The association between serum vitamin D and obstructive sleep apnea: an updated meta-analysis
Bibliographic record
Abstract
BACKGROUND: The objective was to determine whether OSA patients have a low serum vitamin D level by systematic review and meta-analysis. METHODS: This study searched the following electronic bibliographic databases: Embase, Medline, Web of Science, PubMed, VIP, Wanfang, CNKI and SinoMed. All data were searched between January 2000 and August 2020. The quality of the included studies was estimated by two researchers according to the Newcastle-Ottawa Scale and Agency for Healthcare Research and Quality. All qualified studies and statistical analyses were conducted using RevMan 5.2. RESULTS: Twenty-nine eligible studies compromising 6717 participants met the inclusion criteria of the meta-analysis. The results revealed that the serum 25(OH)D level was significantly lower in OSA patients than the controls. According to the severity of the disease, subgroup analysis was performed; the results demonstrated that the serum 25(OH)D level was not decreased in mild OSA patients compared with the controls, while the serum 25(OH)D level in moderate and severe OSA patients was lower than that in the controls. Furthermore, based on ethnicity, BMI, PSG type, study quality and latitude, the subjects were divided into different subgroups for meta-analysis. The results revealed that the serum 25(OH)D level in all OSA subgroups was decreased compared with that in the control group. CONCLUSIONS: The present meta-analysis shows that the serum vitamin D level was different between OSA patients and healthy people. OSA patients could have a low serum vitamin D level.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.042 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".