Owiti, Patrick O. MD; Penner, Jeremy MD, MHSc, DTM&H; Oyanga, Arbogast BScIT; Huchko, Megan MD, MPH; Onchiri, Frankline M. MS, PhD; Cohen, Craig MD, MPH; Bukusi, Elizabeth A. MD, MMed, MPH, PhD
To the Editors:
Opportunistic infections (OIs) are the main cause of morbidity and mortality in patients with HIV-1 infection throughout the world, particularly among patients who have not had access to anti-retroviral therapy (ART) and other HIV care services.1–3 Among patients taking ART, OIs can present when the immune system starts to recover, also known as immune reconstitution inflammatory syndrome.4,5 Also, some patients do not have a sustained response to ART due to the lack of adherence to medications, development of drug resistance, or suboptimal therapeutic regimens.1 Therefore, OIs continue to cause substantial morbidity and mortality even after the initiation of ART.
The World Health Organization (WHO) developed HIV clinical staging criteria based on OIs to standardize disease severity classification in the absence of virologic or immunologic measurements.6,7 Diagnosis of WHO stage 4 conditions remains important in the ART era to (1) help determine timing of ART initiation and (2) treat OIs to reduce morbidity and mortality. There are no published data from Kenya that quantify the burden of WHO stage 4 conditions that persist in the ART era and continue to negatively impact patient survival. Therefore, we set out to determine the prevalence and gender distribution of WHO stage 4 conditions among patients enrolled in a large periurban HIV clinic in western Kenya.
We performed a retrospective review of adult patients who enrolled into care in a comprehensive outpatient HIV clinic between March 2005 and July 2008 and analyzed the frequency of WHO stage 4 conditions.
The Family AIDS Care and Education Services (FACES) program, a collaboration between the Kenya Medical Research Institute and University of California, San Francisco, pioneered a family model of HIV prevention, care, and treatment in Nyanza Province and Nairobi, Kenya.8 This study was conducted at Lumumba Health Centre (LHC), which is one of FACES' largest outpatient HIV clinics in Kisumu, Nyanza Province. Nyanza Province has an HIV prevalence of 15.3%, which is more than twice the national prevalence of 6.3%.9 LHC has the capacity for on-site laboratory tests, including complete blood count, serum chemistries, CD4+ cell count assays, rapid plasma reagin, and serum cryptococcal antigen testing. Tissue biopsies for cytology and chest radiographs are available within Kisumu and are routinely paid for with program funds. Additional tests such as ultrasound, computed tomography scans, and endoscopy are available, but coverage depends on the availability of extra program funds or the patients' ability to pay. ART is available at no cost to patients who qualify based on WHO stage and/or CD4 count, following the Kenya national guidelines.10 Patients attending LHC for HIV care are staged according to WHO criteria as part of their enrollment assessment and reassessed at every follow-up visit.
The HIV clinic at LHC has an electronic medical record system (EMRS) that captures important patient-level demographic and clinical variables at each clinic visit. At every visit, patient encounters are documented using standardized clinical forms, after which the information is entered into the EMRS. Information collected using patient encounter forms includes demographic characteristics, such as age and gender, ART status, and clinical variables, such as WHO stage and staging criteria, and laboratory test results. In September 2009, we used the EMRS database to identify all adult patients (age, >15 years old) who were enrolled into care between March 2005 and July 2008. Out of these newly enrolled patients, we identified those with WHO stage 4 conditions at enrollment or subsequent visits. We obtained data on CD4+ cell count at enrollment, gender, age, and status in care [dead, alive in care, transferred out, or lost to follow-up (LFU)] at the time of data abstraction. The patient files were reviewed to confirm diagnosis and abstract missing variables. For patients who had not attended the clinic for 3 or more months, a community health worker called or attempted a home visit to determine their current status. If the community health worker was not able to locate them or receive a reliable report of their status, then they were classified as LFU.
Data from the EMRS were exported into an Excel (Microsoft, Inc, Redmond, WA) spreadsheet. Data abstracted from manual chart reviews were entered into a standardized data abstraction tool, then transferred to the spreadsheet. Bivariate analysis was performed to examine the association between various WHO stage 4 conditions and age, gender, and CD4+ cell count. The χ2 or Fisher exact tests were used for categorical variables, and the Student t test was used to compare continuous variables. Data were analyzed using STATA version 11.0 (StataCorp, College Station, TX). A value of P < 0.05 was considered significant.
The FACES program obtained ethical approval from the Kenya Medical Research Institute Ethical Review Committee and the University of California, San Francisco Committee on Human Research to utilize routinely gathered retrospective medical information for the evaluation and dissemination purposes, including the data abstracted for this study. To protect patient privacy, all data were deidentified and delinked with patient identifiers.
Of the 5784 adult patients enrolled during the study period, 437 (7.6%) had a WHO stage 4 diagnosis during the study period at enrollment and follow-up, of which 260 (59.5%) were women. Among all women enrolled into care, 6.7% had a WHO stage 4 diagnosis compared with 9.3% among all enrolled men (P < 0.001). The mean age of women was 34.7 years (SD, 9.0) compared with 37.2 years (SD: 8.4) for men. The median CD4+ cell count at enrollment was 84 cells per microliter (interquartile range: 31–191), and 325/423 (76.8%) patients had a baseline CD4+ cell count below 200 cells per microliter. Of the 437 patients with WHO stage 4 diagnosis, 427 (97.7%) patient files were found and reviewed. These 427 patients contributed 483 WHO stage 4 conditions to the analysis as 56 patients had 2 conditions.
Of the 427 patients, 367 (85.9%) were initiated on ART during the study period; 346 of the 367 who had been initiated on ART had dates recorded for ART initiation and the WHO stage 4 diagnosis. Of the 346 patients, 127 (36.7%) had started on ART before the WHO stage 4 diagnosis, 34 (9.8%) started ART on the day of their WHO stage 4 diagnosis, and 185 (53.5%) started ART after the WHO stage 4 diagnosis. Of the 127 patients diagnosed with a WHO stage 4 diagnosis after ART initiation, 78 (61.4%) had the diagnosis within 6 months of ART initiation.
At the end of the study period, 253 (59.2%) were active in care, 60 (14.0%) were confirmed dead, 28 (6.6%) had transferred out to other HIV clinics, and 86 (20.1%) were LFU.
The most common conditions in order of frequency were esophageal candidiasis, extra pulmonary tuberculosis, HIV wasting syndrome, Kaposi's sarcoma (KS), and cryptococcal meningitis (Table 1). Esophageal candidiasis was significantly more frequent among women with WHO stage 4 conditions than among men (P = 0.029), and KS was more frequent among men (P < 0.001). When analyzing frequency of WHO stage 4 conditions based on a CD4+ cutoff of 100 cells per microliter, only esophageal candidiasis was significantly associated with CD4+ count ≤100 cells per microliter (P = 0.003) (data not shown).
Among the 56 patients with more than 1 WHO stage 4 condition, the most frequent combination was esophageal candidiasis and HIV wasting syndrome [15 (26.8%)]. Pleural effusion was the most frequent type of extra pulmonary tuberculosis (58.8%), whereas cutaneous KS involving the lower limbs was the most frequent presentation of KS (64.4%) (data not shown).
Those initially diagnosed with esophageal candidiasis, HIV wasting syndrome, KS, and extra pulmonary tuberculosis contributed most to the number of deaths (data not shown).
Our study found that 7.6% of our patients had a WHO stage 4 diagnosis. We also found a higher proportion of WHO stage 4 conditions among men compared with women enrolled in care, a finding consistent with 2 other studies in east Africa which found that at enrollment, men were more immunocompromised compared with women.11,12 This could be attributed to the poor health seeking behavior of men delaying or avoiding enrollment in care even after they know their HIV status.13–15
We found that esophageal candidiasis was more common among women. This gender distribution is consistent with other HIV-positive cohorts.16,17 KS was more common among men, which is consistent with studies among non–HIV-positive cohorts,18,19 and among HIV-positive patients.16
The major limitation of our study was reliance on clinical diagnosis for many of the WHO stage 4 conditions of interest. Although this may contribute to an underestimation or overestimation of the disease prevalence for certain conditions, it is representative of how patients are diagnosed and treated in similar resource-limited settings.
This study identified the most common WHO stage 4 conditions in a periurban HIV clinic in western Kenya. These findings can provide guidance to HIV programs for prioritizing resources to ensure adequate diagnosis and management of these conditions.
The authors acknowledge the leadership of the Director of KEMRI, Prof Solomon Mpoke and the technical support provided by the CDC Kenya Branch Chief, Dr Lucy Ngang'a and our CDC Technical Manager, Dr Evelyn Ngugi, and the staff of FACES Lumumba HIV Clinic for their dedicated service to patients.
1. Benson CA, Kaplan JE, Masur H, et al.. Treating opportunistic infections among HIV infected adults and adolescents; recommendations from CDC, the National Institutes of Health and the HIV Medicine Association/Infectious Disease Society of America. Clin Infect Dis. 2005;40(suppl 3):s131–s235.
2. Lawn SD, Harries AD, Anglaret X, et al.. Early mortality among adults accessing antiretroviral treatment programs in sub Saharan Africa. AIDS. 2008;22:1897–1908.
3. Badri M, Lawn SD, Wood R, et al.. Short term risk of AIDS or death in people infected with HIV-1 before antiretroviral therapy in South Africa—a longitudinal study. Lancet. 2006;368:1254–1259.
4. Robertson J, Meier M, Wall T, et al.. Immune reconstitution syndrome in HIV: validating a case definition and identifying clinical predictors in persons initiating antiretroviral therapy. Clin Infect Dis. 2006;42:1639–1646.
5. Stoll M, Heiken H, Behrens GM, et al.. Immune reconstitution syndromes [in German]. Internist (Berl). 2004;45:893–903.
6. Mahe C, Mayanja B, Whitworth JA; WHO. Interim proposal for a WHO staging system for HIV infection and disease. Wkly Epidemiol Rec. 1990;65:221–224.
7. World Health Organization. Interim WHO clinical staging of HIV/AIDS and HIV/AIDS case definitions for surveillance: African region. Geneva, Switzerland: World Health Organization; 2005. Available at: www.who.int/hiv/pub/guidelines/clinicalstaging.pdf
. Accessed November 18, 2013.
8. Lewis Kulzer J, Penner JA, Marima R, et al.. Family model of HIV care and treatment: a retrospective study in Kenya. J Int AIDS Soc. 2012;15:8.
9. Kenya National Bureau of Statistics (KNBS) and ICF Macro. Kenya Demographic and Health Survey 2008–09. Calverton, MD: KNBS and ICF Macro; 2010.
10. National Manual for the Management of HIV-related Opportunistic Infections and Conditions, 2nd edition. Nairobi, Kenya: Kenya Ministry of Health; 2007.
11. Mugusi SF, Mwita JC, Francis JM, et al.. Effect of improved access to antiretroviral therapy on clinical characteristics of patients enrolled in the HIV care and treatment clinic at Muhimbili National Hospital (MNH), Dar es salaam, Tanzania. BMC Public Health. 2010;10:291.
12. Diero L, Shaffer D, Kimaiyo S, et al.. Characteristics of HIV infected patients cared for at “academic model for the prevention and treatment of HIV/AIDS” clinics in western Kenya. East Afr Med J. 2006;83:428–433.
13. Hatcher AM, Turan JM, Leslie HH, et al.. Predictors of linkage to HIV care and treatment: findings following a community-based HIV counseling and testing campaign in Kenya. AIDS Behav. 2011;16:1295–1307.
14. Braitstein P, Boulle A, Nash D, et al.. Gender and the use of antiretroviral treatment in resource-constrained settings: findings from a multicenter collaboration. J Womens Health (Larchmt). 2008;17:47–55.
15. Kigozi IM, Dobkin LM, Martin JN, et al.. Late-disease stage at presentation to an HIV clinic in the era of free antiretroviral therapy in Sub-Saharan Africa. J Acquir Immune Defic Syndr. 2009;52:280.
16. Kaplan JE, Hanson D, Dworkin MS, et al.. Epidemiology of human immunodeficiency virus–associated opportunistic infections in the United States in the era of highly active antiretroviral therapy. Clin Infect Dis. 2000;30(suppl 1):S5–S11.
17. Fleming PL, Ciesielski CA, Byers RH, et al.. Gender differences in reported AIDS-indicative diagnoses. J Infect Dis. 1993;168:61–67.
18. Iscovich J, Boffetta P, Franceschi S, et al.. Classic Kaposi's sarcoma: epidemiology and risk factors. Cancer. 2000;88:500–517.
19. Taylor JF, Smith PG, Bull D, et al.. Kaposi's sarcoma in Uganda: geographic and ethnic distribution. Br J Cancer. 1972;26:483–497.