Research Article :
Ausman Ahmed, Desalew Mekonnen, Melaku Kindie Introduction: Tuberculosis is the leading cause of morbidity and mortality among HIV-infected individuals. Tuberculosis and human immune deficiency virus infections are two major public health problems in many parts of the world. Globally tuberculosis is a leading cause of death among people living with HIV and it is the most potent risk factor for the development of tuberculosis. There for the aim of this study assess Background Tuberculosis (TB) is a chronic infectious disease caused by Mycobacterium Tuberculosis (MTB). It is
typically affects the lung but also can affect other parts of
thebody as well [1]. tuberculosis and Human Immune Deficiency Virus (HIV)
infections are two major public health problems in many parts of the world [2,3].
Since thebeginning of the later pandemic, nearly 78 million people have
contracted HIV and close to 39 million have died of AIDS causes [2]. Worldwide,
TB is a leading cause of death among people living with HIV and HIV is the most
potent risk factor for the development of tuberculosis. According to WHO report 2014, 1.1 million incident TB
cases are among people living with HIV. The prevalence of TB-HIV Co-infection is higher
worldwide and 90% of these co-infected cases live in developing nations
[4,5]. Sub-Saharan
Africa accounted for 79% of the burden of TB-HIV co infections, followed by
South-East Asia (11%). In the African region that has the highest TB/HIV
burden, three out of four TB patients knew their HIV status globally, and 70%
of the TB patients known to be living with HIV in 2013 were started on antiretroviral therapy (ART). Even
though tuberculosis is the most commonly diagnosed opportunistic infection and disease in HIV
infected individuals which can be curable and reduced with appropriate measure
of therapy but hidden TB can hasten the progression of HIV. The presence of TB
may affect individuals with HIV infection in numerous ways. TB increase T-cell replication and it increases HIV
replication and it leads to increased viral load. Tuberculosis facilitate
occurrence of other opportunistic infections and become a challenging to
diagnose TB with HIV because the clinical manifestations of TB in HIV infected
individuals are somewhat different. The life time risk of HIV infected individuals
to develop TB is 20-37 times greater than HIV negative individuals to develop
active TB from the latent infection of mycobacterium tuberculosis [1,3, 6]. The
dangerous synergy affects all aspects of both diseases, from pathogenesis and the epidemiologic profile,
to clinical presentation, treatment, and prevention [7]. This synergy also
impacts largely the management of individuals co-infected with this deadly disease
related to pill burden, drug to drug interaction, increased adverse effect and immune reconstitution
inflammatorysyndrome(IRIS) [7-9]. As a result, TB became the leading
opportunistic infection that cause of death among HIV infected people. This
factors and late diagnosis of TB highly contribute to keep the mortality rate of TB very high among the
co-infected people [9]. Several
studies conducted in different places of the world showed the synergic effect
of TB and HIV among HIV infected patients. A large
review conducted on syndemic interaction between HIV and TB epidemics showed
that HIV-associated TB contributes substantially to the burden of TB-associated
morbidity and mortality [10]. HIV infection is the strongest known risk factor for TB. High HIV prevalence
rates are significantly correlated with high TB incidence rates [11]. Similarly, HIV
increases the risk of progression to active TB in both primary and latent TB
[12]. In
developed nations the incident cases of TB was increased with the HIV epidemic
on HIV infected patients [13]. In developing country the synergic effect is worse than the developed
nations. HIV affects and alters TB transmission, duration of infectiousness and
progression of disease Among predictors for the incidence of tuberculosis among
HIV infected individuals low CD4 count [14-18], diabetes mellitus, chronic
kidney disease, functional status and presence of other opportunistic were
significantly associated with reactivation and development of active TB among
HIV infected people [18-21], a low BMI is a risk for development of TB among
HIV patients, hemoglobin of ≤10 mg/dl, BMI ≤15.5 kg/m2,
and opportunistic infections other than TB were significant risk factors for
the development of TB among this group [22]. INH preventive therapy (IPT)
treatment, ART and CPT reduces the risk of active TB in HIV-infected
individuals [23,24]. Therefore the study aimed to assess predictors for
incidence of tuberculosis among HIV infected individuals in Afar public health
facilities. Methods Study design and period A
five year Institution based retrospective follow-up study was employed to
assess the incidence and predictors of tuberculosis among adult people living
with HIV in Afar public health facilities from May to Jun, 2015. Study area The
study was conducted in Afar regional state selected health facilities which is
located in the North-eastern part of Ethiopia. The region has a population of
1,678,000 only 289,000 population live in urban and semi urban area [25].
Administratively the region consists of five administrative zones with 32
districts. The capital city of the region (Samara) is located 536 km away from
Addis Ababa. In Afar there are four hospitals, 40 health centers, 270 health
posts and 15 private clinics delivering health services for the people living in the
region. Since 2006/7 when HIV care service introduced in the region 15 public
health institutions provides HIV
chronic care and support service for around 4,000 PLHIV. The study sites
selected based on their number of client follow and presence of TB and HIV
follow up clinic. Based on this, the study was focused on two health centers
(Awash, and Samara), Asayta hospital, Abala hospital and the only general
hospital (Dubti) in the region. These health institutions provide chronic HIV care and follow up for about 70%
of patients living with HIV in the region. Study
participants were all (503) adult people infected with HIV enrolled to chronic
HIV care from July 2010 to May 2015 in selected Afar public health facilities
(Dubti hospital, AsaytaH ospital, Abala hospital, Awash and Samara health
centers). Those adult HIV infected individuals enrolled to chronic care clinic
from July 2010 to June 2011 were followed till May 2015 and those with
incomplete information like date of enrollment, baseline CD4 count and transfer
in patients and TB patients in the last 3 month were excluded in the
study. Data collection instrument and procedure Registered
patient chart was observed and suitable data extraction format was prepared in
English. Subsequently, the data were collected by four diploma nurses and two
BSc nurses who had ART training using the data collection format from the
patient records. Data clerk and case managers assisted the data collators by
identifying the charts. Charts were retrieved by using the patient medical
record number and ART registration number which is found on the data base of
the health facilities. Data processing and analysis Extracted
data were checked for completeness, coded, and entered to EPI-INFO version 7
and exported to SPSS version 20 for further analysis. Statistical summary was
applied to describe socio demographic, clinical and follow up variables.
Magnitude was calculated and described by frequency and tables. Incidence
density rate was calculated for the study period. Life table and long rank test
was used to estimate TB free survival among study participants and to compare
different categories of survival probability respectively. Bi-variable and
multivariate Cox regression model was used to identify the predictors.
Variables with value of p < 0.2 in the bivariable analysis was candidate for
multivariate proportional hazard model. 95% CI of hazard ratio was computed and
variables having p-value <0.05 in the multivariate Cox proportional hazards
model was taken as significant predictors with the outcome variable. Ethical
Clearance was obtained from the IRB office of the institute of school of
medicine, university of Gondar. Permission was obtained from the Afar regional
health office (ARHO) and written permission letter was sent to each health
facilities to conduct this research. Unique identification information was used
on the extraction format and for all information taken from the chart
confidentiality issue was maintained. The collected information was only used
for the study purpose. Results Baseline socio-demographic characteristics of
PLHIV A
total of 503 records of PLHIV who were enrolled from July 1, 2010 to May 2015
were reviewed. Fifty two (10.44%) of them were not included in the analysis due
to incomplete information. Among the 451 patients remaining in the analysis the
mean age (SD) was 32.55 } 7.48) and almost two third 297(65.9%) of them were
below the age of 35 years. Most of respondents 410 (90.9%) in the study were
urban residents More than half 267(59.2%) of PLHIV were females and 275 (61%)
were also Muslim in religion. (Table 1) At
most half 234(51.9%) of patients were self-employed. One hundred thirty (28.8%)
patients recorded as substance users either of drugs 20% or tobacco 3.1% or
alcohol 5.7%. Majority, 374(93.1%) of the patients were living in family size
of 1-5. Almost half 212(47%) of the patients never went to formal education.
More than two third (68.1%) of the patients were currently or formerly
married (Table 1). Baseline clinical and HIV related follow up
characteristics of PLHIV Baseline
clinical and HIV related follow-up characteristics as shown in table 2 below
(53.4%) had a baseline WHO clinical stage III and IV. Majority 366 (81.2%) of
Participants were enrolled with working functional status. Participants had
baseline median CD4 cell count of 285cell/ml (IQR178-383) at enrollment. Almost
half 218 (48.3%) of the participants were enrolled with BMI < 18.5. More
than half 270 (59.9%) study subjects had a baseline Hgb < 12.5. During the follow
up majority 413 (91.8%) of the participants provided with CPT but only
94(20.8%) of the participants received IPT (Table 2). The eligibility criteria
for the initiation of HAART was mainly WHO clinical stage 183 (40.6%) and both
WHO clinical stage and CD4 cell count 167 (37 %.) respectively. The initial
regimen frequently prescribed for the study participants were a combination of
TDF,3TC and EFV 170 (37.7%) followed with AZT,3TC and EFV110 (24.4%). Ninety
six (21.3%) of participants changed their initial regimen. 92 (95.8%) of change
was substitution and only 4(4.2%) patients switched to second line. Majority of
the drug changes was made following the development of side effect 50 (52.08%)
and 29 (30.2%) changes was following development of TB. Baseline clinical and HIV related follow up characteristics of
PLHIV From
the total of 451 study participants (53.4%) had a baseline WHO clinical stage
III and IV. Majority 366(81.2%) of Participants were enrolled with working
functional status. The average baseline median CD4 cell counts of respondents
at enrollment were 285cell/ ml (IQR178-383). Almost half 218(48.3%) of the
participants were enrolled with BMI <18.5. more than of 270(59.9%) study
subjects had a baseline Hgb<12.5. During the follow up majority 413(91.8%)
of the participants provided with CPT but only 94(20.8%) of the participants
received IPT (Table 2&3) The
eligibility criteria for the initiation of HAART was mainly WHO clinical stage
183(40.6%) and both WHO clinical stage and CD4 cell count 167(37 %.)
respectively. The initial regimen frequently prescribed for the study
participants were a combination of TDF,3TC and EFV 170(37.7%) followed with
AZT,3TC and EFV110(24.4%). Ninety six (21.3%) of participants changed their
initial regimen. 92(95.8%) of change was substitution and only 4(4.2%) patients
switched to second line. Majority of the drug changes was made following the
development of side effect 50(52.08%) and 29(30.2%) changes was following
development of TB (Table 3). TB incidence rate Four
hundred fifty one study participants were followed for different periods in the
follow up for a total of 1377.303 Person Years of observation. One hundred
nineteen (26.4%) of participants develop TB while on follow up and 332
individuals censored (40 patients transferred out, 13 patients died, 21 drop
out and 258 remained till end of follow up. Therefore, the overall TB incidence
rate on the follow up period calculated using Person-year of follow up was 8.64
cases per 100 Person Years. Study participants stayed in the follow up for a
minimum of 0.03 month and maximum of 58.83 months. The median observation
period was 46.74 months [IQR=15.95-52.42 months].The median survival time is
54.00 month. Among the TB cases occurred in the follow up period 67(56.3% were
females. Majority 91(76.47%) of the cases were pulmonary TB. Forty six (38.6%)
of incident TB occurred within the first months of follow up and 68(57.14%) of
incident TB cases occurred within the first year of follow up. Incident of TB
is more common in urban105 (88%) of cases than the rural setting and in family
size of >5 households. Incidence of TB with PLHIV and their
baseline clinical and follow up characteristic From
the study participants who developed incident TB, 41(34.5%) of them had history
of previous TB or treatment history and 47(39.5%) of them were either
ambulatory or bedridden at enrollment. Majority 115(96.6%) of the incident
cases of patients not provided with INH prophylactic therapy. Ninety five
(79.9%) of participants with incident cases of TB were enrolled with Hgb level
below12.5g/dl. Test
of equality for survival distribution for the different levels of the different
categories was performed with Kaplan Meier using the long rank test.
Association of difference was observed among the explanatory variables
like BMI and IPT. Baseline BMI had a significant difference for tuberculosis -
free survival as compared for people living with HIV. BMI < 18.5 kg/m2 had
low TB free survival as compared to those With BMI >18.5 kg/m2 with the
overall comparison result long rank of p-value p< 0.002 and for the IPT was
p<0.0001 which shows significant difference of TB free survival among
patients provided with IPT. [Figure 1] Predictors of tuberculosis in Cox survival
analysis In
a bi-variable Cox regression analysis, variables with p<0.2 value was
candidate for multivariate analysis. Eleven variables were significantly
associated in the Bi variable analyses which were CD4 cell count, WHO clinical
stage, substance use marital status, OI, IPT, past TB history, BMI, Hgb,
functional status and family size were included in the multivariate analysis.
The Enter method was used in the multivariate analysis to see output value of
the variables showed significance in bivariate analysis. Past TB history,
baseline functional status, baseline hemoglobin, baseline BMI and IPT were
found statistically significant with having value of p< 0.05 in multivariate
analysis. According to the Cox multivariate analysis HIV patients who had
history of TB at enrollment were 2.32 times risky to develop TB at a time than
those who had no past TB history (AHR=2.32, 95%CI=. 2.324(1.511-3.573).
Patients enrolled to care with baseline functional status of bed redden and
ambulatory were 2.42 times more prone to develop TB at any follow up time than
those enrolled with working functional status (AHR=2.42,95%CI(1.05-5.59)
,(AHR=2.42 ,95%CI=(1.56-3.75) respectively. Similarly, HIV patients having
baseline BMI<18.5kg/m2 were1.62 times higher risky to get TB at any time
than those with having BMI≥18.5kg/ m2 at baseline (AHR=1.621, 95 %CI
(1.09-2.40). HIV patient who did not take IPT were 6.96 times more likely to
acquire TB at any time compared to those who taken IPT(AHR= 6.96,95%CI (2.53-
19.08). in addition People living with HIV enrolled with baseline Hgb <
12.5g/dl were 2.54 times more to develop TB at certain time than those having
Hgb above 12.5g/dl respectively (AHR=2.00 ,95%(1.08-3.71) (AHR=
2.54,95%CI(1.57-4.11). Discussion It
is universally acknowledged that HIV infection increases the incidence of
tuberculosis. TB and HIV remains as major public health problems in many parts
of the world. The fact, that Ethiopia is among the TB high burden countries
with an estimated annual incidence of 211case per 100,000 populations and with
prevalence of 224 cases per 100,000 [4]. TB is the most common cause of
morbidity and mortality among PLHIV. HIV infected individuals are 20-37 times
greater risk to develop TB in life time compared to non-infected individuals
[6,26]. [Table 4 & 5] This
study tried to assess the overall incidence of TB among the participants for
the entire follow up period. It was found to be 8.64 cases per 100 person
years. This finding was consistent with studies conducted in Ethiopia which
founds (7cases /100 PY and 7.9 cases per/100 PY) [27,28]. It also in lined with
findings from Tanzania 7.9 [(95% CI), 7.6-8.2] per 100 and Sub-Saharan Africa
[29,30]. However, it was high as compared to studies conducted in Korea, Israel
and Malaysia [17,31,32]. This could be explained by the fact that these
countries might have better preventive, diagnostic and treatment setups and
strategies for controlling TB in contrast of this study was done in a high TB
burden country and scarce resources might contribute for this high result. Low
health care coverage and late enrollment to health care facilities might
contribute for this finding. This could be also explained with progression of
the latent infection to active TB after initiation of HIV chronic care with
late presentation of patients to health facility. The patient might get new
infection or IRIS after initiation of HAART and other HIV related services.
IRIS associated TB was commonly seen within the first 6 months after initiation
of HAART [33]. In
different studies as indicated that multiple risk factors can predict the
incidence of TB among PLHIV on HAART and Pre HAART era. Our study found that
having past TB treatment history, non-use of IPT, baseline functional status of
bedridden and ambulatory, low baseline Hemoglobin level and low baseline BMI
were significantly associated with increased risk for acquiring TB in the study
participants. This study revealed that HIV infected individuals with Past TB
history had 2.3 times high risk to develop TB as compared with HIV individuals
with no past TB history. Our finding was similar with findings from studies
done in Israel and Malaysia and Uganda [31,32, 34]. The possible explanation
could be due to poor compliance for their anti TB treatment at first episode
and it could be due to relapse. Reactivation or re-infection might also be
possible explanation for the existing dysregulated immunity. Participants not
provided with IPT were 7 times higher risk to develop TB as compared to
individuals who took IPT (AHR=6.96, 95%2.53-19.08). This study found that IPT
were independent risk factor for the occurrence of incident TB among adult HIV
patients. This is consistent with studies done in Ethiopia, South Africa and
Brazil [24,35,36]. In fact, IPT is recommended to reduce and control TB among
this group of people. Despite the fact, the poor uptake and the ambiguity and
fear of drug resistance might contribute for these participants non- IPT user.
This is an alarming to scale up the IPT on the setting. Patients
ambulatory and bedridden functional status at baseline is 2.42 times more
likely to develop TB in the entire follow up as compared to working functional
status. This finding is in line with other study done in northwest Ethiopia
[27]. The possible explanation was debilitated patients prone to malnutrition
and less physical activity that make them prone for many diseases and TB.
Patients with BMI of <18.5 at baseline was 1.62 times higher risk of
developing TB as compared to adults with BMI≥18.5 at base line. This finding
was consistent with phase III randomized controlled trial study done in
Tanzania (22).It was also agrees with studies done in Ethiopia and south Africa
[29,37]. The possible explanations might be HIV patients are prone for
malnutrition and low BMI is a sign of malnutrition. Malnutrition in HIV
patients associated with increased catabolic activity, infection and loss of
appetite and decreased in take. This all contributes for low BMI. Malnutrition
is one of the pertinent risk factor of TB among HIV and non HIV patients. Similarly
this study found that patients with Hgb level of <10 and 10-12.5 at base
line were 2.00 and 2.54 times higher risk of developing TB than those having
Hgb level >12.5 at base line. Hematologic complications were risk factors
for the incidence of TB among PLHIV. This finding was in line with studies
conducted in Ethiopia, Uganda, Tanzania and South Africa [22,37-39]. The
Possible explanation is due to malnutrition and side effect of medications,
opportunistic infections and advanced stage of the disease. Undiagnosed TB
could explain the low Hgb level at the early enrollment. Variables like CD4
cell count and WHO clinical stage were not independently associated in this
study. Strength of the Study The
study tried to include all possible variables that influences risk of TB among
HIV patients that could accessed from the chart. The study was conducted for a
five year follow up that helps to show the long term impact of HIV on TB. Limitation of the Study This
study might have limitations that shared with limitation of most retrospective
record based studies had. The retrospective and record based nature of the
study design limited to include predictors that could affect the risk of TB
like housing condition, house hold income and other. Due to incomplete data
some study subjects were removed from the study that might undermine the
finding if those study subjects had TB. The study not observed ART group and
Pre ART group separately. Conclusion The
overall incidence of TB in the study setting is high. HIV infected individuals
with history of previous TB, not using IPT, base line BMI<18.5kg/m2,
ambulatory and bedridden functional status and having baseline Hgb <12.5g/dl
were most predictors of incident TB. Recommendation For governmental organizations and stakeholders: •
Strengthen the TB /HIV collaborative activity For health professionals: •
Strength the provision of IPT and nutritional support to all eligible HIV
individuals For patients •
Patients would be encouraged to have improved treatment and care seeking and
infection control behavior. For researchers: •
Further prospective studies might need to include all factors that influence
the risk of TB. Acknowledgement We are highly indebted
to University of Gondar, for giving us this golden opportunity to conduct this
research. We would like to extend our thanks to Afar Regional Health Beauro for
permission to conduct the study, providing the necessary preliminary information
while conducting this study. We are indebted to those patients, data collectors
and supervisors without them this project wouldn t have gone this far. Competing interests We
authors declare that they have no competing of interests. Authors contributions Ausman
Ahmed involved in the conception, design, data collection, analysis and report
writing. Desalew Mekonnen & Melaku Kindie assisted with the design,
approved the proposal with some revisions, participated in data analysis and
manuscript preparation. All authors read and approved the final
manuscript. References
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principle of internal medicine United States of America (2012). *Corresponding author:
Melaku Kindie Yenit,
Department of Epidemiology and Biostatistics,
College of Medicine and Health Sciences,
University of Gondar, Gondar, Ethiopia.
E-mail: melaku98@gmail.com Ahmed A, Mekonnen D, Kindie M
(2015) Incidence and Predictors of Tuberculosis
among Adult People Living with HIV/AIDS in Afar
Public Health Facilities, Northeast Ethiopia.
AIDS 1: 3-10Incidence and Predictors of Tuberculosis among Adult People Living with HIV-AIDS in Afar Public Health Facilities, Northeast Ethiopia
Abstract
incidence and predictors of tuberculosis among adult people living with HIV in Afar health facilities, Northeast Ethiopia.
Method: A five year retrospective follow up study was conducted among 503 adult HIV infected individuals who enrolled in HIV care clinic from July, 2010 to June, 2011. All adult HIV infected persons who enrolled newly in to chronic adult HIV care clinic from July 1, 2010 to June 30, 2011 were included in the study and those with incomplete baseline information (WHO stage, CD4 count and Hgb level) were excluded. Data were entered to EPI-INFO version 7 then exported to SPSS version 20 for further analysis. Bivariate and multivariate Cox proportional hazards model were used to identify predictors.
Result: A total of 451 charts were included and followed for a total of 1377.303 Person Years (PY) of observation, the overall incidence density of tuberculosis was 8.6 per 100person-year. More than half 68 (57.14%) of HIV infected persons developed TB at the first year of follow up. The cumulative proportion of TB free survival was 79%, 76%, 74%and 71% at the end of one year, two, three and four year respectively. Having past TB history (AHR=2.32, 95%CI=1.511-3.573); Ambulatory and bedridden functional status at baseline (AHR=2.42, 95%CI (1.05-5.59), (AHR=2.42, 95%CI=1.56- 3.75); Baseline BMI<18.5kg/m2 (AHR=1.621, 95 %CI =1.09-2.40); Not taking IP (Isoniazid prophylaxis therapy) (AHR= 6.96, 95%CI=2.53-19.08); Baseline Hgb <12.5g/ dl (AHR=2.00, 95% CI=1.08-3.71), and Hgb <10 g/dl (AHR= 2.54, 95%CI=1.57-4.11) were predictors that associated for TB incidence.
Conclusion and recommendation: TB incidence rate is high among adults living with HIV. TB was high in the first year of follow up. Past history TB, not receiving IPT, low BMI, low Hgb and unable to work were the most significant predictors for occurrence of TB. Therefore the result of the study recommends for an improved TB/HIV collaborationactivity and scale up of IPT in the setup to reduce risk of TB. Full-Text
• Giving trainings on the provision of IPT that might Strengthen the
strategies for prevention and control of TB among adult HIV infected
people
• Close supervision for Implementation of the guidelines and standards
strategies to prevent and control TB.
• Continuous follow up and early detection of malnutrition, prevention of other
infection and close monitoring for HIV patients enrolled with ambulatory or
bedridden functional status and low BMI <18.5and low Hgb at baseline to
control TB among this groups.
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Keywords
Incidence and predictors, Tuberculosis, Adult people living with HIV/AIDS, Afar health facilities, Northeast, Ethiopia
