Evidence map›Paper›PMID 42299233›Full record

ArticleInternational journal of general medicine2026

Effects of High-Intensity Interval Training on Cardiopulmonary Function in Patients with Acute Myocardial Infarction with and without Cardiac Arrest: A Retrospective Study.

Yang Zeng, Zequn Zhang, Jiajia Wu, Peibing Ge, Jie Xu, Hailang Liu, Jin Geng

Abstract read
In one paragraph

Article in International journal of general medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Yang Zeng *Department of Cardiology, the Huaian Clinical College of Xuzhou Medical University, Huai'an, People's Republic of China.
Zequn Zhang *Department of Cardiology, the Affiliated Huai'an NO.1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu, People's Republic of China.
Jiajia Wu *Department of Cardiology, the Huaian Clinical College of Xuzhou Medical University, Huai'an, People's Republic of China.
Peibing GeDepartment of Cardiology, the Affiliated Huai'an NO.1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu, People's Republic of China.
Jie XuDepartment of Cardiology, the Affiliated Huai'an NO.1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu, People's Republic of China.
Hailang LiuDepartment of Cardiology, the Affiliated Huai'an NO.1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu, People's Republic of China.
Jin GengDepartment of Cardiology, the Huaian Clinical College of Xuzhou Medical University, Huai'an, People's Republic of China.ORCID 0000-0001-9336-9349

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to explore the efficacy and safety of high-intensity interval training (HIIT) in patients with acute myocardial infarction (AMI) with or without cardiac arrest (CA). Methods: A retrospective analysis of 100 patients with AMI who underwent primary percutaneous coronary intervention was conducted. Fifty patients experienced CA, whereas the other fifty did not. A HIIT program was performed three times per week for a 12-week duration. The target heart rate (THR) method was used to guide the intensity of exercise. The cardiopulmonary function indices include maximum oxygen uptake (VO Results: After HIIT, VO Conclusion: Overall, HIIT-based rehabilitation was associated with significant improvements in cardiopulmonary function, with comparable outcomes in AMI patients with and without CA.

Indexed as

cardiac arrestcardiac rehabilitationexercise prescriptionhigh-intensity interval trainingmyocardial infarction

Identifiers

PMID42299233
PMCPMC13265015

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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.