Improved Mortality and Haemodynamics with Milrinone in Cardiogenic Shock Due to Acute Decompensated Heart Failure
Bibliographic record
Abstract
AIMS: Studies in cardiogenic shock (CS) often have a heterogeneous population of patients, including those with acute myocardial infarction and acute decompensated heart failure (ADHF-CS). The therapeutic profile of milrinone may benefit patients with ADHF-CS. We compared the outcomes and haemodynamic trends in ADHF-CS receiving either milrinone or dobutamine. METHODS AND RESULTS: Patients presenting with ADHF-CS (from 2014 to 2020) treated with a single inodilator (milrinone or dobutamine) were included in this study. Clinical characteristics, outcomes, and haemodynamic parameters were collected. The primary endpoint was 30 day mortality, with censoring at the time of transplant or left ventricular assist device implantation. A total of 573 patients were included, of which 366 (63.9%) received milrinone and 207 (36.1%) received dobutamine. Patients receiving milrinone were younger, had better kidney function, and lower lactate at admission. In addition, patients receiving milrinone received mechanical ventilation or vasopressors less frequently, whereas a pulmonary artery catheter was more frequently used. Milrinone use was associated with a lower adjusted risk of 30 day mortality (hazard ratio = 0.52, 95% confidence interval 0.35-0.77). After propensity-matching, the use of milrinone remained associated with a lower mortality (hazard ratio = 0.51, 95% confidence interval 0.27-0.96). These findings were associated with improved pulmonary artery compliance, stroke volume, and right ventricular stroke work index. CONCLUSIONS: The use of milrinone compared with dobutamine in patients with ADHF-CS is associated with lower 30 day mortality and improved haemodynamics. These findings warrant further study in future randomized controlled trials.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".