Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 30% of its field
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literature
Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
13 authors at 3 institutions in 1 country.
Ayelet Shapira-DanielsSection of General Internal Medicine, Department of Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, United States.ORCID 0000-0002-4920-2397
Jelena KornejBoston University's Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA, United States.ORCID 0000-0003-3551-1145
Nicole L SpartanoSection of Endocrinology, Diabetes, Nutrition and Weight Management, Department of Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, United States.ORCID 0000-0002-0724-8629
Xuzhi WangDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, United States.ORCID 0000-0003-4326-691X
Yuankai ZhangDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, United States.ORCID 0000-0002-2318-7539
Chathurangi H PathiravasanDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, United States.ORCID 0000-0003-2170-1247
Chunyu LiuDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, United States.ORCID 0000-0002-9160-0153
Ludovic TrinquartDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, United States.ORCID 0000-0002-3028-4900
Belinda BorrelliCenter for Behavioral Science Research, Henry M Goldman School of Dental Medicine, Boston University, Boston, MA, United States.ORCID 0000-0002-0859-796X
David D McManusDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.ORCID 0000-0002-9343-6203
Joanne M MurabitoSection of General Internal Medicine, Department of Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, United States.ORCID 0000-0002-0192-7516
Emelia J BenjaminBoston University's Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA, United States.ORCID 0000-0003-4076-2336
Honghuang LinBoston University's Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA, United States.ORCID 0000-0003-3043-3942
Boston University · USUniversity of Massachusetts Chan Medical School · USNational Heart Lung and Blood Institute · US
Funding
The Center for Advancing Point of Care in Heart, Lung, Blood and Sleep DiseasesU54HL143541 · NHLBI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI BRYAN O BUCHHOLZ, Nathaniel Scott Hafer · 2018 to 2026
$141.0M
FRAMINGHAM HEART STUDY - YEAR 5 EXAM75N92019D00031 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · 2019 to 2024
$29.8M
IDENTIFICATION OF COMMON GENETIC VARIANTS FOR ATRIAL FIBRILLATION AND PR INTERVALR01HL092577 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI BENJAMIN, EMELIA J., ELLINOR, PATRICK THOMAS · 2009 to 2025
$20.6M
ConProject-006U54HL120163 · NHLBI · AMERICAN HEART ASSOCIATION · PI BHATNAGAR, ARUNI, ROBERTSON, ROSE MARIE · 2018 to 2022
$18.8M
CAPSITE: Community Assessment of Pain and Sensitization in the ElderlyR01AG066010 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI BENJAMIN, EMELIA J., EDWARDS, ROBERT R · 2020 to 2025
$3.3M
Detecting bleeding events using EHRs for prediction in AfibR01HL137794 · NHLBI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI MCMANUS, DAVID D., YU, HONG · 2018 to 2021
$3.3M
Systematic Assessment of Geriatric Elements in Atrial Fibrillation (SAGE-AF)R01HL126911 · NHLBI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI MCMANUS, DAVID D., SACZYNSKI, JANE STEELE · 2016 to 2019
$3.2M
Smartwatch Monitoring for Atrial Fibrillation After StrokeR01HL137734 · NHLBI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI CHON, KI H, MCMANUS, DAVID D. · 2018 to 2021
$3.1M
Assessing Alzheimer disease risk and heterogeneity using multimodal machine learning approachesU01AG068221 · NIA · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI DESTEFANO, ANITA L, LIN, HONGHUANG · 2021 to 2024
$2.5M
FHS-NEXT - Framingham Novel EXam using TechnologyR01HL141434 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI BENJAMIN, EMELIA J., MCMANUS, DAVID D. · 2019 to 2022
backgroundPhysical 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.
objectiveThe objective of this study was to investigate the association between daily step count and the predicted 5-year risk of AF.
methodsParticipants 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/m
resultsWe 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.
conclusionsHigher 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.
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Step Count, Self-reported Physical Activity, and Predicted 5-Year Risk of Atrial Fibrillation: Cross-sectional Analysis. · full record | OpenQuestion