Evidence map›Paper›PMID 30485284›Full record

ArticlePloS one2018

Validation of the MAGGIC (Meta-Analysis Global Group in Chronic Heart Failure) heart failure risk score and the effect of adding natriuretic peptide for predicting mortality after discharge in hospitalized patients with heart failure.

Sayma Sabrina Khanam, Eunhee Choi, Jung-Woo Son, Jun-Won Lee, Young Jin Youn, Junghan Yoon, Seung-Hwan Lee, Jang-Young Kim, Sung Gyun Ahn, Min-Soo Ahn and 9 more

Open access · goldAbstract readValidation Study
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 4 pooled it
5.6field-weighted citation impact, top 3% 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

32 citing papers in PubMed, 4 syntheses or guidelines pooled it, 61 citations in OpenAlex.

  1. Pooled it
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  3. Catheter ablation of atrial fibrillation in heart failure: clinical, prognostic, and echocardiographic outcome.Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing · 2021
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  13. Performance of risk models to predict mortality risk for patients with heart failure: evaluation in an integrated health system.Clinical research in cardiology : official journal of the German Cardiac Society · 2024
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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

19 authors at 9 institutions in 2 countries.

Sayma Sabrina KhanamDepartment of Cardiology, Wonju College of Medicine, Yonsei University, Wonju, Republic of Korea.
Eunhee ChoiSmith Center for Outcomes Research in Cardiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States of America.ORCID 0000-0002-3449-0672
Jung-Woo SonDepartment of Cardiology, Wonju College of Medicine, Yonsei University, Wonju, Republic of Korea.
Jun-Won LeeDepartment of Cardiology, Wonju College of Medicine, Yonsei University, Wonju, Republic of Korea.
Young Jin YounDepartment of Cardiology, Wonju College of Medicine, Yonsei University, Wonju, Republic of Korea.ORCID 0000-0001-7066-7474
Junghan YoonDepartment of Cardiology, Wonju College of Medicine, Yonsei University, Wonju, Republic of Korea.
Seung-Hwan LeeDepartment of Cardiology, Wonju College of Medicine, Yonsei University, Wonju, Republic of Korea.
Jang-Young KimDepartment of Cardiology, Wonju College of Medicine, Yonsei University, Wonju, Republic of Korea.
Sung Gyun AhnDepartment of Cardiology, Wonju College of Medicine, Yonsei University, Wonju, Republic of Korea.ORCID 0000-0002-1528-2739
Min-Soo AhnDepartment of Cardiology, Wonju College of Medicine, Yonsei University, Wonju, Republic of Korea.
Seok-Min KangYonsei University College of Medicine, Seoul, Korea.
Sang Hong BaekThe Catholic University of Korea, Seoul, Korea.ORCID 0000-0002-7065-3432
Eun-Seok JeonSungkyunkwan University College of Medicine, Seoul, Korea.
Jae-Joong KimUniversity of Ulsan College of Medicine, Seoul, Korea.
Myeong-Chan ChoChungbuk National University College of Medicine, Cheongju, Korea.ORCID 0000-0002-0047-0227
Shung Chull ChaeKyungpook National University College of Medicine, Daegu, Korea.
Byung-Hee OhDepartment of Internal Medicine, Seoul National University Hospital, Seoul, Korea.
Dong-Ju ChoiSeoul National University Bundang Hospital, Seongnam, Korea.
Byung-Su YooDepartment of Cardiology, Wonju College of Medicine, Yonsei University, Wonju, Republic of Korea.ORCID 0000-0002-3395-4279
Yonsei University · KRUlsan College · KRBeth Israel Deaconess Medical Center · USCatholic University of Korea · KRChungbuk National University · KRKyungpook National University · KRSeoul National University Bundang Hospital · KRSeoul National University Hospital · KRSungkyunkwan University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn clinical practice, a risk prediction model is an effective solitary program to predict prognosis in particular patient groups. B-type natriuretic peptide (BNP)and N-terminal pro-b-type natriuretic peptide (NT-proBNP) are widely recognized outcome-predicting factors for patients with heart failure (HF).This study derived external validation of a risk score to predict 1-year mortality after discharge in hospitalized patients with HF using the Meta-analysis Global Group in Chronic Heart Failure (MAGGIC)program data. We also assessed the effect of adding BNP or NT-proBNP to this risk score model in a Korean HF registry population. METHOD AND

resultsWe included 5625 patients from the Korean acute heart failure registry (KorAHF) and excluded those who died in hospital. The MAGGIC constructed a risk score to predict mortality in patients with HF by using 13 routinely available patient characteristics (age, gender, diabetes, chronic obstructive pulmonary disorder (COPD), HF diagnosed within the last 18 months, current smoker, NYHA class, use of beta blocker, ACEI or ARB, body mass index, systolic blood pressure, creatinine, and EF). We added BNP or NT-proBNP, which are the most important biomarkers, to the MAGGIC risk scoring system in patients with HF. The outcome measure was 1-year mortality. In multivariable analysis, BNP or NT-proBNP independently predicted death. The risk score was significantly varied between alive and dead groups (30.61 ± 6.32 vs. 24.80 ± 6.81, p < 0.001). After the conjoint use of BNP or NT-proBNP and MAGGIC risk score in patients with HF, a significant difference in risk score was noted (31.23 ± 6.46 vs. 25.25 ± 6.96, p < 0.001).The discrimination abilities of the risk score model with and without biomarker showed minimal improvement (C index of 0.734 for MAGGIC risk score and 0.736 for MAGGIC risk score plus BNP or NT-proBNP, p = 0.0502) and the calibration was found good. However, we achieved a significant improvement in net reclassification and integrated discrimination for mortality (NRI of 33.4%,p < 0.0001 and IDI of 0.002, p < 0.0001).

conclusionIn the KorAHF, the MAGGIC project HF risk score performed well in a large nationwide contemporary external validation cohort. Furthermore, the addition of BNP or NT-proBNPto the MAGGIC risk score was beneficial in predicting more death in hospitalized patients with HF.

Indexed as

Patient DischargeAgedChronic DiseaseFemaleHeart FailureHumansMaleMeta-Analysis as TopicNatriuretic Peptide, BrainPeptide FragmentsPrognosisRisk AssessmentRisk FactorsNatriuretic Peptide, BrainPeptide Fragmentspro-brain natriuretic peptide (1-76)

Identifiers

PMID30485284
PMCPMC6261415
OpenAlexW2903339917

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LicenceCC BY
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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.