The Prevalence of Obstructive Sleep Apnea and Associated Symptoms among Patients with Sickle Cell Disease: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Previous studies have shown that patients with sickle cell disease (SCD) are at high risk for obstructive sleep apnea (OSA). In the current study, we aimed to systematically review the literature to address the prevalence of OSA and associated symptoms among patients with SCD. Electronic databases, including Web of Science, Scopus, PubMed, Google Scholar, and Embase were systematically searched to identify the relevant original articles on patients with SCD. Newcastle Ottawa scale was used for quality assessment. Data were pooled by using random effects models. Subgroup analyses were performed by age groups. Thirty-nine studies containing details of 299,358 patients with SCD were included. The pooled results showed that more than half of these patients had OSA with different severities. The prevalence rates of OSA among children with apnea hypopnea index (AHI) cutoffs of above 1, 1.5, and 5 were 51% (95% confidence interval (CI) 36-67%), 29% (95% CI 19-40%), and 18% (95% CI 14-23%), respectively. The prevalence of OSA among adults with AHI cutoff of 5 was 43% (95% CI 21-64%). The pooled rates of snoring, nocturnal enuresis, nocturnal desaturation, and daytime sleepiness were 55% (95% CI 42-69%), 37% (95% CI 33-41%), 49% (95% CI 26-72%), and 21% (95% CI 12-30%), respectively. Given the high prevalence of OSA in patients with SCD, probable greater burden of SCD complications, and irreversible consequences of OSA, screening for OSA symptoms and signs seems useful in these patients. By screening and identifying this heterogeneous disorder earlier, available treatment modalities can be individualized for each patient.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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".