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Record W2078918295 · doi:10.1139/h03-040

Blunted Cardiac Autonomic Responsiveness to Hypoxemic Stress in Healthy Older Adults

2003· article· en· W2078918295 on OpenAlexaff
S. Deborah Lucy, John M. Kowalchuk, Richard L. Hughson, Donald H. Paterson, David A. Cunningham

Bibliographic record

VenueCanadian Journal of Applied Physiology · 2003
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsWestern University
Fundersnot available
KeywordsHeart rateHeart rate variabilityCardiologyMedicineSupine positionInternal medicineAnesthesiaCharSpectral analysisBlood pressureChemistryPhysics

Abstract

fetched live from OpenAlex

Supine resting cardiac dynamics and responses to steady-state hypoxemia were investigated in six healthy older (59-72 yrs) adults using coarse-graining spectral analysis of heart rate variability (HRV) and were compared to six young (22-29 yrs) adults studied previously (Lucy et al<normal + trebuchet ms char,12 pt char, black char, condensed by 0.05 pt char>.,</normal + trebuchet ms char,12 pt char, black char, condensed by 0.05 pt char> 2000). End-tidal carbon dioxide pressure (P ET CO 2 ) was clamped at 1-2 mmHg above the usual resting value for 11 min of euoxia (P ET O 2 100 mmHg), followed by 22 min of hypoxia (P ET O 2 55 mmHg). During euoxia, vagally mediated harmonic and fractal power of HRV of older adults was minimal. Hypoxia induced an increase in ventilation, p < 0.01, and heart rate, p < 0.05. The heart rate increase (mean ± SE) of 0.23 ± 0.08 beats•min −1 per 1% decrease in arterial O 2 saturation was 25% of that demonstrated previously by young subjects, p < 0.001. In older adults, HRV spectral power remained unchanged during hypoxia, providing further evidence of an age-related blunting of cardiac autonomic function. Key words: heart rate variability, coarse-graining spectral analysis, cardiac vagal control, acute isocapnic hypoxia, dynamic end-tidal forcing (DEF) technique

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.871
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.235
Teacher spread0.228 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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".

Quick stats

Citations8
Published2003
Admission routes1
Has abstractyes

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