Migration of an Implantable Loop Recorder: A Meta-summary of Case Reports.
The Journal of innovations in cardiac rhythm management(2025)
Abstract
The migration of an implantable loop recorder (ILR) is a rare complication. We aimed to perform a meta-summary of case reports to characterize patients who experienced an ILR migration. We searched for case reports published in PubMed, Google Scholar, Scopus, and Embase from January 2017 to 2023 using the following keywords: "migration ILR," "migration loop recorder," "complication loop recorder," and "complication ILR." Seven case reports/case series reporting ILR migration were included. Data about patients' characteristics, ILR implantation, time of onset, management, and clinical outcome of this complication were collected. Seven patients who experienced the migration of an ILR were examined. All patients experienced migration within 35 days following ILR implantation. The clinical suspicion of ILR migration mainly arose from patients' symptomatology. The migration of the ILR was confirmed by a radiological scan in all cases, and surgical removal, preferably by video-assisted thoracic surgery, was required. In conclusion, intrapleural migration is a rare complication of ILR implantation. It may occur in the early postprocedural period. Clinical suspicion arises from symptoms, but a radiological scan is necessary to confirm the diagnosis. Surgical removal is mandatory.
MoreTranslated text
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined