{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T21:22:55Z","timestamp":1792790575686,"version":"4.5.0"},"reference-count":38,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"1","content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,1]]},"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Plaque instability is a leading cause of morbidity and mortality in coronary artery disease (CAD) patients. Numerous efforts have been made to figure out and manage unstable plaques prior to major cardiovascular events incidence. The current study aims to assess the values of the atherogenic index of plasma (AIP) to detect unstable plaques.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods:<\/jats:title>\n                    <jats:p>\n                      The current case-control study was conducted on 435 patients who underwent percutaneous coronary intervention due to chronic stable angina (stable plaques,\n                      <jats:italic toggle=\"yes\">n<\/jats:italic>\n                      = 145) or acute coronary syndrome (unstable plaques,\n                      <jats:italic toggle=\"yes\">n<\/jats:italic>\n                      = 290). The demographic, comorbidities, chronic medications, biochemical and hematological characteristics of the patients were entered into the study checklist. The baseline AIP was measured according to the formula of triglycerides\/high-density lipoprotein logarithm. Binary logistic regression was applied to investigate the standalone association of AIP with plaque instability. Receiver operating curve (ROC) was depicted to determine a cut-off, specificity, and sensitivity of AIP in unstable plaques diagnosis.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>\n                      AIP was an independent predictor for atherogenic plaque unstability in both crude (odds ratio [OR]: 3.677, 95% confidence interval [CI]: 1.521\u20138.890;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      = 0.004) and full-adjusted models (OR: 15, 95% CI: 2.77\u201381.157;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      = 0.002). According to ROC curve, at cut-point level of 0.62, AIP had sensitivity and specificity of 89.70% and 34% to detect unstable plaques, respectively (area under the curve: 0.648, 95% CI: 0.601\u20130.692,\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt; 0.001).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>According to this study, at the threshold of 0.62, AIP as an independent biomarker associated with plaque instability can be considered a screening tool for patients at increased risk for adverse events due to unstable atherosclerotic plaques.<\/jats:p>\n                  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