Evidence map›Paper›PMID 35160341›Full record

ArticleJournal of clinical medicine2022

Kidney Function According to Different Equations in Patients Admitted to a Cardiology Unit and Impact on Outcome.

Vincenzo Livio Malavasi, Anna Chiara Valenti, Sara Ruggerini, Marcella Manicardi, Carlotta Orlandi, Daria Sgreccia, Marco Vitolo, Marco Proietti, Gregory Y H Lip, Giuseppe Boriani

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of clinical medicine, 2022. 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
2.1field-weighted citation impact, top 12% 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

5 citing papers in PubMed, 13 citations in OpenAlex.

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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 2 institutions in 3 countries.

Vincenzo Livio MalavasiCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy.
Anna Chiara ValentiCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy.
Sara RuggeriniCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy.
Marcella ManicardiCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy.ORCID 0000-0002-3215-9388
Carlotta OrlandiCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy.
Daria SgrecciaCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy.
Marco VitoloCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy.
Marco ProiettiLiverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool L14 3PE, UK.ORCID 0000-0003-1452-2478
Gregory Y H LipLiverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool L14 3PE, UK.ORCID 0000-0002-7566-1626
Giuseppe BorianiCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy.ORCID 0000-0002-9820-4815
University of Modena and Reggio Emilia · ITUniversity of Liverpool · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis paper aims to evaluate the concordance between the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula and alternative equations and to assess their predictive power for all-cause mortality in unselected patients discharged alive from a cardiology ward.

methodsWe retrospectively included patients admitted to our Cardiology Division independently of their diagnosis. The total population was classified according to Kidney Disease: Improving Global Outcomes (KDIGO) categories, as follows: G1 (estimated glomerular filtration rate (eGFR) ≥90 mL/min/1.73 m

resultsA total of 806 patients were included. Good agreement was found between the CKD-EPI formula and CG-BSA, MDRD, BIS-1, and FAS equations. In subjects younger than 65 years or aged ≥85 years, CKD-EPI and MDRD showed the highest agreement (Cohen's kappa (K) 0.881 and 0.588, respectively) while CG showed the lowest. After a median follow-up of 407 days, overall mortality was 8.2%. The risk of death was higher in lower eGFR classes (G3b HR4.35; 95%CI 1.05-17.80; G4 HR7.13; 95%CI 1.63-31.23; G5 HR25.91; 95%CI 6.63-101.21). The discriminant capability of death prediction tested with ROC curves showed the best results for BIS-1 and FAS equations.

conclusionIn our cohort, the concordance between CKD-EPI and other equations decreased with age, with the MDRD formula showing the best agreement in both younger and older patients. Overall, mortality rates increased with the renal function decreasing. In patients aged ≥75 years, the best discriminant capability for death prediction was found for BIS-1 and FAS equations.

Indexed as

cardiovascular diseasechronic kidney diseaseCKD-EPIelderlyglomerular filtration rate

Identifiers

PMID35160341
PMCPMC8837128
OpenAlexW4211037657

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.