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Novel method to quantify loss of heart rate variability in pediatric multiple organ failure*

2003· article· en· W2050803595 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCritical Care Medicine · 2003
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineHeart rate variabilityStandard deviationStatisticsHeart failureLinear regressionConfidence intervalHeart rateCardiologyMathematicsInternal medicineBlood pressure

Abstract

fetched live from OpenAlex

OBJECTIVE: To develop a power-law model for measurement of heart rate variability (HRV) and to compare this model with established methods for measuring HRV in a group of children with organ failure (OF). DESIGN: Prospective, observational study. SETTING: Pediatric intensive care unit of a tertiary children's hospital. PATIENTS: A total of 104 measurements were made on 50 patients (median age, 8 months; range, 2 days to 16 yrs) and categorized into three groups according to the number of simultaneous organs failing: 0-1 OF, 2 OF, and >/=3 OF. INTERVENTIONS: Heart rate was recorded over a 5-min period when patients were hemodynamically stable. The power-law model represents a power function relating frequency distribution to magnitude of effect (in this case, squared deviation from the mean heart rate). Plotting the data on a bi-logarithmic scale produces a regression line for each measurement, described in terms of r2, slope, and x-intercept. Comparison with other HRV measures included two time-domain measures (sd of the normal R-R intervals and the square root of the mean squared differences of successive normal R-R intervals), one frequency-domain method (power spectral analysis), and one nonlinear method (detrended fluctuation analysis). MEASUREMENTS AND RESULTS: For the power-law model, patients exhibited a similar r2 of.87 (.09) (mean [sd]) and slope of -1.80 (0.29), regardless of the degree of OF. HRV could thus be described purely in terms of x-intercept, which demonstrated a left shift with increasing OF (p <.001). This was independent of age and heart rate. Loss of HRV with increasing OF was demonstrated by all methods; however, only the power-law model was able to discriminate between each OF group. Using the model, change in HRV in individual patients over successive days often concurred qualitatively with the change in OF status. CONCLUSION: The power-law model is an appropriate measure of HRV in pediatric patients, being neither age nor heart rate sensitive. Loss of HRV occurs with increasing OF; this effect was better demonstrated by the model compared with other measures of HRV.

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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)0.005
metaresearch head score (Gemma)0.035
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.035
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.350
Teacher spread0.319 · 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