Prognostic value of atherogenic index of plasma in pulmonary hypertension
BackgroundThe atherogenic index of plasma (AIP) is a brand-new lipid parameter that has been used to assess various cardiovascular events. This study aimed to investigate the prognostic value of AIP in patients with pulmonary hypertension (PH).MethodsThis retrospective study was conducted at Shangha...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Medicine |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmed.2024.1490695/full |
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| Summary: | BackgroundThe atherogenic index of plasma (AIP) is a brand-new lipid parameter that has been used to assess various cardiovascular events. This study aimed to investigate the prognostic value of AIP in patients with pulmonary hypertension (PH).MethodsThis retrospective study was conducted at Shanghai Jiao Tong University School of Medicine affiliated Renji Hospital, and included data from 125 PH patients treated during 2014–2018. The endpoint events of this study were clinical worsening outcomes. PH patients include those from group 1 and group 4. AIP was determined as the logarithm of the blood triglycerides ratio to high-density lipoprotein cholesterol.ResultsThe 1-year, 3-year, and 5-year incidence rates of clinical worsening outcomes in PH patients in this study were 20.0, 44.8, and 54.4%, respectively. The median age of the PH patients was 38.00 years, with females accounting for 90.4%. After controlling for multivariable factors, the results of Cox regression analysis indicated that AIP was an independent predictor of adverse outcomes with a hazard ratio and 95% confident interval (CI) of 2.426 (1.021–5.763). The positive linear relationship of AIP was evaluated using restricted cubic spline analysis. Kaplan–Meier curves showed a significantly higher events rate in patients with AIP ≥ 0.144 compared to those with AIP < 0.144 (p = 0.002). Four potential prognostic variables, including AIP, were identified by LASSO regression to construct a nomogram. Compared to the model minus AIP, the AUC of the nomogram displayed a non-significant improvement (0.749 vs. 0.788, p = 0.298). In contrast, the results of net reclassification improvement (0.306, 95% CI: 0.039–0.459, p < 0.001) and integrated discrimination improvement (0.049, 95% CI: 0.006–0.097, p = 0.020) demonstrated significant enhancements in the predictive ability of the model when AIP was added to the clinical model.ConclusionAIP is an independent predictor of long-term clinical worsening in PH patients, and its inclusion in prognostic models could improve risk stratification and management. |
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| ISSN: | 2296-858X |