• Users Online: 8877
  • Home
  • Print this page
  • Email this page

 Table of Contents  
Year : 2022  |  Volume : 11  |  Issue : 1  |  Page : 16-22

Multimorbidity among persons living with human immunodeficiency virus in a moroccan referral hospital

Department of Dermatology-Venereology, Mohammed V Military Teaching Hospital, Mohammed V University, Rabat, Morocco

Date of Submission17-Jan-2022
Date of Decision28-Jan-2022
Date of Acceptance26-Feb-2022
Date of Web Publication12-Mar-2022

Correspondence Address:
Hicham Titou
Department of Dermatology-Venereology, Mohammed V Military Teaching Hospital, Mohammed V University, Rabat 10100
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/2212-5531.307070

Rights and Permissions

Background: Multimorbidity is the co-existing of two or more chronic health conditions in addition to human immunodeficiency virus (HIV). In Morocco, the prevalence of and factors associated with multimorbidity in HIV-infected patients have not been well-documented. Methods: This cross-sectional analysis was conducted in 2018 and included 269 HIV-infected patients. Medical records were reviewed to identify chronic health conditions and to rate multimorbidity using the Cumulative Illness Rating Scale (CIRS). Associations between a higher CIRS score and risk factors were assessed using linear regression. Results: The mean age was 48.9 ± 10.7 years with a male predominance (75.5%). One in 5 (20,8%) had ever been diagnosed with acquired immunodeficiency syndrome. More than a 3rd (34.8%) of the patients had two or more chronic health conditions in addition to HIV. The most frequently documented comorbidities were metabolic complications followed by vascular disease. In multivariate analysis, older age, male gender, duration of receiving antiretroviral therapy, taking indinavir-containing antiretroviral regimen, having ever been stage Centers for Disease Control and Prevention B or C, and current viral load ≥50 copies mL–1 were associated with a higher CIRS score. Conclusion: The prevalence of comorbidities is substantially high. Care models for people living with HIV should include assessing and managing multimorbidity, particularly in patients who present with these associated factors.

Keywords: Ageing, Cumulative Illness Rating Scale score, comorbidities, human immunodeficiency virus, multimorbidity

How to cite this article:
Titou H, Kerrouch H, Boui M, Hjira N. Multimorbidity among persons living with human immunodeficiency virus in a moroccan referral hospital. Int J Mycobacteriol 2022;11:16-22

How to cite this URL:
Titou H, Kerrouch H, Boui M, Hjira N. Multimorbidity among persons living with human immunodeficiency virus in a moroccan referral hospital. Int J Mycobacteriol [serial online] 2022 [cited 2022 May 20];11:16-22. Available from: https://www.ijmyco.org/text.asp?2022/11/1/16/307070

  Introduction Top

Since the widespread use of combination antiretroviral therapy (ART), the life expectancy of people living with human immunodeficiency virus (PLWH) has increased substantially, nearing that of the general population.[1],[2] As a result, human immunodeficiency virus (HIV)-related morbidity and mortality have decreased substantially[3],[4] and the issue of healthy aging with HIV has become a major concern. HIV-related care has transformed from acquired immunodeficiency syndrome (AIDS) and diseases related to immune deficiency to other diseases.[5]

The aging of the HIV-positive population has resulted in a change in the causes of mortality of PLWH and an increasing impact of nonAIDS-related comorbidities.[6],[7] A literature review demonstrates that nonAIDS-related comorbidities appear[8] earlier and with a higher prevalence.[6],[9] These include cardiovascular disease, metabolic syndrome, renal and bone disease, neurocognitive impairment, and cancer.[7],[10]

In several research studies, multimorbidity is defined as the co-occurrence of two or more chronic health conditions in addition to HIV.[11],[12],[13] Among PLWH, studies have reported associations of multimorbidity with age, low immune status, the duration of receiving ART, male gender, and specific drug regimens.[7],[10],[14] In a population of PLWH, multimorbidity has been associated with adverse health outcomes, such as poor quality of life[15] and increased medical care costs.[16] However, studies investigating the prevalence and determinants of multimorbidity of PLWH in low- and middle-income countries, such as Morocco, are scarce. Concomitant management of HIV and other conditions is complicated by polypharmacy/drug interactions and toxicity.[17] HIV and other conditions (obesity, diabetes, and hepatitis C virus coinfection) may amplify, increasing the risk of a third condition or multimorbidity, more than either condition alone.[13],[18]

As the median age of PLWH increases, advocates of PLWH, healthcare workers, and policymakers will need to design health services to manage patients with multimorbidity. For that, improved understanding of the burden and risk factors of multimorbidity contribute to improving the management and care of PLWH. The aims of this study were to investigate the prevalence of and associations with multimorbidity in HIV-positive patients in a Moroccan hospital.

  Methods Top

Study population

This was an analytical study conducted on a monocentric retrospective cohort. The study population consists of all patients infected with HIV type 1 and followed in the Dermatology–Venereology Department of Mohamed V Military Hospital, between February 1, 2018, and January 31, 2019. This regional referral center ensures care and monitoring of HIV-positive military personnel and their families in Morocco.

Data collection

In this study, the inclusion criteria were age ≥18 years, the presence of HIV-1-positive serology confirmed by the Western blot or polymerase chain reaction, and on ART for at least 6 months. Data, including sociodemographic characteristics (age, sex), addictive behaviors (smoking, alcohol and drug use), clinical data (HIV history, duration of receiving ART, current and past therapeutic regimens, number of visits to the clinic), anthropometric data (weight, height), biological data (cluster de differentiation 4 [CD4] counts, viral load). The data were extracted by a single investigator from medical records using a preestablished list of the most common conditions among PLWH.

We evaluated the prevalence of multimorbidity as described by the presence of two or more chronic health conditions in addition to HIV. Multimorbidity was also assessed using the Fourteen-system Modified Version Cumulative Illness Rating Scale (CIRS).[19] As a rapid assessment technique which is objective and easily quantified, The CIRS provides for the rating of 14 independent organ areas. Rating is given on a 5 point “degree of severity” scale, ranging from 0 (none) to 5 (extremely severe). The theoretical score varies from 0 to 56, but scores near the highest value are incompatible with life. The CIRS has been shown to be valid[20] and reliable as a predictor of health-related quality of life.[21] We also calculated the number of systems affected and the number of systems with a score of three or more.[22]

HIV progression was measured using the index Veterans Aging Cohort Study (VACS). It incorporates Age and CD4 count, viral load, renal function, hemoglobin, index of liver fibrosis, and HCV co-infection routinely.[23] The VACS Index is strongly associated with inflammatory biomarkers.

Statistical analysis

The primary outcome measure was the CIRS score. Univariate and multivariate linear regressions were conducted to determine factors associated with a higher CIRS score. Multivariable analyses were performed using the variables with P < 0.05 (95% confidence interval) from the univariable analysis to identify risk factors for multimorbidity. The smoking was excluded in building the multivariate model. The backward stepwise method was used to build a multivariate model.

The chronic health conditions were not included in building a multivariate model, as the existence of these conditions certainly increases the CIRS score. After achieving the final model, we analyzed each of the chronic health conditions individually in the multivariate model. We also used Akaike Information Criteria (AIC) to establish relative participation in the quality of fit of the multivariate model. A lower AIC shows a better quality of fit. Statistical analysis was conducted using the Statistical Package for the Social Sciences (IBM SPSS Statistics for Windows, Version 25.0; IBM Corp., Armonk, New York).

  Results Top

A total of 269 PLWH was recruited into the study with a predominance of males (75.5%) [Table 1]. The mean age was 48.9 ± 10.7 years and the median duration of receiving ART was 11 years (interquartile range [IQR] 6–15 years). More than 70% of patients had ever had A or B clinical Centers for Disease Control and Prevention (CDC) stage. The median CD4 + T-cell count was 613 cells ml–1 (IQR 390–784 cells ml–1). Additional patient characteristics are summarized in [Table 1].
Table 1: Characteristics of 269 HIV-infected patients

Click here to view


Of the specific chronic health conditions evaluated, metabolic complications diagnosis was the most common, followed by vascular disease and mental health disorder [Table 2]. More than a third of the patients (34.8%) had multimorbidity, defined as the co-occurrence of more than one chronic health condition in addition to HIV [Figure 1]. In patients younger than 40 years, multimorbidity was present in 15.4%. In patients aged 41–50 years, multimorbidity was present in 25.6%. Multimorbidity increased over the age of 50 years, with 45.8% and 51.6% of patients aged 51–60 years and 61 years and older, respectively, developed multimorbidity.
Table 2: Prevalence of chronic health conditions in Mohamed V Military Hospital, Department of Dermatology-Venereology

Click here to view
Figure 1: Percentage of patients and number of comorbidities

Click here to view

All patients with metabolic complications, renal disease and stroke had another chronic health condition in addition to HIV and hence had multimorbidity. The most prevalent multimorbidity was the concomitant of metabolic complication diagnosis and alcohol or other drug issues, occurring in 13 patients (4.8%), followed by metabolic complication diagnosis and vascular disease, occurring in 9 patients (3.3%), followed by vascular disease diagnosis and alcohol or other drug issues, occurring in 9 patients (3.3%). The most prevalent combination of three chronic health conditions was the diagnosis of metabolic complications, vascular disease, and alcohol or other drug issues in 10 patients (3.7%).

A median of 4 systems (range 1–11) were affected in CIRS and 160 (96.6%) lived morbidity across two or more systems. The median CIRS score was 8 (range 1–21). The median severity index (score divided by the number of systems touched) was 1.60 (range 1.00–2.75). Ninety-six (35.6%) scored 3–4 in at least one system, showing severe or extremely severe condition, while 37 (13.7%) scored 3–4 in two or more systems in addition to HIV.

Correlates of multimorbidity

In univariate linear regression analysis, increasing age, male gender, smoking, duration of receiving ART, indinavir-containing antiretroviral regimen, having ever been stage CDC B or C, nadir CD4 count <200 cells mL–1, current CD4 cell count >700 cells mL–1, peak viral load >10,000 copies mL–1, and current viral load >50 copies mL–1 were significantly associated with a higher CIRS score [Table 3].
Table 3: Correlates of multimorbidity

Click here to view

In multivariate analysis, a higher CIRS score was significantly associated with increasing age, male gender, duration of receiving ART, indinavir-containing antiretroviral regimen, having ever been stage CDC B or C, and current viral load > 50 copies mL–1 [Table 3].

We explored the correlation between alternative multimorbidity measures and the CIRS score. While all were significantly associated with a higher CIRS score (P < 0.01).

Contribution of chronic health conditions

In univariate analysis, all chronic health conditions except hepatitis C were significantly associated with the CIRS score. As intended, when we fitted each of the conditions into the final model, all except strokes reduced the AIC, meaning everyone contributed to the model. Metabolic complications diagnosis contributed the most to the multivariate model Followed by malignancy. The condition with the next largest contribution to the final model was smoking equals with the mental health diagnosis and renal disease.

  Discussion Top

The present study documents the results of the follow-up of a cohort of 269 PLWH, on ART. To the best of our knowledge, this is the first effort to characterize multimorbidity profiles in an HIV-infected population in Morocco. The results are in line with other epidemiological studies showing an increased prevalence of chronic comorbidities in HIV patients.[8],[11],[12],[18]

More than a third of the study population had 2 or more of chronic health conditions in addition to HIV. The same trend was found in a retrospective study conducted in Thailand in 2011 (41%).[24] Other cross-sectional studies of PLWH in North America have shown multimorbidity rates between 34.4% and 69.0%.[7],[10],[18] However, direct comparisons are not possible because several previous studies used a heterogeneous definition of multimorbidity[21],[25] and a much more restrictive list of chronic conditions.[18],[26]

The CIRS was used in our study to quantify the severity of comorbid conditions. The CIRS is a multivalent tool, benefits a validation[20] and a published guide.[19] In this study, a higher CIRS score was associated with increasing age, male gender, duration of receiving ART, indinavir-containing antiretroviral regimen, having ever been stage CDC B or C, and current viral load >50 copies mL–1.

In the present study, older adults had a higher chance of having multimorbidity compared to younger adults. A similar finding has been reported in previous studies conducted in Australia,[22] Thailand,[24] Italy,[8] and the United States.[11],[12],[18] Some noninfectious comorbidities, such as cardiovascular disease, malignancy, and cognitive decline,[27],[28] occur in excess and at chronologically younger ages among PLWH[18] (approximately 10 years before HIV-uninfected persons).[7],[8]

In our study, adult males were associated with a higher CIRS score. Previous studies have shown that the male gender is a risk factor for metabolic complications.[24],[29] In fact, adult males had a higher rate of the behavioral risk factor for many chronic diseases, such as smoking and substance use disorders.[17]

In this study, the duration of receiving ART was associated with a higher CIRS score. Previous research has identified a similar association.[22],[30] This may be explained by the legacy effects from previous exposure to metabolically toxic regimens or more advanced disease at ART initiation. Following initiation of ART in PLWH, reduction in inflammation has been reported in several studies[31],[32],[33],[34],[35] but there is additional evidence that at some point during continuous ART, the level of inflammation stabilizes and no longer continues to decline.[36]

Indinavir-containing regimens were at a higher risk of multimorbidity compared to efavirenz-containing regimens. Protease inhibitor-containing regimens were a risk factor for multimorbidity in previous studies in the United States and the Netherland.[7],[29] First-generation protease inhibitors have been implicated in the development of insulin resistance, cardiovascular disease, and dyslipidemia.[37],[38] For the two contemporary most frequently used protease inhibitors, darunavir, and atazanavir, has been shown to be associated with dyslipidemia and bone loss, compared to nonNRTIs and integrase inhibitors.[39],[40]

This study shows that adults having ever been staged CDC B or C was associated with a higher CIRS score. However, the nadir CD4 count was not retained among the determinants of multimorbidity in our study. A similar result has been previously described.[22],[41] In our center, the delay in diagnosis (stage B or C) was associated with the nonsuppression of the viral load[42] and a higher mortality.[43] Indeed, an AIDS-defining illness may result in direct end-organ injury and the eventual development of a chronic condition. Finally, having an AIDS-defining disease is likely to produce high levels of immune activation, which may be a factor of multimorbidity.[5]

In our study, the nonsuppression of viral load (≥50 copies mL−1) was a factor associated with the risk of multimorbidity. One observational cohort in Maryland found that Higher viral load has been associated with multimorbidity.[12] As all of the adults in our cohort were on ART, the numbers were likely too small to reveal any association between viral load and CIRS score.

The VACS is a risk index for hospitalization and all-cause mortality in uninfected and HIV-1 infected individuals.[44] It was developed in the US and validated in several European and North American cohorts.[45],[46] The VACS offers an alternative approach based on routinely obtained traditional markers of HIV disease and generic biomarkers of end-organ damage. The practitioners' estimate of complexity and the number of chronic health conditions all correlated better with the CIRS score than with VACS.

There are some limitations to our study that need to be considered. First, this work is limited to medical chronic health conditions. Second, the retrospective nature and the small size of the sample did not permit an assessment of causality or the direction (and whether they are bidirectional) of the associations between risk factors and the CIR score. Longitudinal studies would allow to shed light on the direction of the associations. Our results indicate that multimorbidity and individual chronic health conditions are extremely prevalent in PLWH and constitute a significant health problem for this population. The HIV primary care guidelines[47] offer recommendations for routine screening and preventive care in PLWH, much of which applies to older adults with HIV. Thus, it is not surprising that several studies indicate low or only moderate adherence to published recommendations.[48],[49]

Patient complexity is a combination of multimorbidity and socioeconomic determinants that may be bidirectional. Indeed, socioeconomic deprivation and poverty are strongly associated with multimorbidity.[50],[51] Multimorbidity places patients at an increased risk for functional decline and disability.[52],[53] However, comorbidity and its risk factors can be managed effectively at an early stage, thereby reducing the incidence of end-organ dysfunction. It is imperative, therefore, for clinicians to screen for chronic health conditions and intervene to prevent long-term complications, which pose a major threat to the health of the aging PLWH.


There are some limitations to our study that need to be considered. First, this work is limited to medical chronic health conditions. Second, the retrospective nature and the small size of the sample did not permit an assessment of causality or the direction (and whether they are bidirectional) of the associations between risk factors and the CIR score. Longitudinal studies would allow to shed light on the direction of the associations.

  Conclusion Top

The prevalence of multimorbidity in PLWH is high in a middle-income country. Healthcare providers caring for PLWH must be knowledgeable not only about HIV but also about other chronic health conditions in addition to HIV. Our results highlight the necessity to recognize complex patients and provide them with coordinated care. Special attention must be thus paid to the management and prevention of these comorbidities, with the objective of their early detection, adequate ART selection, and consequently a continuous amelioration of the quality of life of PLWH.

Ethical clearance

Ethical clearance was obtained from the Institutional Review Board of the Faculty of Medicine and Pharmacy of Rabat, Mohammed V University. A formal letter of permission was obtained from the Medical Director of Military Hospital Mohammed V. All obtained data were preserved confidentially and this study was conducted in accordance with the Declaration of Helsinki.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Samji H, Cescon A, Hogg RS, Modur SP, Althoff KN, Buchacz K, et al. Closing the gap: Increases in life expectancy among treated HIV-positive individuals in the United States and Canada. PLoS One 2013;8:e81355.  Back to cited text no. 1
May MT, Gompels M, Delpech V, Porter K, Orkin C, Kegg S, et al. Impact on life expectancy of HIV-1 positive individuals of CD4+ cell count and viral load response to antiretroviral therapy. AIDS 2014;28:1193-202.  Back to cited text no. 2
Palella FJ Jr., Delaney KM, Moorman AC, Loveless MO, J Fuhrer, Satten GA, Aschman DJ, et al. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. N Engl J Med 1998;338:853-60.  Back to cited text no. 3
Weber R, Ruppik M, Rickenbach M, Spoerri A, Furrer H, Battegay M, et al. Decreasing mortality and changing patterns of causes of death in the Swiss HIV Cohort Study. HIV Med 2013;14:195-207.  Back to cited text no. 4
Deeks SG, Phillips AN. HIV infection, antiretroviral treatment, ageing, and non-AIDS related morbidity. BMJ 2009;338:a3172.  Back to cited text no. 5
Costagliola D. Demographics of HIV and aging. Curr Opin HIV AIDS 2014;9:294-301.  Back to cited text no. 6
Schouten J, Wit FW, Stolte IG, Kootstra NA, van der Valk M, Geerlings SE, et al. Cross-sectional comparison of the prevalence of age-associated comorbidities and their risk factors between HIV-infected and uninfected individuals: The AGEhIV cohort study. Clin Infect Dis 2014;59:1787-97.  Back to cited text no. 7
Guaraldi G, Orlando G, Zona S, Menozzi M, Carli F, Garlassi E, et al. Premature age-related comorbidities among HIV-infected persons compared with the general population. Clin Infect Dis 2011;53:1120-6.  Back to cited text no. 8
Smit M, Brinkman K, Geerlings S, Smit C, Thyagarajan K, Sighem AV, et al. Future challenges for clinical care of an ageing population infected with HIV: A modelling study. Lancet Infect Dis 2015;15:810-8.  Back to cited text no. 9
Kendall CE, Wong J, Taljaard M, Glazier RH, Hogg W, Younger J, et al. A cross-sectional, population-base study measuring comorbidity among people living with HIV in Ontario. BMC Public Health 2014;14:161.  Back to cited text no. 10
Goulet JL, Fultz SL, Rimland D, Butt A, Gibert C, Rodriguez Barradas MC, et al. Ageing and infectious diseases: Do patterns of comorbidity vary by HIV status, age and HIV severity? Clin Infect Dis 2007;45:1593-601.  Back to cited text no. 11
Salter M, Lau B, Go VF, Mehta S, Kirk GD. HIV infection, immune suppression, and non-controlled viremia are associated with multimorbidity among aging injection drug users. Clin Infect Dis 2011;53:1256-64.  Back to cited text no. 12
Medapalli RK, Parikh CR, Gordon K, Brown ST, Butt AA, Gibert CL, et al. Comorbid diabetes and the risk of progressive chronic kidney disease in HIV-infected adults: Data from the Veterans Aging Cohort Study. J Acquir Immune Defic Syndr 2012;60:393-9.  Back to cited text no. 13
Negin J, Martiniuk A, Cumming RG, Naidoo N, Phaswana-Mafuya N, Madurai L, et al. Prevalence of HIV and chronic comorbidities among older adults. AIDS 2012;26 Suppl 1:S55-63.  Back to cited text no. 14
Rodriguez-Penney AT, Iudicello JE, Riggs PK, Doyle K, Ellis RJ, Letendre SL, et al. Co-morbidities in persons infected with HIV: Increased burden with older age and negative effects on health-related quality of life. AIDS Patient Care STDS 2013;27:5-16.  Back to cited text no. 15
d'Arminio Monforte A, Diaz-Cuervo H, De Luca A, Maggiolo F, Cingolani A, Bonora S, et al. Evolution of major non-HIV- related comorbidities in HIV-infected patients in the Italian Cohort of Individuals, naïve for Antiretrovirals (ICONA) Foundation Study cohort in the period 2004-2014. HIV Med 2019;20:99-109.  Back to cited text no. 16
Simone MJ, Appelbaum J. HIV in older adults. Geriatrics 2008;63:6-12.  Back to cited text no. 17
Kim DJ, Westfall AO, Chamot E, Willig AL, Mugavero MJ, Ritchie C, et al. Multimorbidity patterns in HIV-infected patients: The role of obesity in chronic disease clustering. J Acquir Immune Defic Syndr 2012;61:600-5.  Back to cited text no. 18
Hudon C, Fortin M, Soubhi H. Abbreviated guidelines for scoring the Cumulative Illness Rating Scale (CIRS) in family practice. J Clin Epidemiol 2007;60:212.  Back to cited text no. 19
de Groot V, Beckerman H, Lankhorst GJ, Bouter LM. How to measure comorbidity. A critical review of available methods. J Clin Epidemiol 2003;56:221-9.  Back to cited text no. 20
Fortin M, Hudon C, Dubois MF, Almirall J, Lapointe L, Soubhi H. Comparative assessment of three different indices of multimorbidity for studies on health-related quality of life. Health Qual Life Outcomes 2005;3:74.  Back to cited text no. 21
Edmiston N, Passmore E, Smith DJ, Petoumenos K. Multimorbidity among people with HIV in regional New South Wales, Australia. Sex Health 2015;12:425-32.  Back to cited text no. 22
Tate JP, Justice AC, Hughes MD, Bonnet F, Reiss P, Mocroft A, et al. The VACS index: An internationally generalizable risk index for mortality after one year of antiretroviral therapy. AIDS 2012;26:1-11.  Back to cited text no. 23
Nakaranurack C, Manosuthi W. Prevalence of Non-AIDS comorbidities and factors associated with metabolic complications among HIV-infected patients at a Thai referral hospital. J Int Assoc Provid AIDS Care 2018;17:2325957417752256.  Back to cited text no. 24
Valderas JM, Starfield B, Sibbald B, Salisbury C, Roland M. Defining comorbidity: Implications for understanding health and health services. Ann Fam Med 2009;7:357-63.  Back to cited text no. 25
De Francesco D, Underwood J, Bagkeris E, Anderson J, Williams I, Vera JH, et al. Pharmacokinetic and Clinical Observations in PeoPle Over fiftY (POPPY) study. Risk factors and impact of patterns of co-occurring comorbidities in people living with HIV. AIDS 2019;33:1871-80.  Back to cited text no. 26
Pathai S, Bajillan H, Landay AL, High KP. Is HIV a model of accelerated or accentuated aging? J Gerontol A Biol Sci Med Sci 2014;69:833-42.  Back to cited text no. 27
Erlandson KM, Schrack JA, Jankowski CM, Brown TT, Campbell TB. Functional impairment, disability, and frailty in adults aging with HIV-infection. Curr HIV/AIDS Rep 2014;11:279-90.  Back to cited text no. 28
Chu C, Umanski G, Blank A, Meissner P, Grossberg R, Selwyn PA. Comorbidity-related treatment outcomes among HIV-infected adults in the Bronx, NY. J Urban Health 2011;88:507-16.  Back to cited text no. 29
Guaraldi G, Zona S, Brothers TD, Carli F, Stentarelli C, Dolci G, et al. Aging with HIV vs. HIV seroconversion at older age: A diverse population with distinct comorbidity profiles. PLoS One 2015;10:e0118531.  Back to cited text no. 30
Hamlyn E, Stöhr W, Cooper DA, Fisher M, Tambussi G, Schechter M, et al. The effect of short-course antiretroviral therapy initiated in primary HIV-1 infection on interleukin-6 and D-dimer levels. AIDS 2015;29:1355-61.  Back to cited text no. 31
Baker JV, Sharma S, Grund B, Rupert A, Metcalf JA, Schechter M, et al. Systemic inflammation, coagulation, and clinical risk in the START trial. Open Forum Infect Dis 2017;4:Ofx262.  Back to cited text no. 32
Baker JV, Neuhaus J, Duprez D, Kuller LH, Tracy R, Belloso WH, et al. Changes in inflammatory and coagulation biomarkers: A randomized comparison of immediate versus deferred antiretroviral therapy in patients with HIV infection. J Acquir Immune Defic Syndr 2011;56:36-43.  Back to cited text no. 33
McComsey GA, Kitch D, Daar ES, Tierney C, Jahed NC, Melbourne K, et al. Inflammation markers after randomization to abacavir/lamivudine or tenofovir/emtricitabine with efavirenz or atazanavir/ritonavir: ACTG A5224 s, A5202 sub study. AIDS 2012;26:1371-85.  Back to cited text no. 34
Ledwaba L, Tavel JA, Khabo P, Maja P, Qin J, Sangweni P, et al. PreART levels of inflammation and coagulation markers are strong predictors of death in a South African Cohort with advanced HIV disease. PLoS One 2012;7:E24243.  Back to cited text no. 35
Gandhi RT, McMahon DK, Bosch RJ, Lalama CM, Cyktor JC, Macatangay BJ, et al. Levels of HIV-1 persistence on antiretroviral therapy are not associated with markers of inflammation or activation. PLoS Pathog 2017;13:E1006285.  Back to cited text no. 36
Scherzer R, Heymsfield SB, Lee D, Powderly WG, Tien PC, Bacchetti P, et al. Decreased limb muscle and increased central adiposity are associated with 5-year all-cause mortality in HIV infection. AIDS 2011;25:1405-14.  Back to cited text no. 37
Erlandson KM, Reynolds SM, Cox C, Palella FJ, Witt MD, Kingsley LA, et al. Self-reported body fat change in HIV-infected men is a marker of decline in physical health-related quality of life with aging, independent of co-morbidity. PLoS One 2014;9:e114166.  Back to cited text no. 38
Ofotokun I, Na LH, Landovitz RJ, Ribaudo HJ, McComsey GA, Godfrey C, et al. Comparison of the metabolic effects of ritonavir-boosted darunavir or atazanavir versus raltegravir, and the impact of ritonavir plasma exposure: ACTG 5257. Clin Infect Dis 2015;60:1842-51.  Back to cited text no. 39
Brown TT, Moser C, Currier JS, Ribaudo HJ, Rothenberg J, Kelesidis T, et al. Changes in bone mineral density after initiation of antiretroviral treatment with tenofovir disoproxil fumarate/emtricitabine plus atazanavir/ritonavir, darunavir/ritonavir, or raltegravir. J Infect Dis 2015;212:1241-9.  Back to cited text no. 40
Ryom L, Mocroft A, Kirk O, Worm SW, Kamara DA, Reiss P, et al. Association between antiretroviral exposure and renal impairment among HIVpositive persons with normal baseline renal function: The D: A: D study. J Infect Dis 2013;207:1359-69.  Back to cited text no. 41
Hicham T, Ilyas E, Tarik H, Noureddine B, Omar B, Rachid F, et al. Risk factors associated with unsuppressed viral load in HIV-1 infected patients at the first antiretroviral therapy in Morocco. Int J Mycobacteriol 2019;8:113-7.  Back to cited text no. 42
[PUBMED]  [Full text]  
Titou H, Baba N, Kasouati J, Oumakir S, Frikh R, Boui M, et al. Survival in HIV-1 patients receiving antiretroviral therapy in Morocco. Rev Epidemiol Sante Publique 2018;66:311-16.  Back to cited text no. 43
Akgün KM, Gordon K, Pisani M, Fried T, McGinnis KA, Tate JP, et al. Risk factors for hospitalization and medical intensive care unit (MICU) admission among HIV-infected Veterans. J Acquir Immune Defic Syndr 2013;62:52-9.  Back to cited text no. 44
Brown TT, Guaraldi G. Multimorbidity and burden of disease. Interdiscip Top Gerontol Geriatr 2017;42:59-73.  Back to cited text no. 45
Berry SA, Fleishman JA, Moore RD, Gebo KA. HIV Research Network Trends in reasons for hospitalization in a multisite United States cohort of persons living with HIV, 2001-2008. J Acquir Immune Defic Syndr 2012;59:368-75.  Back to cited text no. 46
Aberg JA, Gallant JE, Ghanem KG, Emmanuel P, Zingman BS, Horberg MA, et al. Primary care guidelines for the management of persons infected with HIV: 2013 update by the HIV Medicine Association of the Infectious Diseases Society of America. Clin Infect Dis 2014;58:1-10.  Back to cited text no. 47
Lichtenstein KA, Armon C, Buchacz K, Chmiel JS, Buckner K, Tedaldi E, et al. Provider compliance with guidelines for management of cardiovascular risk in HIV-infected patients. Prev Chronic Dis 2013;10:E10.  Back to cited text no. 48
Landovitz RJ, Desmond KA, Gildner JL, Leibowitz AA. Quality of care for HIV/AIDS and for primary prevention by HIV specialists and nonspecialists. AIDS Patient Care STDS 2016;30:395-408.  Back to cited text no. 49
Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: A cross-sectional study. Lancet 2012;380:37-43.  Back to cited text no. 50
Agborsangaya CB, Lau D, Lahtinen M, Cooke T, Johnson JA. Multimorbidity prevalence and patterns across socioeconomic determinants: A cross-sectional survey. BMC Public Health 2012;12:201.  Back to cited text no. 51
Guaraldi G, Silva AR, Stentarelli C. Multimorbidity and functional status assessment. Curr Opin HIV AIDS 2014;9:386-97.  Back to cited text no. 52
Althoff KN, Jacobson LP, Cranston RD, Detels R, Phair JP, Li X, et al. Age, comorbidities, and AIDS predict a frailty phenotype in men who have sex with men. J Gerontol A Biol Sci Med Sci 2014;69:189-98.  Back to cited text no. 53


  [Figure 1]

  [Table 1], [Table 2], [Table 3]


Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

  In this article
Article Figures
Article Tables

 Article Access Statistics
    PDF Downloaded60    
    Comments [Add]    

Recommend this journal