The Influence of OSA Severity on Muscle Sympathetic Nerve Activity: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Introduction Microneurography has been used to measure efferent postganglionic muscle sympathetic nerve activity (MSNA) via direct interneural recordings in individuals with obstructive sleep apnea (OSA) to gain an understanding of the cardiovascular control and disease risk in this population. Purpose We conducted a meta‐analysis to identify a relationship between OSA severity, determined by the apnea‐hypopnea index (AHI), and MSNA. Methods A structured search of electronic databases was performed by a research librarian. Two reviewers independently assessed the titles of abstracts of articles; studies meeting eligibility criteria were selected for full‐text review. Two reviewers independently extracted the data and assessed the quality of the studies using Joanna Briggs Institute Critical Appraisal of Evidence Effectiveness tool. Review Manager v5.3 was used to conduct the statistical analyses, and significance was set at P < 0.05. When 10 or more studies were included, meta‐regression analyses were also performed in STATA 15.0. Results Data from 36 studies indicating higher burst frequency in individuals with OSA (n=622) when compared to author‐defined controls (n=573) (Mean Differences, +15.1 bursts/min; 95% CI, 12.6‐17.6 bursts/min; I 2 = 81%). 26 studies showed higher burst incidence in individuals with OSA when compared to controls as well (MD, +23.2 bursts/100 hbs; 95% CI, 19.7‐26.6 bursts/100 hbs; I 2 = 66%). Higher burst frequency and burst incidence was seen for all OSA subgroups: obese, overweight and obese, lean, Metabolic Syndrome, and Heart Failure. Meta‐regression analyses were performed for burst frequency and burst incidence, and a relationship was identified with OSA severity (AHI) for both (burst frequency, R 2 = 0.294, p<0.001; burst incidence, R 2 = 0.373, p<0.001). This relationship remained when other confounding variables were included (age, body‐mass index [BMI], systolic, diastolic, and mean arterial pressure), suggesting this relationship is specific to OSA severity. Conclusion MSNA was significantly higher in individuals with OSA when compared to healthy controls. Furthermore, MSNA was higher when BMI and other common comorbidities (Metabolic Syndrome and Heart Failure) were accounted for, and a significant positive relationship was identified between OSA severity and metrics of sympathetic activity. These data are clinically important for understanding cardiovascular disease risk in patients with OSA.
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.036 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".