Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: Despite advancements in the management of patients with sickle cell disease (SCD), the involvement of the cardiovascular system in these patients remains a significant concern. Cardiovascular manifestations of SCD are well-documented, with electrocardiography (ECG) serving as a valuable diagnostic tool. Studies have reported a high rate of critical ECG findings in patients with SCD that warrants consideration when managing these patients, indicating the need for proactive cardiac screening and management strategies in this patient population. This study aims to systematically review the literature to identify sociodemographic, clinical, and paraclinical factors associated with ECG abnormalities in patients with SCD.
Methods: A comprehensive search strategy will be employed across multiple online databases, including PubMed, Embase, Scopus, Web of Science, and Google Scholar, for published and gray literature. Eligible studies will include original articles reporting associations between sociodemographic, clinical, and paraclinical variables and a spectrum of ECG findings in patients with SCD. Independent reviewers will conduct the screening, quality assessment, and data extraction. Quantitative analyses will be performed under a random-effect model using Comprehensive Meta-Analysis software, with subgroup analyses based on SCD status, sickle hemoglobinopathy form, and age group.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11194293 | PMC |
http://dx.doi.org/10.1002/hsr2.2212 | DOI Listing |
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