ArticleKidney medicine2026
Concordance Analysis Between KDIGO Definition of Acute Kidney Injury and Its Coding in Clinical Practice.
Article in Kidney medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
Rationale & Objective: Acute kidney injury (AKI) in research is typically identified using KDIGO criteria based on changes in serum creatinine (SCr) levels and urine output volumes, whereas in clinical practice, AKI is documented through Study Design: Retrospective cohort study. Setting & Participants: We analyzed 54,210 hospital admissions with intensive care unit stays from 43,530 patients at Beth Israel Deaconess Medical Center over 15 years (2008-2022). Predictors: SCr levels and urine output volumes recorded during a hospital admission. Outcomes: Hospital-coded AKI, defined as the presence of AKI among the ICD-9/10 codes assigned at discharge. Analytical Approach: We quantified concordance between KDIGO-defined AKI and hospital-coded AKI using Cohen's kappa (κ) and examined patterns of disagreement. Machine learning models were trained to assess the association between SCr level and hospital-coded AKI. Results: KDIGO criteria-defined AKI had low concordance with ICD-coded AKI (κ = 0.37), whereas a formula using the maximum SCr level achieved higher concordance (κ = 0.61). KDIGO criteria frequently detected small increases in SCr levels that were not coded, whereas coding frequently detected patients with high SCr levels at presentation that were missed using KDIGO criteria. Limitations: Our analysis is confined to a single hospital system in the United States. Data used in this study lacked information about preadmission SCr baseline levels. Conclusions: Further work is needed to clarify how KDIGO criteria are used in clinical practice and to refine how AKI is identified.
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