Assessment of Concussion/Mild Traumatic Brain Injury-Related Fatigue, Alertness, and Daytime Sleepiness: A Diagnostic Modelling Study
Bibliographic record
Abstract
Objective: Fatigue, alertness and daytime sleepiness are complex perceived states with significant implications for health and safety. These states are not diagnostically specific, and they may, or may not share interrelated features. Potential commonality or discordance is challenging in clinical situations, especially in controversial neurologic disorders, as in cases of concussion/ mild traumatic brain injury (mTBI). Methods: We performed a diagnostic multivariable modeling study to explore associations between patients’ characteristics, results of imaging tests and clinical investigations, and the states of fatigue, alertness and daytime sleepiness. The intensity of fatigue, alertness and daytime sleepiness was measured using the standardized Fatigue Severity Scale (FSS), the Toronto Hospital Alertness Test (THAT), and the Epworth Sleepiness Scale (ESS). Univariate and multivariate linear regression models were used to explicate covariates of fatigue, alertness, and daytime sleepiness. Results: A total of 94 patients (45.20 ± 9.94 years; 61.2% males) with an established diagnosis of concussion/mTBI were included in the current analysis. Our results revealed that fatigue and alertness are associated with covariates within the domain of brain function integrity, and that daytime sleepiness is associated with cultural and physiological bodily states. In the final fully adjusted multivariable regression models, several covariates accounted for 57.2% of the fatigue variance, 41.2% of alertness variance, and 27.1% of the sleepiness variance. While fatigue and alertness share covariates, daytime sleepiness represents a distinct construct in persons with concussion/mTBI. Conclusions: Our findings challenge the commonly held view that fatigue, alertness and daytime sleepiness are perceived states on the same continuum. The implications of this finding have direct relevance to the clinical approach towards patients presenting with fatigue, impaired alertness or excessive daytime sleepiness after concussion/mTBI.
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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 | 0.001 | 0.001 |
| 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".