B-type natriuretic peptides for the prediction of cardiovascular events and mortality in patients living with HIV: Results from the HIV-HEART study

Cardiac and Renal Comorbidities in Aging People Living With HIV

Contemporary World Health Organization data indicates that ≈39 million people are living with the human immunodeficiency virus. Of these, 24 million have been reported to have successfully accessed combination antiretroviral therapy. In 1996, the World Health Organization endorsed the widespread use of combination antiretroviral therapy, transforming human immunodeficiency virus infection from being a life-threatening disease to a chronic illness characterized by multiple comorbidities. The increased access to combination antiretroviral therapy has translated to people living with human immunodeficiency virus (PLWH) no longer having a reduced life expectancy. Although aging as a biological process increases exposure to oxidative stress and subsequent systemic inflammation, this effect is likely enhanced in PLWH as they age. This narrative review engages the intricate interplay between human immunodeficiency virus associated chronic inflammation, combination antiretroviral therapy, and cardiac and renal comorbidities development in aging PLWH. We examine the evolving demographic profile of PLWH, emphasizing the increasing prevalence of aging individuals within this population. A central focus of the review discusses the pathophysiological mechanisms that underpin the heightened susceptibility of PLWH to renal and cardiac diseases as they age.

The predictive accuracy of machine learning for the risk of death in HIV patients: a systematic review and meta-analysis

BACKGROUND

Early prediction of mortality in individuals with HIV (PWH) has perpetually posed a formidable challenge. With the widespread integration of machine learning into clinical practice, some researchers endeavor to formulate models predicting the mortality risk for PWH. Nevertheless, the diverse timeframes of mortality among PWH and the potential multitude of modeling variables have cast doubt on the efficacy of the current predictive model for HIV-related deaths. To address this, we undertook a systematic review and meta-analysis, aiming to comprehensively assess the utilization of machine learning in the early prediction of HIV-related deaths and furnish evidence-based support for the advancement of artificial intelligence in this domain.

METHODS

We systematically combed through the PubMed, Cochrane, Embase, and Web of Science databases on November 25, 2023. To evaluate the bias risk in the original studies included, we employed the Predictive Model Bias Risk Assessment Tool (PROBAST). During the meta-analysis, we conducted subgroup analysis based on survival and non-survival models. Additionally, we utilized meta-regression to explore the influence of death time on the predictive value of the model for HIV-related deaths.

RESULTS

After our comprehensive review, we analyzed a total of 24 pieces of literature, encompassing data from 401,389 individuals diagnosed with HIV. Within this dataset, 23 articles specifically delved into deaths during long-term follow-ups outside hospital settings. The machine learning models applied for predicting these deaths comprised survival models (COX regression) and other non-survival models. The outcomes of the meta-analysis unveiled that within the training set, the c-index for predicting deaths among people with HIV (PWH) using predictive models stands at 0.83 (95% CI: 0.75-0.91). In the validation set, the c-index is slightly lower at 0.81 (95% CI: 0.78-0.85). Notably, the meta-regression analysis demonstrated that neither follow-up time nor the occurrence of death events significantly impacted the performance of the machine learning models.

CONCLUSIONS

The study suggests that machine learning is a viable approach for developing non-time-based predictions regarding HIV deaths. Nevertheless, the limited inclusion of original studies necessitates additional multicenter studies for thorough validation.

The Association of HIV-Specific Risk Factors with Cardiovascular Events in Addition to Traditional Risk Factors in People Living with HIV

Traditional cardiovascular risk scores underestimate the incidence of cardiovascular diseases (CVD) in people living with HIV (PLH). This study compared the effect of HIV-specific cardiovascular risk factors (CRF) with traditional CRF at baseline for their association with incident CVD in PLH. The ongoing, prospective HIV HEART Aging (HIVH) study assesses CVD in PLH in the German Ruhr Area since 2004. PLH from the HIVH study with at least 5 years of follow-up were examined with the help of Cox proportional hazards models using inverse probability-of-censoring weights. The models were adjusted for age and sex. The obtained hazard ratios (HR) and 95% confidence limits (CL) assessed the strength of the associations between CRF and CVD. One thousand two hundred forty-three individuals (male 1,040, female 203; mean age of 43 ± 10 years) with 116 incident CVD events were analyzed. After adjusting for the traditional CRF, the HIV-specific CRF "a history of AIDS" and "higher age at diagnosis of HIV infection" (per 10 years) were associated with an increased CVD risk (HR 1.55, 95% CL: 1.05-2.28 and HR 1.55, 95% CL: 1.09-1.22, respectively). Higher CD4/CD8 ratio (per standard deviation), longer cumulative duration of antiretroviral therapies, and longer duration of HIV infection (per 10 years) showed indications for a decreased CVD risk (HR 0.75, 95% CL: 0.58-0.97, HR 0.71, 95% CL: 0.41-1.23, and HR 0.63, 95% CL: 0.44-0.90, respectively). Out of the traditional CRF, current smoking showed the strongest impact on CVD risk (HR 3.12, 95% CL: 2.06-4.74). In conclusion, HIV-specific factors, such as history of AIDS and CD4/CD8 ratio, were independently associated with an increased cardiovascular risk. Traditional CRF maintained a major effect on CVD. Clinical Trials Number (NCT04330287).

The Interplay between Adipose Tissue Properties and Levels of NT-proBNP in People with HIV

Objective

We aimed to assess the association between low N-terminal pro-brain natriuretic peptide (NT-proBNP) and body mass index (BMI), adipose tissue distribution, adiponectin, and HIV-specific risk factors among people with HIV (PWH).

Methods

We included 811 PWH with measurement of height, weight and waist circumference, blood samples analyzed for NT-proBNP, and visceral-(VAT) and subcutaneous (SAT) adipose tissue areas measured from CT-scans. Low concentrations of NT-proBNP were defined as concentrations below the limit of quantification (5.9 pmol/L). Associations were explored with multivariable logistic regression analyses adjusted for relevant confounders.

Results

We identified 471 (58%) individuals with low concentrations of NT-proBNP. Increasing BMI was associated with higher odds of low NT-proBNP (adjusted OR (aOR) 1.06 (95% CI: 1.01-1.11) per 1 kg/m2). Central obesity and large areas of VAT were associated with higher odds of low NT-proBNP (aOR 1.66 (1.16-2.36) and aOR 1.69 (1.09-2.62), respectively). Higher adiponectin was associated with lower odds of low NT-proBNP (aOR 0.86 (0.79-0.95) per 10% increase). No associations were found between low NT-proBNP and HIV-specific risk factors.

Conclusions

In PWH, low NT-proBNP is associated with an adverse adipose tissue profile with high BMI, central obesity, accumulation of VAT, and low adiponectin.