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The exact incidence of chronic kidney disease (CKD) in HIV-positive patients is still up for debate, and a large spectrum of risk factors have been described in field literature. CKD also associates metabolic and hormonal abnormalities that may lead to an impairment of bone turnover, mineralization and volume, the so called chronic kidney disease-mineral and bone disorder (CKD-MBD). In addition, HIV-positive patients are considered to have a higher risk of bone demineralization and osteopenia. Methods Two categories of HIV-positive patients, with different epidemiological features, were screened for renal impairment and for osteopenia/osteoporosis. Multivariate regression models were used to investigate traditional risk factors for bone demineralization and kidney impairment. Differences between the two groups were also evaluated. Results The clinical team screened a cohort of 125 patients who were divided into two groups: group A included 64 patients in whom HIV infection had occurred in early childhood and who had received long-term treatment, group B included 61 patients in whom HIV infection had occurred during teenage years or in adulthood. Interestingly, no significant differences were identified in albuminuria, renal function, and the presence of osteopenia or osteoporosis. In patients from the Romanian HIV cohort we identified higher current or nadir CD4 cell counts (p=0.031 and p=0.041, respectively), a more frequent medical history of over three antiretroviral regimens (p=0.000), a higher rate of HBV coinfection (p=0.0002), and a lower proportion of hyperparathyroidism (p=0.011). Conclusion Traditional risk factors such as BMI, presence of comorbidities such as diabetes mellitus or hypertension, smoking status and vitamin D deficiency or insufficiency, were similar in the studied groups. Overall, the rate of renal and bone impairment was low in the studied groups.
The exact incidence of chronic kidney disease (CKD) in HIV-positive patients is still up for debate, and a large spectrum of risk factors have been described in field literature, including but not limited to: patient age, smoker status, duration of HIV infection, history of antiretroviral therapy, or associated conditions such as hypertension, diabetes. In this context, the periodic assessment of kidney function is of outmost importance,1,2 with urine albumin and estimated glomerular filtration rate (eGFR) being two key markers for chronic kidney disease (CKD). Renal biopsy can provide histological evidence of HIV-associated nephropathy (HIVAN), but being an invasive procedure, its use may be limited to a small subset of patients.
Different mathematical models to ascertain the incidence of CKD in HIV-positive patients have been used, considering various associated risk factors. One study proposes the measurement of serum creatinine levels every 3 months, up to 18 months and includes as associated risk factors the so-called classic comorbidities associated to CKD: chronic hypertension and diabetes mellitus (DM).3 Quantitation of albuminuria could be useful as marker for the progression of HIVAN, even when serum creatinine remains within normal ranges. A study performed by Estrella et al. presented a set of recommendations for the early detection of renal dysfunction and mentioned certain additional risk factors for CKD, besides HIV infection: intravenous drug use (IVDU), nephrotoxic therapy for chronic diseases or coinfection with hepatitis C virus.4
CKD can also associate metabolic and hormonal abnormalities that lead to an impairment of bone turnover, mineralization and volume, the so-called chronic kidney disease-mineral and bone disorder (CKD-MBD).5 In addition, HIV-positive patients are considered to have a higher risk of bone demineralization and osteopenia, and this may in part be due to cumulating risk factors such as poor nutrition (particularly during childhood), low body mass index (BMI), low vitamin D levels6 (although not consistently confirmed in all studies),7 high consumption of nicotine and alcohol,6 Caucasian race, chronic inflammation due to progression of HIV infection,7 as well as antiretroviral therapy (ART – either through the associated immune reconstitution,8 or through consequences such as metabolic syndrome, direct bone demineralization or osteonecrosis).9,10
Certain studies mention high rates of fractures and an increased severity of fractures occurring in HIV-positive patients.11,12 Multiple technologies are available for the screening of bone density and quality, and for a subsequent calculation of the fracture risk. Among these, dual-energy X-ray absorptiometry (DXA) determination of bone mineral density (BMD), has been reported to be a robust and consistent indicator for the risk of fractures, either alone or in combination with other variables computed into the FRAX WHO fracture risk assessment tool.13 However, this instrument has been designed mainly for patients in the age range of 40 to 90 years, and since other scores are also highly age-dependent14 no particular tool can be used for estimating the probability of fractures specifically in young adults such as those in the Romanian HIV cohort.
In 2014 the National Institute for Infectious Diseases "Prof. Dr. Matei Balș” initiated a national survey for osteo-renal impairment in the Romanian HIV cohort, designed to screen and monitor a total of 1000 patients from all over the country. The statistical reports for Romania from 2013 showed that 11,960 patients were living with HIV and 7,934 of them were on ART.15 Therefore, a nationwide screening could comprise 1,000 patients, with a predictive error of 2.95%, as statistically evaluated by the Taro-Jamane equation.
The main goal of the current research was to develop a predictive model for osteopenia and chronic kidney dysfunction in this cohort, based on a proper analysis of specific risk factors. We present the interim results of this survey, by analyzing the data from patients on antiretroviral treatment and in active medical care at the National Institute for Infectious Diseases "Prof. Dr. Matei Balș” from Bucharest, Romania, consenting to participate in this screening study.
For the purposes of this study, moderately increased albuminuria was defined as 30-300 mg/dL, according to Kidney Disease Improving Global Outcomes (KDIGO), and the estimated glomerular filtration rate (eGFR) was computed based on the 2009 CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) equation,16 as it has been shown to be a more accurate formula for eGFR higher that 60 mL/min per 1.73 sqm, although it does not have the same relevance for the elderly and the obese.17
The risk factors reviewed in literature were stratified in the current study. The proposed predictive model comprised several clusters of risk factors, as follows: individual-related factors (quantitative independent variables: age, BMI; qualitative independent variable: gender), HIV-related factors (quantitative variable: CD4 cell count), HAART-related (exposure to protease inhibitors – PIs – and tenofovir), chronic diseases (DM, hypertension, HBV or HCV co-infection), or behavioral factors (qualitative – smoking). Risk factors associated to lifestyle were evaluated with a self-administered questionnaire.
For statistical analysis we evaluated the distribution of data and, for continuous variables with normal distribution we applied the two-tailed independent groups T-tests and calculated Hedges' g to measure the effect size weighted according to the relative sample size.
The clinical team screened a cohort of 125 patients. In order to monitor the effect of long-term antiretroviral therapy and the effect of living with HIV since childhood, subject were divided into two groups, based on patient age at HIV diagnosis: group A included 64 patients (51.2%) in whom HIV infection had occurred in early childhood and who had received long-term treatment (the "pediatric cohort”); group B included 61 patients in whom HIV infection had occurred during teenage years or in adulthood.
Groups A and B included 43.8% and 42.6% females, respectively. In the proposed predictive model, patient's gender was considered an independent variable. Patient characteristics are presented in Table.
Group A included younger patients, with a mean age of 25.8 years at screening, significantly lower compared to 39.5 years in group B (p<0.00001), but with an almost double duration since HIV diagnosis, 16.2 years compared with 8.8 years. In patients from Group A we identified a more frequent medical history of over three ART regimens (p=0.000), a significantly higher rate of coinfection with HBV (p=0.0002), and a significantly lower proportion of hyperparathyroidism (p=0.011). Current and nadir CD4 cell counts were comparable in the two groups (611 vs. 528, p=0.031 and 391 vs. 387 cells/cmm, p=0.041), the slightly higher trend seen in Group A potentially being due to a closer long-term monitoring of patients from this cohort. The body mass index was similar between the two groups, slightly higher in the older group (B), but without statistical significance. The rate of smoking appeared to be higher in group B compared to group A, but the difference was not statistically significant. We identified a higher rate of hypertension in the younger group (A), 7.8% compared with 1.6% in group B, but the difference was not statistically significant (p=0.107). The use of PIs and of tenofovir (TDF) was similar in the two groups (p=0.928 and p=0.529, respectively). Interestingly, we did not identify statistically significant differences regarding eGFR in the two groups. We found no significant difference in the rate of osteoporosis and osteopenia among the studied groups (p=0.180 and p=0.689, respectively), nor in the rate of vitamin D deficiency or insufficiency (p=0.114 and p=0.569, respectively).
We identified no significant correlation between age and CD4 count (r2=0.0029). Using multivariate analysis, in Group A we found an asymmetric distribution of the BMI and PTH levels based on vitamin D levels, both presenting a small positive correlation (r2=0.3123 on a 6-rank polynomial function for BMI depending on vitamin D; r2=0.32362 on a 6-rank polynomial function for PTH depending on vitamin D). Both BMI and PTH share a similar slope, which could be explained by the increasing BMI when patients develop secondary hyperparathyroidism due to lack of vitamin D. We have also noticed that moderate overweight status (25 <bmi<30) (r<sup="" correlation="" positive="" high="" a="" had="">2=0.6923) with vitamin D insufficiency and deficiency, but associated a minor impact on the PTH level. Furthermore, vitamin D deficiency appeared to be linked with global or femoral osteopenia and osteoporosis for the patients in Group A, although there was a very low negative correlation between BMD and vitamin D levels (R=0.1292). Although only 35 patients have been screened with DXA so far, 3 had osteoporosis and 16 had osteopenia, of which 9 had global osteopenia. The DXA screening will be continued in order to be able to accurately determine the rate and the impact of the evaluated risk factors.</bmi<30)>
In group B there was no significant correlation between serum vitamin D levels and BMI or PTH levels, as the values for PTH were too scattered, with several peaks. Nevertheless, in this group we identified lower levels of eGFR, with 11 patients in the stage G2 (eGFR of 60-89.9 mL/min/1.73 sqm and albuminuria of 3-30 mg/mmol). Interestingly, all of them had received PIs and 4 of them had received more than 3 previous antiretroviral regimens.
In Romania approximately 45% of HIV-positive patients are young adults born during 1987-1990.15 They have a long history of ART and a high rate of related adverse events, particularly linked with the administration of first generation drugs. In our study we have compared a group of patients from the Romanian HIV cohort to a group of older patients, relatively recently diagnosed with HIV infection. We focused on renal and bone mineralization disorders and we assessed the role of different risk factors.
The distribution of the following risk factors was similar in the two studied groups: BMI, HAART at screening and rate of PI and TDF use, presence of comorbidities such as diabetes mellitus or hypertension, smoking status and vitamin D deficiency or insufficiency. Interestingly, no significant differences were identified in albuminuria (p=0.976), renal function as measured by eGFR (p=0.180), and the presence of osteopenia (p=0.180) or osteoporosis (p=0.689).
In our study we observed significant differences between the two groups in terms of current (p=0.031) and nadir (p=0.041) CD4 cell count, HBV coinfection (p=0.0002), history of multiple ART regimens (p=0.000) and prevalence of hyper-parathyroidism (p=0.001). The higher percentage of HIV-HBV coinfection in Group A (29.7% compared with 4.9%) is suggestive for the epidemiologic history of co-transmission of HBV and HIV in the pediatric cohort in the late 1980s, before the implementation of active screening measures. The overall rate of 17.6% HBV coinfection appears to be higher than that reported in other countries, for example 8.5% in Saudi Arabia,18 10.4% in Zambia,198.8% in Senegal,20 7% in pregnant women in South Africa and Botswana,21 4.1% and 4.26% in newly diagnosed cases in Italy22and Kenya,23 respectively. The overall rate of 2.4% HCV coinfection is lower than that reported in field literature, for example 2.8% in Saudi Arabia,18 12.9% in Brazil,24 7.3% in China,25 7.8% and 0.46% in newly diagnosed cases in Italy22 and Kenya,23respectively.
The age distribution, the duration since HIV diagnosis and the number of ART regimens used are characteristics of the HIV epidemiology in Romania.15 We experienced two main waves of the HIV epidemic: an initial pediatric infection in children born in the late 1980s, and a new wave, noticed during the past 10 years, with infection occurring in adults and being transmitted mainly through unprotected heterosexual intercourse or intravenous drug use.
A limitation of the current study resides in the low yield of patients with bone and renal disorders, which limited the power to identify significant associations with traditional and non-traditional risk factors. However, the results are encouraging from a medical point of view, as the prevalence of bone and renal diseases in this particular population appears to be lower than expected.
When managing HIV-positive patients who are adherent to ART and have undetectable viral loads, the main objective has become improving their quality of life. Therefore, the ultimate goal of this study is to develop a clinical application of evaluating risk factors for bone and renal disorders. Therefore, a risk profile has been designed and will be improved by continuing the screening program until the target number of patients are included. Ultimately, we aim to use this patient risk profile as an "alarm system” that triggers early diagnostic and therapeutic interventions in particular subsets of patients at risk for progression of osteo-renal impairment. The first half of the study consisted in the assessment of potential risk factors and the evaluation of their impact in the two categories of Romanian patients. The second half of the study aims to develop a predictive model along with dynamic programming tools useful in computing and simulating the impact of changing therapies, of providing additional treatment (mineral or vitamin supplements) or of behavioral factors (following a specific diet or quitting smoking).
In conducting a cross sectional study with the two groups of patients specific for the dual epidemiology of HIV infection in Romania, we found that patients from the pediatric cohort, diagnosed in early childhood and having received long-term ART share a similar profile of risk factors for osteo-renal impairment as the patients more recently diagnosed with HIV infection, such as vitamin D deficiency of insufficiency, smoking, exposure to PIs and TDF, and prevalence of comorbidities such as diabetes mellitus or hypertension. Moreover, the two groups share a relatively similar rate of renal and bone disease (1.6% albuminuria in both groups and 4.7% vs. 3.3% osteoporosis).
1. Streinu-Cercel A. Osteo-renal impairment in HIV infection. GERMS 2014;4:29. [CrossRef]
2. Streinu-Cercel A. HIV and bone mineral density. GERMS 2015;5:7. [CrossRef]
3. Ganesan A, Krantz EM, Huppler Hullsiek K, et al. Determinants of incident chronic kidney disease and progression in a cohort of HIV-infected persons with unrestricted access to health care. HIV Med 2013;14:65-76. [CrossRef]
4. Estrella MM, Fine DM. Screening for chronic kidney disease in HIV-infected patients. Adv Chronic Kidney Dis 2010;17:26-35. [CrossRef]
5. Goldenstein PT, Jamal SA, Moyses RM. Fractures in chronic kidney disease: pursuing the best screening and management. Curr Opin Nephrol Hypertens 2015;24:317-23. [CrossRef]
6. McComsey GA, Tebas P, Shane E, et al. Bone disease in HIV infection: a practical review and recommendations for HIV care providers. Clin Infect Dis 2010;51:937-46. [CrossRef]
7. Hileman CO, Labbato DE, Storer NJ, Tangpricha V, McComsey GA. Is bone loss linked to chronic inflammation in antiretroviral-naive HIV-infected adults? A 48-week matched cohort study. AIDS 2014;28:1759-67. [CrossRef]
8. Ofotokun I, Titanji K, Vunnava A, et al. Antiretroviral therapy induces a rapid increase in bone resorption that is positively associated with the magnitude of immune reconstitution in HIV infection. AIDS 2016;30:405-14. [CrossRef]
9. Meyer D, Behrens G, Schmidt RE, Stoll M. Osteonecrosis of the femoral head in patients receiving HIV protease inhibitors. AIDS 1999;13:1147-8. [CrossRef]
10. Miller KD, Masur H, Jones EC, et al. High prevalence of osteonecrosis of the femoral head in HIV-infected adults. Ann Intern Med 2002;137:17-25. [CrossRef]
11. Grund B, Peng G, Gibert CL, et al. Continuous antiretroviral therapy decreases bone mineral density. AIDS 2009;23:1519-29. [CrossRef]
12. Negredo E, Domingo P, Ferrer E, et al. Peak bone mass in young HIV-infected patients compared with healthy controls. J Acquir Immune Defic Syndr 2014;65:207-12. [CrossRef]
13. Yin MT, Falutz J. How to predict the risk of fracture in HIV? Curr Opin HIV AIDS 2016. [CrossRef]
14. Rubin KH, Abrahamsen B, Friis-Holmberg T, et al. Comparison of different screening tools (FRAX(R), OST, ORAI, OSIRIS, SCORE and age alone) to identify women with increased risk of fracture. A population-based prospective study. Bone 2013;56:16-22. [CrossRef]
15. Romanian National Committee for Fighting Against AIDS, Romania HIV/AIDS statistical data - 30 June 2013. 2013. Accessed on: 10 January 2016. Available at: http://www.cnlas.ro/images/doc/rom_30_iunie2013eng.pdf
16. Levey AS, Stevens LA. Estimating GFR using the CKD Epidemiology Collaboration (CKD-EPI) creatinine equation: more accurate GFR estimates, lower CKD prevalence estimates, and better risk predictions. Am J Kidney Dis 2010;55:622-7. [CrossRef]
17. Hougardy JM, Delanaye P, Le Moine A, Nortier J. [Estimation of the glomerular filtration rate in 2014 by tests and equations: strengths and weaknesses]. Rev Med Brux 2014;35:250-7.
18. Al-Mughales JA. Co-infection assessment in HBV, HCV and HIV patients in western Saudi Arabia. J Med Virol 2016. [CrossRef]
19. Peebles K, Nchimba L, Chilengi R, Bolton Moore C, Mubiana-Mbewe M, Vinikoor MJ. Pediatric HIV-HBV Coinfection in Lusaka, Zambia: Prevalence and Short-Term Treatment Outcomes. J Trop Pediatr 2015;61:464-7. [CrossRef]
20. Lo G, Sow-Sall A, Diop-Ndiaye H, et al. Prevalence of hepatitis B markers in Senegalese HIV-1-infected patients. J Med Virol 2016;88:461-5. [CrossRef]
21. Matthews PC, Beloukas A, Malik A, et al. Prevalence and Characteristics of Hepatitis B Virus (HBV) Coinfection among HIV-Positive Women in South Africa and Botswana. PLoS One 2015;10:e0134037. [CrossRef]
22. Puglia M, Stasi C, Da Fre M, Voller F. Prevalence and characteristics of HIV/HBV and HIV/HCV coinfections in Tuscany. Braz J Infect Dis 2015. [CrossRef]
23. Kerubo G, Khamadi S, Okoth V, et al. Hepatitis B, Hepatitis C and HIV-1 Coinfection in Two Informal Urban Settlements in Nairobi, Kenya. PLoS One 2015;10:e0129247. [CrossRef]
24. Tizzot MR, Grisbach C, Beltrame MH, Messias-Reason IJ. Seroprevalence of HCV markers among HIV infected patients from Curitiba and metropolitan region. Rev Assoc Med Bras 2016;62:65-71. [CrossRef]
25. Zhou L, Wu Q, Shen W, et al. [Co-infection of hepatitis C virus among newly diagnosed HIV-infected adults in Taizhou prefecture of Zhejiang province, China]. Zhonghua Liu Xing Bing Xue Za Zhi 2015;36:862-6.
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