Evidence map›Paper›PMID 26123617›Full record

ArticleInternal and emergency medicine2015

Clinical implications of the CKD epidemiology collaboration (CKD-EPI) equation compared with the modification of diet in renal disease (MDRD) study equation for the estimation of renal dysfunction in patients with cardiovascular disease.

Luigi Tarantini, Giulia Barbati, Giovanni Cioffi, Finlay Aleck McAlister, Justin Adrian Ezekowitz, Carmine Mazzone, Giorgio Faganello, Giulia Russo, Enrico Franceschini Grisolia, Andrea Di Lenarda

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Internal and emergency medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Reply to Correspondence on "Glomerular Filtration Rate as a Prognostic Factor for Long-Term Mortality after Acute Pulmonary Embolism".Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2019
    Article
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.

Luigi TarantiniUOC Cardiologia Azienda ULSS numero 1 Belluno, Belluno, Italy.
Giulia BarbatiCardiovascular Center, ASS 1 Trieste, Trieste, Italy.
Giovanni CioffiDepartment of Cardiology, Villa Bianca Hospital, Trento, Italy. gcioffi@villabiancatrento.it.
Finlay Aleck McAlisterDepartment of Medicine and Mazankowski Alberta Heart Institute, University of Alberta, Edmonton, Canada.
Justin Adrian EzekowitzDepartment of Medicine and Mazankowski Alberta Heart Institute, University of Alberta, Edmonton, Canada.
Carmine MazzoneCardiovascular Center, ASS 1 Trieste, Trieste, Italy.
Giorgio FaganelloCardiovascular Center, ASS 1 Trieste, Trieste, Italy.
Giulia RussoCardiovascular Center, ASS 1 Trieste, Trieste, Italy.
Enrico Franceschini GrisoliaUOC Cardiologia Azienda ULSS numero 1 Belluno, Belluno, Italy.
Andrea Di LenardaCardiovascular Center, ASS 1 Trieste, Trieste, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The CKD-EPI equation is more accurate than the MDRD equation in the general population. We performed this study to establish whether chronic kidney disease (CKD) is commonly recognized by clinicians and whether the CKD-EPI equation improves prognosis estimation in patients with chronic cardiovascular disease (CVD). We analyzed data on 12394 CVD patients consecutively examined at the Cardiovascular Center of Trieste (Italy) between November 2009 and October 2013. The outcomes were all-cause death and a composite outcome of death/hospitalization for CV events (D+cvH). CKD-EPI formula reclassified 1786 (14.4 %) patients between KDIGO categories compared to the MDRD: 2.3 % (n = 280) placed in a lower risk and 12.1 % (n = 1506) into a higher risk group. CKD, defined as eGFR-CKD-EPI formula <60 ml/min, was present in 3083 patients (24.9 %) but not recognized by clinicians in 1946 (63.1 % of patients with CKD). The lack of recognition of CKD was inversely proportional to the KDIGO class for both equations. There were 986 deaths and 2726 D+cvH during 24 months follow-up. The incidence of death and D+cvH was about twice as high in patients with unrecognized CKD than in those with normal renal function (31 % vs. 17.1 %, aHR: 1.35, 95 % CI: 1.15 to 1.60), even in those patients with eGFR-MDRD >60 but eGFR-CKD-EPI formula <60 (31.1 % vs 17.1 %, p < 0.001). CKD-EPI equation provides more accurate risk stratification than MDRD equation in patients with CVD. CKD was unrecognized in nearly two-thirds of these patients but clinical outcomes were similar in those for patients with recognized CKD.

Indexed as

Glomerular Filtration RateMathematical ConceptsAdultAgedAged, 80 and overCardiovascular DiseasesCreatinineFemaleHumansItalyMaleMiddle AgedRenal Insufficiency, ChronicCreatinineCardiovascular diseaseChronic kidney diseaseCKD-EPI equationMDRD equationPrognosis

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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.