Identifying children who develop severe chronic kidney disease using primary care records

Despite increased consultation frequency and several symptoms being associated with severe chronic kidney disease, the positive predictive value of symptoms is low given disease rarity making earlier diagnosis challenging.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2025-02-10
DOI
https://doi.org/10.1371/journal.pone.0314084
Citations
3
Primary Topic
Dialysis and Renal Disease Management
Type
article
Field-Weighted Citation Impact
4.29

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identifying children who develop severe chronic kidney disease using primary care records

Manish D. Sinha, Tim Jones, Amanda Owen‐Smith, Matthew J Ridd et al.
3 citations
PLoS ONE
Dialysis and Renal Disease Management
4.29
article

Identifying children who develop severe chronic kidney disease using primary care records

Manish D. Sinha, Tim Jones, Amanda Owen‐Smith, Matthew J Ridd, Yoav Ben‐Shlomo, Maria Theresa Redaniel, Lucy Plumb, Fergus John Caskey
article en
3 citations

Abstract

Despite increased consultation frequency and several symptoms being associated with severe chronic kidney disease, the positive predictive value of symptoms is low given disease rarity making earlier diagnosis challenging.

PLoS ONEVol. 20(2)
University Hospitals Bristol NHS Foundation Trust (GB), University of Bristol (GB), Evelina London Children's Healthcare (GB)
National Institute for Health and Care Research, Department of Health and Social Care
Peace, Justice and strong institutions
Openalex Percentile: Top 7%
Dialysis and Renal Disease Management
4.29
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.