SynthesisKidney international2016
Methodological issues in current practice may lead to bias in the development of biomarker combinations for predicting acute kidney injury.
Synthesis in Kidney international, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Overinterpretation and misreporting of prognostic factor studies in oncology: a systematic review.British journal of cancer · 2018Pooled it
- Machine learning models for predicting acute kidney injury: a systematic review and critical appraisal.Clinical kidney journal · 2022Article
- Results from the TRIBE-AKI Study found associations between post-operative blood biomarkers and risk of chronic kidney disease after cardiac surgery.Kidney international · 2021Article
- The Differences Between Individuals Engaging in Nonsuicidal Self-Injury and Suicide Attempt Are Complex (Frontiers in psychiatry · 2020Article
- [Biomarkers of cardiac surgery-associated acute kidney injury: a narrative review].Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences · 2019Review
- Plasma endostatin predicts kidney outcomes in patients with type 2 diabetes.Kidney international · 2019Article
- Biomarkers of Acute Kidney Injury after Cardiac Surgery: A Narrative Review.BioMed research international · 2019Review
- Biomarkers of AKI Progression after Pediatric Cardiac Surgery.Journal of the American Society of Nephrology : JASN · 2018Article
- Development of biomarker combinations for postoperative acute kidney injury via Bayesian model selection in a multicenter cohort study.Biomarker research · 2018Article
- Biomarkers of Kidney Injury in Very-low-birth-weight Preterm Infants: Influence of Maternal and Neonatal Factors.In vivo (Athens, Greece)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Individual biomarkers of renal injury are only modestly predictive of acute kidney injury (AKI). Using multiple biomarkers has the potential to improve predictive capacity. In this systematic review, statistical methods of articles developing biomarker combinations to predict AKI were assessed. We identified and described three potential sources of bias (resubstitution bias, model selection bias, and bias due to center differences) that may compromise the development of biomarker combinations. Fifteen studies reported developing kidney injury biomarker combinations for the prediction of AKI after cardiac surgery (8 articles), in the intensive care unit (4 articles), or other settings (3 articles). All studies were susceptible to at least one source of bias and did not account for or acknowledge the bias. Inadequate reporting often hindered our assessment of the articles. We then evaluated, when possible (7 articles), the performance of published biomarker combinations in the TRIBE-AKI cardiac surgery cohort. Predictive performance was markedly attenuated in six out of seven cases. Thus, deficiencies in analysis and reporting are avoidable, and care should be taken to provide accurate estimates of risk prediction model performance. Hence, rigorous design, analysis, and reporting of biomarker combination studies are essential to realizing the promise of biomarkers in clinical practice.
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