Pre-ART enrollment increased from 254 to 2,396 patients between 2004 and 2008. This could have been explained by the adoption of broader diagnostic interventions, particularly, the implementation of Provider Initiated Testing and Counselling (PITC) in 2008 to augment the initial client-initiated approaches (14). This was followed by a decrease in the absolute pre-ART numbers from 2009-2013 following scale-up of decentralized treatment programs and further in 2014, due to the change in treatment guidelines lowering the threshold for initiation of ART to CD4 counts of 500 cells/µl (15).
The majority of pre-ART patients on follow-up were women during the 11 year period with a non-significant change in gender trends. More women than men were infected with HIV as reported in the Kenya AIDS Indicator Survey (KAIS) 2012 (3). This is consistent with the 2016 county profiles data that reported more women than men as having HIV infection (16). The explanation could be that women are twice as likely to acquire HIV infection compared to men (17). Women also tend to encounter more social, cultural and economic inequalities compared to men making them more vulnerable to HIV acquisition (17). Another explanation for the higher number of women is that fewer men enroll into HIV services and even fewer initiate ART (18). This is probably due to poorer health seeking behavior, perceived low risk of infection, and poor social support systems for among men (19). These may be addressed through implementation of men friendly and culturally acceptable interventions to improve identification, linkage and enrollment into HIV care (20).
There was no statistically significant difference in the proportions of children, adolescents and adults enrolling into HIV care over the years. This is in contrast to the KAIS 2012 report that suggested a change in the peaks in age specific prevalence in men and women from 2003 to 2012 (3). Our findings could be a result of having a relatively stable HIV disease burden in central Kenya over the years. However, the proportion of patients aged between 0-4 years reduced from 8.7% in 2004 to 1.1% in 2014 due to effective PMTCT interventions in the region.
Our study demonstrated a reduction in number of patients enrolling with advanced HIV disease. This is similar to trends seen in several studies in sub Saharan Africa (SSA). A study in Rwanda reported marked improvement in the immune status of patients at enrollment into care (21). Enrollment into HIV care at earlier disease stages across all HIV testing points was also reported in Ethiopia (22). Similarly, accessing ART at advanced disease peaked at 35.0% in 2005-06 and fell to 27.0% in 2008-09 in a study conducted in Kenya, Tanzania, and Uganda (23). Another study of 334,557 adults from several countries in sub-Saharan Africa between 2006 and 2011, reported that the proportion of patients initiating ART with advanced HIV disease decreased from 42.0% to 29.0% (24). In contrast, a study conducted at Mbarara University between 2007 and 2008 reported that more than one third (40.0%) of patients newly diagnosed with HIV infection were categorized as late presenters, classified as WHO clinical stage III or IV (25).
Enrollment in early stage HIV disease can be explained by the scale up of PITC initiatives in the country resulting in earlier identification prior to onset of AIDS defining illnesses (14). Further, there was increased access to HIV services through decentralization in the period (26)(27). The UTT guidelines are expected to translate into earlier ART initiation, resulting in improvement in morbidity and mortality (28).
This study reported a reduction in HIV patients on TB treatment over time while those screening positive for TB signs increased over time. This is similar to findings from the 2016 Kenya TB prevalence survey (29). Similarly, a study conducted among 274 patients who were asymptomatic for TB and ART naïve reported a high prevalence of subclinical TB in HIV-1 infected patients (30).
Pre-ART retention, LTFU and mortality outcomes at 6 and 12 months improved from the year 2013 onwards compared to years 2006 – 2012 even though mortality slightly increased from 2012 to 2014 . The improvement in later cohorts could be due to improved health systems and revision of the Kenya HIV treatment guidelines in line with emerging evidence such as replacement of D4T with TDF as the preferred first line resulting in better toxicity profile and hence better adherence as well as raising the CD4 cut-off at ART initiation from 350 cell/mm3 to 500 cells/mm3. (15)(31). Despite the improvement in later cohorts, retention in this study averaged 40.0-50.0% at both 6 and 12 months of follow-up. This is similar to what has been reported by other studies. A systematic review in SSA on retention of pre-ART patients from time of HIV testing to ART eligibility reported that the median proportion that was retained between HIV testing and CD4 testing was 59.0% and between CD4 testing and ART eligibility was 46.0% (32). In contrast, some studies have shown lower retention among the pre-ART population. A study conducted in Nigeria among 5320 patients reported 12 month retention of 23.4% among pre-ART patients seen at 37 health facilities (33). Lower retention in pre-ART could be due to the asymptomatic state of early HIV disease with patients not perceiving themselves as requiring care. This suggests the challenges of retaining relatively well or asymptomatic patients in treatment programs.
LTFU was noted to be a major contributor to attrition averaging at 50.0% for most cohort years at both six and twelve months. The high LTFU reported in our study is similar to data reported by other studies conducted in SSA. A prospective cohort study of 530 clients registering for HIV care between July 2008 and August 2009 at Kilifi District Hospital in Kenya and followed up for 6 months recorded a LTFU rate of 33.6% (34). In Ethiopia, a single centre study among 626 patients enrolled in pre ART care between 2010 and 2013 reported that the LTFU was 28.4% after a median follow-up of 6 months (35). A systematic review and meta-analysis conducted in SSA on pre ART patients followed up from time of HIV diagnosis to initiation of ART regardless of the number of months of follow-up, reported that among patients eligible for ART, 24.6% were LTFU whereas among ineligible patients 54.2% were LTFU (36).
The high rates of LTFU among ineligible patients may suggests the difficulty of retaining asymptomatic patients in care especially due to lack of motivation to attend clinic in absence of ART. A study in western Kenya reported higher rates of disengagement from care among those on pre ART who reported feeling well and therefore not requiring care. Among the same group, re-engagement to care was limited by ack of locator information hampering tracing efforts (37). Further, patients reported as LTFU may have died and therefore could have been wrongly classified. Other reasons for the high LTFU may be self-referral (38), stigma and denial of HIV status, non-disclosure to sources of social support including peers and family (39). Personal drive has also been described as a likely barrier or facilitator of engagement and retention in care (40). Health facility barriers to retention have also been reported in a western Kenya study, including lack of patient incentives, poor provider-patient interactions, access, and health facility related stigma (41).
The other contributor to attrition was mortality. Our study demonstrated a reduction in mortality over time from earlier cohorts to later cohorts. The mortality rate also generally remained low throughout the cohorts years. The low mortality points towards earlier diagnosis of HIV disease as well as earlier treatment. Similar to our study, a study conducted in Nigeria reported that 5.9% of pre-ART patients died during the first 12 months of follow-up (33). A study in western Kenya also found proportionaly lower mortality among pre ART patients who were traced back to care compared to those on ART (37). In contrast, some studies from SSA have reported higher mortality. A study conducted in Cote d’Ivoire among 860 patients during the pre ART period, reported an increase in mortality with reduction in CD4 cell counts (42). The main advantage of this study was the use of a large dataset with many patients data collected over a long period of time which allows for better inference. However there were some limitations which included poor documentation for patients who may have self-transferred or died. This may have resulted in an overestimation of LTFU outcome. Another limitation was missing data where no WHO staging and TB status was documented during the study period which could have affected the results. There is also a possibility that the results may have been influenced by the natural maturation of the program and improvements in HIV service delivery over time. Data was routinely collected and entered into the electronic system and could have included transcription errors. Lack of unique patient identifiers limited the capacity to track patients through various service delivery points and even across various healthcare facilities.