Risk of acute kidney injury associated with anti-pseudomonal and anti-MRSA antibiotic strategies in critically ill patients
Bibliographic record
Abstract
BACKGROUND: An increased risk of acute kidney injury (AKI) with the widely prescribed piperacillin-tazobactam(PTZ)-vancomycin combination in hospitalized patients has recently been reported, but evidence in ICU patients remain uncertain. This study evaluates the association between the exposure of various broad-spectrum antibiotic regimens with Pseudomonas and/or methicillin-resistance Staphylococcus aureus (MRSA) coverage and the risk of AKI in critically ill patients. METHODS AND FINDINGS: A retrospective cohort study based on the publicly available MIMIC-III database reporting hospitalization data from ICU patients from a large academic medical center between 2001 and 2012. Adult patients receiving an anti-pseudomonal or an anti-MRSA agent in the ICU for more than 24-hours were included. Non-PTZ anti-pseudomonal agents were compared to PTZ; non-vancomycin agents covering MRSA were compared to vancomycin; and their combinations were compared to the PTZ-vancomycin combination. The primary outcome was defined as new or worsening AKI within 7 days of the antibiotic exposure using an adjusted binomial generalized estimating equation. Overall, 18 510 admissions from 15 673 individual patients, cumulating 169 966 days of antibiotherapy were included. When compared to PTZ, exposure to another anti-pseudomonal agent was associated with lower AKI risk (OR, 0.85; 95% CI, 0.80-0.91; p < .001). When compared to vancomycin, exposure to another anti-MRSA was also associated with lower AKI risk (OR, 0.71; 95% CI, 0.64-0.80; p < .001). Finally, when compared to the PTZ-vancomycin combination, exposure to another regimen with a similar coverage was associated with an even lower risk (OR, 0.63; 95% CI; 0.54-0.73; p < .001). A sensitivity analysis of patients with high illness severity showed similar results. CONCLUSIONS: These results suggest that the risk of AKI in ICU patients requiring antibiotherapy may be partially mitigated by the choice of antibiotics administered. Further clinical trials are required to confirm these findings.
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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 | 0.004 |
| 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 | 0.001 |
| 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".