One Size Does Not Fit All: An Exploration of Compression Garment Use in Patients With Postural Orthostatic Tachycardia Syndrome
Bibliographic record
Abstract
Background: Postural orthostatic tachycardia syndrome (POTS) is a chronic form of orthostatic intolerance that primarily affects female patients. Despite the severity of POTS, there are no approved medications for use in patients with this disorder. Compression garments are a commonly prescribed nonpharmacological treatment, but little is known about the patient experience with compression. In this study we aimed to evaluate the patient experience with compression garments using a structured survey and semistructured telephone interviews. Methods: A focused survey was designed as a component of a larger clinical trial on compression garment use in patients diagnosed with POTS. Building on the survey, semistructured telephone interviews were conducted with POTS patients. Recorded interviews were transcribed and coded in a thematic analysis using a descriptive-interpretive approach. Results: A total of 27 participants completed the survey, and 20 participants completed the telephone interview. Patient experiences with compression were variable, with some participants experiencing significant benefits, and others reporting minimal to no benefits. Six themes that influenced garment use were identified: the potential benefit of the garment to improve symptoms, specific activities patients will be undertaking, environmental conditions, garment attributes, psychological and cognitive aspects, and financial considerations. Conclusions: Participants engage in a daily cost-benefit analysis when making decisions to use a compression garment. Clinicians should be aware of the benefits of and factors that limit use of compression garments as a treatment for POTS.
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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".