ArticleBMC nephrology2021
A nomogram incorporating functional and tubular damage biomarkers to predict the risk of acute kidney injury for septic patients.
Article in BMC nephrology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.
- Prediction models for sepsis-associated acute kidney injury: a systematic review and meta-analysis.Frontiers in endocrinology · 2026Pooled it
- Plasma VGF as a Predictive Biomarker for Early Acute Kidney Injury in Critically Ill Elderly Patients:Saudi medical journal · 2026Article
- Early recognition of sepsis-associated acute kidney injury based on BioBERT-BPNN multimodal clinical data analysis.PloS one · 2026Article
- Transparent AI-driven personalized risk prediction system for acute kidney injury after total hip arthroplasty.Scientific reports · 2025Article
- Application of biomarkers in the diagnosis of kidney disease.Frontiers in medicine · 2025Review
- The nadir platelet count in the first 48 h after ICU admission is a potential predictor of acute kidney injury in hemorrhagic shock patients.BMC cardiovascular disorders · 2024Observational
- Predictive models of sepsis-associated acute kidney injury based on machine learning: a scoping review.Renal failure · 2024Article
- Article
- Construction, validation, and visualization of a web-based nomogram to predict overall survival in small-cell lung cancer patients with brain metastasis.Cancer causes & control : CCC · 2024Article
- Prediction of acute kidney injury after cardiac surgery with fibrinogen-to-albumin ratio: a prospective observational study.Frontiers in cardiovascular medicine · 2024Article
- A visualized dynamic prediction model for overall survival in patients diagnosed with brain metastases from lung squamous cell carcinoma.The clinical respiratory journal · 2023Article
- Revisiting the Role of NAG across the Continuum of Kidney Disease.Bioengineering (Basel, Switzerland) · 2023Review
- Population Pharmacokinetics of Caspofungin and Dose Simulations in Heart Transplant Recipients.Antimicrobial agents and chemotherapy · 2022Article
- The incidence, risk factors and outcomes of acute kidney injury in critically ill patients undergoing emergency surgery: a prospective observational study.BMC nephrology · 2022Observational
- Isoliquiritigenin attenuates septic acute kidney injury by regulating ferritinophagy-mediated ferroptosis.Renal failure · 2021Article
- Assessment of 17 clinically available renal biomarkers to predict acute kidney injury in critically ill patients.Journal of translational internal medicine · 2021Article
- Development and Validation of a Nomogram Incorporating Colloid Osmotic Pressure for Predicting Mortality in Critically Ill Neurological Patients.Frontiers in medicine · 2021Article
- Development and External Verification of a Nomogram for Patients with Persistent Acute Kidney Injury in the Intensive Care Unit.International journal of general medicine · 2021Article
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCombining tubular damage and functional biomarkers may improve prediction precision of acute kidney injury (AKI). Serum cystatin C (sCysC) represents functional damage of kidney, while urinary N-acetyl-β-D-glucosaminidase (uNAG) is considered as a tubular damage biomarker. So far, there is no nomogram containing this combination to predict AKI in septic cohort. We aimed to compare the performance of AKI prediction models with or without incorporating these two biomarkers and develop an effective nomogram for septic patients in intensive care unit (ICU).
methodsThis was a prospective study conducted in the mixed medical-surgical ICU of a tertiary care hospital. Adults with sepsis were enrolled. The patients were divided into development and validation cohorts in chronological order of ICU admission. A logistic regression model for AKI prediction was first constructed in the development cohort. The contribution of the biomarkers (sCysC, uNAG) to this model for AKI prediction was assessed with the area under the receiver operator characteristic curve (AUC), continuous net reclassification index (cNRI), and incremental discrimination improvement (IDI). Then nomogram was established based on the model with the best performance. This nomogram was validated in the validation cohort in terms of discrimination and calibration. The decision curve analysis (DCA) was performed to evaluate the nomogram's clinical utility.
resultsOf 358 enrolled patients, 232 were in the development cohort (69 AKI), while 126 in the validation cohort (52 AKI). The first clinical model included the APACHE II score, serum creatinine, and vasopressor used at ICU admission. Adding sCysC and uNAG to this model improved the AUC to 0.831. Furthermore, incorporating them significantly improved risk reclassification over the predictive model alone, with cNRI (0.575) and IDI (0.085). A nomogram was then established based on the new model including sCysC and uNAG. Application of this nomogram in the validation cohort yielded fair discrimination with an AUC of 0.784 and good calibration. The DCA revealed good clinical utility of this nomogram.
conclusionsA nomogram that incorporates functional marker (sCysC) and tubular damage marker (uNAG), together with routine clinical factors may be a useful prognostic tool for individualized prediction of AKI in septic patients.
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