The investigators enrolled 126 clinically stable adults with HIV and obesity (BMI >30 kg/m²) in Lima-Callao in 2024. The cohort was predominantly male (77.7%) and middle-aged, with a mean age of 50.6 years. Mean BMI measured 34.0 kg/m². Participants had long-standing HIV care: mean time on antiretroviral therapy (ART) was 12.4 years, mean CD4 count was 759.8 cells/µL, and 97.6% had HIV-RNA below 200 copies/mL.
Clinical cardiovascular disease history was rare, recorded in 2.4% of participants. The study team described a largely virologically suppressed, immunologically stable sample, yet they set out to quantify subclinical and metabolic risk beyond self-reported clinical events.
Carotid imaging revealed a substantial burden of subclinical disease: 34.4% of participants had atherosclerotic changes defined by increased carotid intima-media thickness or presence of carotid plaque. The cohort-level finding contrasted sharply with the low prevalence of clinically reported cardiovascular disease. Data indicated that atherosclerotic changes were associated with older age and longer time on ART, according to the authors' observations.
The study reported these imaging results without detailing specific CIMT thresholds or ultrasound protocol parameters in the abstract; the source did not provide those imaging-method specifics in the available text.
Metabolic dysfunction was widespread. The study team observed abnormal glucose metabolism in 89.7% of participants and dyslipidemia in 82.5%. Half the cohort met criteria for metabolic syndrome (50.8%). Laboratory markers of systemic inflammation were elevated in 28.2% of participants, and low apolipoprotein A1 was present in 22.6%.
Only 8.1% of the sample had normal findings across all cardiometabolic evaluations. The authors reported these proportions directly; the abstract did not include subgroup breakdowns by sex, ART regimen, or duration beyond the aggregate associations noted with age and ART exposure.
Cardiovascular risk classification diverged markedly depending on the algorithm used. By Framingham risk score, 19.4% of participants were categorized as high risk. Using ACC/AHA criteria, 9.4% were high risk. The HIV-CARDIO-PREDICT score, an HIV-specific instrument, identified 75.4% of participants as high risk.
These contrasting proportions underscore how application of general-population tools versus an HIV-specific score can yield very different clinical risk flags in the same cohort. The abstract did not specify which input variables or thresholds produced the discordance nor whether the scores were recalibrated for local epidemiology; those methodological details were not reported in the source text provided.
The authors concluded that middle-aged, clinically stable people with HIV and obesity had a substantial burden of subclinical atherosclerosis and metabolic abnormalities despite minimal reported cardiovascular disease history. They observed that an HIV-specific risk tool classified a much larger proportion as high cardiovascular risk compared with general-population scores.
This study used a cross-sectional, observational design in a sample drawn from Lima-Callao in 2024. The design allows prevalence estimates but does not establish causality or temporal sequence for the associations reported. The abstract does not describe longitudinal follow-up, nor does it report the carotid ultrasound protocol thresholds, ART regimen-specific analyses, or detailed subgroup outcomes; the source did not include those elements in the available text.
Key unanswered clinical questions remain: which prevention strategies—behavioral, pharmacologic, or ART modification—would most effectively reduce progression from subclinical atherosclerosis to clinical events in this population? Which risk score best predicts hard cardiovascular outcomes among people with HIV and obesity in Peru? The authors recommended targeted evaluation and timely preventive management but did not report follow-up data showing the impact of such interventions.
Clinicians and program planners reading these results should note the high prevalence of metabolic abnormalities and the wide variation between risk calculators. Further studies with longitudinal outcomes, standardized imaging protocols, and regimen-stratified analyses will be necessary to guide case finding and prevention pathways in similar populations.