Evidence mapPaperPMID 41134814Full record

ArticlePloS one2025

Quantifying the impact of clinical coding in chronic kidney disease on risk of death and COVID-19 death.

Stuart Stewart, Philip A Kalra, Evangelos Kontopantelis, Tom Blakeman, George Tilston, Smeeta Sinha

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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Stuart StewartDonal O'Donoghue Renal Research Centre, Research & Innovation, Northern Care Alliance NHS Foundation Trust, Salford, England, United Kingdom.ORCID https://orcid.org/0000-0002-7767-4308
Philip A KalraDonal O'Donoghue Renal Research Centre, Research & Innovation, Northern Care Alliance NHS Foundation Trust, Salford, England, United Kingdom.
Evangelos KontopantelisCentre for Primary Care & Health Services Research, University of Manchester, Manchester, England, United Kingdom.
Tom BlakemanCentre for Primary Care & Health Services Research, University of Manchester, Manchester, England, United Kingdom.
George TilstonNational Institute for Health and Care Research (NIHR) Manchester Biomedical Research Centre, University of Manchester, England, United Kingdom.
Smeeta SinhaDonal O'Donoghue Renal Research Centre, Research & Innovation, Northern Care Alliance NHS Foundation Trust, Salford, England, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients with biochemical evidence of chronic kidney disease (CKD) without a diagnostic code (uncoded CKD) in primary care are at increased risk of death, acute kidney injury (AKI), and unplanned hospital care. Uncoded CKD is highly prevalent and there is no data to evaluate whether patients with uncoded CKD were at an increased risk of COVID-19 death. Aim: to assess whether patients with uncoded CKD stages 3-5 were at increased risk of death and COVID-19 deaths.

methodsDescriptive and inferential analyses to measure adjusted hazard of death, and COVID-19 death in patients with CKD stages 3-5 from 2.85 million primary care patients in Greater Manchester, England. Sensitivity analyses using propensity score matching and competing risk regression.

resultsCoded CKD stages 3 and 4 (versus uncoded) were associated with significantly lower adjusted hazards of death (HR 0.81, CIs 0.77-0.86, p=<0.0001; HR 0.45, CIs 0.34-0.60, p=<0.0001, respectively), and COVID-19 death (HR 0.74, CIs 0.55-0.99, p = 0.03; HR 0.55, CIs 0.30-0.99, p = 0.045, respectively). Descriptive analyses were conducted for patients with CKD stage 5 due to low numbers of patients with uncoded CKD stage 5, precluding survival analyses.

conclusionOur retrospective cohort study suggests that clinical coding is a digital intervention associated with a lower adjusted hazard of death and COVID-19 death in patients with CKD stages 3 and 4, and should be considered a key element in the organisation and delivery of care for people with CKD.

Indexed as

Clinical CodingCOVID-19Renal Insufficiency, ChronicAdultAgedAged, 80 and overEnglandFemaleHumansMaleMiddle AgedPropensity ScoreRetrospective StudiesRisk FactorsSARS-CoV-2

Identifiers

PMID41134814
PMCPMC12551823

What Socratic holds

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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 Socratic graph.