Association of large core middle cerebral artery stroke and hemorrhagic transformation with hospitalization outcomes.

Historically, investigators have not differentiated between patients with and without hemorrhagic transformation (HT) in large core ischemic stroke at risk for life-threatening mass effect (LTME) from cerebral edema. Our objective was to determine whether LTME occurs faster in those with HT compared to those without. We conducted a two-center retrospective study of patients with ≥ 1/2 MCA territory infarct between 2006 and 2021. We tested the association of time-to-LTME and HT subtype (parenchymal, petechial) using Cox regression, controlling for age, mean arterial pressure, glucose, tissue plasminogen activator, mechanical thrombectomy, National Institute of Health Stroke Scale, antiplatelets, anticoagulation, temperature, and stroke side. Secondary and exploratory outcomes included mass effect-related death, all-cause death, disposition, and decompressive hemicraniectomy. Of 840 patients, 358 (42.6%) had no HT, 403 (48.0%) patients had petechial HT, and 79 (9.4%) patients had parenchymal HT. LTME occurred in 317 (37.7%) and 100 (11.9%) had mass effect-related deaths. Parenchymal (HR 8.24, 95% CI 5.46-12.42, p < 0.01) and petechial HT (HR 2.47, 95% CI 1.92-3.17, p < 0.01) were significantly associated with time-to-LTME and mass effect-related death. Understanding different risk factors and sequelae of mass effect with and without HT is critical for informed clinical decisions.

Bidirectional Association Between Atrial Fibrillation and Myocardial Infarction, and Relation to Mortality in the Framingham Heart Study.

BACKGROUND: Individuals with both atrial fibrillation (AF) and myocardial infarction (MI) have higher mortality compared with individuals with only 1 condition. Whether mortality differs according to the temporal order of AF and MI is unclear. METHODS AND RESULTS: We included participants from the FHS (Framingham Heart Study) from 1960 and onwards. We assessed the hazard ratio (HR) of new-onset AF and MI, and mortality according to MI and AF status (prevalent and interim) using multivariable-adjusted Cox proportional hazards models. Interim diseases were modeled as time-varying variables. For the analysis of new-onset AF, 10 923 participants (55% women; mean±SD age, 54±8 years) were included. For new-onset MI, 10 804 participants (55% women; mean±SD age, 54±8 years) were included. Compared with no MI, the hazard of new-onset AF was higher in participants with prevalent (HR, 1.60 [95% CI, 1.32-1.94]) and interim MI (HR, 3.96 [95% CI, 3.18-4.91]). Both ST-segment-elevation MI and non-ST-segment-elevation MI were associated with new-onset AF. Interim AF, not prevalent AF, was associated with higher hazard rate of new-onset MI (HR, 2.21 [95% CI, 1.67-2.92]). Interim AF was associated with both ST-segment-elevation MI and non-ST-segment-elevation MI. Mortality was significantly greater among participants with AF and MI compared with participants with 1 of the 2, regardless of temporal order. CONCLUSIONS: We report a bidirectional association between AF and MI, which was observed for both non-ST-segment-elevation MI and ST-segment-elevation MI. Participants with both AF and MI had considerably higher mortality compared with participants with only 1 of the 2 conditions, regardless of order.

Temporal trends in lifetime risks of atrial fibrillation and its complications between 2000 and 2022: Danish, nationwide, population based cohort study.

OBJECTIVES: To examine how the lifetime risks of atrial fibrillation and of complications after atrial fibrillation changed over time. DESIGN: Danish, nationwide, population based cohort study. SETTING: Population of Denmark from 1 January 2000 to 31 December 2022. PARTICIPANTS: 3.5 million individuals (51.7% women and 48.3% men) who did not have atrial fibrillation at 45 years of age or older were followed up until incident atrial fibrillation, migration, death, or end of follow-up, whichever came first. All 362 721 individuals with incident atrial fibrillation (46.4% women and 53.6% men), but with no prevalent complication, were further followed up until incident heart failure, stroke, or myocardial infarction. MAIN OUTCOME MEASURES: Lifetime risk of atrial fibrillation and lifetime risks of complications after atrial fibrillation over two prespecified periods (2000-10 v 2011-22). RESULTS: The lifetime risk of atrial fibrillation increased from 24.2% in 2000-10 to 30.9% in 2011-22 (difference 6.7% (95% confidence interval 6.5% to 6.8%)). After atrial fibrillation, the most frequent complication was heart failure with a lifetime risk of 42.9% in 2000-10 and 42.1% in 2011-22 (-0.8% (-3.8% to 2.2%)). Individuals with atrial fibrillation lost 14.4 years with no heart failure. The lifetime risks of stroke and of myocardial infarction after atrial fibrillation decreased slightly between the two periods, from 22.4% to 19.9% for stroke (-2.5% (-4.2% to -0.7%)) and from 13.7% to 9.8% for myocardial infarction (-3.9% (-5.3% to -2.4%). No evidence was reported of a differential decrease between men and women. CONCLUSION: Lifetime risk of atrial fibrillation increased over two decades of follow-up. In individuals with atrial fibrillation, about two in five developed heart failure and one in five had a stroke over their remaining lifetime after atrial fibrillation diagnosis, with no or only small improvement over time. Stroke risks and heart failure prevention strategies are needed for people with atrial fibrillation.

Birth cohort effects on diagnosed atrial fibrillation incidence: nationwide cohort study from 1980 to 2018.

BACKGROUND: The incidence of atrial fibrillation (AF) shows substantial temporal trends, but the contribution of birth cohort effects is unknown. These effects refer to the relationship between birth year and the likelihood of developing AF. We aimed to assess trends in cumulative incidence of diagnosed AF across birth cohorts and to disentangle the effects of age, birth cohort and calendar period by using age-period-cohort analyses. METHODS: In a Danish nationwide population-based cohort study, 4.7 million individuals were selected at a given index age (45, 55, 65 and 75 years) free of AF and followed up for diagnosed AF. For each index age, we assessed trends in 10-year cumulative incidence of AF across six 5-year birth cohorts. An age-period-cohort model was estimated using Poisson regression with constrained spline functions collapsing data into 1-year intervals across ages and calendar years. RESULTS: Cumulative incidence of AF diagnosis increased across birth cohorts for all index ages (ptrend<0.001). Compared with the first birth cohort, the diagnosed AF incidence rate ratio in the last birth cohort was 3.0 (95% CI 2.9 to 3.2) for index age 45 years, 2.9 (2.8 to 3.0) for 55 years, 2.8 (2.7 to 2.8) for 65 years and 2.7 (2.6 to 2.7) for 75 years. Age-period-cohort analyses showed substantial birth cohort effects independent of age, with no clear period effect. Compared with individuals born in 1930, the diagnosed AF incidence rate was 0.125 smaller among individuals born in 1885 and was four times larger among individuals born in 1975. CONCLUSION: Substantial birth cohort effects, independent of age and calendar period, influence trends in diagnosed AF incidence.

Incidence and prognostic significance of newly-diagnosed atrial fibrillation among older U.S. veterans hospitalized with COVID-19.

Most prior studies on the prognostic significance of newly-diagnosed atrial fibrillation (AF) in COVID-19 did not differentiate newly-diagnosed AF from pre-existing AF. To determine the association between newly-diagnosed AF and in-hospital and 30-day mortality among regular users of Veterans Health Administration using data linked to Medicare. We identified Veterans aged ≥ 65 years who were hospitalized for ≥ 24 h with COVID-19 from 06/01/2020 to 1/31/2022 and had ≥ 2 primary care visits within 24 months prior to the index hospitalization. We performed multivariable logistic regression analyses to estimate adjusted risks, risk differences (RD), and odds ratios (OR) for the association between newly-diagnosed AF and the mortality outcomes adjusting for patient demographics, baseline comorbidities, and presence of acute organ dysfunction on admission. Of 23,299 patients in the study cohort, 5.3% had newly-diagnosed AF, and 29.2% had pre-existing AF. In newly-diagnosed AF adjusted in-hospital and 30-day mortality were 16.5% and 22.7%, respectively. Newly-diagnosed AF was associated with increased mortality compared to pre-existing AF (in-hospital: OR 2.02, 95% confidence interval [CI] 1.72-2.37; RD 7.58%, 95% CI 5.54-9.62) (30-day: OR 1.86; 95% CI 1.60-2.16; RD 9.04%, 95% CI 6.61-11.5) or no AF (in-hospital: OR 2.24, 95% CI 1.93-2.60; RD 8.40%, 95% CI 6.44-10.4) (30-day: 2.07, 95% CI 1.80-2.37; RD 10.2%, 95% CI 7.89-12.6). There was a smaller association between pre-existing AF and the mortality outcomes. Newly-diagnosed AF is an important prognostic marker for patients hospitalized with COVID-19. Whether prevention or treatment of AF improves clinical outcomes in these patients remains unknown.

Comparative Effectiveness of PET and SPECT MPI for Predicting Cardiovascular Events After Kidney Transplant.

BACKGROUND: Advanced chronic kidney disease is associated with high cardiovascular risk, even after kidney transplant. Pretransplant cardiac testing may identify patients who require additional assessment before transplant or would benefit from risk optimization. The objective of the current study was to determine the relative prognostic utility of pretransplant positron emission tomography (PET) and single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) for posttransplant major adverse cardiovascular events (MACEs). METHODS: We retrospectively followed patients who underwent MPI before kidney transplant for the occurrence of MACE after transplant including myocardial infarction, stroke, heart failure, and cardiac death. An abnormal MPI result was defined as a total perfusion deficit >5% of the myocardium. To determine associations of MPI results with MACE, we utilized Cox hazard regression with propensity weighting for PET versus SPECT with model factors, including demographics and cardiovascular risk factors. RESULTS: A total of 393 patients underwent MPI (208 PET and 185 SPECT) and were followed for a median of 5.9 years post-transplant. Most were male (58%), median age was 58 years, and there was a high burden of hypertension (88%) and diabetes (33%). A minority had abnormal MPI (n=58, 15%). In propensity-weighted hazard regression, abnormal PET result was associated with posttransplant MACE (hazard ratio, 3.02 [95% CI, 1.78-5.11]; P<0.001), while there was insufficient evidence of an association of abnormal SPECT result with MACE (1.39 [95% CI, 0.72-2.66]; P=0.33). The explained relative risk of the PET result was higher than the SPECT result (R2 0.086 versus 0.007). Normal PET was associated with the lowest risk of MACE (2.2%/year versus 3.6%/year for normal SPECT; P<0.001). CONCLUSIONS: Kidney transplant recipients are at high cardiovascular risk, despite a minority having obstructive coronary artery disease on MPI. PET MPI findings predict posttransplant MACE. Normal PET may better discriminate lower risk patients compared with normal SPECT, which should be confirmed in a larger prospective study.

Relative likelihood ratios for neutral comparisons of statistical tests in simulation studies.

When comparing the performance of two or more competing tests, simulation studies commonly focus on statistical power. However, if the size of the tests being compared are either different from one another or from the nominal size, comparing tests based on power alone may be misleading. By analogy with diagnostic accuracy studies, we introduce relative positive and negative likelihood ratios to factor in both power and size in the comparison of multiple tests. We derive sample size formulas for a comparative simulation study. As an example, we compared the performance of six statistical tests for small-study effects in meta-analyses of randomized controlled trials: Begg's rank correlation, Egger's regression, Schwarzer's method for sparse data, the trim-and-fill method, the arcsine-Thompson test, and Lin and Chu's combined test. We illustrate that comparing power alone, or power adjusted or penalized for size, can be misleading, and how the proposed likelihood ratio approach enables accurate comparison of the trade-off between power and size between competing tests.

Dynamic trajectories of life-threatening mass effect in patients with large middle cerebral artery stroke.

Background: Life-threatening, space-occupying mass effect due to cerebral edema and/or hemorrhagic transformation is an early complication of patients with middle cerebral artery (MCA) stroke. Little is known about longitudinal trajectories of laboratory and vital signs leading up to radiographic and clinical deterioration related to this mass effect. Methods: We curated a granular retrospective dataset of 635 patients with large middle cerebral artery (MCA) stroke totaling 108,547 data points for repeated measurements of 10 covariates, and 40 time-independent covariates. We assessed longitudinal trajectories of the 10 longitudinal variables during the 72 hours preceding three outcomes representative of life-threatening mass effect: midline shift (MLS) ≥5mm, pineal gland shift (PGS) >4mm, and decompressive hemicraniectomy (DHC). We used a "backward looking" trajectory approach. Patients were aligned according to the time of outcome occurrence and the trajectory of each variable was assessed prior to that outcome by accounting for both cases and non-cases. Results: Of 635 patients, 49% were female, and mean age was 69 years. Thirty five percent of patients had MLS ≥ 5mm, 24.1% had PGS >4mm, and DHC occurred in 10.7%. For the three outcomes of interest, backward-looking trajectories showed mild increases in white blood cell count (10 up to 11 K/UL within 72 hours), temperature (up to half a degree within 24 hours), and sodium (1-3 mEq/L within 24 hours) leading up to outcomes. We also observed a decrease in heart rate (75 - 65 beats per minute) 24 hours prior to DHC. Conclusions: Univariable longitudinal profiling showed that temperature, white blood cell count, and sodium increase prior to radiographic and clinical indicators of space-occupying mass effect. These findings will inform development of multivariable dynamic risk models to aid prediction of life-threatening space-occupying mass effect.

From a decentralized clinical trial to a decentralized and clinical-trial-in-a-box platform: Towards patient-centric and equitable trials.

Background/Objective: Despite the intuitive attractiveness of bringing research to participants rather than making them come to central study sites, widespread decentralized enrollment has not been common in clinical trials. Methods: The need for clinical research in the context of the COVID-19 pandemic, along with innovations in technology, led us to use a decentralized trial approach in our Phase 2 COVID-19 trial. We used real-time acquisition and transmission of health-related data using home-based monitoring devices and mobile applications to assess outcomes. This approach not only avoids spreading COVID-19 but it also can support inclusion of participants in more diverse socioeconomic circumstances and in rural settings. Results: Our team developed and deployed a decentralized trial platform to support patient engagement and adverse event reporting. Clinicians, engineers, and informaticians on our research team developed a Clinical-Trial-in-a-Box tool to optimally collect and analyze data from multiple decentralized platforms. Conclusion: Applying the decentralized model in Long COVID, using digital health technology and personal devices integrated with our telehealth platform, we share the lessons learned from our work, along with challenges and future possibilities.

MSGene: Derivation and validation of a multistate model for lifetime risk of coronary artery disease using genetic risk and the electronic health record.

Currently, coronary artery disease (CAD) is the leading cause of death among adults worldwide. Accurate risk stratification can support optimal lifetime prevention. We designed a novel and general multistate model (MSGene) to estimate age-specific transitions across 10 cardiometabolic states, dependent on clinical covariates and a CAD polygenic risk score. MSGene supports decision making about CAD prevention related to any of these states. We analyzed longitudinal data from 480,638 UK Biobank participants and compared predicted lifetime risk with the 30-year Framingham risk score. MSGene improved discrimination (C-index 0.71 vs 0.66), age of high-risk detection (C-index 0.73 vs 0.52), and overall prediction (RMSE 1.1% vs 10.9%), with external validation. We also used MSGene to refine estimates of lifetime absolute risk reduction from statin initiation. Our findings underscore the potential public health value of our novel multistate model for accurate lifetime CAD risk estimation using clinical factors and increasingly available genetics.

Electrical energy by electrode placement for cardioversion of atrial fibrillation: a systematic review and meta-analysis.

OBJECTIVE: Electrode patch position may not be critical for success when cardioverting atrial fibrillation (AF), but the relevance of applied electrical energy is unclarified. Our objective was to perform a meta-analysis of randomised trials to examine the dose-response relation between energy level and cardioversion success by electrode position in elective cardioversion. METHODS: We searched PubMed, Embase, The Cochrane Library, Google Scholar and Scopus Citations. Inclusion criteria were randomised controlled trials using biphasic shock waves and self-adhesive patches, and publication date from 2000 to 2023. We used random-effects dose-response models to meta-analyse the relation between energy level and cardioversion success by anterolateral and anteroposterior position. Random-effects models estimated pooled risk ratios (RR) for cardioversion success after the first and the final shocks between the two electrode positions. RESULTS: We included five randomised controlled trials (N=1078). After the first low-energy shock, the electrode position was not significantly associated with the likelihood of successful cardioversion (pooled RR anterolateral vs anteroposterior placement 1.28, 95% CI 0.93 to 1.76, with considerable heterogeneity). After a high-energy final shock, there was no evidence of an association between the electrode position and the cumulative chance of cardioversion success (pooled RR anterolateral vs anteroposterior 1.05, 95% CI 0.97 to 1.14). Regardless of electrode position, cardioversion success was significantly less likely with shock energy levels < 200J compared with 200J. CONCLUSION: Evidence from contemporary randomised trials suggests that higher level of electrical energy is associated with higher conversion rate when cardioverting AF with a biphasic shockwave. Positioning of electrodes can be based on convenience.

The use of N-of-1 trials to generate real-world evidence for optimal treatment of individuals and populations.

Introduction: Ideally, real-world data (RWD) collected to generate real-world evidence (RWE) should lead to impact on the care and health of real-world patients. Deriving from care in which clinicians and patients try various treatments to inform therapeutic decisions, N-of-1 trials bring scientific methods to real-world practice. Methods: These single-patient crossover trials generate RWD and RWE by giving individual patients various treatments in a double-blinded way in sequential periods to determine the most effective treatment for a given patient. Results: This approach is most often used for patients with chronic, relatively stable conditions that provide the opportunity to make comparisons over multiple treatment periods, termed Type 1 N-of-1 trials. These are most helpful when there is heterogeneity of treatment effects among patients and no a priori best option. N-of-1 trials also can be done for patients with rare diseases, potentially testing only one treatment, to generate evidence for personalized treatment decisions, designated as Type 2 N-of-1 trials. With both types, in addition to informing individual's treatments, when uniform protocols are used for multiple patients with the same condition, the data collected in the individual N-of-1 trials can be aggregated to provide RWD/RWE to inform more general use of the treatments. Thereby, N-of-1 trials can provide RWE for the care of individuals and for populations. Conclusions: To fulfill this potential, we believe N-of-1 trials should be built into our current healthcare ecosystem. To this end, we are building the needed infrastructure and engaging the stakeholders who should receive value from this approach.

Extending the vision of adaptive point-of-care platform trials to improve targeted use of drug therapy regimens: An agile approach in the learning healthcare system toolkit.

OBJECTIVES: Improving the targeted use of drug regimens requires robust real-world evidence (RWE) to address the uncertainties that remain regarding their real-world performance following market entry. However, challenges in the current state of RWE production limit its impact on clinical decisions, as well as its operational scalability and sustainability. We propose an adaptive point-of-care (APoC) platform trial as an approach to RWE production that improves both clinical and operational efficiencies. METHODS AND FINDINGS: We explored design innovations, operational challenges, and infrastructure needs within a multi-stakeholder consortium to evaluate the potential of an APoC platform trial for studying chronic disease treatment regimens using rheumatoid arthritis as a case study. The concept integrates elements from adaptive clinical trials (dynamic treatment regimen strategies) and point-of-care trials (research embedded into routine clinical care) under a perpetual platform infrastructure. The necessary components to implement an APoC platform trial within outpatient settings exist, and present an opportunity for a cross-disciplinary, multi-stakeholder approach. Effective engagement of key stakeholders involved in and impacted by the platform is critical to success. Our collaborative design process identified three high-impact stakeholder-engagement areas: (1) focus on research question(s), (2) design and implementation planning such that it is feasible and fit-for-purpose, and (3) measurement, or meaningful metrics for both clinical (patient outcomes) and system (operational efficiencies) impact. CONCLUSIONS: An APoC platform trial for rheumatoid arthritis integrating innovative design elements in a scalable infrastructure has the potential to reduce important uncertainties about the real-world performance of biomedical innovations and improve clinical decisions.

Rapid Whole-Genomic Sequencing and a Targeted Neonatal Gene Panel in Infants With a Suspected Genetic Disorder.

Importance: Genomic testing in infancy guides medical decisions and can improve health outcomes. However, it is unclear whether genomic sequencing or a targeted neonatal gene-sequencing test provides comparable molecular diagnostic yields and times to return of results. Objective: To compare outcomes of genomic sequencing with those of a targeted neonatal gene-sequencing test. Design, Setting, and Participants: The Genomic Medicine for Ill Neonates and Infants (GEMINI) study was a prospective, comparative, multicenter study of 400 hospitalized infants younger than 1 year of age (proband) and their parents, when available, suspected of having a genetic disorder. The study was conducted at 6 US hospitals from June 2019 to November 2021. Exposure: Enrolled participants underwent simultaneous testing with genomic sequencing and a targeted neonatal gene-sequencing test. Each laboratory performed an independent interpretation of variants guided by knowledge of the patient's phenotype and returned results to the clinical care team. Change in clinical management, therapies offered, and redirection of care was provided to families based on genetic findings from either platform. Main Outcomes and Measures: Primary end points were molecular diagnostic yield (participants with ≥1 pathogenic variant or variant of unknown significance), time to return of results, and clinical utility (changes in patient care). Results: A molecular diagnostic variant was identified in 51% of participants (n = 204; 297 variants identified with 134 being novel). Molecular diagnostic yield of genomic sequencing was 49% (95% CI, 44%-54%) vs 27% (95% CI, 23%-32%) with the targeted gene-sequencing test. Genomic sequencing did not report 19 variants found by the targeted neonatal gene-sequencing test; the targeted gene-sequencing test did not report 164 variants identified by genomic sequencing as diagnostic. Variants unidentified by the targeted genomic-sequencing test included structural variants longer than 1 kilobase (25.1%) and genes excluded from the test (24.6%) (McNemar odds ratio, 8.6 [95% CI, 5.4-14.7]). Variant interpretation by laboratories differed by 43%. Median time to return of results was 6.1 days for genomic sequencing and 4.2 days for the targeted genomic-sequencing test; for urgent cases (n = 107) the time was 3.3 days for genomic sequencing and 4.0 days for the targeted gene-sequencing test. Changes in clinical care affected 19% of participants, and 76% of clinicians viewed genomic testing as useful or very useful in clinical decision-making, irrespective of a diagnosis. Conclusions and Relevance: The molecular diagnostic yield for genomic sequencing was higher than a targeted neonatal gene-sequencing test, but the time to return of routine results was slower. Interlaboratory variant interpretation contributes to differences in molecular diagnostic yield and may have important consequences for clinical management.

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.

Clinical and Genetic Atrial Fibrillation Risk and Discrimination of Cardioembolic From Noncardioembolic Stroke.

BACKGROUND: Stroke is a leading cause of death and disability worldwide. Atrial fibrillation (AF) is a common cause of stroke but may not be detectable at the time of stroke. We hypothesized that an AF polygenic risk score (PRS) can discriminate between cardioembolic stroke and noncardioembolic strokes. METHODS: We evaluated AF and stroke risk in 26 145 individuals of European descent from the Stroke Genetics Network case-control study. AF genetic risk was estimated using 3 recently developed PRS methods (LDpred-funct-inf, sBayesR, and PRS-CS) and 2 previously validated PRSs. We performed logistic regression of each AF PRS on AF status and separately cardioembolic stroke, adjusting for clinical risk score (CRS), imputation group, and principal components. We calculated model discrimination of AF and cardioembolic stroke using the concordance statistic (c-statistic) and compared c-statistics using 2000-iteration bootstrapping. We also assessed reclassification of cardioembolic stroke with the addition of PRS to either CRS or a modified CHA2DS2-VASc score alone. RESULTS: Each AF PRS was significantly associated with AF and with cardioembolic stroke after adjustment for CRS. Addition of each AF PRS significantly improved discrimination as compared with CRS alone (P<0.01). When combined with the CRS, both PRS-CS and LDpred scores discriminated both AF and cardioembolic stroke (c-statistic 0.84 for AF; 0.74 for cardioembolic stroke) better than 3 other PRS scores (P<0.01). Using PRS-CS PRS and CRS in combination resulted in more appropriate reclassification of stroke events as compared with CRS alone (event reclassification [net reclassification indices]+=14% [95% CI, 10%-18%]; nonevent reclassification [net reclassification indices]-=17% [95% CI, 15%-0.19%]) or the modified CHA2DS2-VASc score (net reclassification indices+=11% [95% CI, 7%-15%]; net reclassification indices-=14% [95% CI, 12%-16%]) alone. CONCLUSIONS: Addition of polygenic risk of AF to clinical risk factors modestly improves the discrimination of cardioembolic from noncardioembolic strokes, as well as reclassification of stroke subtype. Polygenic risk of AF may be a useful biomarker for identifying strokes caused by AF.

Pulmonary Artery Catheter Use and Risk of In-hospital Death in Heart Failure Cardiogenic Shock.

BACKGROUND: Pulmonary artery catheters (PACs) are increasingly used to guide management decisions in cardiogenic shock (CS). The goal of this study was to determine if PAC use was associated with a lower risk of in-hospital mortality in CS owing to acute heart failure (HF-CS). METHODS AND RESULTS: This multicenter, retrospective, observational study included patients with CS hospitalized between 2019 and 2021 at 15 US hospitals participating in the Cardiogenic Shock Working Group registry. The primary end point was in-hospital mortality. Inverse probability of treatment-weighted logistic regression models were used to estimate odds ratios (ORs) and corresponding 95% confidence intervals (CI), accounting for multiple variables at admission. The association between the timing of PAC placement and in-hospital death was also analyzed. A total of 1055 patients with HF-CS were included, of whom 834 (79%) received a PAC during their hospitalization. In-hospital mortality risk for the cohort was 24.7% (n = 261). PAC use was associated with lower adjusted in-hospital mortality risk (22.2% vs 29.8%, OR 0.68, 95% CI 0.50-0.94). Similar associations were found across SCAI stages of shock, both at admission and at maximum SCAI stage during hospitalization. Early PAC use (≤6 hours of admission) was observed in 220 PAC recipients (26%) and associated with a lower adjusted risk of in-hospital mortality compared with delayed (≥48 hours) or no PAC use (17.3% vs 27.7%, OR 0.54, 95% CI 0.37-0.81). CONCLUSIONS: This observational study supports PAC use, because it was associated with decreased in-hospital mortality in HF-CS, especially if performed within 6 hours of hospital admission. CONDENSED ABSTRACT: An observational study from the Cardiogenic Shock Working Group registry of 1055 patients with HF-CS showed that pulmonary artery catheter (PAC) use was associated with a lower adjusted in-hospital mortality risk (22.2% vs 29.8%, odds ratio 0.68, 95% confidence interval 0.50-0.94) compared with outcomes in patients managed without PAC. Early PAC use (≤6 hours of admission) was associated with a lower adjusted risk of in-hospital mortality compared with delayed (≥48 hours) or no PAC use (17.3% vs 27.7%, odds ratio 0.54, 95% confidence interval 0.37-0.81).

The bidirectional association between atrial fibrillation and myocardial infarction.

Atrial fibrillation (AF) is associated with an increased risk of myocardial infarction (MI) and vice versa. This bidirectional association relies on shared risk factors as well as on several direct and indirect mechanisms, including inflammation, atrial ischaemia, left ventricular remodelling, myocardial oxygen supply-demand mismatch and coronary artery embolism, through which one condition can predispose to the other. Patients with both AF and MI are at greater risk of stroke, heart failure and death than patients with only one of the conditions. In this Review, we describe the bidirectional association between AF and MI. We discuss the pathogenic basis of this bidirectional relationship, describe the risk of adverse outcomes when the two conditions coexist, and review current data and guidelines on the prevention and management of both conditions. We also identify important gaps in the literature and propose directions for future research on the bidirectional association between AF and MI. The Review also features a summary of methodological approaches for the study of bidirectional associations in population-based studies.

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.

Increasing Engagement in the Electronic Framingham Heart Study: Factorial Randomized Controlled Trial.

BACKGROUND: Smartphone apps and mobile health devices offer innovative ways to collect longitudinal cardiovascular data. Randomized evidence regarding effective strategies to maintain longitudinal engagement is limited. OBJECTIVE: This study aimed to evaluate smartphone messaging interventions on remote transmission of blood pressure (BP) and heart rate (HR) data. METHODS: We conducted a 2 × 2 × 2 factorial blinded randomized trial with randomization implemented centrally to ensure allocation concealment. We invited participants from the Electronic Framingham Heart Study (eFHS), an e-cohort embedded in the FHS, and asked participants to measure their BP (Withings digital cuff) weekly and wear their smartwatch daily. We assessed 3 weekly notification strategies to promote adherence: personalized versus standard; weekend versus weekday; and morning versus evening. Personalized notifications included the participant's name and were tailored to whether or not data from the prior week were transmitted to the research team. Intervention notification messages were delivered weekly automatically via the eFHS app. We assessed if participants transmitted at least one BP or HR measurement within 7 days of each notification after randomization. Outcomes were adherence to BP and HR transmission at 3 months (primary) and 6 months (secondary). RESULTS: Of the 791 FHS participants, 655 (82.8%) were eligible and randomized (mean age 53, SD 9 years; 392/655, 59.8% women; 596/655, 91% White). For the personalized versus standard notifications, 38.9% (126/324) versus 28.8% (94/327) participants sent BP data at 3 months (difference=10.1%, 95% CI 2.9%-17.4%; P=.006), but no significant differences were observed for HR data transmission (212/324, 65.4% vs 209/327, 63.9%; P=.69). Personalized notifications were associated with increased BP and HR data transmission versus standard at 6 months (BP: 107/291, 36.8% vs 66/295, 22.4%; difference=14.4%, 95% CI 7.1- 21.7%; P<.001; HR: 186/281, 66.2% vs 158/281, 56.2%; difference=10%, 95% CI 2%-18%; P=.02). For BP and HR primary or secondary outcomes, there was no evidence of differences in data transmission for notifications sent on weekend versus weekday or morning versus evening. CONCLUSIONS: Personalized notifications increased longitudinal adherence to BP and HR transmission from mobile and digital devices among eFHS participants. Our results suggest that personalized messaging is a powerful tool to promote adherence to mobile health systems in cardiovascular research. TRIAL REGISTRATION: ClinicalTrials.gov NCT03516019; https://clinicaltrials.gov/ct2/show/NCT03516019.