ArticleClinical and translational gastroenterology2019
Development and Validation of a Model to Predict Acute Kidney Injury in Hospitalized Patients With Cirrhosis.
Article in Clinical and translational gastroenterology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 27 citations in OpenAlex.
- APASL clinical practice guidelines on the management of acute kidney injury in acute-on-chronic liver failure.Hepatology international · 2024Guideline
- Characterization of Risk Prediction Models for Acute Kidney Injury: A Systematic Review and Meta-analysis.JAMA network open · 2023Pooled it
- Linear correlation between white blood cell counts and the progression and prognosis of acute kidney injury.The Journal of international medical research · 2025Trial
- Clinical diagnosis and biomarkers of acute kidney injury in liver cirrhosis: a systematic review.Therapeutic advances in gastroenterology · 2026Review
- Development and validation of machine learning models for predicting acute kidney injury in acute-on-chronic liver failure: a multimodel comparative study.Renal failure · 2025Article
- Tracking the trajectory of kidney dysfunction in cirrhosis: the acute kidney injury: chronic kidney disease spectrum.Clinical and molecular hepatology · 2025Review
- A novel risk-predicted nomogram for acute kidney injury progression in decompensated cirrhosis: a double-center study in Vietnam.International urology and nephrology · 2025Article
- Leveraging Large Language Models for Predicting Postoperative Acute Kidney Injury in Elderly Patients.BME frontiers · 2025Article
- A dynamic model to predict early occurrence of acute kidney injury in ICU hospitalized cirrhotic patients: a MIMIC database analysis.BMC gastroenterology · 2024Article
- Prediction of acute kidney injury in patients with liver cirrhosis using machine learning models: evidence from the MIMIC-III and MIMIC-IV.International urology and nephrology · 2024Article
- Review
- Serum Cystatin C within 24 hours after admission: a potential predictor for acute kidney injury in Chinese patients with community acquired pneumonia.Renal failure · 2023Article
- The kidney releases a nonpolymerizing form of uromodulin in the urine and circulation that retains the external hydrophobic patch domain.American journal of physiology. Renal physiology · 2022Article
- A prediction model for acute kidney injury in adult patients with hemophagocytic lymphohistiocytosis.Frontiers in immunology · 2022Article
- Nomogram Prediction Model of Serum Chloride and Sodium Ions on the Risk of Acute Kidney Injury in Critically Ill Patients.Infection and drug resistance · 2022Article
- Prognostic nutritional index predicts acute kidney injury and mortality of patients in the coronary care unit.Experimental and therapeutic medicine · 2021Article
- Development and Validation of a Nomogram for Predicting Drug-Induced Acute Kidney Injury in Hospitalized Patients: A Case-Control Study Based on Propensity-Score Matching.Frontiers in pharmacology · 2021Article
- Hospital-Acquired Versus Community-Acquired Acute Kidney Injury in Patients With Cirrhosis: A Prospective Study.The American journal of gastroenterology · 2020Article
Corrections and comments
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Authors and funding
14 authors at 6 institutions in 1 country.
Funding
Abstract
objectivesAcute kidney injury (AKI) is a common complication in hospitalized patients with cirrhosis which contributes to morbidity and mortality. Improved prediction of AKI in this population is needed for prevention and early intervention. We developed a model to identify hospitalized patients at risk for AKI.
methodsAdmission data from a prospective cohort of hospitalized patients with cirrhosis without AKI on admission (n = 397) was used for derivation. AKI development in the first week of admission was captured. Independent predictors of AKI on multivariate logistic regression were used to develop the prediction model. External validation was performed on a separate multicenter cohort (n = 308).
resultsIn the derivation cohort, the mean age was 57 years, the Model for End-Stage Liver Disease score was 17, and 59 patients (15%) developed AKI after a median of 4 days. Admission creatinine (OR: 2.38 per 1 mg/dL increase [95% CI: 1.47-3.85]), international normalized ratio (OR: 1.92 per 1 unit increase [95% CI: 1.92-3.10]), and white blood cell count (OR: 1.09 per 1 × 10/L increase [95% CI: 1.04-1.15]) were independently associated with AKI. These variables were used to develop a prediction model (area underneath the receiver operator curve: 0.77 [95% CI: 0.70-0.83]). In the validation cohort (mean age of 53 years, Model for End-Stage Liver Disease score of 16, and AKI development of 13%), the area underneath the receiver operator curve for the model was 0.70 (95% CI: 0.61-0.78). DISCUSSION: A model consisting of admission creatinine, international normalized ratio, and white blood cell count can identify patients with cirrhosis at risk for in-hospital AKI development. On further validation, our model can be used to apply novel interventions to reduce the incidence of AKI among patients with cirrhosis who are hospitalized.
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