Acute Kidney Injury in Cardiorenal Syndrome Type 1 Patients: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: We evaluated the epidemiology and outcome of acute kidney injury (AKI) in patients with cardiorenal syndrome type 1 (CRS-1) and its subgroups: acute heart failure (AHF), acute coronary syndrome (ACS) and after cardiac surgery (CS). SUMMARY: We performed a systematic review and meta-analysis. CRS-1 was defined by AKI (based on RIFLE, AKIN and KDIGO), worsening renal failure (WRF) and renal replacement therapy (RRT). We investigated the three most common clinical causes of CRS-1: AHF, ACS and CS. Out of 332 potential papers, 64 were eligible - with AKI used in 41 studies, WRF in 25 and RRT in 20. The occurrence rate of CRS-1, defined by AKI, WRF and RRT, was 25.4, 22.4 and 2.6%, respectively. AHF patients had a higher occurrence rate of CRS-1 compared to ACS and CS patients (AKI: 47.4 vs. 14.9 vs. 22.1%), but RRT was evenly distributed among the types of acute cardiac disease. AKI was associated with an increased mortality rate (risk ratio = 5.14, 95% CI 3.81-6.94; 24 studies and 35,227 patients), a longer length of stay in the intensive care unit [LOSICU] (median duration = 1.37 days, 95% CI 0.41-2.33; 9 studies and 10,758 patients) and a longer LOS in hospital [LOShosp] (median duration = 3.94 days, 95% CI 1.74-6.15; 8 studies and 35,227 patients). Increasing AKI severity was associated with worse outcomes. The impact of CRS-1 defined by AKI on mortality was greatest in CS patients. RRT had an even greater impact compared to AKI (mortality risk ratio = 9.2, median duration of LOSICU = 10.6 days and that of LOShosp = 20.2 days). KEY MESSAGES: Of all included patients, almost one quarter developed AKI and approximately 3% needed RRT. AHF patients experienced the highest occurrence rate of AKI, but the impact on mortality was greatest in CS patients.
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How this classification was reachedexpand
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.038 | 0.004 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".