Evidence map›Paper›PMID 17803203›Full record

ArticleClinical cardiology2007

Glomerular filtration rate and coronary artery disease burden in patients with acute coronary syndrome.

José Pedro L Nunes, Maria do Sameiro Faria, J M Mota Garcia, Francisco Rocha Gonçalves

Abstract readEvaluation Study
In one paragraph

Article in Clinical cardiology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

4 authors.

José Pedro L NunesFaculty of Medicine, University of Porto, Porto, Portugal. jplnunes@med.up.pt
Maria do Sameiro Faria
J M Mota Garcia
Francisco Rocha Gonçalves

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMild renal dysfunction may be associated with increased cardiovascular morbidity and mortality.

methodsThe relation between estimated glomerular filtration rate (eGFR), as calculated from plasma creatinine at admission, and coronary artery disease burden (CADB), was studied in a cohort of 110 patients with acute coronary syndrome and coronary atherosclerosis.

resultsA relatively weak but significant negative correlation was found between eGFR and CADB as measured by angiography (coefficient correlation of - 0.26, probability value of 0.006); a similar association was seen in multiple regression analysis, taking CADB as dependent variable, and eGFR, age, plasma calcium and plasma phosphorus as independent variables. After dividing the 110 patients into eGFR tertiles (with mean values of 102.9 +/- 22.8, n = 37, 75.7 + or - 5.6, n = 36, and 53.1 +/- 13.4, n = 37, all in mL/min per 1.73 m(2)), mean CADB values of the lower and higher eGFR tertiles were found to be significantly different (270.6 +/- 176.4 and 192.9 +/- 78.5, respectively). Similar mean values for CADB and for eGFR were noted when patients with elevated ST segment/new left bundle branch block and patients with nonelevated ST segment acute coronary syndrome were compared.

conclusionsWe conclude that renal function of patients with acute coronary syndromes and coronary atherosclerosis, as estimated at admission, is negatively correlated with coronary artery disease burden. It is unknown whether renal dysfunction acts as a cause for accelerated coronary artery disease or if it merely acts as a surrogate marker for the overall systemic vascular system status.

Indexed as

Glomerular Filtration RateCoronary Artery DiseaseFemaleHumansKidney DiseasesMaleMiddle AgedPredictive Value of TestsProspective StudiesSeverity of Illness Index

Identifiers

PMID17803203
PMCPMC6652889

What OpenQuestion holds

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Registered trials

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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.