Fragmentation of Rest/Activity Patterns in Community-Based Elderly Individuals Predicts Incident Heart Failure
Bibliographic record
Abstract
Lei Gao,1,2 Andrew SP Lim,3 Patricia M Wong,4 Arlen Gaba,2 Longchang Cui,2 Lei Yu,5 Aron S Buchman,5 David A Bennett,5 Kun Hu,2,6 Peng Li2,6 1Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA; 2Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA 02115, USA; 3Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, USA; 4Department of Psychology, University of Pittsburgh, Pittsburgh, PA 15260, USA; 5Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL 60612, USA; 6Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USACorrespondence: Lei GaoDepartment of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USATel +1 617 888-2941Fax +1 617 732-7337Email lgao@mgh.harvard.eduPeng LiDivision of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA 02115, USATel +1 617 278-0061Fax +1 617 732-7337Email pli9@bwh.harvard.eduStudy Objectives: Heart failure has previously been linked to sleep disorders that are often associated with frequent disturbances to human rest/activity patterns. We tested whether fragmentation of sustained rest/activity patterns derived from actigraphic recordings at baseline predicts incident heart failure in community-based elderly individuals.Methods: We studied 1099 community-based elderly adults participating in the Rush Memory and Aging Project who had baseline motor activity monitoring up to 11 days and were followed annually for up to 14 years. Fragmentation was assessed using previously validated indexes, derived from the probability of transitions once sustained rest or activity has been established. Heart failure was recorded via a clinical interview during the annual follow-up. Cox proportional hazards models were constructed to examine the relationship between rest fragmentation index and incident heart failure. Covariates grouped in terms of demographics, lifestyle factors and co-morbidities and cardiovascular risk factors/diseases were included.Results: Increased rest fragmentation (but not activity fragmentation) was associated with higher risk for incident heart failure. Specifically, a subject with a rest fragmentation at the 90th percentile showed a 57% increased risk of developing incident heart failure compared to a subject at the 10th percentile in this cohort. This effect was equivalent to that of being over a decade older. These observations were consistent after adjusting for all covariates.Conclusion: Increased rest fragmentation, a potential surrogate for sleep fragmentation, is independently associated with a higher risk of developing heart failure in community-based elderly adults during up to 14 years of follow-up. Further work is required to examine the specific contributions from daytime napping versus nighttime sleep periods in the elderly, as well as the underlying autonomic and cardio-dynamic pathways that may explain the effects on heart function.Keywords: sleep fragmentation, heart failure, mobile health, unobtrusive monitoring
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".