ArticleScientific reports2021
Development of mortality prediction model in the elderly hospitalized AKI patients.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 11 citations in OpenAlex.
- Predicting Acute Kidney Injury with Nephrotoxic Burden in Noncritical Patients: An Internal and External Validation Study.Kidney360 · 2026Article
- Assessing renal recovery after acute kidney injury in elderly patients: a retrospective cohort study.Renal failure · 2025Article
- Quinolinic acid metabolism may mitigate AKI to CKD transition.bioRxiv : the preprint server for biology · 2025Article
- Metabolic Syndrome Is Associated with the Prognosis in Elderly Critically Ill Patients with Acute Kidney Injury.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
- Combined lineage tracing and scRNA-seq reveal the activation of Sox9Cell proliferation · 2024Article
- Generalizability of an acute kidney injury prediction model across health systems.Nature machine intelligence · 2022Article
- Development and deployment of interpretable machine-learning model for predicting in-hospital mortality in elderly patients with acute kidney disease.Renal failure · 2022Article
- Prediction of Mortality Risk After Ischemic Acute Kidney Injury With a Novel Prognostic Model: A Multivariable Prediction Model Development and Validation Study.Frontiers in medicine · 2022Article
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Authors and funding
13 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute kidney injury (AKI) correlates with increased health-care costs and poor outcomes in older adults. However, there is no good scoring system to predict mortality within 30-day, 1-year after AKI in older adults. We performed a retrospective analysis screening data of 53,944 hospitalized elderly patients (age > 65 years) from multi-centers in China. 944 patients with AKI (acute kidney disease) were included and followed up for 1 year. Multivariable regression analysis was used for developing scoring models in the test group (a randomly 70% of all the patients). The established models have been verified in the validation group (a randomly 30% of all the patients). Model 1 that consisted of the risk factors for death within 30 days after AKI had accurate discrimination (The area under the receiver operating characteristic curves, AUROC: 0.90 (95% CI 0.875-0.932)) in the test group, and performed well in the validation groups (AUROC: 0.907 (95% CI 0.865-0.949)). The scoring formula of all-cause death within 1 year (model 2) is a seven-variable model including AKI type, solid tumor, renal replacement therapy, acute myocardial infarction, mechanical ventilation, the number of organ failures, and proteinuria. The area under the receiver operating characteristic (AUROC) curves of model 2 was > 0.80 both in the test and validation groups. Our newly established risk models can well predict the risk of all-cause death in older hospitalized AKI patients within 30 days or 1 year.
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