Heart Rate Variability in Children with Moderate and Severe Traumatic Brain Injury: A Prospective Observational Study
Bibliographic record
Abstract
Abstract The aim of this study was to assess the feasibility of continuous monitoring of heart rate variability (HRV) in children with traumatic brain injury (TBI) hospitalized in a pediatric intensive care unit (PICU) and collect preliminary data on the association between HRV, neurological outcome, and complications. This is a prospective observational cohort study in a tertiary academic PICU. Children admitted to the PICU ≤24 hours after moderate or severe TBI were included in the study. Children suspected of being brain dead at PICU entry or with a pacemaker were excluded. Children underwent continuous monitoring of electrocardiographic (ECG) waveforms over 7 days post-TBI. HRV analysis was performed retrospectively, using a standardized, validated HRV analysis software (CIMVA). The occurrence of medical complications (“event”: intracranial hypertension, cerebral hypoperfusion, seizure, and cardiac arrest) was prospectively documented. Outcome of children 6 months post-TBI was assessed using the Glasgow Outcome Scale – Extended Pediatric (GOS-E Peds). Fifteen patients were included over a 20-month period. Thirteen patients had ECG recordings available and 4 had >20% of missing ECG data. When ECG was available, HRV calculation was feasible (average 88%; range 70–97%). Significant decrease in overall HRV coefficient of variation and Poincaré SD2 (p < 0.05) at 6 hours post–PICU admission was associated with an unfavorable outcome (defined as GOS-E Peds ≥ 3, or a deterioration of ≥2 points over baseline score). Several HRV metrics exhibited significant and nonsignificant variation in HRV during event. This study demonstrates that it is feasible to monitor HRV in the PICU provided ECG data are available; however, missing ECG data are not uncommon. These preliminary data suggest that altered HRV is associated with unfavorable neurological outcome and in-hospital medical complications. Larger prospective studies are needed to confirm these findings and to explore if HRV offers reliable and clinically useful prediction data that may help clinical decision making.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".