Midodrine for the prevention of vasovagal syncope: a systematic review and meta-analysis
Bibliographic record
Abstract
AIMS: Vasovagal syncope (VVS) is a common clinical condition that lacks effective medical therapies despite being associated with significant morbidity. Current guidelines suggest that midodrine, a prodrug for an α1-adrenergic receptor agonist, might suppress VVS but supporting studies have utilized heterogeneous methods and yielded inconsistent results. To evaluate the efficacy of midodrine to prevent syncope in patients with recurrent VVS by conducting a systematic review and meta-analysis of published studies. METHODS AND RESULTS: Relevant randomized controlled trials were identified from the MEDLINE, Embase, CENTRAL, and CINAHL databases without language restriction from inception to June 2021. All studies were conducted in clinical syncope populations and compared the benefit of midodrine vs. placebo or non-pharmacological standard care. Weighted relative risks (RRs) were estimated using random effects meta-analysis techniques. Seven studies (n = 315) met inclusion criteria. Patients were 33 ± 17 years of age and 31% male. Midodrine was found to substantially reduce the likelihood of positive head-up-tilt (HUT) test outcomes [RR = 0.37 (0.23-0.59), P < 0.001]. In contrast, the pooled results of single- and double-blind clinical trials (I2 = 54%) suggested a more modest benefit from midodrine for the prevention of clinical syncope [RR = 0.51 (0.33-0.79), P = 0.003]. The two rigorous double-blind, randomized, placebo-controlled clinical trials included 179 VVS patients with minimal between-study heterogeneity (I2 = 0%) and reported a risk reduction with midodrine [RR = 0.71 (0.53-0.95), P = 0.02]. CONCLUSIONS: Midodrine is effective in preventing syncope induced by HUT testing and less, but still significant, RR reduction in randomized, double-blinded clinical trials.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".