Use of Continuous Negative Pressure Around the Chest Increases Exercise Performance in Chronic Obstructive Pulmonary Disease Patients: A Pilot Study
Bibliographic record
Abstract
BACKGROUND: Patients with severe chronic obstructive pulmonary disease (COPD) often have intrinsic positive end-expiratory pressure. Continuous positive airway pressure has been shown to decrease the inspiratory work of breathing and increases exercise capacity in these patients. OBJECTIVE: To determine whether continuous negative pressure (CNP) around the chest is able to bring the positive end-expiratory pressure closer to atmospheric pressure, thereby reducing the threshold load and increasing exercise capability. METHODS: A pilot study was undertaken with eight COPD patients who had been hospitalized for exacerbation and were close to discharge. For CNP, a shell (around the thorax from under the axillae to the mid abdomen) and wrap were used. Each of the eight patients was assessed with a 6 min walk test in three modes (in randomized order) with 30 min of rest in between: a control walk with no shell or wrap; a sham CNP in which the applied CNP was negligible; and CNP, with pressure chosen by the patient that provided maximal relief of dyspnea at rest. RESULTS: At the end of each of the 6 min walk tests, there was no difference in heart rate, oxygen saturation or level of dyspnea among the three test modes. Respiratory rate was reduced with CNP compared with sham. The patients walked furthest with CNP compared with control (mean ± SD) (313 ± 66.2 m versus 257 ± 65.2 m; P<0.01) and compared with sham. CONCLUSIONS: In the present pilot study, COPD patients improved their exercise performance with CNP.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".