Enhanced external counterpulsation for management of symptoms associated with long COVID
Bibliographic record
Abstract
Study objective: Enhanced external counterpulsation (EECP) as a possible therapy for Long COVID. Design: Retrospective analysis of a contemporary, consecutive patient cohort. Setting: 7 outpatient treatment centers. Participants: Long COVID patients. Intervention: 15-35 EECP treatments. Main outcome measures: The change from baseline in 1) Patient Reported Outcome Measurement Information System (PROMIS) Fatigue; 2) Seattle Angina Questionnaire (SAQ); 3) Duke Activity Status Index (DASI); 4) 6-Minute Walk Test (6MWT); 5) Canadian Cardiovascular Society (CCS) Angina Grade; 6) Rose Dyspnea Scale (RDS); and 7) Patient Health Questionnaire (PHQ-9). Results: Compared to baseline, the PROMIS Fatigue, SAQ, DASI, and 6MWT improved by 4.63 ± 3.42 (p < 0.001), 21.44 ± 16.54 (p < 0.001), 18.08 ± 13.82 (p < 0.001), and 200.00 ± 180.14 (p = 0.002), respectively. CCS and RDS improved in 63% and 44% of patients, respectively. All patients unable to work prior to EECP were able to return post-therapy. Conclusions and relevance: EECP significantly improved validated fatigue and cardiovascular-related markers in patients with Long COVID.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".