Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&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: Various multifactorial elements may contribute toward the urban and rural disparities in cardiovascular disease (CVD) risk, particularly among patients with psychiatric diseases.
Objective: To investigate whether rural patients diagnosed and treated for Bipolar Disorder (BD) have different risk profiles and outcomes of CVD compared to urban (BD) patients.
Methods: We conducted a case-control study that included 125 BD patients (cases) from rural Filadelfia, Colombia and 250 BD patients (controls) treated in Bogotá, Colombia. Cases and controls were 2:1, matched by age and sex. We applied the Framingham Heart Study (FHS) risk calculator to assess risk. Differences by rural/urban status (i.e., case-control status) were assessed by chi-square, paired t-tests, and logistic regression.
Findings: Rural BD patients were found to have lower education (p = 1.0 × 10), alcohol consumption (p = 3.0 × 10), smoking (p = 0.015), psychiatric (p = 1.0 × 10) and CV family history (p = 0.0042) compared to urban BD patients. Rural BD patients were 81% more likely to have a more favorable CVD risk profile (OR: 0.19, 95% CI [0.06-0.62]) than urban BD patients, despite rural BD patients having increased CVD morbidity (p = 1.0 × 10).
Conclusion: Based on increase in morbidity but lower predictive risk in the rural population, our study suggests that the FHS-CVD calculator may not be optimal to assess CVD risk in this population.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8603855 | PMC |
http://dx.doi.org/10.5334/aogh.3479 | DOI Listing |
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