ReviewUrology annals
Atlas of predictive tools and scoring systems for outcomes in patients with posterior urethral valves: A comprehensive review of the literature.
Review in Urology annals. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Posterior urethral valves (PUVs) are a common cause of congenital bladder outlet obstruction and obstructive uropathy in male infants and are a leading cause of chronic kidney disease (CKD)/end-stage renal failure (ESRF) in the pediatric population. Despite this, it remains challenging to predict which patients will go on to develop CKD/ESRF, and thus management and follow-up are left to the discretion of the treating department. Many different methods have been proposed to predict outcomes in these patients and several tools, including predictive scores and models, have been published. Here, we provide an up-to-date summary of the tools currently published. A comprehensive search of literature available on MEDLINE and Google Scholar was performed to identify scoring systems, predictive models, and predictive tools relating to progression to CKD/ESRF/bladder dysfunction in patients with PUVs. Six predictive tools were identified and so were included in the analysis. Three are based on clinical/biochemical findings, 2 utilize machine learning/artificial intelligence, and one is purely based on radiological findings. Three out of 6 have undergone some form of external validation. Four provide a numerical risk and 2 stratify patients into risk categories. There are currently 6 predictive tools that have been published that quantify the risk of developing long-term complications associated with PUVs. Further validation is required to establish these scores/predictive models as a clinical standard of care.
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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.