Factors associated with the frequency of monitoring of liver enzymes, renal function and lipid laboratory markers among individuals initiating combination antiretroviral therapy: a cohort study

BMC Infectious Diseases

Janet Raboud⁵  Robert S Hogg⁹  Chris Tsoukas⁷  Julio SG Montaner⁶  Nima Machouf¹  Mona Loutfy³  Marina B Klein⁷  Curtis Cooper⁴  Ann N Burchell⁸  Ahmed M Bayoumi²  Jennifer Gillis⁵ 

[1]Clinique Médicale l’Actuel, Montreal, Canada

[2]Centre for Research on Inner City Health, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, Canada

[3]Maple Leaf Medical Clinic, Toronto, Canada

[4]University of Ottawa, The Ottawa Hospital Research Institute, Ottawa, Canada

[5]University of Toronto, Toronto, Canada

[6]British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada

[7]McGill University Health Centre, McGill University, Montreal, Canada

[8]Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, Canada

[9]Simon Fraser University, Burnaby, Canada

关键词: Clinical monitoring;    Lipids;    Renal function;    Liver enzymes;    Laboratory markers;    Antiretroviral therapy;    HIV;   

Others  :  1232846
DOI  :  10.1186/s12879-015-1206-3

 received in 2015-05-19, accepted in 2015-10-12,  发布年份 2015

【 摘 要 】

Background

As the average age of the HIV-positive population increases, there is increasing need to monitor patients for the development of comorbidities as well as for drug toxicities.

Methods

We examined factors associated with the frequency of measurement of liver enzymes, renal function tests, and lipid levels among participants of the Canadian Observational Cohort (CANOC) collaboration which follows people who initiated HIV antiretroviral therapy in 2000 or later. We used zero-inflated negative binomial regression models to examine the associations of demographic and clinical characteristics with the rates of measurement during follow-up. Generalized estimating equations with a logit link were used to examine factors associated with gaps of 12 months or more between measurements.

Results

Electronic laboratory data were available for 3940 of 7718 CANOC participants. The median duration of electronic follow-up was 3.5 years. The median (interquartile) rates of tests per year were 2.76 (1.60, 3.73), 2.55 (1.44, 3.38) and 1.42 (0.50, 2.52) for liver, renal and lipid parameters, respectively. In multivariable zero-inflated negative binomial regression models, individuals infected through injection drug use (IDU) were significantly less likely to have any measurements. Among participants with at least one measurement, rates of measurement of liver, renal and lipid tests were significantly lower for younger individuals and Aboriginal Peoples. Hepatitis C co-infected individuals with a history of IDU had lower rates of measurement and were at greater risk of having 12 month gaps between measurements.

Conclusions

Hepatitis C co-infected participants infected through IDU were at increased risk of gaps in testing, despite publicly funded health care and increased risk of comorbid conditions. This should be taken into consideration in analyses examining factors associated with outcomes based on laboratory parameters.

【 授权许可】

   
2015 Gillis et al.

【 参考文献 】

• [1]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; 53:1120-1126.
• [2]Antoniou T, Zagorski B, Bayoumi A, Loutfy MR, Strike C, Raboud JM et al.. Trends in HIV prevalence, new diagnoses and mortality in Ontario, Canada, 1996 to 2009: a population-based study. Open Med. 2013; 7:e98-e106.
• [3]Tseng A, Szadkowski L, Walmsley S, Salit I, Raboud J. Association of age with polypharmacy and risk of drug interactions with antiretroviral medications in HIV-positive patients. Ann Pharmacother. 2013; 47:1429-1439.
• [4]Panel on Antiretroviral Guidelines for Adults and Adolescents. Guidelines for the use of antiretroviral agents in HIV-1-infected adults and adolescents. Department of Health and Human Services. Available at: http://aidsinfo.nih.gov/contentfiles/lvguidelines/AdultAndAdolescentGL.pdf AdolescentGL.pdf. Accessed 1 July 2013.
• [5]The European AIDS Clinical Society (EACS) Guidelines Version 6.1–November 2012. The European AIDS Clinical Society. Available at: http://www.eacsociety.org/. Accessed 1 July 2013.
• [6]Asboe D, Aitken C, Boffito M, Booth C, Cane P, Fakoya A et al.. British HIV Association guidelines for the routine investigation and monitoring of adult HIV-1 infected individuals 2011. HIV Med. 2012; 13:1-44.
• [7]Montaner J, Guillemi S, Harris M for the Therapeutic Guidelines Committee, British Columbia Centre for Excellence (BC CfE). Antiretroviral (ARV) treatment of adult HIV infection, February 2013. Available at: http://www.cfenet.ubc.ca/therapeutic-guidelines/adult. Accessed 10 January 2015.
• [8]Peters B, Post F, Wierzbicki AS, Phillips A, Power L, Das S et al.. Screening for chronic comorbid diseases in people with HIV: the need for a strategic approach. HIV Med. 2013; 14 Suppl1:1-11.
• [9]Primary Care Guidelines Panel British Columbia Centre for Excellence (BC CfE). Primary care guidelines for the management of HIV/AIDS in British Columbia-March 2011. Available at: http://www.cfenet.ubc.ca/therapeutic-guidelines/primary-care. Accessed 10 January 2015
• [10]Palmer A, Klein M, Raboud J, Cooper C, Loutfy M, Machouf N et al.. Cohort Profile: The Canadian Observational Cohort Collaboration. Int J Epidemiol. 2011; 40:25-32.
• [11]Yanik E, Napravnik S, Ryscavage P, Eron JJ, Koletar S, Moore RD et al.. Hematologic, Hepatic, Renal and Lipid Monitoring Following Initiation of Combination Antiretroviral Therapy in the United States, 2000-2010. JAIDS. 2013; 63:216-220.
• [12]Raboud JM, Loutfy M, Su D, Bayoumi A, Klein M, Cooper C et al.. Regional differences in rates of HIV-1 viral load monitoring in Canada. BMC Infect Dis. 2010; 10:40. BioMed Central Full Text
• [13]Raboud JM, Abdurrahman ZB, Major C, Millson P, Robinson G, Rachlis A et al.. Non-financial factors associated with decreased plasma viral load testing in Ontario, Canada. JAIDS. 2005; 39:327-332.
• [14]Gillis J, Loutfy M, Bayoumi A, Cooper C, Klein M, Antoniou T et al.. Factors associated with recommended and low engagement in HIV care after initiating combination antiretroviral therapy. Can J Infect Dis Med Microbiol. 2014; 25(S4):041.
• [15]Wood E, Kerr T, Tyndall MW, Montaner JSG. A review of barriers and facilitators of HIV treatment among injection drug uses. AIDS. 2008; 22:1247-1256.
• [16]Wandeler G, Gsponer T, Bregenzer A, Gunthard HF, Clerc O, Calmy A et al.. Hepatitis C Virus Infections in the Swiss HIV Cohort Study: A Rapidly Evolving Epidemic. Clin Infect Dis. 2012; 55:1408-1416.
• [17]Burchell AN, Gardner S, Mazzulli T, Manno M, Raboud J, Allen VG et al.. Hepatitis C virus seroconversion among HIV-positive men who have sex with men with no history of injection drug use: Results from a clinical HIV cohort. Can J Infect Dis Med Microbiol. 2015; 26:17-22.
• [18]Griffin JT, Fraser C, Gras L, De Wolf F, Ghani A. The effect of treatment comparisons of different measurement frequencies in human immunodeficiency virus observational databases. Am J Epidemiol. 2006; 163:676-683.
• [19]Hernan MA, McAdams M, McGrath N, Lanoy E, Costagliola D. Observations plans in longitudinal studies with time-varying treatments. Stat Methods Med Res. 2009; 18:27-52.
• [20]Singer JD, Willett JB. It’s about time: using discrete-time survival analysis to study duration and time of events. J Educ Behav Stat. 1993; 18:155-195.
• [21]Shah BR, Gunraj N, Hux JE. Markers of access to and quality of primary care for aboriginal people in Ontario, Canada. Am J Public Health. 2003; 93:798-802.
• [22]Gao S, Manns BJ, Culleton BF, Tonelli M, Quan H, Crowshoe L et al.. Access to health care among status Aboriginal people with chronic kidney disease. Can Med Assoc J. 2008; 179:1007-1012.
• [23]Fairbalm N, Milloy MJ, Zhang R, Lai C, Grafstein E, Kerr T et al.. Emergency department utilization among a cohort of HIV-positive injecting drug users in a Canadian setting. J Emerg Med. 2011; 43:236-243.