ArticleNephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association2022
Development and external validation of a diagnostic model for biopsy-proven acute interstitial nephritis using electronic health record data.
Article in Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 13 papers.
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13 citing papers in PubMed, 24 citations in OpenAlex.
- Concordance of Prebiopsy and Postbiopsy Diagnosis in Hospitalized Patients with Acute Kidney Injury.Kidney360 · 2026Article
- Associations between Immune-related Adverse Events and Prognosis in Cancer Patients Receiving Immune Checkpoint Inhibitor Therapy.Internal medicine (Tokyo, Japan) · 2026Review
- Immune Checkpoint Inhibitor-Associated Acute Kidney Injury: A Single-Center Experience of Biopsy-Proven Cases.Journal of clinical medicine · 2025Article
- External Validation of an Electronic Health Record-Based Diagnostic Model for Histological Acute Tubulointerstitial Nephritis.Journal of the American Society of Nephrology : JASN · 2025Article
- Noninvasive Diagnosis of Acute Tubulointerstitial Nephritis in Clinical Practice.Journal of the American Society of Nephrology : JASN · 2025Article
- Advances in the diagnosis of early biomarkers for acute kidney injury: a literature review.BMC nephrology · 2025Review
- Urinary RANTES and MCP-1 as noninvasive biomarkers for differential diagnosis and prediction of treatment response in acute interstitial nephritis.Clinical kidney journal · 2025Article
- All-cause and immune checkpoint inhibitor-associated acute kidney injury in immune checkpoint inhibitor users: a meta-analysis of occurrence rate, risk factors and mortality.Clinical kidney journal · 2024Article
- Precision management of acute kidney injury in the intensive care unit: current state of the art.Intensive care medicine · 2023Review
- Biomarkers in acute kidney injury: On the cusp of a new era?The Journal of clinical investigation · 2023Article
- Identification and validation of urinary CXCL9 as a biomarker for diagnosis of acute interstitial nephritis.The Journal of clinical investigation · 2023Article
- Mortality after acute kidney injury and acute interstitial nephritis in patients prescribed immune checkpoint inhibitor therapy.Journal for immunotherapy of cancer · 2022Observational
- The role of kidney biopsy in immune checkpoint inhibitor nephrotoxicity.Frontiers in medicine · 2022Review
Corrections and comments
- Erratum issued
Authors and funding
16 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundPatients with acute interstitial nephritis (AIN) can present without typical clinical features, leading to a delay in diagnosis and treatment. We therefore developed and validated a diagnostic model to identify patients at risk of AIN using variables from the electronic health record.
methodsIn patients who underwent a kidney biopsy at Yale University between 2013 and 2018, we tested the association of >150 variables with AIN, including demographics, comorbidities, vital signs and laboratory tests (training set 70%). We used least absolute shrinkage and selection operator methodology to select prebiopsy features associated with AIN. We performed area under the receiver operating characteristics curve (AUC) analysis with internal (held-out test set 30%) and external validation (Biopsy Biobank Cohort of Indiana). We tested the change in model performance after the addition of urine biomarkers in the Yale AIN study.
resultsWe included 393 patients (AIN 22%) in the training set, 158 patients (AIN 27%) in the test set, 1118 patients (AIN 11%) in the validation set and 265 patients (AIN 11%) in the Yale AIN study. Variables in the selected model included serum creatinine {adjusted odds ratio [aOR] 2.31 [95% confidence interval (CI) 1.42-3.76]}, blood urea nitrogen:creatinine ratio [aOR 0.40 (95% CI 0.20-0.78)] and urine dipstick specific gravity [aOR 0.95 (95% CI 0.91-0.99)] and protein [aOR 0.39 (95% CI 0.23-0.68)]. This model showed an AUC of 0.73 (95% CI 0.64-0.81) in the test set, which was similar to the AUC in the external validation cohort [0.74 (95% CI 0.69-0.79)]. The AUC improved to 0.84 (95% CI 0.76-0.91) upon the addition of urine interleukin-9 and tumor necrosis factor-α.
conclusionsWe developed and validated a statistical model that showed a modest AUC for AIN diagnosis, which improved upon the addition of urine biomarkers. Future studies could evaluate this model and biomarkers to identify unrecognized cases of AIN.
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