Evidence mapPaperPMID 33326459Full record

ArticlePLoS medicine2020

Long-term health outcomes of people with reduced kidney function in the UK: A modelling study using population health data.

Iryna Schlackow, Claire Simons, Jason Oke, Benjamin Feakins, Christopher A O'Callaghan, F D Richard Hobbs, Daniel Lasserson, Richard J Stevens, Rafael Perera, Borislava Mihaylova

Open access · goldAbstract readValidation Study
In one paragraph

Article in PLoS medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.1field-weighted citation impact, top 22% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
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  5. Review
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  7. Radioligand Therapy with [Pharmaceuticals (Basel, Switzerland) · 2023
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Iryna SchlackowNuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-4154-1431
Claire SimonsNuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.ORCID 0000-0003-0822-7261
Jason OkeNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.ORCID 0000-0003-3467-6677
Benjamin FeakinsNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-3928-6750
Christopher A O'CallaghanNuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-9962-3248
F D Richard HobbsNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-7976-7172
Daniel LassersonWarwick Medical School, Population Evidence and Technologies, University of Warwick, Warwick, United Kingdom.ORCID 0000-0001-8274-5580
Richard J StevensNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-9258-4060
Rafael PereraNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
Borislava MihaylovaNuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-0951-1304
University of Oxford · GBQueen Mary University of London · GBUniversity of Warwick · GB

Funding

Department of Health RP-PG-1210-12003
6 · The paper itself

Abstract

backgroundPeople with reduced kidney function have increased cardiovascular disease (CVD) risk. We present a policy model that simulates individuals' long-term health outcomes and costs to inform strategies to reduce risks of kidney and CVDs in this population. METHODS AND

findingsWe used a United Kingdom primary healthcare database, the Clinical Practice Research Datalink (CPRD), linked with secondary healthcare and mortality data, to derive an open 2005-2013 cohort of adults (≥18 years of age) with reduced kidney function (≥2 measures of estimated glomerular filtration rate [eGFR] <90 mL/min/1.73 m2 ≥90 days apart). Data on individuals' sociodemographic and clinical characteristics at entry and outcomes (first occurrences of stroke, myocardial infarction (MI), and hospitalisation for heart failure; annual kidney disease stages; and cardiovascular and nonvascular deaths) during follow-up were extracted. The cohort was used to estimate risk equations for outcomes and develop a chronic kidney disease-cardiovascular disease (CKD-CVD) health outcomes model, a Markov state transition model simulating individuals' long-term outcomes, healthcare costs, and quality of life based on their characteristics at entry. Model-simulated cumulative risks of outcomes were compared with respective observed risks using a split-sample approach. To illustrate model value, we assess the benefits of partial (i.e., at 2013 levels) and optimal (i.e., fully compliant with clinical guidelines in 2019) use of cardioprotective medications. The cohort included 1.1 million individuals with reduced kidney function (median follow-up 4.9 years, 45% men, 19% with CVD, and 74% with only mildly decreased eGFR of 60-89 mL/min/1.73 m2 at entry). Age, kidney function status, and CVD events were the key determinants of subsequent morbidity and mortality. The model-simulated cumulative disease risks corresponded well to observed risks in participant categories by eGFR level. Without the use of cardioprotective medications, for 60- to 69-year-old individuals with mildly decreased eGFR (60-89 mL/min/1.73 m2), the model projected a further 22.1 (95% confidence interval [CI] 21.8-22.3) years of life if without previous CVD and 18.6 (18.2-18.9) years if with CVD. Cardioprotective medication use at 2013 levels (29%-44% of indicated individuals without CVD; 64%-76% of those with CVD) was projected to increase their life expectancy by 0.19 (0.14-0.23) and 0.90 (0.50-1.21) years, respectively. At optimal cardioprotective medication use, the projected health gains in these individuals increased by further 0.33 (0.25-0.40) and 0.37 (0.20-0.50) years, respectively. Limitations include risk factor measurements from the UK routine primary care database and limited albuminuria measurements.

conclusionsThe CKD-CVD policy model is a novel resource for projecting long-term health outcomes and assessing treatment strategies in people with reduced kidney function. The model indicates clear survival benefits with cardioprotective treatments in this population and scope for further benefits if use of these treatments is optimised.

Indexed as

Glomerular Filtration RateModels, TheoreticalPreventive Health ServicesAgedAged, 80 and overCardiovascular DiseasesDatabases, FactualEnglandFemaleHealth Care CostsHealth StatusHumansKidneyMaleMarkov ChainsMiddle Aged

Identifiers

PMID33326459
PMCPMC7769604
OpenAlexW3112508793

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.