0.001) due to changes in the osteophyte component. We did not observe statistically significant differences in the KL grade. Sensitivity analyses yielded similar findings to the primary analysis. CONCLUSION: Subjects treated with APM had greater progression in the OARSI score because of osteophyte progression but not in the KL grade. The clinical implications of these findings require investigation.

Screening for undiagnosed atrial fibrillation using a single-lead electrocardiogram at primary care visits: patient uptake and practitioner perspectives from the VITAL-AF trial.

BACKGROUND: Screening for atrial fibrillation (AF) is appealing because AF is common, when undiagnosed may increase stroke risk, and stroke is preventable with anticoagulants. This study assessed patient and primary care practitioner (PCP) acceptability of screening for AF using a 30-s single-lead electrocardiogram (SL-ECG) during outpatient visits. METHODS: Secondary analyses of a cluster randomized trial. All patients ≥ 65 years old without prevalent AF seen during a 1-year period and their PCPs. Screening using a SL-ECG was performed by medical assistants during check-in at 8 intervention sites among verbally consenting patients. PCPs were notified of "possible AF" results; management was left to their discretion. Control practices continued with usual care. Following the trial, PCPs were surveyed about AF screening. Outcomes included screening uptake and results, and PCP preferences for screening. RESULTS: Fifteen thousand three hundred ninety three patients were seen in intervention practices (mean age 73.9 years old, 59.7% female). Screening occurred at 78% of 38,502 individual encounters, and 91% of patients completed ≥ 1 screening. The positive predictive value of a "Possible AF" result (4.7% of SL-ECG tracings) at an encounter prior to a new AF diagnosis was 9.5%. Same-day 12-lead ECGs were slightly more frequent among intervention (7.0%) than control (6.2%) encounters (p = 0.07). Among the 208 PCPs completing a survey (73.6%; 78.9% intervention, 67.7% control), most favored screening for AF (87.2% vs. 83.6%, respectively), though SL-ECG screening was favored by intervention PCPs (86%) while control PCPs favored pulse palpation (65%). Both groups were less certain if AF screening should be done outside of office visits with patch monitors (47% unsure) or consumer devices (54% unsure). CONCLUSIONS: Though the benefits and harms of screening for AF remain uncertain, most older patients underwent screening and PCPs were able to manage SL-ECG results, supporting the feasibility of routine primary care screening. PCPs exposed to a SL-ECG device preferred it over pulse palpation. PCPs were largely uncertain about AF screening done outside of practice visits. TRIAL REGISTRATION: ClinicalTrials.gov NCT03515057. Registered May 3, 2018.

Health Care Utilization among Homeless-Experienced Adults Who Were Seen by a Mobile Addiction Health Clinic in Boston, Massachusetts: A Quasi-Experimental Study.

Background: Mobile health clinics improve access to care for marginalized individuals who are disengaged from the healthcare system. This study evaluated the association between a mobile addiction health clinic and health care utilization among people experiencing homelessness. Methods: Using Medicaid claims data, we evaluated adults who were seen by a mobile addiction health clinic in Boston, Massachusetts from 1/16/18-1/15/19 relative to a propensity score matched control cohort. We evaluated both cohorts from four years before to one year after the index visit date with the mobile clinic. The primary outcome was the number of outpatient visits; secondary outcomes were the number of hospitalizations and emergency department (ED) visits. We used Poisson regression to compare changes in outcomes from before to after the index date in a quasi-experimental design. Results: 138 adults were seen by the mobile clinic during the observation period; 29.7% were female, 16.7% were Black, 8.0% Hispanic, 68.1% White, and the mean age was 40.4 years. The mean number of mobile clinic encounters was 3.1. The yearly mean number of outpatient visits increased from 11.5 to 12.1 (p = 0.43; pdiff-in-diff = 0.15), the number of hospitalizations increased from 2.2 to 3.0 (p = 0.04; pdiff-in-diff = 0.87), and the number of ED visits increased from 5.4 to 6.5 (p = 0.04; pdiff-in-diff = 0.40). Conclusions: The mobile addiction health clinic was not associated with statistically significant changes in health care utilization in the first year. Further research in larger samples using a broader set of outcomes is needed to quantify the benefits of this innovative care delivery model.

Tobacco-Related Disease, Health Beliefs, and Post-hospital Tobacco Abstinence.

INTRODUCTION: Most hospitalized patients who smoke resume after discharge. Associations of tobacco-related disease and health beliefs with post-hospitalization abstinence were examined. METHODS: This was a cohort study using data from a 2018-2020 multicenter trial of hospitalized adults who smoked and wanted to quit. Tobacco-related disease was defined using primary discharge diagnosis codes. Baseline health beliefs included (1) smoking caused hospitalization, (2) quitting speeds recovery, and (3) quitting prevents future illness. Outcomes included self-reported 7-day point prevalence abstinence 1, 3, and 6 months after discharge. Separate logistic regression models for each of the three health beliefs were constructed. Models stratified by tobacco-related disease explored effect modification. Analysis was performed in 2022-2023. RESULTS: Of 1,406 participants (mean age 52 years, 56% females, 77% non-Hispanic White), 31% had tobacco-related disease, 42% believed that smoking caused hospitalization, 68% believed that quitting speeds recovery, and 82% believed that quitting prevents future illness. Tobacco-related disease was associated with higher 1-month point prevalence abstinence in each health belief model (AOR=1.55, 95% CI=1.15, 2.10; 1.53, 95% CI=1.14, 2.05; and 1.64, 95% CI=1.24, 2.19, respectively) and higher 6-month point prevalence abstinence in models including health beliefs 2 and 3. Quitting speeds recovery was the only belief associated with higher 1-month point prevalence abstinence (AOR=1.39, 95% CI=1.05, 1.85). Among patients with tobacco-related disease, the belief that quitting prevents future illness was associated with higher 1-month point prevalence abstinence (AOR=2.00, 95% CI=1.06, 3.78). CONCLUSIONS: Tobacco-related disease predicts abstinence 1 and 6 months after hospitalization independent of health beliefs. Beliefs that quitting speeds recovery and prevents future illness may serve as targets for smoking-cessation interventions.