Evidence map›Paper›PMID 41930459›Full record

ArticlePacing and clinical electrophysiology : PACE2026

Influencing Factors and Prediction of Complications After Implantation of Cardiac Electronic Devices.

Chuan-Jiang Chen, Ming Gui, Mei-Ping Lin, Shuping Huang, Yiting Tan, Xinyan He, Karina Yuanyuan Yu, Yumei Xue, Wenjing Zhao, Hai Deng and 1 more

Abstract read
In one paragraph

Article in Pacing and clinical electrophysiology : PACE, 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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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

11 authors.

Chuan-Jiang ChenSchool of Public Health, Guangdong Pharmaceutical University, Guangzhou, China.
Ming GuiSchool of Public Health, Guangdong Pharmaceutical University, Guangzhou, China.
Mei-Ping LinDepartment of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Science, Southern Medical University, Guangzhou, China.
Shuping HuangDepartment of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Science, Southern Medical University, Guangzhou, China.
Yiting TanSchool of Public Health, Guangdong Pharmaceutical University, Guangzhou, China.
Xinyan HeDepartment of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Science, Southern Medical University, Guangzhou, China.
Karina Yuanyuan YuThe Department of Medicine and Therapeutics, Prince of Wales Hospital, Shatin, Hong Kong, SAR, China.
Yumei XueDepartment of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Science, Southern Medical University, Guangzhou, China.ORCID https://orcid.org/0000-0001-7354-0014
Wenjing ZhaoSchool of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China.
Hai DengDepartment of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Science, Southern Medical University, Guangzhou, China.ORCID https://orcid.org/0000-0002-3285-441X
Xudong LiuSchool of Public Health, Guangdong Pharmaceutical University, Guangzhou, China.ORCID https://orcid.org/0000-0003-2911-4899

Funding

Clinical Research Fund of Guangdong Medical Association 2025MB-A1063Guangdong Basic and Applied Basic Research Foundation 2025A1515012363Shenzhen Medical Research Fund B2303004
6 · The paper itself

Abstract

backgroundCardiac implantable electronic device (CIED) related complications occur frequently. Given the uncertainties, a comprehensive investigation of predictive factors is crucial. This study aimed to identify the determinants influencing the occurrence of CIED-related complications and to evaluate their predictive capability for the onset of CIED-related complications.

methodsThis retrospective cohort study recruited 870 patients who underwent CIED implantation. The primary outcome was overall complications, and the secondary was pocket hematomas (PH). Logistic regression model was used to estimate the odds ratio (OR) with the 95% confidence interval (CI), and to establish the prediction models for all complications and PH.

results43 cases (4.95%) developed complications during follow-up, including 24 (2.8%) PH and 19 others. After adjusted for potential confounders, body mass index (BMI), having diabetes and chronic kidney disease (CKD), usage of anticoagulants and antiplatelets, device type, device replacement, and device electrode quantities were all associated with the risk of both the complications and PH. The prediction model with these variables displayed a good performance in predicting the complications occurrence, with AUC and C-statistic being 0.886 and 0.886 in training dataset, and 0.780 and 0.761 in the test dataset. Similar good performance in predicting PH onset were also observed.

conclusionThe results indicate that BMI, diabetes, CKD, anticoagulants, antiplatelets, device types, device replacement, and device electrode quantities are critical risk factors, which can help predict the onset of the complications and PH.

Indexed as

Defibrillators, ImplantableHematomaPacemaker, ArtificialPostoperative ComplicationsAgedFemaleHumansMaleMiddle AgedRetrospective StudiesRisk FactorsCardiac implantable electronic deviceCohort studyComplicationPredictionRisk factors

Identifiers

PMID41930459
PMCPMC13542326

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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.