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Record W3215044387 · doi:10.1016/j.jshs.2021.12.002

Heart rate response and recovery during exercise predict future delirium risk—A prospective cohort study in middle- to older-aged adults

2021· article· en· W3215044387 on OpenAlexaff
Lei Gao, Arlen Gaba, Peng Li, Richa Saxena, Frank A. J. L. Scheer, Oluwaseun Akeju, Martin K. Rutter, Kun Hu

Bibliographic record

VenueJournal of sport and health science/Journal of Sport and Health Science · 2021
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsLMC Diabetes & Endocrinology (Canada)
FundersNational Institute on AgingNational Institutes of HealthNational Heart, Lung, and Blood InstituteMedical Research CouncilFoundation for Anesthesia Education and Research
KeywordsDeliriumProspective cohort studyMedicineCohort studyHeart ratePsychologyPhysical medicine and rehabilitationPhysical therapyInternal medicinePsychiatryBlood pressure

Abstract

fetched live from OpenAlex

BACKGROUND: Delirium is a neurocognitive disorder characterized by an abrupt decline in attention, awareness, and cognition after surgical/illness-induced stressors on the brain. There is now an increasing focus on how cardiovascular health interacts with neurocognitive disorders given their overlapping risk factors and links to subsequent dementia and mortality. One common indicator for cardiovascular health is the heart rate response/recovery (HRR) to exercise, but how this relates to future delirium is unknown. METHODS: Electrocardiogram data were examined in 38,740 middle- to older-aged UK Biobank participants (mean age = 58.1 years, range: 40-72 years; 47.3% males) who completed a standardized submaximal exercise stress test (15-s baseline, 6-min exercise, and 1-min recovery) and required hospitalization during follow-up. An HRR index was derived as the product of the heart rate (HR) responses during exercise (peak/resting HRs) and recovery (peak/recovery HRs) and categorized into low/average/high groups as the bottom quartile/middle 2 quartiles/top quartile, respectively. Associations between 3 HRR groups and new-onset delirium were investigated using Cox proportional hazards models and a 2-year landmark analysis to minimize reverse causation. Sociodemographic factors, lifestyle factors/physical activity, cardiovascular risk, comorbidities, cognition, and maximal workload achieved were included as covariates. RESULTS: During a median follow-up period of 11 years, 348 participants (9/1000) newly developed delirium. Compared with the high HRR group (16/1000), the risk for delirium was almost doubled in those with low HRR (hazard ratio = 1.90, 95% confidence interval (95%CI): 1.30-2.79, p = 0.001) and average HRR (hazard ratio = 1.54, 95%CI: 1.07-2.22, p = 0.020)). Low HRR was equivalent to being 6 years older, a current smoker, or ≥3 additional cardiovascular disease risks. Results were robust in sensitivity analysis, but the risk appeared larger in those with better cognition and when only postoperative delirium was considered (n = 147; hazard ratio = 2.66, 95%CI: 1.46-4.85, p = 0.001). CONCLUSION: HRR during submaximal exercise is associated with future risk for delirium. Given that HRR is potentially modifiable, it may prove useful for neurological risk stratification alongside traditional cardiovascular risk factors.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.020
GPT teacher head0.324
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations1
Published2021
Admission routes1
Has abstractyes

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