Evidence map›Paper›PMID 38243376›Full record

ArticleESC heart failure2024

Prognostic impact of MitraScore in elderly Asian patients with heart failure: sub-analysis of FRAGILE-HF.

Tomohiro Kaneko, Nobuyuki Kagiyama, Takatoshi Kasai, Kentaro Kamiya, Hiroshi Saito, Kazuya Saito, Yuki Ogasahara, Emi Maekawa, Masaaki Konishi, Takeshi Kitai and 17 more

Open access · goldAbstract read
In one paragraph

Article in ESC heart failure, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  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

27 authors at 15 institutions in 2 countries.

Tomohiro KanekoDepartment of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Nobuyuki KagiyamaDepartment of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.ORCID https://orcid.org/0000-0002-2305-0049
Takatoshi KasaiDepartment of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Kentaro KamiyaDepartment of Rehabilitation, School of Allied Health Science, Kitasato University, Tokyo, Japan.
Hiroshi SaitoDepartment of Rehabilitation, Kameda Medical Center, Kamogawa, Japan.
Kazuya SaitoDepartment of Rehabilitation, The Sakakibara Heart Institute of Okayama, Okayama, Japan.
Yuki OgasaharaDepartment of Nursing, The Sakakibara Heart Institute of Okayama, Okayama, Japan.
Emi MaekawaDepartment of Cardiovascular Medicine, Kitasato University School of Medicine, Tokyo, Japan.
Masaaki KonishiDivision of Cardiology, Yokohama City University Medical Center, Yokohama, Japan.
Takeshi KitaiDepartment of Cardiovascular Medicine, Kobe City Medical Center General Hospital, Kobe, Japan.
Kentaro IwataDepartment of Rehabilitation, Kobe City Medical Center General Hospital, Kobe, Japan.
Kentaro JujoDepartment of Cardiology, Nishiarai Heart Center Hospital, Tokyo, Japan.
Hiroshi WadaDepartment of Cardiovascular Medicine, Saitama Medical Center, Jichi Medical University, Shimotsuke, Japan.
Daichi MaedaDepartment of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Masaru HikiDepartment of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Tsutomu SunayamaDepartment of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Taishi DotareDepartment of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Hirofumi NagamatsuDepartment of Cardiology, Tokai University School of Medicine, Tokyo, Japan.
Tetsuya OzawaDepartment of Rehabilitation, Odawara Municipal Hospital, Odawara, Japan.
Katsuya IzawaDepartment of Rehabilitation, Matsui Heart Clinic, Saitama, Japan.
Shuhei YamamotoDepartment of Rehabilitation, Shinshu University Hospital, Matsumoto, Japan.
Naoki AizawaDepartment of Cardiovascular Medicine, Nephrology and Neurology, University of the Ryukyus, Nishihara, Japan.
Akihiro MakinoDepartment of Rehabilitation, Kitasato University Medical Center, Kitasato, Japan.
Kazuhiro OkaDepartment of Rehabilitation, Saitama Citizens Medical Center, Saitama, Japan.
Shin-Ichi MomomuraDepartment of Cardiovascular Medicine, Saitama Citizens Medical Center, Saitama, Japan.
Yuya MatsueDepartment of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Tohru MinaminoDepartment of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Juntendo University · JPCitizen (Japan) · JPKitasato University · JPKobe City Medical Center General Hospital · JPSakakibara Hospital · JPAvera Heart Hospital · USJichi Medical University · JPKameda Medical Center · JPKitasato University Medical Center · JPOdawara Municipal Hospital · JPShinshu University Hospital · JPTokai University · JPUnited Heart and Vascular Clinic · USUniversity of the Ryukyus · JPYokohama City University Medical Center · JP

Funding

Japan Heart Foundation Research GrantJapan Society for the Promotion of Science 21K18086Novartis Pharma Research Grants
6 · The paper itself

Abstract

aimsMitraScore is a novel, simple, and manually calculatable risk score developed as a prognostic model for patients undergoing transcatheter edge-to-edge repair (TEER) for mitral regurgitation. As its components are considered prognostic in heart failure (HF), we aimed to investigate the usefulness of the MitraScore in HF patients. METHODS AND

resultsWe calculated MitraScore for 1100 elderly patients (>65 years old) hospitalized for HF in the prospective multicentre FRAGILE-HF study and compared its prognostic ability with other simple risk scores. The primary endpoint was all-cause deaths, and the secondary endpoints were the composite of all-cause deaths and HF rehospitalization and cardiovascular deaths. Overall, the mean age of 1100 patients was 80 ± 8 years, and 58% were men. The mean MitraScore was 3.2 ± 1.4, with a median of 3 (interquartile range: 2-4). A total of 326 (29.6%), 571 (51.9%), and 203 (18.5%) patients were classified into low-, moderate-, and high-risk groups based on the MitraScore, respectively. During a follow-up of 2 years, 226 all-cause deaths, 478 composite endpoints, and 183 cardiovascular deaths were observed. MitraScore successfully stratified patients for all endpoints in the Kaplan-Meier analysis (P < 0.001 for all). In multivariate analyses, MitraScore was significantly associated with all endpoints after covariate adjustments [adjusted hazard ratio (HR) (95% confidence interval): 1.22 (1.10-1.36), P < 0.001 for all-cause deaths; adjusted HR 1.17 (1.09-1.26), P < 0.001 for combined endpoints; and adjusted HR 1.24 (1.10-1.39), P < 0.001 for cardiovascular deaths]. The Hosmer-Lemeshow plot showed good calibration for all endpoints. The net reclassification improvement (NRI) analyses revealed that the MitraScore performed significantly better than other manually calculatable risk scores of HF: the GWTG-HF risk score, the BIOSTAT compact model, the AHEAD score, the AHEAD-U score, and the HANBAH score for all-cause and cardiovascular deaths, with respective continuous NRIs of 0.20, 0.22, 0.39, 0.39, and 0.29 for all-cause mortality (all P-values < 0.01) and 0.20, 0.22, 0.42, 0.40, and 0.29 for cardiovascular mortality (all P-values < 0.02).

conclusionsMitraScore developed for patients undergoing TEER also showed strong discriminative power in HF patients. MitraScore was superior to other manually calculable simple risk scores and might be a good choice for risk assessment in clinical practice for patients receiving TEER and those with HF.

Indexed as

Heart FailureAgedFemaleHumansMalePrognosisProspective StudiesRisk AssessmentRisk FactorsHeart failureMitraScoreRisk scoreTranscatheter edge‐to‐edge repair

Identifiers

PMID38243376
PMCPMC10966225
OpenAlexW4391053125

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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.