Calcium Channel Blockers and Clinical Outcomes in Patients with Continuous-Flow Left Ventricular Assist Devices
Bibliographic record
Abstract
AIMS: Current guidelines suggest calcium channel blockers (CCBs) as the second or third option for blood pressure management in patients with left ventricular assist device (LVAD). However, the clinical outcomes of patients with LVAD who receive CCBs remain unclear. Our study aims to analyse the association of CCBs with clinical outcomes in patients after LVAD implantation. METHODS AND RESULTS: This is a retrospective analysis based on the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) from 2006 to 2017, and adult patients who were alive with LVAD and CCB treatment information at 6 months after implantation were included. Among 10 717 patients, 1369 received CCBs 6 months after implantation, and there was an increasing trend of CCB use after LVAD. Patients receiving CCB therapy at 6 months had a similar 5 year survival rate to those not receiving CCB [49.6%, 95% confidence interval (CI): 47.5-51.7% vs. 51.1%, 95% CI: 45.3-56.7%]. In both Cox and competing risk regressions after adjusting for confounding factors, CCB treatment at 6 months after implantation was not associated with long-term mortality [hazard ratio (HR): 1.03, 95% CI: 0.91-1.17, P = 0.624 and subdistribution HR (SHR): 1.07, 95% CI: 0.95-1.22, P = 0.260]. Consistently, in time-varying models, CCB treatment was not linked to long-term mortality (HR: 0.97, 95% CI: 0.87-1.09, P = 0.682 and SHR: 1.05, 95% CI: 0.94-1.18, P = 0.359). This null association remained in subgroup analysis according to device strategy and propensity-matching analyses. Neurological dysfunction, stroke, bleeding, rehospitalization, and renal dysfunction were more likely to occur among those with CCB when compared with those without CCB treatment. CONCLUSIONS: In patients with LVAD, CCB therapy fails to show benefits in long-term survival and is associated with increased incidences of neurological dysfunction, bleeding, renal dysfunction, and rehospitalization.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".