Impact of Pulmonary Hypertension on the Response to Pulmonary Rehabilitation in Obstructive Lung Disease
Bibliographic record
Abstract
Pulmonary rehabilitation (PR) is beneficial in respiratory diseases such as COPD and pulmonary hypertension (PH). Whether PH impacts the response to PR in patients with obstructive lung disease (OLD) is unclear. We assessed the impact of PH on the outcomes and safety of PR in a cohort of patients with OLD (COPD, asthma and bronchiectasis). Patients with OLD who attended our PR program (2010-2018) were included if they had an echocardiogram performed <1 year before beginning PR. They were split based on the presence (group A) or the absence (group B) of possible PH (systolic pulmonary artery pressure (sPAP) >36 mmHg). Exercise time on endurance test (Tlim), 6-minute walk distance (6MWD), COPD assessment test (CAT) and stair-climbing test (SCT) results were collected before and after PR. Dropout rate and adverse events were also evaluated. 99 patients were included. sPAP was higher in group A (44±9 mmHg, n=24) than in group B (30±4 mmHg, n=75, p<0.0001). Baseline FEV1, CAT score and 6MWD were similar between groups (53±19 vs 56±19%, p=0.49, 20.8±6.2 vs 19.6±7.7 units, p=0.55 and 297±97 vs 304±127 m, p=0.85). Diffusion capacity was lower in group A (46±14 vs 57±21%, p=0.008). Compared to baseline, both groups improved after PR. The magnitude of improvement was not statistically different for Tlim, 6MWD and CAT score (210±360 vs 372±384 s, p=0.30, 20±51 vs 48±36 m, p=0.11 and -3±4 vs -2±4 units, p=0.49, respectively). Group A improved less in SCT (107±57% vs 226±214%, p=0.03). There was no statistically significant difference in dropout rate and adverse events. In patients with OLD, PH did not negatively impact the safety and efficacy of PR, except for the improvement in SCT.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".