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Mild renal impairment is associated with calcified plaque parameters assessed by computed tomography angiography in people living with HIV.

ABSTRACT: OBJECTIVE:To investigate the association of mild renal impairment and coronary plaque in people living with HIV (PLHIV). METHODS:PLHIV and non-HIV controls with serum creatinine less than 1.5?mg/dl were investigated. Estimated glomerular filtration rate (eGFR) (calculated by CKD-EPI formula) was related to coronary plaque indices obtained by CT angiography. RESULTS:One hundred and eighty-four PLHIV [HIV viral load, 49 (47,49) copies/ml, CD4+ cell count, median 536 (370, 770) cells/?l, duration HIV, 15?±?7 years] and 72 HIV-negative controls without known cardiovascular disease (CVD) were studied. The two groups were well matched for traditional CVD risk factors. Serum creatinine (0.9?±?0.2 vs. 0.9?±?0.2?mg/dl, P?=?0.96) and eGFR (96?±?22 vs. 96?±?24?ml/min per 1.73?m(2), P?=?0.99) were similar between PLHIV and non-HIV, respectively. In PLHIV, eGFR inversely related to total severity of coronary plaque score (r?=?-0.27, P?=?0.002), total coronary segments with plaque (r?=?-0.21, P?=?0.005), calcified plaque segments (r?=?-0.15, P?=?0.045), and Agatston score (r?=?-0.21, P?=?0.006). Adjusting for total Framingham point score, BMI, and HIV parameters, eGFR remained significantly associated with calcified plaque and Agatston score in PLHIV. In HIV negative controls, eGFR did not correlate with calcified plaque (r?=?-0.20, P?=?0.10) or Agatston score (r?=?-0.13, P?=?0.29). Among PLHIV, those with eGFR less than 90?ml/min per 1.73?m(2) demonstrated increased total severity of coronary plaque score compared with those with eGFR greater than or equal to 90, P?=?0.02). This relationship was stronger in PLHIV than the non-HIV group. CONCLUSION:Our data highlight a robust relationship between subclinical renal impairment and coronary artery disease among PLHIV. Further research is needed to understand the relationship between mild renal impairment and CVD in HIV.

SUBMITTER: Cheru LT

PROVIDER: S-EPMC6298826 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Mild renal impairment is associated with calcified plaque parameters assessed by computed tomography angiography in people living with HIV.

Cheru Lediya T LT Fitch Kathleen V KV Saylor Charles F CF Lu Michael M Hoffmann Udo U Lo Janet J Grinspoon Steven K SK

AIDS (London, England) 20190201 2

<h4>Objective</h4>To investigate the association of mild renal impairment and coronary plaque in people living with HIV (PLHIV).<h4>Methods</h4>PLHIV and non-HIV controls with serum creatinine less than 1.5 mg/dl were investigated. Estimated glomerular filtration rate (eGFR) (calculated by CKD-EPI formula) was related to coronary plaque indices obtained by CT angiography.<h4>Results</h4>One hundred and eighty-four PLHIV [HIV viral load, 49 (47,49) copies/ml, CD4+ cell count, median 536 (370, 770 ...[more]

PMID: 30325774

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Project description:Vulnerable carotid atherosclerotic plaque (CAP) significantly contributes to ischemic stroke. Neovascularization within plaques is an emerging biomarker linked to plaque vulnerability that can be detected using contrast-enhanced ultrasound (CEUS). Computed tomography angiography (CTA) is a common method used in clinical cerebrovascular assessments that can be employed to evaluate the vulnerability of CAPs. Radiomics is a technique that automatically extracts radiomic features from images. This study aimed to identify radiomic features associated with the neovascularization of CAP and construct a prediction model for CAP vulnerability based on radiomic features. CTA data and clinical data of patients with CAPs who underwent CTA and CEUS between January 2018 and December 2021 in Beijing Hospital were retrospectively collected. The data were divided into a training cohort and a testing cohort using a 7:3 split. According to the examination of CEUS, CAPs were dichotomized into vulnerable and stable groups. 3D Slicer software was used to delineate the region of interest in CTA images, and the Pyradiomics package was used to extract radiomic features in Python. Machine learning algorithms containing logistic regression (LR), support vector machine (SVM), random forest (RF), light gradient boosting machine (LGBM), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and multi-layer perception (MLP) were used to construct the models. The confusion matrix, receiver operating characteristic (ROC) curve, accuracy, precision, recall, and f-1 score were used to evaluate the performance of the models. A total of 74 patients with 110 CAPs were included. In all, 1,316 radiomic features were extracted, and 10 radiomic features were selected for machine-learning model construction. After evaluating several models on the testing cohorts, it was discovered that model_RF outperformed the others, achieving an AUC value of 0.93 (95% CI: 0.88-0.99). The accuracy, precision, recall, and f-1 score of model_RF in the testing cohort were 0.85, 0.87, 0.85, and 0.85, respectively. Radiomic features associated with the neovascularization of CAP were obtained. Our study highlights the potential of radiomics-based models for improving the accuracy and efficiency of diagnosing vulnerable CAP. In particular, the model_RF, utilizing radiomic features extracted from CTA, provides a noninvasive and efficient method for accurately predicting the vulnerability status of CAP. This model shows great potential for offering clinical guidance for early detection and improving patient outcomes.

Dataset Information

Mild renal impairment is associated with calcified plaque parameters assessed by computed tomography angiography in people living with HIV.

Publications

Mild renal impairment is associated with calcified plaque parameters assessed by computed tomography angiography in people living with HIV.

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