Elicit: Real-Time Kidney Damage Markers (public)
What are the most effective real-time markers of kidney cell damage?
NGAL,
[TIMP‑2]·[IGFBP7], and KIM-1 are the most effective real-time markers of kidney cell damage, showing high diagnostic accuracy when measured at appropriate time windows and achieving superior performance when combined in multi-marker panels.
Abstract
Real‐time markers for kidney cell damage most consistently report high diagnostic accuracy when measured in the appropriate clinical context and time window. Urinary neutrophil gelatinase‐associated lipocalin (NGAL) rises within 2–6 hours after injury, with studies reporting area under the curve (AUC) values up to 0.91, sensitivities of 84–100%, and specificities as high as 99.5%. Urinary [TIMP‑2]·[IGFBP7] is typically measured at 6–12 hours post‐injury and shows AUC values ranging from 0.70 to 0.94, with reported sensitivities of 42–96% and specificities up to 95%. Urinary kidney injury molecule‑1 (KIM‑1) measured at 12–24 hours post‐insult yields moderate performance (AUC 0.66–0.84) with sensitivities between 75.9% and 91.6% and specificities up to 95.2%.
When combined in multi‐marker panels, these biomarkers often achieve superior performance. For example, panels including NGAL, [TIMP‑2]·[IGFBP7], and cystatin C have produced AUC values as high as 0.98, while combinations with additional markers have reached similar levels of discrimination. These findings, drawn from a diverse set of populations and clinical settings—ranging from cardiac surgery and intensive care to emergency presentations—support the use of NGAL, [TIMP‑2]·[IGFBP7], and KIM‑1 as effective real‐time indicators of kidney cell damage.
Methods
We analyzed 40 sources from an initial pool of 999, using 8 screening criteria. Each paper was reviewed for 5 key aspects that mattered most to the research question. More on methods
Papers identified with Elicit search
n = 999
Papers screened using: Real-time Biomarker Detection, Human Participants, Diagnostic Performance Assessment, Appropriate Study Design, Comparative Assessment, Clinical Study Setting, Primary Research Quality, Clinical Utility Assessment
n = 999
Papers screened out
n = 959
Papers included for extraction
n = 40
Characteristics of Included Studies
| Study | Study Population | Biomarkers Evaluated | AKI Definition | Primary Outcome |
|---|---|---|---|---|
| Bihorac et al., 2014 | Critically ill patients (n=420) | Urinary [TIMP-2]·[IGFBP7] | No mention found | Prediction of moderate to severe acute kidney injury (AKI) within 12h |
| Piedrafita et al., 2022 | Cardiac surgery (n=1170), intensive care unit (ICU) (n=1569) | Urinary peptide signature, NGAL, calprotectin, [TIMP-2]/[IGFBP7] | KDIGO 2012 | Early AKI prediction (7-day KDIGO) |
| Sun et al., 2024 | Critically ill patients (n=417+164) | 12 urinary biomarkers, U-AKIpredTM (alpha-1-microglobulin, liver-type fatty acid-binding protein (L-FABP), IGFBP7) | KDIGO | AKI within 12h of panel measurement |
| ... | ... | ... | ... | ... |
Summary of Study Characteristics:
- Most commonly evaluated biomarkers:
- Neutrophil gelatinase-associated lipocalin (NGAL): 29 studies
- Kidney injury molecule-1 (KIM-1): 21 studies
- [TIMP-2]·[IGFBP7]: 12 studies
- AKI definitions used:
- KDIGO: 15 studies
- AKIN: 8 studies
- RIFLE: 3 studies
Effects
Individual Biomarker Performance
| Biomarker | AUC Range | Sensitivity Range | Specificity Range |
|---|---|---|---|
| [TIMP-2]·[IGFBP7] | 0.70–0.94 | 42–96% | 50–95% |
| NGAL (urine) | 0.62–0.91 | 55–100% | 64–99.5% |
| KIM-1 (urine) | 0.66–0.84 | 75.9–91.6% | 61.8–95.2% |
| ... | ... | ... | ... |
Combined Biomarker Performance
Several studies reported that combinations of biomarkers outperformed individual markers. Key findings from these studies include:
- Combination of NGAL, IL-18, and [TIMP-2] yielded an AUC of 0.973 at 12 hours post-cardiopulmonary bypass.
- Combination of five biomarkers achieved an AUC of 0.98.
Summary of Timing and Context
| Biomarker/Combination | Optimal Detection Window | Clinical Context | Performance Metrics |
|---|---|---|---|
| NGAL (urine) | 2–6 hours post-injury | Pediatric cardiopulmonary bypass, sepsis, ICU | AUC >0.9 (early), Sensitivity 84–100%, Specificity 80–99.5% |
| [TIMP-2]·[IGFBP7] | 6–12 hours post-injury | ICU, cardiac surgery, ED | AUC 0.70–0.94, Sensitivity 89–96%, Specificity 50–95% |
Factors Affecting Biomarker Performance
- Patient population: Performance varied by clinical context, including ICU, surgery, sepsis, drug-induced injury.
- AKI definition: Variability in AKI definitions (KDIGO, AKIN, RIFLE) affected comparability across studies.
References
- Ravi J. Desai et al., (2022). Kidney Damage and Stress Biomarkers for Early Identification of Drug-Induced Kidney Injury: A Systematic Review. Drug Safety.
- W. Han et al., (2008). Urinary biomarkers in the early diagnosis of acute kidney injury. Kidney International.
- S. Jarvis, (2011). The ROMA for estimating the risk of epithelial ovarian cancer in women presenting with pelvic mass. Kidney International.
- J. Koyner et al., (2010). Urinary biomarkers in the clinical prognosis and early detection of acute kidney injury. Clinical Journal.
- H. Pan et al., (2022). Comparative accuracy of biomarkers for the prediction of hospital-acquired acute kidney injury: a systematic review and meta-analysis. Critical Care.
- T. Nickolas et al., (2012). Diagnostic and prognostic stratification in the emergency department using urinary biomarkers of nephron damage.