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.

Paper search

Using your research question "What are the most effective real-time markers of kidney cell damage?", we searched across over 126 million academic papers from the Semantic Scholar corpus. We retrieved the 999 papers most relevant to the query.

Screening

We screened in sources based on their abstracts that met these criteria:

Data extraction

We asked a large language model to extract each data column below from each paper. We gave the model the extraction instructions shown below for each column.

Results

Characteristics of Included Studies

Study Study Population Biomarkers Evaluated AKI Definition Primary Outcome Full text retrieved
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 No
Piedrafita et al., 2022 Cardiac surgery (n=1170), intensive care unit (ICU) (n=1569) Urinary peptide signature, NGAL, calprotectin, [TIMP-2]/[IGFBP7] Kidney Disease: Improving Global Outcomes (KDIGO) 2012 Early AKI prediction (7-day KDIGO) Yes
Sun et al., 2024 Critically ill patients (n=417+164) 12 urinary biomarkers, U-AKIpredTM KDIGO AKI within 12h of panel measurement No
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Summary of Study Characteristics

Individual Biomarker Performance

Biomarker Area Under the Curve (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%
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Combined Biomarker Performance

Timing of Detection and Clinical 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%
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Factors Affecting Biomarker Performance

References

  1. Ravi J. Desai, C. Kazarov, Adrian Wong et al. (2022). Kidney Damage and Stress Biomarkers for Early Identification of Drug-Induced Kidney Injury
  2. W. Han et al. (2008). Urinary biomarkers in the early diagnosis of acute kidney injury. Kidney International
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