Evidence map›Paper›PMID 32607637›Full record

Observational studyHeart and vessels2021

Impact of nutritional index on long-term outcomes of elderly patients with coronary artery disease: sub-analysis of the SHINANO 5 year registry.

Shusaku Maruyama, Souichiro Ebisawa, Takashi Miura, Hisanori Yui, Daisuke Kashiwagi, Ayumu Nagae, Takahiro Sakai, Tamon Kato, Tatsuya Saigusa, Ayako Okada and 2 more

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Heart and vessels, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 3 pooled it
–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

20 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  19. A simply calculated nutritional index provides clinical implications in patients undergoing transcatheter aortic valve replacement.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

12 authors.

Shusaku MaruyamaDepartment of Cardiovascular Medicine, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, 390-8621, Japan. smaruyama@shinshu-u.ac.jp.ORCID http://orcid.org/0000-0002-2970-5835
Souichiro EbisawaDepartment of Cardiovascular Medicine, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, 390-8621, Japan.
Takashi MiuraDepartment of Cardiology, Nagano Municipal Hospital, Nagano, Japan.
Hisanori YuiDepartment of Cardiovascular Medicine, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, 390-8621, Japan.
Daisuke KashiwagiDepartment of Cardiovascular Medicine, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, 390-8621, Japan.
Ayumu NagaeDepartment of Cardiovascular Medicine, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, 390-8621, Japan.
Takahiro SakaiDepartment of Cardiovascular Medicine, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, 390-8621, Japan.
Tamon KatoDepartment of Cardiovascular Medicine, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, 390-8621, Japan.
Tatsuya SaigusaDepartment of Cardiovascular Medicine, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, 390-8621, Japan.
Ayako OkadaDepartment of Cardiovascular Medicine, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, 390-8621, Japan.
Hirohiko MotokiDepartment of Cardiovascular Medicine, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, 390-8621, Japan.
Koichiro KuwaharaDepartment of Cardiovascular Medicine, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, 390-8621, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nutritional status is a novel approach to prognostic assessment in patients with cardiovascular disease. However, assessment of nutritional status in elderly patients is challenging due to the significant differences between young patients. The TCBI (Triglycerides × Total cholesterol × Body Weight Index) is a novel and simple nutritional index for predicting long-term outcomes in patients with coronary artery disease. This retrospective study evaluated the efficacy of TCBI in 597 elderly (≥ 75 years) patients enrolled in the SHINANO 5 year registry. The SHINANO 5 year registry, a prospective observational multicenter cohort study, had enrolled 1501 consecutive patients who underwent elective/urgent percutaneous coronary intervention (PCI). In this study, patients were categorized into TCBI quartile groups. The primary endpoints were the occurrence of major adverse cardiac and cerebrovascular events (MACCE), including all-cause death, stroke, and myocardial infarction at 5 year. The mean duration of follow up was 4.3 ± 1.7 years. The average patient age was 80.9 ± 4.3 years. MACCE was observed in 61 (40.9%) patients in the lowest TCBI quartile group. Kaplan-Meier analysis demonstrated an inverse relationship between MACCE and TCBI (log-lank P < 0.001). Multivariate analysis demonstrated that low TCBI significantly predicted the incidence of MACCE (hazard ratio: 1.44, 95% confidence interval: 1.03-2.00; P = 0.031). The TCBI is useful in predicting long-term outcomes in elderly patients undergoing PCI.

Indexed as

Nutritional StatusPercutaneous Coronary InterventionRegistriesAgedAged, 80 and overCoronary Artery DiseaseFemaleFollow-Up StudiesHumansIncidenceJapanMaleMalnutritionPostoperative PeriodPrognosisProspective StudiesCoronary artery diseaseNutritional indexPrognosis

Identifiers

PMID32607637
PMCPMC7788017

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.