Borderline pulmonary arterial pressure in systemic sclerosis patients: a post-hoc analysis of the DETECT study
Bibliographic record
Abstract
INTRODUCTION: Patients with mean pulmonary artery pressures (mPAP) of 21 to 24 mm Hg have a so-called borderline elevation of mPAP (BoPAP)--a condition thought to represent early-stage pulmonary arterial vasculopathy. Based on the DETECT study, this post-hoc analysis examined patient characteristics of systemic sclerosis (SSc) patients with normal mPAP, BoPAP and elevated mPAP, fulfilling pulmonary arterial hypertension (PAH) criteria. METHODS: Adult patients with a duration of SSc more than 3 years, a diffusing capacity of the lung for carbon monoxide less than 60% predicted, and no previous diagnosis of any form of pulmonary hypertension (PH) underwent screening tests followed by right heart catheterization. Subjects were divided into three groups: normal mPAP, BoPAP, and PAH. Exploratory comparative and binary logistic regression analyses were performed for the BoPAP versus normal mPAP and PAH versus BoPAP groups. RESULTS: Of 244 patients evaluated, 148 (60%) had normal mPAP, 36 (15%) had BoPAP, and 60 (25%) had definite PAH. Univariable logistic regression (ULR) showed the mean tricuspid regurgitation velocity in patients with BoPAP to be intermediate between normal mPAP and PAH. In the ULR analyses BoPAP versus normal mPAP and PAH versus BoPAP, the statistically significant predictors were, amongst others: demographic, clinical, pulmonary function, echocardiographic and hemodynamic variables. CONCLUSIONS: In this exploratory post-hoc analysis of the DETECT study population patients with BoPAP could be distinguished from patients with normal mPAP and PAH, and it appears that BoPAP may be an intermediate stage on the continuum between normal PA pressures and 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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".