Hemodynamic effects of incremental dynamic hyperinflation
Bibliographic record
Abstract
Dynamic hyperinflation (DH) is common in COPD and is often associated with exertional dyspnea. However, there is increasing evidence that DH may also impair hemodynamics via adverse cardiopulmonary interaction, though the mechanisms responsible remain unclear. As such, we examined the effect of incremental DH on left ventricular (LV) filling and ejection, and the role of direct ventricular interaction (DVI). We hypothesized that increasing DH would reduce LV end diastolic volume (LVEDV) and stroke volume (LVSV) due to DVI. 23 healthy subjects were randomly exposed to varying degrees of expiratory loading to induce DH such that end-expiratory lung volumes were increased by 25, 50, 75 and 100%, where 100% corresponded to an inspiratory reserve volume (IRV) of <0.5L. LV volumes, LV geometry, IVC collapsibility (cIVC) and LV end-systolic wall-stress (LVESWS) were assessed by tri-plane echocardiography. 25% DH reduced LVEDV (-6±5%) and LVSV (-9±8%). 50% DH elicited a similar response in LVEDV (-6±7%) and LVSV (-11±10%). 75% DH caused a larger reduction (-9±7% and -16±10%, respectively), which was associated with significant septal flattening as indicated by a 49±70% increase in the radius of septal curvature at end-diastole (RSC-ED). 100% DH caused the largest reduction in LVEDV and LVSV (-13±9% and -18±9%). 100% DH also caused the largest increase in RSC-ED (56±63%). cIVC, MAP and LV afterload (LVESWS) were unchanged at all levels of DH. Modest DH reduces LVSV due to under-filling of the LV, likely due to increased PVR. At higher levels of DH, DVI may be the primary cause of reduced LVSV, as indicated by septal flattening due to a greater relative increase in RV pressure and/or mediastinal constraint.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".