Evidence map›Paper›PMID 40075270›Full record

ArticleBMC cardiovascular disorders2025

Impact of COVID-19 on door-to-wire time in ST-segment elevation myocardial infarction treatment: the role of digital communication.

Changqing Zhong, Shanjun Mao, Shan Tang, Pengfei Zheng, Jianqiang Peng

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Article in BMC cardiovascular disorders, 2025. 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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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Changqing ZhongDepartment of Cardiovascular Medicine, Hunan Provincial People's Hospital, Changsha, Hunan, China.
Shanjun MaoDepartment of Statistics, Hunan University, Changsha, Hunan, 410006, China. shjmao@hnu.edu.cn.ORCID 0000-0001-9212-4761
Shan TangDepartment of Statistics, Hunan University, Changsha, Hunan, 410006, China.
Pengfei ZhengDepartment of Cardiovascular Medicine, Hunan Provincial People's Hospital, Changsha, Hunan, China.
Jianqiang PengDepartment of Cardiovascular Medicine, Hunan Provincial People's Hospital, Changsha, Hunan, China.

Funding

Excellent Young Scholar Project of Hunan Provincial Education Department 23B0033Hunan province science and technology innovation key project SK1013National Natural Science Foundation of China 12401381Natural Science Foundation of Changsha kq2004113Natural Science Foundation of Changsha kq2402048Natural Science Foundation of Hunan Province of China 2020JJ8061Science and Technology Innovation Project of Hunan Province of China 2020SK50921
6 · The paper itself

Abstract

introductionST-segment elevation myocardial infarction (STEMI) is a life-threatening cardiovascular emergency necessitating rapid reperfusion. During the COVID-19 pandemic, healthcare providers faced the challenge of ensuring timely STEMI interventions while managing the risk of viral transmission in hospitals. This study aims to analyze changes in the door-to-wire (D-to-W) time for STEMI treatment across three pandemic phases-early pre-epidemic phase (Group C), initial lockdown phase (Group A), and intermediate normalization phase (Group B). It also examines the impact of digital communication tools, collectively referred to as "InterNet

methodsBased on data of 630 STEMI patients treated in Chest Pain Center in a particular hospital in China from 2019 to 2020, changes in D-to-W time in different groups are measured. Time intervals in STEMI treatment process are also predicted by Bayesian statistics approach. The study investigated the influence of InterNet

resultsFor transfer-non-emergency- treatment, the time from first-electrocardiogram to preliminary-diagnosis in Group-A is significantly longer than that in Groups-B and -C (p = 0.004, p = 0.004); the time from decision-on-intervention to catheterization-room-activation in Group-A and -B is significantly longer than that in Group-C (p = 0.003, p < 0.001). For transfer-emergency- treatment, the time from first-medical-contact to arterial-puncture in Group-A and -B is remarkably shorter than that in Group-C (p = 0.006). Meanwhile, Bayesian method performs well in forecasting time intervals, so it can provide effective assistance for STEMI treatment. The findings from the questionnaire indicated that physicians perceived a significant association between the optimal management of STEMI and an increased frequency of InterNet

conclusionsThe treatment and management of STEMI patients have been in dilemmas and various time intervals of D-to-W are inevitably prolonged during the COVID-19 pandemic. The implementation of InterNet CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

COVID-19Percutaneous Coronary InterventionST Elevation Myocardial InfarctionTime-to-TreatmentAgedChinaFemaleHumansMaleMiddle AgedTime FactorsChest pain centerCOVID-19D-to-WST-segment elevation myocardial infarctionTime prediction

Identifiers

PMID40075270
PMCPMC11899889

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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.