The effect of obstructive sleep apnea syndrome on serum S100B and NSE levels: a systematic review and meta-analysis of observational studies
Bibliographic record
Abstract
BACKGROUND: Obstructive sleep apnea syndrome (OSAS) is a common disorder that is accompanied by structural brain changes. This meta-analysis aimed to evaluate the effect of OSAS on the serum levels of astrocytic protein (S100B) and neuron-specific enolase (NSE) in observational studies. METHODS: A comprehensive search was performed in the PubMed/Medline, Web of Science, Scopus, ScienceDirect, and Cochrane Library databases to assess the serum level of S100B and/or NSE in patients with OSAS and/or controls. The quality of the study was evaluated by the Newcastle-Ottawa Scale (NOS). A random-effects model was performed using RevMan 5.3 with the mean difference (MD) and 95% confidence intervals (CIs). RESULTS: Out of 63 studies found in the mentioned databases and one identified by a manual search, nine studies were included and analyzed in this meta-analysis (three cross-sectional and six case-control studies). The analysis showed that the S100B [MD = 53.58 pg/ml, 95%CI: 1.81, 105.35; P = 0.04] and NSE levels [MD = 3.78 ng/ml, 95%CI: 2.07, 5.48; P < 0.0001] were significantly higher in patients than the controls. However, there were no significant differences between the S100B [MD = -28.00 pg/ml, 95%CI: - 79.48, 23.47; P = 0.29] and NSE levels [MD = 0.49 ng/ml, 95%CI: - 0.82, 1.80; P = 0.46]. CONCLUSIONS: This meta-analysis found elevated serum S100B and NSE levels in OSAS patients compared to the controls, which suggests that these markers may be used as peripheral indicators of brain damage in OSAS.
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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 | 0.016 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.041 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".