Levosimendan to Facilitate Weaning From Cardiorespiratory Support in Critically Ill Patients: A Meta-Analysis
Bibliographic record
Abstract
Background: Cardiopulmonary support, as extracorporeal membrane oxygenation (ECMO) or mechanical ventilation (MV), is crucial for ICU patients. However, some of these patients are difficult to wean. Therefore, we aimed to assess the efficacy and safety of levosimendan in facilitating weaning from cardiorespiratory support in this patient population. Methods: We searched for potentially relevant articles in PubMed, Embase, China National Knowledge Infrastructure, Wanfang, and the Cochrane database from inception up to Feb 30, 2021. Studies focusing on weaning data in MV/ECMO adult patients who received levosimendan compared to controls were included. We used the Cochrane risk of bias tool or the Newcastle-Ottawa Quality Assessment Scale to evaluate the study quality. The primary outcome was the weaning rate from MV/ECMO. Secondary outcomes were mortality, duration of MV, and ICU stay. Subgroup analysis, sensitivity analysis, and publication bias were also conducted. Results: Eighteen studies with 2,274 patients were included. The quality of the included studies was low to moderate. Overall, levosimendan effectively improved weaning rates from MV/ECMO [odds ratio (OR) = 2.32; 95%CI, 1.60–3.36; P < 0.00001, I 2 = 68%]. Subgroup analyses confirmed the higher successful weaning rates in ventilated patients with low left ventricular ejection fractions (OR = 4.06; 95%CI, 2.16–7.62), patients with ECMO after cardiac surgery (OR = 2.04; 95%CI, 1.25–3.34), and patients with ECMO and cardiogenic shock (OR = 1.98; 95%CI, 1.34–2.91). However, levosimendan showed no beneficial effect on patients with MV weaning difficulty (OR = 2.28; 95%CI, 0.72–7.25). Additionally, no differences were found concerning the secondary outcomes between the groups. Conclusions: Levosimendan therapy significantly increased successful weaning rates in patients with cardiopulmonary support, especially patients with combined cardiac insufficiency. Large-scale, well-designed RCTs will be needed to define the subgroup of patients most likely to benefit from this strategy.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.045 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".