ArticleDisease markers2022
Construction and Validation of a Risk Prediction Model for Acute Kidney Injury in Patients Suffering from Septic Shock.
Article in Disease markers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.
- Pooled it
- Early prediction of sepsis in the ICU: a comparative analysis of multiple machine-learning algorithms using the MIMIC-III database.BMC medical informatics and decision making · 2026Article
- Integrative multimodal hybrid data fusion for mortality prediction.Scientific reports · 2026Article
- Prediction of severe sepsis-associated acute kidney injury incorporating immune-inflammatory profiles: development and validation of a machine learning model in a multicenter prospective cohort study.Frontiers in immunology · 2026Article
- Interpretable machine learning for the early prediction of acute kidney injury in preterm infants in the neonatal intensive care unit.Renal failure · 2025Article
- Predictive Nomogram for Acute Kidney Injury Risk with Vancomycin and Piperacillin Tazobactam in Sepsis Treatment.Medical science monitor : international medical journal of experimental and clinical research · 2025Article
- Strategic Care of Ballistic Injuries: A Retrospective Observational Study at a Moroccan Military Hospital.Cureus · 2025Article
- Aromadendrin alleviates LPS-induced kidney apoptosis and inflammation by inhibiting phosphorylation of MAPK and NF-κB signaling pathways.Histology and histopathology · 2025Article
- Comment on "Could signal peptide complement C1r/C1s, Uegf, and Bmp1, and epidermal growth factor-containing protein 1 be a therapeutic target in the pathogenesis of preeclampsia?"Revista da Associacao Medica Brasileira (1992) · 2025Article
- Machine Learning-Based Prediction Model for Multidrug-Resistant Organisms Infections: Performance Evaluation and Interpretability Analysis.Infection and drug resistance · 2025Article
- Development and external validation of a nomogram for the early prediction of acute kidney injury in septic patients: a multicenter retrospective clinical study.Renal failure · 2024Article
- Interleukin-10: Genetic and biochemical prediction of sepsis-induced acute kidney injury in critically ill patients in intensive care unit: A cross-sectional study.Journal of the Chinese Medical Association : JCMA · 2024Article
- A dynamic model to predict early occurrence of acute kidney injury in ICU hospitalized cirrhotic patients: a MIMIC database analysis.BMC gastroenterology · 2024Article
- A clinical risk score for predicting acute kidney injury in sepsis patients receiving normal saline in Northern Thailand: a retrospective cohort study.Acute and critical care · 2024Article
- An early warning model to predict acute kidney injury in sepsis patients with prior hypertension.Heliyon · 2024Article
- Assessment of the renal angina index in patients hospitalized in a cardiac intensive care unit.Scientific reports · 2024Article
- The Relationship Between Acute Kidney Injury in Sepsis Patients and Coagulation Dysfunction and Prognosis.Open access emergency medicine : OAEM · 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
- Construction of a Nomogram-Based Prediction Model for the Risk of Diabetic Kidney Disease in T2DM.Diabetes, metabolic syndrome and obesity : targets and therapy · 2024Article
- Association of serum phosphate and changes in serum phosphate with 28-day mortality in septic shock from MIMIC-IV database.Scientific reports · 2023Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAcute kidney injury (AKI) is an important complication in critically ill patients, especially in sepsis and septic shock patients. Early prediction of AKI in septic shock can provide clinicians with sufficient information for timely intervention so that improve the patients' survival rate and quality of life. The aim of this study was to establish a nomogram that predicts the risk of AKI in patients with septic shock in the intensive care unit (ICU).
methodsThe data were collected from the Medical Information Mart for Intensive Care III (MIMIC-III) database between 2001 and 2012. The primary outcome was AKI in the 48 h following ICU admission. Univariate and multivariate logistic regression analyses were used to screen the independent risk factors of AKI. The performance of the nomogram was evaluated according to the calibration curve, receiver operating characteristic (ROC) curve, decision curve analysis, and clinical impact curve.
resultsA total of 2415 patients with septic shock were included in this study. In the training and validation cohort, 1091 (64.48%) of 1690 patients and 475 (65.52%) of 725 patients developed AKI, respectively. The predictive factors for nomogram construction were gender, ethnicity, congestive heart failure, diabetes, obesity, Simplified Acute Physiology Score II (SAPS II), angiotensin-converting enzyme inhibitors (ACEI) or angiotensin receptor blockers (ARBs), bilirubin, creatinine, blood urea nitrogen (BUN), and mechanical ventilation. The model had a good discrimination with the area under the ROC curve of 0.756 and 0.760 in the training and validation cohorts, respectively. The calibration curve for probability of AKI in septic shock showed optimal agreement between prediction by nomogram and actual observation. Decision curve and clinical impact curve analysis indicated that the nomogram conferred high clinical net benefit.
conclusionThe proposed nomogram can quickly and effectively predict the risk of AKI at an early stage in patients with septic shock in ICU, which can provide information for timely and efficient intervention in patients with septic shock in the ICU setting.
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