Urinary Biomarkers for Early Detection of Kidney Injury Following Extracorporeal Shock Wave Lithotripsy: A Systematic Review
Bibliographic record
Abstract
Extracorporeal shock wave lithotripsy (ESWL) is a commonly used, non-invasive intervention used for the treatment of urinary stones, however, it carries the risk of causing renal injury. Renal function parameters such as serum creatinine and estimated glomerular filtration rate (eGFR) often fail to detect early or subclinical damage. This systematic review evaluates the diagnostic utility of urinary and plasma biomarkers, particularly neutrophil gelatinase-associated lipocalin (NGAL), cystatin C, KIM-1, and IL-18, for early detection of renal injury following ESWL. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, databases such as PubMed, EMBASE, CENTRAL, and SCOPUS were used to identify studies published between 1st January 2015 to 15th June 2025. Eligible studies included adults undergoing ESWL which reported pre- and post-procedure urinary biomarker levels. Eight studies met the inclusion criteria, including two randomized controlled trials, four prospective cohort studies, and two controlled observational studies. Risk of bias was assessed using RoB 2.0, ROBINS-I, and the Newcastle-Ottawa Scale. Across 412 participants, NGAL was the most frequently evaluated biomarker, showing early and significant increases within six to 12 hours post-ESWL, often before changes in serum creatinine or eGFR. Cystatin C also rose consistently post-procedure and proved more sensitive than creatinine in some studies. KIM-1 and IL-18 showed high diagnostic accuracy (area under the curve (AUC) up to 0.951) for tubular injury. However, heterogeneity in ESWL protocols, sample timing, and study populations limited comparability. Some studies suggested that NGAL responses may be affected by factors like hydration or stone location. Urinary biomarkers including NGAL, cystatin C, and KIM-1 offer promising, non-invasive tools for early detection of renal injury after ESWL. Traditional markers such as serum creatinine often remain unchanged immediately post-ESWL, and novel biomarkers can reflect subclinical tubular and glomerular damage within hours of treatment. Despite these encouraging findings, variability across studies and lack of long-term outcome data warrant further standardized research. Future studies should assess biomarker kinetics in relation to ESWL parameters and their prognostic value for sustained renal dysfunction.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 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".