Evidence map›Paper›PMID 29415138›Full record

ArticleEuropean heart journal. Cardiovascular Imaging2018

Validation of 2-year 123I-meta-iodobenzylguanidine-based cardiac mortality risk model in chronic heart failure.

Kenichi Nakajima, Tomoaki Nakata, Takahiro Doi, Toshiaki Kadokami, Shinro Matsuo, Tetsuo Konno, Takahisa Yamada, Arnold F Jacobson

Open access · hybridAbstract readValidation Study
In one paragraph

Article in European heart journal. Cardiovascular Imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.4field-weighted citation impact, top 10% 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

14 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Seeing is believing: Visualization of multivariable risk models.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023
    Article
  5. Validation of a Five-Year Prognostic Model UsingAnnals of nuclear cardiology · 2023
    Article
  6. Article
  7. Article
  8. Machine learning-based risk model usingJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2022
    Article
  9. Review
  10. Article
  11. Article
  12. Risk stratification based on J-ACCESS risk models with myocardial perfusion imaging: Risk versus outcomes of patients with chronic kidney disease.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2020
    Article
  13. Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2020
    Article
  14. Review
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

8 authors at 5 institutions in 1 country.

Kenichi NakajimaDepartment of Nuclear Medicine, Kanazawa University Hospital, 13-1 Takara-machi, Kanazawa, 920-8641, Japan.
Tomoaki NakataDepartment of Cardiology, Hakodate-Goryoukaku Hospital, Hakodate, Japan.
Takahiro DoiDepartment of Cardiology, Obihiro-Kosei Hospital, Obihiro, Japan.
Toshiaki KadokamiDepartment of Cardiology, Saiseikai-Futsukaichi Hospital, Tsukushino, Japan.
Shinro MatsuoDepartment of Nuclear Medicine, Kanazawa University Hospital, 13-1 Takara-machi, Kanazawa, 920-8641, Japan.
Tetsuo KonnoDepartment of Cardiology, Kanazawa University Hospital, Kanazawa, Japan.
Takahisa YamadaDepartment of Cardiology, Osaka Prefectural General Medical Center, Osaka, Japan.
Arnold F JacobsonDiagram Consulting, Kihei, HI, USA.
Kanazawa University Hospital · JPFukui-ken Saiseikai Hospital · JPHakodate National Hospital · JPObihiro Kosei General Hospital · JPOsaka Prefectural Medical Center · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: The aim of this study was to validate a four-parameter risk model including 123I-meta-iodobenzylguanidine (MIBG) imaging, which was previously developed for predicting cardiac mortality, in a new cohort of patients with chronic heart failure (CHF). Methods and results: Clinical and outcome data were retrospectively obtained from 546 patients (age 66 ± 14 years) who had undergone 123I-MIBG imaging with a heart-to-mediastinum ratio (HMR). The mean follow-up time was 30 ± 20 months, and the endpoint was cardiac death. The mortality outcome predicted by the model was compared with actual 2-year event rates in pre-specified risk categories of three or four risk groups using Kaplan-Meier survival analysis for cardiac death and receiver-operating characteristic (ROC) analysis. Cardiac death occurred in 137 patients, including 105 (68%) patients due to heart-failure death. With a 2-year mortality risk from the model divided into three categories of low- (<4%), intermediate- (4-12%), and high-risk (>12%), 2-year cardiac mortality was 1.1%, 7.9%, and 54.7%, respectively in the validation population (P < 0.0001). In a quartile analysis, although the predicted numbers of cardiac death was comparable with actual number of cardiac death for low- to intermediate-risk groups with a mortality risk <13.8%, it was underestimated in the high-risk group with a mortality risk ≥13.8%. The ROC analysis showed that the 2-year risk model had better (P < 0.0001) diagnostic ability for predicting heart failure death than left ventricular ejection fraction, natriuretic peptides or HMR alone. Conclusion: The 2-year risk model was successfully validated particularly in CHF patients at a low to intermediate cardiac mortality risk.

Indexed as

3-IodobenzylguanidineCause of DeathAgedAged, 80 and overArea Under CurveChronic DiseaseCohort StudiesDisease-Free SurvivalFemaleHeart FailureHumansKaplan-Meier EstimateMaleMiddle AgedPositron-Emission TomographyPredictive Value of Tests3-IodobenzylguanidineRadiopharmaceuticals

Identifiers

PMID29415138
PMCPMC6012774
OpenAlexW2790883112

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.