Single versus multi‐drug antimicrobial surgical infection prophylaxis for left ventricular assist devices: A systematic review and meta‐analysis
Bibliographic record
Abstract
Infection remains the Achilles heel of left ventricular assist device (LVAD) therapy. However, an optimal antimicrobial surgical infection prophylaxis (SIP) regimen has not been established. This study evaluated the efficacy of a single-drug SIP compared to a multi-drug SIP on clinical outcomes in patients undergoing continuous-flow LVAD (CF-LVAD) and pulsatile LVAD (P-LVAD) implantation. An electronic search was performed to identify studies in the English literature on SIP regimens in patients undergoing LVAD implantation. Identified articles were assessed for inclusion and exclusion criteria. Fourteen articles with 1,311 (CF-LVAD: 888; P-LVAD: 423) patients were analyzed. Overall, 501 (38.0%) patients received single-drug SIP, whereas 810 (62.0%) received multi-drug SIP. Time to infection was comparable between groups. There was no significant difference in overall incidence of LVAD-specific infections [single-drug: 18.7% vs. multi-drug: 24.8%, P = 0.49] including driveline infections [single-drug: 14.1% vs. multi-drug: 20.8%, P = 0.37]. Compared to single-drug SIP, patients who received multi-drug SIP had a significantly lower survival rate [single-drug: 90.0% vs. multi-drug: 76.0%, P = 0.01] and infection-free survival rate [single-drug: 88.4% vs. multi-drug: 77.3%, P = 0.04] at 90 days. However, there were no significant differences in 1-year survival and 1-year infection-free survival between groups. No survival differences were observed in the CF-LVAD subset as well. This study demonstrated no additional advantage of a multi-drug compared to a single-drug regimen for SIP. Although there was a modest advantage in early survival among CF-LVAD and P-LVAD patients who received single-drug SIP, there were no significant differences in the 1-year survival and 1-year infection-free survival.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.022 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".