Evidence map›Paper›PMID 34486830›Full record

ArticleESC heart failure2021

Plasma amino acid profiling improves predictive accuracy of adverse events in patients with heart failure.

Hidemichi Kouzu, Satoshi Katano, Toshiyuki Yano, Katsuhiko Ohori, Ryohei Nagaoka, Takuya Inoue, Yuhei Takamura, Tomoyuki Ishigo, Ayako Watanabe, Masayuki Koyama and 5 more

Open access · goldAbstract read
In one paragraph

Article in ESC heart failure, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 3 pooled it
2.3field-weighted citation impact, top 11% 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

26 citing papers in PubMed, 3 syntheses or guidelines pooled it, 35 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

15 authors at 5 institutions in 1 country.

Hidemichi KouzuDepartment of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University School of Medicine, South-1 West-16, Chuo-ku, Sapporo, 060-8543, Japan.ORCID 0000-0001-7815-1464
Satoshi KatanoDivision of Rehabilitation, Sapporo Medical University Hospital, Sapporo, Japan.ORCID 0000-0002-2562-1685
Toshiyuki YanoDepartment of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University School of Medicine, South-1 West-16, Chuo-ku, Sapporo, 060-8543, Japan.ORCID 0000-0001-9655-3985
Katsuhiko OhoriDepartment of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University School of Medicine, South-1 West-16, Chuo-ku, Sapporo, 060-8543, Japan.
Ryohei NagaokaDivision of Rehabilitation, Sapporo Medical University Hospital, Sapporo, Japan.
Takuya InoueDivision of Rehabilitation, Hokuto Hospital, Obihiro, Japan.
Yuhei TakamuraDepartment of Rehabilitation, Hokkaido Ohno Memorial Hospital, Sapporo, Japan.
Tomoyuki IshigoDivision of Hospital Pharmacy, Sapporo Medical University Hospital, Sapporo, Japan.
Ayako WatanabeDivision of Nursing, Sapporo Medical University Hospital, Sapporo, Japan.
Masayuki KoyamaDivision of Rehabilitation, Sapporo Medical University Hospital, Sapporo, Japan.
Nobutaka NaganoDepartment of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University School of Medicine, South-1 West-16, Chuo-ku, Sapporo, 060-8543, Japan.
Takefumi FujitoDepartment of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University School of Medicine, South-1 West-16, Chuo-ku, Sapporo, 060-8543, Japan.
Ryo NishikawaDepartment of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University School of Medicine, South-1 West-16, Chuo-ku, Sapporo, 060-8543, Japan.
Wataru OhwadaDepartment of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University School of Medicine, South-1 West-16, Chuo-ku, Sapporo, 060-8543, Japan.
Tetsuji MiuraDepartment of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University School of Medicine, South-1 West-16, Chuo-ku, Sapporo, 060-8543, Japan.
Sapporo Medical University · JPSapporo Medical University Hospital · JPCardiovascular Center Hokkaido Ohno Hospital · JPHokkaido University of Science · JPHokuto Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsThe clinical outcome of heart failure (HF) is complicated by the presence of multiple comorbidities including malnutrition and cachexia, and prediction of the outcome is still difficult in each patient. Metabolomics including amino acid profiling enables detection of alterations in whole body metabolism. The aim of this study was to determine whether plasma amino acid profiling improves prediction of clinical outcomes in patients with HF. METHODS AND

resultsWe retrospectively examined 301 HF patients (70 ± 15 years old; 59% male). Blood samples for measurements of amino acid concentrations were collected in a fasting state after stabilization of HF. Plasma amino acid concentrations were measured using ultraperformance liquid chromatography. Clinical endpoint of this study was adverse event defined as all-cause death and unscheduled readmission due to worsening HF or lethal arrhythmia. During a mean follow-up period of 380 ± 214 days, 40 patients (13%) had adverse events. Results of analyses of variable importance in projection score, a measure of a variable's importance in partial least squares-discriminant analysis (PLS-DA) showed that the top five amino acids being associated with adverse events were 3-methylhistidine (3-Me-His), β-alanine, valine, hydroxyproline, and tryptophan. Multivariate Cox-proportional hazard analyses indicated that a high 3-Me-His concentration and low β-alanine and valine concentrations were independently associated with adverse events. When HF patients were divided according to the cut-off values of amino acids calculated from receiver operating characteristic curves, Kaplan-Meier survival curves showed that event-free survival rates were lower in HF patients with high 3-Me-His than in HF patients with low 3-Me-His (68% vs. 91%, P < 0.01). In a subgroup with high 3-Me-His, HF patients with low β-alanine and those with low valine had significantly lower event-free survival rates than did HF patients with high β-alanine and those with high valine, respectively. On the other hand, Kaplan-Meier curves of event-free survival rates did not differ between HF patients with and those without low β-alanine and low valine in subgroups of patients with low 3-Me-His. Inclusion of both high 3-Me-His and low β-alanine or low valine into the adjustment model including N-terminal pro-brain natriuretic peptide improved the accuracy of prediction of adverse events after discharge. 3-Me-His concentration was associated with muscle mass and nutritional status.

conclusionsSimple measurement of 3-Me-His with either β-alanine or valine improved the predictive ability for adverse events, indicating the utility of plasma amino acid profiling in risk stratification of hospitalized HF patients.

Indexed as

Heart FailureAgedAged, 80 and overAmino AcidsFemaleHumansKaplan-Meier EstimateMaleMiddle AgedPrognosisRetrospective StudiesAmino AcidsAmino acidsCachexiaHeart failureMetabolismPreventive cardiologyPrognosis

Identifiers

PMID34486830
PMCPMC8712896
OpenAlexW3196643373

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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.