Details

Autor(en) / Beteiligte

• Schwager, Emma
• Ghosh, Erina
• Eshelman, Larry
• Pasupathy, Kalyan S.
• Barreto, Erin F.
• Kashani, Kianoush

Titel

Accurate and interpretable prediction of ICU-acquired AKI

Ist Teil von

• Journal of critical care, 2023-06, Vol.75, p.154278-154278, Article 154278

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2023

Quelle

MEDLINE

Beschreibungen/Notizen

• We developed and validated two parsimonious algorithms to predict the time of diagnosis of any stage of acute kidney injury (any-AKI) or moderate-to-severe AKI in clinically actionable prediction windows. In this retrospective single-center cohort of adult ICU admissions, we trained two gradient-boosting models: 1) any-AKI model, predicting the risk of any-AKI at least 6 h before diagnosis (50,342 admissions), and 2) moderate-to-severe AKI model, predicting the risk of moderate-to-severe AKI at least 12 h before diagnosis (39,087 admissions). Performance was assessed before disease diagnosis and validated prospectively. The models achieved an area under the receiver operating characteristic curve (AUROC) of 0.756 at six hours (any-AKI) and 0.721 at 12 h (moderate-to-severe AKI) prior. Prospectively, both models had high positive predictive values (0.796 and 0.546 for any-AKI and moderate-to-severe AKI models, respectively) and triggered more in patients who developed AKI vs. those who did not (median of 1.82 [IQR 0–4.71] vs. 0 [IQR 0–0.73] and 2.35 [IQR 0.14–4.96] vs. 0 [IQR 0–0.8] triggers per 8 h for any-AKI and moderate-to-severe AKI models, respectively). The two AKI prediction models have good discriminative performance using common features, which can aid in accurately and informatively monitoring AKI risk in ICU patients. •We validated separate models for any acute kidney injury stage (any-AKI or stage ≥1) and moderate-to-severe AKI (stage >1).•The models are parsimonious, use commonly-available features, clinically-actionable lead times, and handle missing inputs.•The models identified 80% of any-AKI and 55% of moderate-to-severe AKI patients from admission to AKI diagnosis.