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Cardiac patients

HIV Patients at Higher Risk of Cardiovascular Diseases, Study Suggests

Strategic Insights

— 1 min read

Researchers at Polytechnic University Milan conducted a study to investigate the 15-year risk of cardiovascular diseases (CVDs) in people living with HIV (PLWH). The study used a neural network-based deep learning approach to analyze real-world data and predict the time to a CVD event. The results showed that PLWH are at a higher risk of developing CVDs, with a significant number of participants experiencing comorbidities such as hypertension and dyslipidemia. The study's findings highlight the need for early detection and management of CVDs in PLWH to improve their overall health outcomes.

Key Takeaways:

  • The study analyzed the 15-year CVD risk in PLWH using a survival analysis approach based on neural networks (NNs).
  • The research adopted a NN-based deep learning approach to flexibly model and predict the time to a CVD event, relaxing the linearity and proportional-hazard assumptions typical of the COX model.
  • The study included time-varying features and compared the results with classical survival analysis methods in terms of predictive performance and interpretability.
  • The study found that PLWH are at a higher risk of developing CVDs, with a significant number of participants experiencing comorbidities such as hypertension and dyslipidemia.
  • The researchers aimed to explore the potential of deep learning approaches in modeling survival data with time-varying features for supporting decision-making in real clinical settings.
  • The study involved a team of researchers from Polytechnic University Milan, including Chiara Masci, Agostino Lurani Cernuschi, Federica Corso, Francesca Ieva, Anna Maria Paganoni, Camilla Muccini, Daniele Ceccarelli, Laura Galli, and Antonella Castagna.
  • The study was conducted in collaboration with other institutions, with NSF funding, and has been peer-reviewed.

Statistics:

  • According to the study, 38.4 million people were living with HIV worldwide at the end of 2021.
  • The study analyzed real-world data from PLWH, which included 15 years of follow-up data.
  • The researchers used a deep learning approach to predict the time to a CVD event, which showed a significant correlation between HIV and CVD risk.
  • The study found that a significant number of participants experienced comorbidities such as hypertension and dyslipidemia.

Sources:

  • A Neural-network Approach for Predicting Time To Cardiovascular Diseases In Hiv Patients Based On Real-world Data. Operational Research, 2025;25(4).
  • Polytechnic University Milan. (www.polimi.it)
  • Springer Heidelberg. (www.springer.com)
  • NewsRx. (www.newsrx.com)

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