Clinical Implementation of Urinary Neutrophil Gelatinase-Associated Lipocalin Testing for Diagnosing Acute Kidney Injury in an Academic Tertiary Care Medical Centre
Bibliographic record
Abstract
Key Points Urinary neutrophil gelatinase-associated lipocalin is a sensitive urinary biomarker in the differentiation of intrinsic (intrarenal) AKI from nonintrinsic (prerenal and postrenal) AKI. Urinary neutrophil gelatinase-associated lipocalin in addition to fractional excretion of urinary sodium and serum creatinine improves accuracy in differentiating intrinsic from nonintrinsic AKI. Background Differentiating functional AKI from structural/intrinsic AKI with tubular injury remains a clinical challenge. Urinary neutrophil gelatinase-associated lipocalin (uNGAL) has shown promise in distinguishing these conditions. This study evaluated the implementation of uNGAL in a heterogeneous medical cohort at an academic tertiary care center in Ireland over a 3-year period. Methods A retrospective audit was conducted from 2020 to 2023. Standard clinical data around the time of AKI and uNGAL request were recorded. Blinded case adjudication of the differential diagnosis of AKI cause using the standard clinical information (but not urine neutrophil gelatinase-associated lipocalin results) was performed by two expert nephrologists. Analysis of uNGAL focused on the accuracy in differentiating adjudicated (intrarenal) AKI from nonintrinsic AKI (prerenal and postrenal). Results A total of 323 uNGAL tests were performed, with 292 AKI cases adjudicated. Intrinsic AKI cases had significantly higher uNGAL and uNGAL/creatinine ratio (uNGAL/Cr) levels than nonintrinsic cases ( P < 0.001), including after excluding urinary tract infection cases. uNGAL (area under the receiver operation curve [AUC], 0.71; 95% confidence interval [CI], 0.65 to 0.77) and uNGAL/Cr (AUC, 0.73; 95% CI, 0.67 to 0.79) showed moderate discriminative performance. uNGAL (threshold [Thr] 150 ng/ml) had high sensitivity (0.87) and negative predictive value (0.82). uNGAL/Cr was similar at the 288 ng/mg Thr. Discriminative performance improved for uNGAL and uNGAL/Cr, but not for serum creatinine, fractional excretion of urinary sodium, or serum urea, after excluding urinary tract infection cases. Both uNGAL (adjusted odds ratios, 2.05; 95% CI, 1.59 to 2.71) and uNGAL/Cr (adjusted odds ratios, 2.07; 95% CI, 1.64 to 2.68) were independently associated with intrinsic AKI. Adding these biomarkers to a logistic regression model significantly improved discrimination performance (AUC, 0.79; 95% CI, 0.76 to 0.84; P = 0.0116). Conclusions The use of uNGAL improved the discriminative accuracy of differential diagnosis of AKI in clinical practice by differentiating intrinsic AKI from nonintrinsic. Specificity was low at the manufacturer's recommended Thr (150 ng/ml), but the sensitivity and negative predictive value were high in all analyses. These findings support the clinical utility of uNGAL at the 150 ng/ml Thr as a “rule-out” test for intrinsic AKI, thereby helping to direct management toward functional (prerenal) or obstructive (postrenal) causes when uNGAL is negative.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".