Treatment of Postural Orthostatic Tachycardia Syndrome With Medication: A Systematic Review
Bibliographic record
Abstract
PURPOSE: Postural orthostatic tachycardia syndrome has been recognized for decades, but treatment is largely based on anecdotal experience and expert opinion. Pharmacologic treatment is inconsistent and unstandardized. We did a systematic review to identify controlled studies from which informed treatment decisions can be made. METHOD: Through a standard systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we identified all English-language studies of a medication treatment for postural orthostatic tachycardia syndrome that included a comparison or control group and followed outcomes for at least 1 week of treatment. RESULTS: A total of 626 studies were identified by the search criteria, and 8, involving a total of 499 patients, met the criteria. No studies were adequately similar to allow for meta-analysis. Of the identified 8 studies, 2 were randomized controlled trials and 4 had been subjected to peer review. In individual studies, there was some favorable effect with fludrocortisone, beta blockers, midodrine, and selective serotonin reuptake inhibitors. CONCLUSION: There is a paucity of high-quality data about effectiveness of medication in the treatment of postural orthostatic tachycardia syndrome. Nonetheless, 2 randomized trials and 6 other reports show some favorable effects of medication.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".