Nephroprotective Effects of Cilastatin in People at Risk of Acute Kidney Injury: A Systematic Review and Meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Rationale & Objective: Cilastatin is an inhibitor of drug metabolism in the proximal tubule that demonstrates nephroprotective effects in animals. It has been used in humans in combination with the antibiotic imipenem to block imipenem's renal metabolism. This systematic review and meta-analysis evaluated the nephroprotective effects of cilastatin in humans. Study Design: Systematic review and meta-analysis of observational (comparative effectiveness) studies or randomized clinical trials (RCTs). Setting & Study Populations: People of any age at risk of acute kidney injury (AKI). Selection Criteria for Studies: We systematically searched MEDLINE, Embase, Web of Science, and the Cochrane Controlled Trials registry from database inception to November 2023 for observational studies or RCTs that compared kidney outcomes among groups treated with cilastatin, either alone or as combination imipenem-cilastatin, versus an inactive or active control group not treated with cilastatin. Data Extraction: Two reviewers independently evaluated studies for inclusion and risk of bias. Analytical Approach: statistic. Results: = 0%). The overall certainty of the evidence was low due to heterogeneity of the results, high risk of bias, and indirectness among the identified studies. Limitations: Clinical and statistical heterogeneity could not be fully explained due to a limited number of studies. Conclusions: Patients treated with imipenem-cilastatin developed AKI less frequently and had lower serum creatinine concentration following treatment than control groups or those who had received comparator antibiotics. Larger clinical trials with less risk of detection bias due to lack of allocation concealment and blinding are needed to establish the efficacy of cilastatin for AKI prevention.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.030 | 0.003 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 it