The Bidirectional Relationship Between Obstructive Sleep Apnea and Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD): A Systematic Review and Meta-Analysis of Longitudinal Studies
Bibliographic record
Abstract
Background: Obstructive sleep apnea (OSA) and metabolic dysfunction-associated steatotic liver disease (MASLD) are highly prevalent, interconnected metabolic disorders. While their cross-sectional association is established, the temporal and potentially causal relationship remains unclear. This study aimed to quantitatively synthesize longitudinal evidence on the bidirectional risk between OSA and MASLD. Methods: We systematically searched PubMed, Scopus, and Web of Science (January 1st, 2015 - July 1st, 2025) for longitudinal cohort studies in adults assessing the OSA-MASLD relationship. Two reviewers independently selected studies, extracted data, and assessed quality using the Newcastle-Ottawa Scale (NOS). The primary analysis, pre-specified for studies using objective diagnostics (Polysomnography/Imaging), utilized a random-effects model to pool hazard ratios (HR). Heterogeneity was quantified with the I2 statistic. Results: The search identified 2,148 articles, with six longitudinal studies (185,432 participants) meeting eligibility criteria. Four studies (116,298 participants) assessed incident MASLD, while two (69,134 participants) assessed incident OSA. The primary meta-analysis of two studies using objective diagnostics found that baseline OSA was associated with a significantly increased risk of incident MASLD (pooled HR: 2.29; 95% CI: 1.93-2.71; I2=35%). A secondary analysis including two studies using administrative codes yielded a pooled HR of 1.87 (95% CI: 1.51-2.32), though with substantial heterogeneity (I2=78%). For the reverse direction, a narrative synthesis of two studies suggests MASLD increases the risk of incident OSA; an exploratory pooled analysis yielded an HR of 1.65 (95% CI: 1.39-1.96; I2=45%), a finding to be interpreted with caution due to the small study number. Conclusion: This systematic review of longitudinal data provides the strongest evidence to date supporting a significant, bidirectional relationship between OSA and MASLD. The presence of objectively-diagnosed OSA more than doubles the risk of developing future MASLD. These findings provide a strong rationale for implementing mutual, risk-stratified screening and developing integrated management strategies to disrupt the vicious cycle linking these two common and morbid conditions.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".