Evidence map›Paper›PMID 29856143›Full record

ArticleKorean circulation journal2018

Risk Scoring System to Assess Outcomes in Patients Treated with Contemporary Guideline-Adherent Optimal Therapies after Acute Myocardial Infarction.

Pil Sang Song, Dong Ryeol Ryu, Min Jeong Kim, Ki Hyun Jeon, Rak Kyeong Choi, Jin Sik Park, Young Bin Song, Joo Yong Hahn, Hyeon Cheol Gwon, Youngkeun Ahn and 3 more

Open access · hybridAbstract read
In one paragraph

Article in Korean circulation journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 18% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 4 institutions in 1 country.

Pil Sang Song *Division of Cardiology, Heart Stroke Vascular Center, Mediplex Sejong General Hospital, Incheon, Korea.ORCID https://orcid.org/0000-0001-6427-3911
Dong Ryeol Ryu *Division of Cardiology, Department of Internal Medicine, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon, Korea.ORCID https://orcid.org/0000-0002-5309-7606
Min Jeong KimDivision of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Korea.ORCID https://orcid.org/0000-0001-8398-7020
Ki Hyun JeonDivision of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Korea.ORCID https://orcid.org/0000-0002-6277-7697
Rak Kyeong ChoiDivision of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Korea.ORCID https://orcid.org/0000-0001-7432-1390
Jin Sik ParkDivision of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Korea.ORCID https://orcid.org/0000-0001-9847-4439
Young Bin SongDivision of Cardiology, Department of Internal Medicine, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-3986-9152
Joo Yong HahnDivision of Cardiology, Department of Internal Medicine, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-4412-377X
Hyeon Cheol GwonDivision of Cardiology, Department of Internal Medicine, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-8967-4305
Youngkeun AhnHeart Research Center, Chonnam National University College of Medicine, Gwangju, Korea.ORCID https://orcid.org/0000-0003-2022-9366
Myung Ho JeongHeart Research Center, Chonnam National University College of Medicine, Gwangju, Korea.ORCID https://orcid.org/0000-0003-2424-810X
Seung Hyuk ChoiDivision of Cardiology, Department of Internal Medicine, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. sh1214.choi@samsung.com.ORCID https://orcid.org/0000-0001-6716-4884
Korea Acute Myocardial Infarction Registry Investigators
Sejong General Hospital · KRSamsung Medical Center · KRChonnam National University · KRKangwon National University Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesA risk prediction is needed even in the contemporary era of acute myocardial infarction (AMI). We sought to develop a risk scoring specific for patients with AMI being treated with guideline-adherent optimal therapies, including percutaneous coronary intervention and all 5 medications (aspirin, thienopyridine, β-blocker, angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, and statin).

methodsFrom registries, 12,174 AMI patients were evaluated. The primary outcome was 1-year all-cause death or AMI. The Korea Working Group in Myocardial Infarction (KorMI) system was compared with the Assessment of Pexelizumab in Acute Myocardial Infarction (APEX AMI), Controlled Abciximab and Device Investigation to Lower Late Angioplasty Complications (CADILLAC), and Global Registry of Acute Coronary Events scores (GRACE) models.

resultsTen predictors were identified: left ventricular dysfunction (hazard ratio [HR], 2.3), bare-metal stent (HR, 2.0), Killip class ≥II (HR, 1.9), renal insufficiency (HR, 1.8), previous stroke (HR, 1.6), regional wall-motion- score >20 on echocardiography (HR, 1.5), body mass index ≤24 kg/m² (HR, 1.4), age ≥70 years (HR, 1.4), prior coronary heart disease (HR, 1.4), and diabetes (HR, 1.4). Compared with the previous models, the KorMI system had good discrimination (time-dependent C statistic, 0.759) and showed reasonable goodness-of-fit by Hosmer-Lemeshow test (p=0.84). Moreover, the continuous-net reclassification improvement varied from -27.3% to -19.1%, the integrated discrimination index varied from -2.1% to -0.9%, and the median improvement in risk score was from -1.0% to -0.4%.

conclusionsThe KorMI system would be a useful tool for predicting outcomes in survivors treated with guideline-adherent optimal therapies after AMI.

Indexed as

AngioplastyDrug TherapyMyocardial InfarctionRisk Risk stratification

Identifiers

PMID29856143
PMCPMC5986748
OpenAlexW2791775870

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.