Early Decline in Six-Minute Walk Distance from the Time of Diagnosis Predicts Clinical Worsening in Pulmonary Arterial Hypertension
Bibliographic record
Abstract
BACKGROUND: The six-minute walk distance (6MWD) is commonly used to assess pulmonary arterial hypertension (PAH). However, the role of 6MWD in predicting outcomes in PAH is controversial. Clinical worsening is being increasingly considered as a clinically meaningful end point in PAH. OBJECTIVES: We aimed to investigate whether early longitudinal changes in 6MWD (Δ6MWD) in meters and percent predicted (%pred) from the time of diagnosis predict clinical worsening of PAH. METHODS: One hundred patients with group I PAH were retrospectively assessed. 6MWD was calculated using American (%pred US) or Canadian (%pred CAN) reference equations. Δ6MWD at 6 months were recorded. Clinical worsening was defined as either: development of right heart failure, hospital admission for PAH, referral for lung transplantation or initiation of prostanoids after oral therapy failed. Optimal 6-month differences in 6MWD to detect worsening were defined with receiver operating characteristics (ROC) analysis. RESULTS: Progressors, i.e. patients with clinical worsening, and nonprogressors showed significant differences in Δ6MWD. The most clinically significant declines in 6MWD at 6 months were ≥35 m, ≥8%pred US and ≥6%pred CAN. ROC and Cox proportional hazard analyses showed equivalent results for 6MWD %pred and meters. Six-month declines in 6MWD predicted worsening with a high specificity (94%) but a low sensitivity (33%). CONCLUSIONS: Early declines in 6MWD (within the first 6 months) predict future clinical worsening of PAH with high specificity. Δ6MWD may still be part of a comprehensive assessment of a patient's clinical status. However, given the poor sensitivity, a decline in 6MWD should be used with other clinical tools to make an appropriate assessment of the progression of PAH.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".