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: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
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
Post-COVID-19 syndrome (PCS) is an emerging health problem in people recovering from COVID-19 infection within the past 3-6 months. The current study aimed to define the predictive factors of PCS development by assessing the mitochondrial DNA (mtDNA) levels in blood leukocytes, inflammatory markers and HbA1c in type 2 diabetes patients (T2D) with regard to clinical phenotype, gender, and biological age. In this case-control study, 65 T2D patients were selected. Patients were divided into 2 groups depending on PCS presence: the PCS group (n = 44) and patients who did not develop PCS (n = 21) for up to 6 months after COVID-19 infection. HbA1c and mtDNA levels were the primary factors linked to PCS in different models. We observed significantly lower mtDNA content in T2D patients with PCS compared to those without PCS (1.26 ± 0.25 vs. 1.44 ± 0.24; p = 0.011). In gender-specific and age-related analyses, the mt-DNA amount did not differ significantly between the subgroups. According to the stepwise multivariate logistic regression analysis, low mtDNA content and HbA1c were independent variables associated with PCS development, regardless of oxygen, glucocorticoid therapy and COVID-19 severity. The top-performing model for PCS prediction was the gradient boosting machine (GBM). HbA1c and mtDNA had a notably greater influence than the other variables, indicating their potential as prognostic biomarkers.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11513135 | PMC |
http://dx.doi.org/10.1038/s41598-024-77496-2 | DOI Listing |
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