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Record W2112657890 · doi:10.1109/ccece.2008.4564863

Computer model study of magnitude and phase relations of arterial pressure in response to respiratory fluctuations

2008· article· en· W2112657890 on OpenAlexafffundvenue
Younhee Choi, Seok‐Bum Ko, Yang Shi, Jenny Basran, Vanina Dal Bello‐Haas, Anh Dinh

Bibliographic record

VenueConference proceedings - Canadian Conference on Electrical and Computer Engineering · 2008
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBlood pressureBaroreflexMathematicsAutoregressive–moving-average modelAutoregressive modelHemodynamicsCardiologyCorrelation coefficientRespiratory systemInternal medicineAnesthesiaMean arterial pressureMedicineHeart rateStatistics

Abstract

fetched live from OpenAlex

A comprehensive computer model has been developed and used for studying hemodynamic waveforms and various cardiopulmonary mechanisms. Inspiratory fall of systolic arterial pressure (IFSBP) is used as an index to assess the respiratory influences on non-linear dynamics of heart rate variability. Two approaches for baroreflex regulation were tested, including a simple 1st-order relationship between R-R interval (RRI) and systolic blood pressure (SBP) and the autoregressive moving average (ARMA) model. Experimental data were obtained retrospectively from 22 patients with chronic airway obstruction before and during breathing through an external resistance. Magnitude and phase relations between arterial pressure and pleural pressure were evaluated. The computer model provided good fits to arterial pressure waveforms: correlation coefficients (r) ranging from 0.71 to 0.96 (meanplusmnSD: 0.87plusmn0.06) with a simple 1st-order model. It was observed that the ARMA model did not further improve the goodness of fit. Higher correlation coefficient between IFSBP and respiratory variation in the elderly subjects supported that aging impairs baroreflex mechanism. In terms of phase relations, no dominant parameter was found.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.828
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.028
GPT teacher head0.247
Teacher spread0.219 · 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 designSimulation or modeling
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

Citations0
Published2008
Admission routes3
Has abstractyes

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