Skip to content
2000
Volume 23, Issue 4
  • ISSN: 1570-162X
  • E-ISSN: 1873-4251

Abstract

Objective

Patients living with HIV (PLHIV) have a higher cardiovascular risk than others, which is why the early detection of atherosclerosis in this population is important. The present study reports predictive models of subclinical atherosclerosis for this population of patients, made up of variables that are easily collected in the clinic.

Methods

The study design is a cross-sectional observational study. PLHIV without established cardiovascular disease were recruited for this study. Predictive models of subclinical atherosclerosis (Doppler ultrasound) were developed by testing sociodemographic variables, pathological history, data related to HIV infection, laboratory parameters, and capillaroscopy as potential predictors. Logistic regression with internal validation (bootstrapping) and machine learning techniques were used to develop the models.

Results

Data from 96 HIV patients were analysed, 19 (19.8%) of whom had subclinical atherosclerosis. The predictors that went into both machine learning models and the regression model were hypertension, dyslipidaemia, protease inhibitors, triglycerides, fibrinogen, and alkaline phosphatase. Age and C-reactive protein were also part of the machine learning models. The logistic regression model had an area under the receiver operating characteristic curve (AUC) of 0.91 (95% CI: 0.84-0.99), which became 0.80 after internal validation by bootstrapping. The machine learning techniques produced models with AUCs ranging from 0.73 to 0.86.

Conclusion

We report predictive models for subclinical atherosclerosis in PLHIV, demonstrating relevant predictive performance based on easily accessible parameters, making them potentially useful as a screening tool. However, given the study’s limitations—primarily the sample size-external validation in larger cohorts is warranted.

© 2025 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/chr/10.2174/011570162X373384250529110832
2025-06-05
2025-11-16

  • From This Site

    /content/journals/chr/10.2174/011570162X373384250529110832
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. WandelerG. JohnsonL.F. EggerM. Trends in life expectancy of HIV-positive adults on antiretroviral therapy across the globe.Curr. Opin. HIV AIDS201611549250010.1097/COH.000000000000029827254748
     [Google Scholar]
  2. ManfrediR. HIV infection and advanced age.Ageing Res. Rev.200431315410.1016/j.arr.2003.07.00115164725
     [Google Scholar]
  3. TeeraananchaiS. KerrS.J. AminJ. RuxrungthamK. LawM.G. Life expectancy of HIV ‐positive people after starting combination antiretroviral therapy: A meta‐analysis.HIV Med.201718425626610.1111/HIV.1242127578404
     [Google Scholar]
  4. DurandM. SheehyO. BarilJ.G. LelorierJ. TremblayC.L. Association between HIV infection, antiretroviral therapy, and risk of acute myocardial infarction: A cohort and nested case-control study using Québec’s public health insurance database.J. Acquir. Immune Defic. Syndr.201157324525310.1097/QAI.0b013e31821d33a521499115
     [Google Scholar]
  5. ShahA.S.V. StelzleD. LeeK.K. Global burden of atherosclerotic cardiovascular disease in people living with HIV.Circulation2018138111100111210.1161/CIRCULATIONAHA.117.03336929967196
     [Google Scholar]
  6. YangY. YaoX. LiuY. Global and regional estimate of HIV-associated stroke burden: A meta-analysis and population attributable modeling study.Stroke20235492390240010.1161/STROKEAHA.123.04341037477007
     [Google Scholar]
  7. ZhuS. WangW. HeJ. Higher cardiovascular disease risks in people living with HIV: A systematic review and meta-analysis.J. Glob. Health2024140407810.7189/jogh.14.0407838666515
     [Google Scholar]
  8. AlonsoA. BarnesA.E. GuestJ.L. ShahA. ShaoI.Y. MarconiV. HIV infection and incidence of cardiovascular diseases: An analysis of a large healthcare database.J. Am. Heart Assoc.2019814e01224110.1161/JAHA.119.01224131266386
     [Google Scholar]
  9. NouE. LoJ. HadiganC. GrinspoonS.K. Pathophysiology and management of cardiovascular disease in patients with HIV.Lancet Diabetes Endocrinol.20164759861010.1016/S2213‑8587(15)00388‑526873066
     [Google Scholar]
  10. SackoffJ.E. HannaD.B. PfeifferM.R. TorianL.V. Causes of death among persons with AIDS in the era of highly active antiretroviral therapy: New York City.Ann. Intern. Med.2006145639740610.7326/0003‑4819‑145‑6‑200609190‑0000316983127
     [Google Scholar]
  11. SchwarczS.K. VuA. HsuL.C. HessolN.A. Changes in causes of death among persons with AIDS: San Francisco, California, 1996-2011.AIDS Patient Care STDS2014281051752310.1089/apc.2014.007925275657
     [Google Scholar]
  12. TriantV.A. LeeH. HadiganC. GrinspoonS.K. Increased acute myocardial infarction rates and cardiovascular risk factors among patients with human immunodeficiency virus disease.J. Clin. Endocrinol. Metab.20079272506251210.1210/jc.2006‑219017456578
     [Google Scholar]
  13. FreibergM.S. ChangC.C.H. KullerL.H. HIV infection and the risk of acute myocardial infarction.JAMA Intern. Med.2013173861462210.1001/jamainternmed.2013.372823459863
     [Google Scholar]
  14. HasseB. LedergerberB. FurrerH. Morbidity and aging in HIV-infected persons: The Swiss HIV cohort study.Clin. Infect. Dis.201153111130113910.1093/cid/cir62621998280
     [Google Scholar]
  15. FeinsteinM.J. HsueP.Y. BenjaminL.A. Characteristics, prevention, and management of cardiovascular disease in people living with HIV: A scientific statement from the american heart association.Circulation20191402e98e12410.1161/CIR.000000000000069531154814
     [Google Scholar]
  16. RaddusaP.M.S. MarinoA. CelesiaB.M. Atherosclerosis and cardiovascular complications in people living with HIV: A focused review.Infect. Dis. Rep.202416584686310.3390/idr1605006639311207
     [Google Scholar]
  17. ObareL.M. TemuT. MallalS.A. WanjallaC.N. Inflammation in HIV and its impact on atherosclerotic cardiovascular disease.Circ. Res.2024134111515154510.1161/CIRCRESAHA.124.32389138781301
     [Google Scholar]
  18. Friis-MøllerN. ThiébautR. ReissP. Predicting the risk of cardiovascular disease in HIV-infected patients: The Data collection on Adverse Effects of Anti-HIV Drugs Study.Eur. J. Cardiovasc. Prev. Rehabil.201017549150110.1097/HJR.0b013e328336a15020543702
     [Google Scholar]
  19. PostW.S. BudoffM. KingsleyL. Associations between HIV infection and subclinical coronary atherosclerosis.Ann. Intern. Med.2014160745846710.7326/M13‑175424687069
     [Google Scholar]
  20. Serrano-VillarS. EstradaV. Gómez-GarreD. Diagnosis of subclinical atherosclerosis in HIV-infected patients: Higher accuracy of the D:A:D risk equation over Framingham and SCORE algorithms.Eur. J. Prev. Cardiol.201421673974810.1177/204748731245296422718798
     [Google Scholar]
  21. CardinalR.M.H. DurandM. Chartrand-LefebvreC. SoulezG. TremblayC. CloutierG. Associative prediction of carotid artery plaques based on ultrasound strain imaging and cardiovascular risk factors in people living with HIV and age-matched control subjects of the CHACS cohort.J. Acquir. Immune Defic. Syndr.20229119110010.1097/QAI.000000000000301635510848
     [Google Scholar]
  22. SocioD.G.V.L. MartinelliC. RicciE. Relations between cardiovascular risk estimates and subclinical atherosclerosis in naïve HIV patients: Results from the HERMES study.Int. J. STD AIDS201021426727210.1258/ijsa.2009.00916520378899
     [Google Scholar]
  23. SotoF.J. Romero-JiménezM.J. GarcíaA.J.C. EstruchB.E. RamosS.J.L. LópezC.M.Á. Predictors of subclinical atherosclerosis in HIV.BMC Infect. Dis.20232311710.1186/s12879‑022‑07976‑136627565
     [Google Scholar]
  24. Verdejo-MuñozG. Gálvez-BarrónC. TelloG.B. Capillaroscopy, microangiopathy, and HIV. Descriptive study of capillaroscopy findings in HIV positive patients.An. Sist. Sanit. Navar.2022453e101510.23938/ASSN.101536468584
     [Google Scholar]
  25. Verdejo-MuñozG. Gálvez-BarrónC. Gamarra-CalvoS. CondeC.I. CatenaA. RamosB.J.R. Usefulness of artery femoral ultrasound complementary to carotid exploration for the detection of subclinical atheromatosis in patients with human immunodeficiency virus infection.Med. Clin.20231601044344610.1016/j.medcli.2022.11.02436759302
     [Google Scholar]
  26. SmithV. HerrickA.L. IngegnoliF. Standardisation of nailfold capillaroscopy for the assessment of patients with Raynaud’s phenomenon and systemic sclerosis.Autoimmun. Rev.202019310245810.1016/j.autrev.2020.10245831927087
     [Google Scholar]
  27. BergmanR. SharonyL. SchapiraD. NahirM.A. Balbir-GurmanA. The handheld dermatoscope as a nail-fold capillaroscopic instrument.Arch. Dermatol.200313981027103010.1001/archderm.139.8.102712925391
     [Google Scholar]
  28. TouboulP.J. HennericiM.G. MeairsS. Mannheim intima-media thickness consensus.Cerebrovasc. Dis.200418434634910.1159/00008181215523176
     [Google Scholar]
  29. TouboulP.J. HennericiM.G. MeairsS. Mannheim carotid intima-media thickness consensus (2004-2006). An update on behalf of the Advisory Board of the 3rd and 4th Watching the Risk Symposium, 13th and 15th European Stroke Conferences, Mannheim, Germany, 2004, and Brussels, Belgium, 2006.Cerebrovasc. Dis.2007231758010.1159/00009703417108679
     [Google Scholar]
  30. TouboulP.J. HennericiM.G. MeairsS. Mannheim carotid intima-media thickness and plaque consensus (2004-2006-2011). An update on behalf of the advisory board of the 3rd, 4th and 5th watching the risk symposia, at the 13th, 15th and 20th european stroke conferences, mannheim, germany, 2004, brussels, belgium, 2006, and hamburg, germany, 2011.Cerebrovasc. Dis.201234429029610.1159/00034314523128470
     [Google Scholar]
  31. LorenzM.W. MarkusH.S. BotsM.L. RosvallM. SitzerM. Prediction of clinical cardiovascular events with carotid intima-media thickness: A systematic review and meta-analysis.Circulation2007115445946710.1161/CIRCULATIONAHA.106.62887517242284
     [Google Scholar]
  32. O’LearyD.H. PolakJ.F. WolfsonS.K. Use of sonography to evaluate carotid atherosclerosis in the elderly. The Cardiovascular Health Study.Stroke19912291155116310.1161/01.STR.22.9.11551926258
     [Google Scholar]
  33. PetersS.A.E. RuijterD.H.M. BotsM.L. MoonsK.G.M. Improvements in risk stratification for the occurrence of cardiovascular disease by imaging subclinical atherosclerosis: A systematic review.Heart201298317718410.1136/heartjnl‑2011‑30074722095617
     [Google Scholar]
  34. HannaD.B. MoonJ.Y. HaberlenS.A. Carotid artery atherosclerosis is associated with mortality in HIV-positive women and men.AIDS201832162393240310.1097/QAD.000000000000197230102657
     [Google Scholar]
  35. MangiliA. PolakJ.F. QuachL.A. GerriorJ. WankeC.A. Markers of atherosclerosis and inflammation and mortality in patients with HIV infection.Atherosclerosis2011214246847310.1016/j.atherosclerosis.2010.11.01321130995
     [Google Scholar]
  36. BelcaroG. NicolaidesA.N. RamaswamiG. Carotid and femoral ultrasound morphology screening and cardiovascular events in low risk subjects: A 10-year follow-up study (the CAFES-CAVE study).Atherosclerosis2001156237938710.1016/S0021‑9150(00)00665‑111395035
     [Google Scholar]
  37. ProtogerouA.D. FransenJ. ZampeliE. The Additive value of femoral ultrasound for subclinical atherosclerosis assessment in a single center cohort of 962 adults, including high risk patients with rheumatoid arthritis, human immunodeficiency virus infection and type 2 diabetes mellitus.PLoS One2015107e013230710.1371/journal.pone.013230726230728
     [Google Scholar]
  38. PostleyJ.E. LuoY. WongN.D. GardinJ.M. Identification by ultrasound evaluation of the carotid and femoral arteries of high-risk subjects missed by three validated cardiovascular disease risk algorithms.Am. J. Cardiol.2015116101617162310.1016/j.amjcard.2015.08.03126434511
     [Google Scholar]
  39. SimonN. FriedmanJ. HastieT. TibshiraniR. Regularization paths for cox’s proportional hazards model via coordinate descent.J. Stat. Softw.201139511310.18637/jss.v039.i0527065756
     [Google Scholar]
  40. MoonsK.G.M. AltmanD.G. ReitsmaJ.B. Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): Explanation and elaboration.Ann. Intern. Med.20151621W1W7310.7326/M14‑069825560730
     [Google Scholar]
  41. BurnhamK.P. EfronB. The jackknife, the bootstrap and other resampling plans.Biometrics198339381681710.2307/2531123
     [Google Scholar]
  42. RossumV.G. DrakeF.L. Python 3 Reference Manual.Scotts Valley, CaliforniaCreateSpace200919
     [Google Scholar]
  43. Team RC. R: A language and environment for statistical computing.2022Available from: http://www.R-project.org/
  44. Friis-MøllerN. ReissP. SabinC.A. Class of antiretroviral drugs and the risk of myocardial infarction.N. Engl. J. Med.2007356171723173510.1056/NEJMoa06274417460226
     [Google Scholar]
  45. SankatsingR.R. WitF.W. VogelM. Increased carotid intima-media thickness in HIV patients treated with protease inhibitors as compared to non-nucleoside reverse transcriptase inhibitors.Atherosclerosis2009202258959510.1016/j.atherosclerosis.2008.05.02818599064
     [Google Scholar]
  46. HolmbergS.D. MoormanA.C. WilliamsonJ.M. Protease inhibitors and cardiovascular outcomes in patients with HIV-1.Lancet200236093471747174810.1016/S0140‑6736(02)11672‑212480430
     [Google Scholar]
  47. AlviR.M. NeilanA.M. TariqN. Protease inhibitors and cardiovascular outcomes in patients with HIV and heart failure.J. Am. Coll. Cardiol.201872551853010.1016/j.jacc.2018.04.08330049313
     [Google Scholar]
  48. KannG. OwasilJ. KuczkaK. Evaluation of platelet activation by HIV protease inhibitors – the HIV-PLA II study.HIV AIDS20211378980010.2147/HIV.S26228234393518
     [Google Scholar]
  49. TurcotteI. El-FarM. SadouniM. Association between the development of subclinical cardiovascular disease and human immunodeficiency virus (HIV) reservoir markers in people with HIV on suppressive antiretroviral therapy.Clin. Infect. Dis.20237671318132110.1093/cid/ciac87436346439
     [Google Scholar]
  50. VemulapalliA.C. EliasA.A. YerramsettiM.D. The impact of contemporary antiretroviral drugs on atherosclerosis and its complications in people living with HIV: A systematic review.Cureus20231510e4773010.7759/cureus.4773038021858
     [Google Scholar]
  51. LaurenceJ. ElhadadS. AhamedJ. HIV-associated cardiovascular disease: Importance of platelet activation and cardiac fibrosis in the setting of specific antiretroviral therapies.Open Heart201852e00082310.1136/openhrt‑2018‑00082330018781
     [Google Scholar]
  52. SukumaranL. KunisakiK.M. BakewellN. Association between inflammatory biomarker profiles and cardiovascular risk in individuals with and without.HIV AIDS202337459560310.1097/QAD.000000000000346236541572
     [Google Scholar]
  53. MooneyS. TracyR. OslerT. GraceC. Elevated biomarkers of inflammation and coagulation in patients with HIV are associated with higher framingham and vacs risk index scores.PLoS One20151012e014431210.1371/journal.pone.014431226641655
     [Google Scholar]
  54. TriantV.A. MeigsJ.B. GrinspoonS.K. Association of C-reactive protein and HIV infection with acute myocardial infarction.J. Acquir. Immune Defic. Syndr.200951326827310.1097/QAI.0b013e3181a9992c19387353
     [Google Scholar]
  55. BakerJ.V. DuprezD. Biomarkers and HIV-associated cardiovascular disease.Curr. Opin. HIV AIDS20105651151610.1097/COH.0b013e32833ed7ec20978394
     [Google Scholar]
  56. SubramanyaV. McKayH.S. BruscaR.M. Inflammatory biomarkers and subclinical carotid atherosclerosis in HIV-infected and HIV-uninfected men in the Multicenter AIDS Cohort Study.PLoS One2019144e021473510.1371/journal.pone.021473530946765
     [Google Scholar]
  57. SsinabulyaI. KayimaJ. LongeneckerC. Subclinical atherosclerosis among HIV-infected adults attending HIV/AIDS care at two large ambulatory HIV clinics in Uganda.PLoS One201492e8953710.1371/journal.pone.008953724586854
     [Google Scholar]
  58. MoranC.A. ShethA.N. MehtaC.C. The association of C-reactive protein with subclinical cardiovascular disease in HIV-infected and HIV-uninfected women.AIDS2018328999100610.1097/QAD.000000000000178529438198
     [Google Scholar]
  59. TonelliM. CurhanG. PfefferM. Relation between alkaline phosphatase, serum phosphate, and all-cause or cardiovascular mortality.Circulation2009120181784179210.1161/CIRCULATIONAHA.109.85187319841303
     [Google Scholar]
  60. LaiZ. LiuY. HuangM. Associations between atherosclerosis and elevated serum alkaline phosphatase in patients with coronary artery disease in an inflammatory state.Heart Lung Circ.20233291096110610.1016/j.hlc.2023.05.01237550157
     [Google Scholar]
  61. PanhL. RuidavetsJ.B. RousseauH. Association between serum alkaline phosphatase and coronary artery calcification in a sample of primary cardiovascular prevention patients.Atherosclerosis2017260818610.1016/j.atherosclerosis.2017.03.03028371683
     [Google Scholar]
  62. HaarhausM. RayK.K. NichollsS.J. Apabetalone lowers serum alkaline phosphatase and improves cardiovascular risk in patients with cardiovascular disease.Atherosclerosis2019290596510.1016/j.atherosclerosis.2019.09.00231568963
     [Google Scholar]
  63. RyuW.S. LeeS.H. KimC.K. KimB.J. KwonH.M. YoonB.W. High serum alkaline phosphatase in relation to cerebral small vessel disease.Atherosclerosis2014232231331810.1016/j.atherosclerosis.2013.11.04724468144
     [Google Scholar]
/content/journals/chr/10.2174/011570162X373384250529110832
Loading
Predictive Model for the Detection of Subclinical Atherosclerosis in HIV Patients on Antiretroviral Treatment
Cur. HIV Res. 23, 230 (2025); https://doi.org/10.2174/011570162X373384250529110832
/content/journals/chr/10.2174/011570162X373384250529110832
/content/journals/chr/10.2174/011570162X373384250529110832
Loading

Data & Media loading...


  • Article Type:     Research Article
Keyword(s): atherosclerosis; cardiovascular diseases; carotid arteries; coronary artery disease; development of HIV; heart disease risk factors; HIV; ultrasonography

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test