Heart-lung interaction in a model of COPD: importance of lung volume and direct ventricular interaction
Bibliographic record
Abstract
Chronic obstructive pulmonary disease (COPD) is associated with dynamic lung hyperinflation (DH), increased pulmonary vascular resistance (PVR), and large increases in negative intrathoracic pressure (nITP). The individual and interactive effect of these stressors on left ventricular (LV) filling, emptying, and geometry and the role of direct ventricular interaction (DVI) in mediating these interactions have not been fully elucidated. Twenty healthy subjects were exposed to the following stressors alone and in combination: 1) inspiratory resistive loading of −20 cmH2O (nITP), 2) expiratory resistive loading to cause dynamic hyperinflation (DH), and 3) normobaric-hypoxia to increase PVR (hPVR). LV volumes and geometry were assessed using triplane echocardiography. LV stroke volume (LVSV) was reduced during nITP by 7 ± 7% (mean ± SD; P < 0.001) through a 4 ± 5% reduction in LV end-diastolic volume (LVEDV) ( P = 0.002), while DH reduced LVSV by 12 ± 13% ( P = 0.001) due to a 9 ± 10% reduction in LVEDV ( P < 0.001). The combination of nITP and DH (nITP+DH) caused larger reductions in LVSV (16 ± 16%, P < 0.001) and LVEDV (12 ± 10%, P < 0.001) than nITP alone ( P < 0.05). The addition of hPVR to nITP+DH did not further reduce LV volumes. Significant septal flattening (indicating DVI) occurred in all conditions, with a significantly greater leftward septal shift occurring with nITP+DH than either condition alone ( P < 0.05). In summary, the interaction of nITP and DH reduces LV filling through DVI. However, DH may be more detrimental to LV hemodynamics than nITP, likely due to mediastinal constraint of the heart amplifying DVI.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".