Evidence map›Paper›PMID 28979779›Full record

ArticleClinical kidney journal2017

A clinical-genetic approach to assessing cardiovascular risk in patients with CKD.

Emilio Rodrigo, Sara Pich, Isaac Subirana, Gema Fernandez-Fresnedo, Paloma Barreda, Carles Ferrer-Costa, Ángel Luis M de Francisco, Eduardo Salas, Roberto Elosua, Manuel Arias

Abstract read
In one paragraph

Article in Clinical kidney journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. 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.

Emilio RodrigoNephrology Service, University Hospital Marques de Valdecilla, Santander, Spain.
Sara PichScientific Department, Gendiag.exe., Barcelona, Spain.
Isaac SubiranaCIBER Epidemiology and Public Health (CIBERESP), Barcelona, Spain.
Gema Fernandez-FresnedoNephrology Service, University Hospital Marques de Valdecilla, Santander, Spain.
Paloma BarredaNephrology Service, University Hospital Marques de Valdecilla, Santander, Spain.
Carles Ferrer-CostaScientific Department, Gendiag.exe., Barcelona, Spain.
Ángel Luis M de FranciscoNephrology Service, University Hospital Marques de Valdecilla, Santander, Spain.
Eduardo SalasScientific Department, Gendiag.exe., Barcelona, Spain.
Roberto ElosuaCardiovascular Epidemiology and Genetics, IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.
Manuel AriasNephrology Service, University Hospital Marques de Valdecilla, Santander, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoronary heart disease (CHD) is the primary cause of death in individuals with chronic kidney disease (CKD), but current equations for assessing coronary risk have low accuracy in this group. We have reported that the addition of a genetic risk score (GRS) to the Framingham risk function improved its predictive capacity in the general population. The aims of this study were to evaluate the association between this GRS and coronary events in the CKD population and to determine whether the addition of the GRS to coronary risk prediction functions improves the estimation of coronary risk at the earliest possible stages of kidney disease.

methodsA total of 632 CKD patients, aged 35-74 years, who had Stage 4-5 CKD, were on dialysis, had a functioning renal transplant or had returned to dialysis after transplant failure were included and followed up for a mean of 9.3 years. The transitions between disease states and the development of coronary events were registered. The increase in predictive ability that was obtained by including the GRS was measured as the improvement in the C-statistic and as the net reclassification index.

resultsThe GRS was independently associated with the risk of CHD (hazards ratio 1.34; 95% confidence interval 1.04-1.71; P = 0.022), especially in Stages 4 and 5 CKD, and kidney transplant patients. A coronary risk prediction function that incorporated chronic kidney disease (CKD) disease state, age, sex and the GRS had significantly greater predictive capacity (AUC 70.1, P = 0.01) and showed good reclassification (net reclassification improvement 28.6).

conclusionThis new function, combining genetic and clinical data, identifies CKD patients with a high risk of coronary events more accurately, allowing us to prevent such events more effectively.

Indexed as

cardiovascular riskchronic kidney diseasegenetic risk scorekidney transplantprevention

Identifiers

PMID28979779
PMCPMC5622901

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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 OpenQuestion graph.