Klotho as an Early Marker of Acute Kidney Injury Following Cardiac Surgery: A Systematic Review
Bibliographic record
Abstract
Acute kidney injury is a common complication following cardiac surgery (CSA-AKI). Serum creatinine levels require a minimum of 24-48 h to indicate renal injury. Nevertheless, early diagnosis remains critical for improving patient outcomes. A PRISMA-compliant systematic review of the PubMed and CENTRAL databases was performed to assess the role of Klotho as a predictive biomarker for CSA-AKI (end-of-search date: 17 February 2024). An evidence quality assessment of the four included studies was performed with the Newcastle-Ottawa scale. Among the 234 patients studied, 119 (50.8%) developed CSA-AKI postoperatively. Serum Klotho levels above 120 U/L immediately postoperatively correlated with an area under the curve (AUC) of 0.806 and 90% sensitivity. Additionally, a postoperative serum creatinine to Klotho ratio above 0.695 showed 94.7% sensitivity and 87.5% specificity, with an AUC of 92.4%, maintaining its prognostic validity for up to three days. Urinary Klotho immunoreactivity was better maintained in samples obtained via direct catheterization rather than indwelling catheter collection bags. Storage at -80 °C was necessary for delayed testing. Optimal timing for both serum and urine Klotho measurements was from the end of cardiopulmonary bypass to the time of the first ICU lab tests. In conclusion, Klotho could be a promising biomarker for the early diagnosis of CSA-AKI. Standardization of measurement protocols and larger studies are needed to validate 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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".