A systematic review and meta-analysis of heart rate variability in COPD
Bibliographic record
Abstract
Background: Chronic obstructive pulmonary disease (COPD) is associated with disruption in autonomic nervous control of the heart rhythm. We present here quantitative evidence of the reduction in HRV measures as well as the challenges to clinical application of HRV in COPD clinics. Method: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we search in June 2022 Medline and Embase databases for studies reporting HRV in COPD patients using relevant medical subject headings (MeSH) terms. The quality of included studies was assessed using the modified version of the Newcastle-Ottawa Scale (NOS). Descriptive data were extracted, while standardized mean difference was computed for changes in HRV due to COPD. Leave-one-out sensitivity test was performed to assess exaggerated effect size and funnel plots to assess publication bias. Results: The databases search yielded 512 studies, of which we included 27 that met the inclusion criteria. The majority of the studies (73%) had a low risk of bias and included a total of 839 COPD patients. Although there were high between-studies heterogeneity, HRV time and frequency domains were significantly reduced in COPD patients compared with controls. Sensitivity test showed no exaggerated effect sizes and the funnel plot showed general low publication bias. Conclusion: COPD is associated with autonomic nervous dysfunction as measured by HRV. Both sympathetic and parasympathetic cardiac modulation were decreased, but there is still a predominance of sympathetic activity. There is high variability in the HRV measurement methodology, which affects clinical applicability.
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 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 | 0.028 | 0.076 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.033 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".