Association between Physiological Signal Complexity and Outcomes in Moderate and Severe Traumatic Brain Injury: A CENTER-TBI Exploratory Analysis of Multi-Scale Entropy
Bibliographic record
Abstract
In traumatic brain injury (TBI), preliminary retrospective work on signal entropy suggests an association with global outcome. The goal of this study was to provide multi-center validation of the association between multi-scale entropy (MSE) of cardiovascular and cerebral physiological signals, with six-month outcome. Using the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) high-resolution intensive care unit (ICU) cohort, we selected patients with a minimum of 72 h of physiological recordings and a documented six-month Glasgow Outcome Scale Extended (GOSE) score. The 10-sec summary data for heart rate (HR), mean arterial pressure (MAP), intracranial pressure (ICP), and pulse amplitude of ICP (AMP) were derived across the first 72 h of data. The MSE complexity index (MSE-Ci) was determined for HR, MAP, ICP, and AMP, with the association between MSE and dichotomized six-month outcomes assessed using Mann-Whitney U testing and logistic regression analysis. A total of 160 patients had a minimum of 72 h of recording and a documented outcome. Decreased HR MSE-Ci (7.3 [interquartile range (IQR) 5.4 to 10.2] vs. 5.1 [IQR 3.1 to 7.0]; p = 0.002), lower ICP MSE-Ci (11.2 [IQR 7.5 to 14.2] vs. 7.3 [IQR 6.1 to 11.0]; p = 0.009), and lower AMP MSE-Ci (10.9 [IQR 8.0 to 13.7] vs. 8.7 [IQR 6.6 to 11.0]; p = 0.022), were associated with death. Similarly, lower HR MSE-Ci (8.0 [IQR 6.2 to 10.9] vs. 6.2 [IQR 3.9 to 8.7]; p = 0.003) and lower ICP MSE-Ci (11.4 [IQR 8.6 to 14.4)] vs. 9.2 [IQR 6.0 to 13.5]), were associated with unfavorable outcome. Logistic regression analysis confirmed that lower HR MSE-Ci and ICP MSE-Ci were associated with death and unfavorable outcome at six months. These findings suggest that a reduction in cardiovascular and cerebrovascular system entropy is associated with worse outcomes. Further work in the field of signal complexity in TBI multi-modal monitoring is required.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".