Impact of Extended Shifts on Cerebral Oxygen Saturation and Cognitive Function in Pediatric Residents (Preprint)
Bibliographic record
Abstract
BACKGROUND In-training physicians frequently experience acute sleep deprivation periods due to the on-call shifts’ lengths. Many studies showed that on-call shifts are associated with negative impacts on cognitive function, alertness, and mood. Near-infrared spectroscopy (NIRS) is a useful non-invasive tool for regional cerebral oxygen saturation (rScO2) monitoring. We hypothesized that rScO2 might be decreased in sleep-deprived brains. OBJECTIVE This study aimed to determine effects of sleep deprivation following the nightshifts on rScO2 and cognitive function. METHODS This prospective study included 50 in-training pediatricians. The rScO2 was monitored using two rScO2 sensors placed on the forehead at pre on-call (T0), immediate post-call (T16), 24-h from pre on-call (T24), and 48-h from pre on call (T48) in each physician. All physicians continued their working without post-call day. The mathematical test was performed at T0, T16, T24, and T48 and the Montreal cognitive assessment (MoCA) test at T0 and T24. RESULTS The mean (SD) rScO2 at immediate post-call [65.8%(5.3)] and 24-h from pre on-call [64.6%(6.4)] were significantly declined from pre on-call [68.2%(5.6)], p<0.001, and then returned to baseline at 48-h from pre on-call [68.9%(5.5)]. The mathematical test scores were not different among all-time points. The mean (SD) MoCA score was significantly decreased at 24-h from pre on-call [T0, 28.4(1.4) to T24, 27.7(1.8), p<0.001]. Seven out of 50 pediatricians (14%) had MoCA scores lower than normal (less than 25). CONCLUSIONS The 16-h nightshifts and continuous working among in-training pediatricians might cause a transient reduction of rScO2, which, could led to decreased cognitive function scores.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".