Effects of levosimendan on respiratory muscle function in patients weaning from mechanical ventilation
Bibliographic record
Abstract
Respiratory muscle weakness frequently develops in critically ill patients and is associated with adverse outcome, including difficult weaning from mechanical ventilation. Today, no drug is approved to improve respiratory muscle function in these patients. Previously, we have shown that the calcium sensitizer levosimendan improves calcium sensitivity of human diaphragm muscle fibers in vitro and contractile efficiency of the diaphragm in healthy subjects. The main purpose of this study is to investigate the effects of levosimendan on diaphragm contractile efficiency in mechanically ventilated patients. In a double-blind randomized placebo-controlled trial, mechanically ventilated patients performed two 30-min continuous positive airway pressure (CPAP) trials with 5-h interval. After the first CPAP trial, study medication (levosimendan 0.2 µg/kg/min continuous infusion or placebo) was administered. During the CPAP trials, electrical activity of the diaphragm (EA di ), transdiaphragmatic pressure ( P di ), and flow were measured. Neuromechanical efficiency (primary outcome parameter) was calculated. Thirty-nine patients were included in the study. Neuromechanical efficiency was not different during the CPAP trial after levosimendan administration compared to the CPAP trial before study medication. Tidal volume and minute ventilation were higher after levosimendan administration (11 and 21%, respectively), whereas EA di and P di were higher in both groups in the CPAP trial after study medication compared to the CPAP trial before study medication. Levosimendan does not improve diaphragm contractile efficiency.
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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 | 0.001 | 0.002 |
| 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 | 0.000 | 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".