Procedural Variation May Contribute to 6-Minute Walk Distance Variability in Real-World Pediatric Pulmonary Arterial Hypertension Study
Bibliographic record
Abstract
The six-minute walk test (6MWT) is a common method to assess submaximal exercise capacity in children and adults with pulmonary arterial hypertension (PAH) and other chronic diseases. There is no guideline specifically for 6MWT in children. In this observational pilot study, we evaluated the impact of procedural variations on the outcome of the 6MWT in the real-world clinical setting at pediatric PAH programs. We collected 6MWT data from 33 children with PAH participating in a multicenter, prospective, non-interventional study. Data range/quantiles and standard deviation (SD) were used to describe distribution of the six-minute walk distance (6MWD) and data variability. Levene's test was used to test for heterogeneity of variance with the two sites of similar altitude and their age/height/weight-matched Panama Function Class II participants. We analyzed all 33 eligible participants and their qualified first walks at five centers (A-E) with 6MWD ranges of 420-570, 357-683, 418-481, 400-700, 377-549 m, respectively. Site D performed the 6MWT in a busy hallway and allowed parental/caregiver's cheering, while Site E performed the 6MWT in a secluded area with no parental/caregiver involvement. Mean 6MWD and SD for Sites D and E were 547 (125) and 432 (67.5) meters, respectively (p = 0.03). In conclusion, procedural variations seem to associate with 6MWD data variability. Although interpretation of our results is limited by the small sample size, our findings suggest that standardizing pediatric 6MWT procedures are needed.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".