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: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1075
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3195
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Background: The current research was to investigate the relationship between prognostic nutritional index (PNI) and mortality, with a focus on all-cause and cardiovascular disease (CVD) mortality, for those with non-alcoholic fatty liver disease (NAFLD).
Methods: Data from 20,142 patients who participated in the National Health and Nutrition Examination Survey (NHANES), which was carried out between 2005 and 2014, were included in this research. To examine the relationship between PNI and both all-cause and cardiovascular mortality, we employed weighted Cox regression models with multiple variables. Kaplan-Meier survival curves were utilized to visualize the survival distribution across different levels of PNI. The non-linear association between PNI and mortality was addressed through penalized spline smoothing. Subgroup analyses were conducted to examine the potential influence of relevant clinical variables on the relationship between PNI and mortality. The precision of PNI in forecasting the outcome of survival was assessed as well using time-dependent receiver operating characteristic curve (ROC) analysis.
Results: Kaplan-Meier analysis linked higher PNI to significantly reduced all-cause and CVD mortality. Multivariable Cox models demonstrated that increasing PNI consistently lowered mortality risks. With a threshold value of 50.5, the link between PNI and mortality showed a non-linear pattern after adjusting for confounding factors. Subgroup analyses confirmed robust associations, particularly in race, education, BMI, and fibrosis. Time-dependent ROC analysis highlighted the strong predictive performance of PNI across various time points.
Conclusion: PNI played a significant role as an effective predictor of prognosis in individuals diagnosed with NAFLD.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11847695 | PMC |
http://dx.doi.org/10.3389/fnut.2025.1526801 | DOI Listing |