0854 Observation-based Diurnal Sleepiness Inventory (ODSI) is associated with Objective Sleepiness via Psychomotor Vigilance Task
Bibliographic record
Abstract
Abstract Introduction The Epworth Sleepiness Scale (ESS) is commonly used to assess excessive daytime sleepiness, but its accuracy is limited. In this study, we aim to compare the ESS with the Observation-based Diurnal Sleepiness Inventory (ODSI), a subjective measure of sleepiness that has been validated using the ESS in older adults, to objective measures of sleepiness obtained through the Psychomotor Vigilance Task (PVT). Despite being validated with the ESS, the ODSI has not yet been tested with objective measures of sleepiness. By comparing subjective measures of sleepiness (ODSI and ESS) to objective measures (PVT), we aim to expand the usage of ODSI to other populations. Methods 91 persons with newly diagnosed obstructive sleep apnea and not yet treated on continuous positive airway pressure (CPAP) were administered the ESS, ODSI, and PVT sleepiness tests, and the results were analyzed for correlations using linear regression. The average age was 50.48 ± 12.74, the mean body mass index (BMI) was 35.9 ± 9.3, the mean apnea hypopnea index was 30.9 ± 23.7, and 53.5% were male. The ESS and ODSI scores were run against PVT lapses and transformed average reaction time, which are the two primary outcomes of PVT. Results PVT lapses were significantly different between sleepy and non-sleepy individuals as defined by both ESS and ODSI categorization. Both the ODSI and the ESS were significantly correlated to the transformed average reaction time. The second question on the ODSI was also significantly correlated to PVT lapses as well as the transformed average reaction time. Conclusion The ODSI and ESS correlated well with objective measures of sleepiness through the PVT. The ODSI is a suitable measure of sleepiness appropriate for usage in middle-aged adults with obstructive sleep apnea. Support (if any) R00NR014675-05 (PI: Pak)
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.001 | 0.001 |
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".