ArticlePediatric research2020
The effectiveness of urinary TIMP-2 and IGFBP-7 in predicting acute kidney injury in critically ill neonates.
Article in Pediatric research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 2 syntheses or guidelines pooled it, 37 citations in OpenAlex.
- Optimizing pediatric AKI diagnosis: a patient-tailored meta-analysis of urinary TIMP-2/IGFBP7 performance across clinical scenarios and assay platforms.Frontiers in pediatrics · 2025Pooled it
- Predictive value of urinary cell cycle arrest biomarkers for all cause-acute kidney injury: a meta-analysis.Scientific reports · 2023Pooled it
- TIMP-2 and IGFBP7 for the differentiation of functional and intrinsic pediatric acute kidney injury.Pediatric research · 2026Article
- Understanding the Impact of Patent Ductus Arteriosus and Treatment Strategies on Acute Kidney Injury in Preterm Infants.American journal of perinatology · 2026Review
- Interpretable machine learning for the early prediction of acute kidney injury in preterm infants in the neonatal intensive care unit.Renal failure · 2025Article
- Advances in pediatric acute kidney injury detection and prediction: biomarkers and artificial intelligence.World journal of pediatrics : WJP · 2025Article
- Evaluation of uNGAL and TIMP-2*IGFBP7 as early biomarkers of Acute Kidney Injury in Caucasian term and preterm neonates: a prospective observational cohort study.Italian journal of pediatrics · 2025Observational
- The promise of biomarkers: precision medicine will pave a roadmap for pediatric acute kidney injury management in critically ill children.Intensive care medicine. Paediatric and neonatal · 2025Review
- Artificial intelligence and pediatric acute kidney injury: a mini-review and white paper.Frontiers in nephrology · 2025Review
- Insulin-like growth factor-1 effects on kidney development in preterm piglets.Pediatric research · 2024Article
- Utility of plasma suPAR to identify AKI and sepsis associated AKI in critically ill children.iScience · 2024Article
- Early Diagnostic and Prognostic Value of the Urinary TIMP-2 and IGFBP-7 in Acute Kidney Injury in Critically Ill Children.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2024Article
- Artificial intelligence in early detection and prediction of pediatric/neonatal acute kidney injury: current status and future directions.Pediatric nephrology (Berlin, Germany) · 2024Review
- Acute Kidney Injury in Neonatal Intensive Care Unit: Epidemiology, Diagnosis and Risk Factors.Journal of clinical medicine · 2024Review
- Urinary TIMP-2*IGFBP-7 to diagnose acute kidney injury in children receiving cisplatin.Pediatric nephrology (Berlin, Germany) · 2024Article
- Gut microbiota and neonatal acute kidney injury biomarkers.Pediatric nephrology (Berlin, Germany) · 2023Review
- Improving acute kidney injury diagnostic precision using biomarkers.Practical laboratory medicine · 2022Review
- In PICU acute kidney injury stage 3 or mortality is associated with early excretion of urinary renin.Pediatric research · 2022Article
- Derivation and validation of urinary TIMP-1 for the prediction of acute kidney injury and mortality in critically ill children.Journal of translational medicine · 2022Article
- Neonatal acute kidney injury: a case-based approach.Pediatric nephrology (Berlin, Germany) · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroudUrinary tissue inhibitor of metalloproteinase-2 (TIMP-2), insulin-like growth factor binding protein-7 (IGFBP-7) and the combination of TIMP-2 and IGFBP-7 ([TIMP-2]•[IGFBP7]) are proposed to be predictive biomarkers for acute kidney injury (AKI). The intention of our study was to determine whether there is any significant predictive value of these biomarkers for the occurrence of AKI and severe AKI in critically ill neonates.
methodsUrinary samples were serially collected in 237 neonates during neonatal intensive care unit (NICU) stay for measurements of TIMP-2 and IGFBP-7 in this prospective study. AKI diagnosis was based on KDIGO classification without urine output or serum creatinine >1.2 mg/dL.
resultsTwenty neonates developed AKI, including 11 with KDIGO stage 1, defined as mild AKI, and 9 with stages 2 and 3, defined as severe AKI. Urinary IGFBP-7 and [TIMP-2]•[IGFBP7] remained associated with AKI after adjustment for gestational age, gender and illness severity. Urinary [TIMP-2]•[IGFBP7] achieved an AUC of 0.71 (P = 0.034) and displayed a sensitivity of 88.9% and a specificity of 50.9% for discriminating severe AKI at the optimal cut-off value of 0.045.
conclusionThe combination of TIMP-2 and IGFBP-7 had independent discriminative value for severe AKI in critically ill neonates.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.