Full Member

Lucy OBONYO NYANG'AU

Membership since: 2025

Africa

Currently in:

Other Memberships/Affiliations

Kenya Medical Laboratory Technician and Technologists Board(KMLTTB)

African Society for Laboratory Medicine(ASLM)

American Society for Microbiology(ASM)

British Society for Antimicrobial Chemotherapy(BSAC)

Degrees:

2021

Doctorate Medical and Health Sciences incl Neurosciences

Publications resulting from Research

Arch Microbiol Immunology 2020; 4 (2): 57-65 10.26502/ami.93650045
Archives of Microbiology & Immunology Vol. 4 No. 2 – June 2020 57
Research Article
False Positive Tuberculosis Cases (Xpert MTB/RIF Assay)
Among People Living With HIV Attending Bahati
Comprehensive Care Centre Nairobi, Kenya
Lucy Obonyo Nyang’au1*, Evans Amukoye2, Stanley Kangethe3, Jackson Onyuka4
1Mount Kenya University, Thika, Nairobi, Kenya
2Kenya Medical Research Institute, Nairobi, Kenya
3Mount Kenya University, Thika, Nairobi, Kenya
4Mount Kenya University, Thika, Nairobi, Kenya
*Corresponding Author: Lucy Obonyo Nyang’au, Department of Medical Laboratory Sciences, Mount
Kenya University, P.O Box 342-01000, Thika, Kenya; Tel: +254-0722816265; E-mail:
lucynyangau@yahoo.com
Received: 06 April 2020; Accepted: 16 April 2020; Published: 24 April 2020
Citation: Lucy Obonyo Nyang’au, Evans Amukoye, Stanley Kangethe, Jackson Onyuka. False Positive
Tuberculosis Cases (Xpert MTB/RIF Assay) Among People Living With HIV Attending Bahati Comprehensive
Care Centre Nairobi, Kenya. Archives of Microbiology & Immunology 4 (2020): 57-65.
Abstract
The introduction of GeneXpert MTB/RIF assay has
impacted positively in tuberculosis diagnosis,
providing a rapid way of identifying tuberculosis
patients in high burden, low income countries.
However Mycobacterium tuberculosis (MTB)
detection in previously treated patients, which may
be due to old deoxyribonucleic acid or active
disease, still remains a diagnostic dilemma for
diagnosis of tuberculosis. A retrospective cohort
study was conducted among consenting patients
with signs and symptoms of tuberculosis attending
Bahati comprehensive care centers. A total of three
hundred and forty six patients were sampled and
their sputa collected, subsequently laboratory
analysis was carried out for detection and culture of
Mycobacterium tuberculosis. Seventy seven (22%)
sputa had Mycobacterium tuberculosis detected on
Xpert MTB/RIF assay sputa from these patients
with bacteriologically confirmed pulmonary
tuberculosis were subjected to culture on
Mycobacterium Growth Indicator Tube (MGIT)
media. Detection of Mycobacterium tuberculosis
on Xpert MTB/RIF assay with no isolation of
growth on culture indicated a false positive
tuberculosis diagnosis. Out of 77 isolates subjected
for culture a total of 0(0%) and 5(7.5%); P=0.484,
isoniazid preventive therapy and non- isoniazid
preventive therapy patients had false positive
Arch Microbiol Immunology 2020; 4 (2): 57-65 10.26502/ami.93650045
Archives of Microbiology & Immunology Vol. 4 No. 2 – June 2020 58
tuberculosis cases, while 0(0%) and 5(25%);
P=0.001 new and retreatment patient’s had false
positive tuberculosis. Our study concluded that
there was no significant association between
isoniazid preventive therapy and tuberculosis false
positivity but there was significant association
between patient treatment status and tuberculosis
false positivity. Previously treated tuberculosis
patients were significantly associated with false
positivity, this call for clinicians to exercise caution
when interpreting results from previously treated
tuberculosis patients.
Keywords: False positive tuberculosis;
GeneXpert MTB/RIF assay; Mycobacterium
tuberculosis
1. Introduction
Tuberculosis is one of the top ten causes of death
globally and the leading cause of death from a
single infectious agent (ranking above HIV/AIDS)
[1]. Despite declining global incidence and
mortality tuberculosis (TB) remains a major
challenge worldwide, an estimated 10.0 million
people fell ill with TB in 2018, with estimated 1.2
million TB deaths among HIV negative people and
an additional 2,51,000 deaths among HIV positive
people were recorded respectively [1]. TB affects
people of all age groups and gender, the highest
burden was in Men aged >15 years in 2018, they
accounted for 57% of all TB cases, while Women
accounted for 32% and children aged < 15 years
accounted for 11% TB cases globally [1].
People living with HIV (PLHIV) accounted for
8.6% TB cases in 2018 [1]. HIV co-infection is
associated with unusual presentations of TB such
as smear negative and abnormal chest radiographs
this causes a diagnostic challenge, poor treatment
outcome and subsequent increased mortality [2].
Previous studies have shown that pauci-bacillary
forms of TB are more commonly identified in
patients who are HIV positive and these patients
happen to be sputum smear negative, but because
microscopy is less sensitive in these populations
these groups are the ones most likely to benefit
from Xpert MTB/RIF assay [2].
The introduction of GeneXpert MTB/RIF assay has
contributed a huge positive impact in tuberculosis
(TB) diagnosis, by providing a rapid way of
identifying TB patients in high burden, low income
countries [3]. The Xpert MTB/RIF assay is an
automated cartridge based nucleic acid
amplification test (NAAT) capable of
simultaneously detecting Mycobacterium
tuberculosis complex (MTBC) and Rifampicin
(RIF) resistance within 2 hours; this assay was
endorsed by the WHO in 2010, and approved by
FDA in 2013, and it is regarded as a breakthrough
in TB diagnostics [3]. The assay is performed on
the Cepheid GeneXpert multi-disease instrument
system which integrates sample purification,
nucleic acid amplification, and detection of target
sequences [3]. It uses hemi-nested real time PCR
(polymerase chain reaction) for the detection of
MTBC specific sequence of the rpoB gene and five
molecular probes to detect mutations within the
genes rifampicin resistance determining region
(RRDR). The assay can be performed directly on
raw sputum or concentrated sediments.
Nevertheless post implementation studies have
identified several challenges [4], emphasizing the
need for deeper understanding of clinical and
operational factors affecting performance.
2 Materials and Methods
Following approval by the ethics review committee
of Mount Kenya University (Ref.
No.MKU/ERC/1305) and research clearance by
National Commission for Science Technology and
Innovation (NACOSTI/P/19/13045/31000), 346
respondents were recruited for the study using
cluster random sampling.
Arch Microbiol Immunology 2020; 4 (2): 57-65 10.26502/ami.93650045
Archives of Microbiology & Immunology Vol. 4 No. 2 – June 2020 59
2.1 Study Design
Retrospective cohort study design was used where
eligible HIV positive participants with or without
use of isoniazid preventive therapy (IPT) were
recruited through cluster random sampling, only
those who gave consent were enrolled in the study.
2.2 Study Site
The study was conducted in Makadara sub-county,
Nairobi the capital city of Kenya. The sub-county
covers an area of 13Km2 and comprises of five
wards; Maringo, Hamza, Viwandani, Harambee,
and Makongeni [5]. Viwandani ward is an informal
settlement which is characterized by increased
population. Tuberculosis being airborne,
congestion especially in the houses facilitates
increases in tuberculosis transmission.
2.3 Sample Size Determination
Data from National tuberculosis, leprosy and Lung
disease program (NTLD-P) annual report (2017)
for Nairobi county, a TB prevalence of 0.1%
(147per 100,000) in HIV positive people was
established. Using Habib et al., (2014) [6] formula
and 0.1% as the working prevalence rate (P) for
tuberculosis and assuming a standard error (Z)
from the mean of 1.96 and in absolute precision (d)
of 5%, and design effect (D) being taken as (2)
sample size (n) was calculated as follows.
(1.96)2 (0.1) (0.9)/ (0.05)2 = 276 Clients
The estimated sample size was 276; it was adjusted
to allow for attrition /refusals which was estimated
for 20% [7] thus n= 276/ (1-0.2) =346 Clients.
2.4 Inclusion and Exclusion Criteria
Patients who were HIV positive, on care, above 15
years, with signs and symptoms of tuberculosis,
one year post isoniazid preventive therapy (IPT),
were included in the study upon consent. While
patients with isoniazid preventive therapy and age
records not clear, less than one year post isoniazid
preventive therapy, unable to consent, with other
samples other than sputum were excluded from the
study.
2.5 Laboratory Methods
2.5.1 Identification of Mycobacterium
tuberculosis
Using the geneXpert MTB/RIF assay sputa and the
reagent buffer were mixed according to the
standard operating procedure and loaded into the
Xpert MTB/RIF assay cartridge and test started on
Xpert MTB/RIF assay machine platform [8].
2.6 Culture of Mycobacterium tuberculosis
Mycobacterium tuberculosis (MTB) culture was
performed using non-radiometric method
Mycobacterium Growth Indicator Tube (MGIT)
BACTEC 960. Sputa decontamination was
performed using sodium hydroxide solution (40%
w/v) combined with 2.9% sodium citrate solution
and N-acetyl-L-cystein (NALC) powder [9]. Sterile
phosphate buffer was added and the organisms
concentrated by centrifugation at 3,000 rpm for 15
minutes. The supernatant was decanted and the
sediment suspended with phosphate buffer and
inoculated in liquid MGIT media and incubated
along with negative control (un-inoculated MGIT
media) and positive control (H37Rv ATCC 27294)
[9]. The MGIT tubes were incubated in the
BACTEC MGIT 960 machine at 37oC until the
instrument flagged them positive. After a
maximum of six weeks the instrument flagged the
tubes negative, if there was no growth at 37oC [10-
13]. Confirmative identification of MTB was done
using BD MGIT TBc, on all positive cultures.
Positive culture for MTB confirmed diagnosis of
active disease.
Arch Microbiol Immunology 2020; 4 (2): 57-65 10.26502/ami.93650045
Archives of Microbiology & Immunology Vol. 4 No. 2 – June 2020 60
3. Data management and Statistical
Analysis
Data was tabulated in a computer database
designed using MS-Access, and then transferred to
statistical package for the social sciences (SPSS)
version 20.0 for analysis. Pearson’s Chi-square test
was applied to determine the differences in
proportion for both groups in isoniazid preventive
therapy (IPT) status, type of patient and gender
against the detection of Mycobacterium
tuberculosis (MTB). Pearson’s Chi-square test was
applied to determine the differences in proportion
for both groups in isoniazid preventive therapy
(IPT) status, type of patients and demographics
against TB and TB false positives. While Fisher’s
exact test was applied to determine the difference
in proportions among the MTB detection levels in
GeneXpert MTB/RIF assay and among the age
groups. These results were presented by
appropriate tabulations based on the determined
variables, odds ratio (OR) with 95% confidence
interval (CI) and the corresponding p values. The
threshold for statistical significance was set at P≤
0.05.
4. Results
Prevalence of Tuberculosis false positives in
relation to Isoniazid Preventive Therapy and
Treatment status
Of the 77 Mycobacterium Tuberculosis (MTB)
positive Xpert MTB/RIF assay samples subjected
to culture 5(7.5%) and 0(0%) were false positive
for tuberculosis (TB) among the non-isoniazid
preventive therapy and isoniazid preventive therapy
arms respectively, P=0.484 while on the other hand
0(0%) and 5(25%) were false positive for TB
among new and retreatment patients P= 0.001
(Table 1). This indicates that there was no
significant association between isoniazid
preventive therapy and TB false positivity, while
on the other hand there was significant association
between TB false positivity and retreatment
patients. Further study findings indicated that
10(100%) and 62(92.5%) were true Xpert
MTB/RIF assay TB results in isoniazid preventive
therapy and Non- isoniazid preventive therapy
patients respectively (Table 1). While 57(100%)
and 15(75%) were true Xpert MTB/RIF assay TB
results among new and retreatment TB patients
respectively (Table 1). The true results were
concordant in Xpert MTB/RIF assay and BACTEC
MGIT 960 culture results while the false positive
cases had discordant results in the two methods.
Culture was taken as the reference standard.
Arch Microbiol Immunology 2020; 4 (2): 57-65 10.26502/ami.93650045
Archives of Microbiology & Immunology Vol. 4 No. 2 – June 2020 61
Table 1: False positive tuberculosis cases among study patients
Variables Total (N) True Xpert results n (%) False positives n (%) OR (95% CI) P Value
MTB+ve/Growth MTB+ve /No Growth
IPT status
IPT patients 10 10 (100) 0 (0) UD
0.484
Non-IPT patients 67 62 (92.5) 5 (7.5)
Type of patients
New patients 57 57 (100) 0 (0) UD
0.001
RT patients 20 15 (75) 5 (25)
MTB detection
levels
MTB detected
high
26 25 (96.2) 1 (3.8)
MTB detected
medium
45 41 (91.1) 4 (8.9) 0.690 (0.205-
1.226)
0.999
MTB detected
low
4 4 (100) 0 (0) UD 0.895
MTB detected
very low
2 2(100) 0 (0) UD 0.999
Gender
Female 30 28 (93.3) 2 (6.7) 0.92 (0.144-
5.867)
0.652
Male 47 44 (93.6) 3 (6.4)
Age (years)
< 20 4 4 (100) 0 (0)
20 – 39 47 42 (89.4) 5 (10.6) 0.111 (0.09-
1.271)
0.388
40 – 59 23 23 (100) 0 (0) UD 0.999
60 + 3 3 (100) 0 (0) UD 0.999
Key: MTB: Mycobacterium Tuberculosis; +Ve: Positive; IPT: Isoniazid Preventive Therapy; RT: Retreatment;
OR: Odds Ratio; C.I: Confidence Interval
Further the findings revealed that there was no significant difference between TB false positivity and the
Mycobacterium tuberculosis detection levels (high, medium, low and very low) gender and age of the patients
(Table 1). In all age categories of the isoniazid preventive therapy arm there were 0(0%) false positive TB cases
in males and females respectively, the study further revealed that there were 3(4.5%) and 2(3%) false positive
TB cases in male and female patients from the non-isoniazid preventive therapy arm respectively, in the age
category (20-39) (Table 2). This indicates the age category 20-39 was more prone to false positive TB cases,
and males had higher rate of false positivity than females having 4.5% and 3% respectively.
Arch Microbiol Immunology 2020; 4 (2): 57-65 10.26502/ami.93650045
Archives of Microbiology & Immunology Vol. 4 No. 2 – June 2020 62
Table 2: Distribution of false positives tuberculosis Cases among study patients
True Xpert MTB/RIF
assay Positive results;
False Xpert MTB/RIF
assay positive results;
Total
IPT status Gender
MTB+ve /Growth MTB+ve /No Growth
IPT
patients
Male
Age
(Years)
60+ 1(10%) 0(0%) 1
40 – 59 2(20%) 0(0%) 2
20 – 39 3(30%) 0(0%) 3
Total 6(60%) 0(0%) 6
Female
Age
(Years)
60+ 1(10%) 0(0%) 1
40 – 59 1(10%) 0(0%) 1
20 – 39 1(10%) 0(0%) 1
< 20 1(10%) 0(0%) 1
Total 4(40%) 0(0%) 4
Total
Age
(Years)
60+ 2(20%) 0(0%) 2
40 – 59 3(30%) 0(0%) 3
20 – 39 4(40%) 0(0%) 4
< 20 1(10%) 0(0%) 1
Total 10(100%) 0(0%) 10
Non IPT
patients
Male
Age
(Years)
60+ 1(1.5%) 0(0%) 1
40 – 59 12(17.9%) 0(0%) 12
20 – 39 24(35.8%) 3(4.5%) 27
< 20 1(1.5%) 0(0%) 1
Total 38(56.7%) 3(4.5%) 41
Female
Age
(Years)
40 – 59 8(11.9%) 0(0%) 8
20 – 39 14(20.9%) 2(3%) 16
< 20 2(3%) 0(0%) 2
Total 24(35.8%) 2(3%) 26
Total
Age
(Years)
60+ 1(1.5%) 0(0%) 1
40 – 59 20(29.9%) 0(0%) 20
20 – 39 38(56.7%) 5(7.5%) 43
< 20 3(4.5%) 0(0%) 3
Total 62(92.5%) 5(7.5%) 67
Total 72 5 77
Key: IPT: Isoniazid Preventive Therapy; +Ve: Positive; MTB: Mycobacterium Tuberculosis
Discussion
Xpert MTB/RIF assay is a molecular technique
widely used currently all over the World for
diagnosis of active tuberculosis (TB) [1]. This
assay’s positivity for Mycobacterium tuberculosis
deoxyribonucleic acid (DNA) can remain detected
for years after treatment in the absence of viable
Arch Microbiol Immunology 2020; 4 (2): 57-65 10.26502/ami.93650045
Archives of Microbiology & Immunology Vol. 4 No. 2 – June 2020 63
organisms for culture [4]. Understanding these
Xpert false positive results is of paramount
importance given the large global burden of
symptomatic patients who present in health
institutions for investigation of active TB but have
previously been treated for active TB disease [4].
The current study revealed that 25% (P=0.001)
false positive TB cases (MTB detection on Xpert
MTB/RIF assay and negative result on BACTEC
MGIT 960 culture) among previously treated TB
patients, while there were 0(0%) false positive TB
cases among the new patients. These study findings
revealed significant association between TB false
positivity and retreatment TB patients, but there
was no significant association between TB false
positivity and the IPT status of the patients, MTB
detection levels, age and gender of the patients.
These findings concur with previous studies where
the rate of TB false positivity among retreatment
patients was South Africa 14% [14] 7 % [4], Egypt
2% [15], India 5.3% [16] and China 0.8% [17].
The current study findings confirm with other
previous studies that false positive TB cases are
significantly associated with previously treated TB
patients who had active TB disease. These findings
can be attributed to the fact that Xpert MTB/RIF
assay being a molecular technique cannot
differentiate between viable and non-viable
mycobacterial DNA, hence therefore the assay can
detect DNA from dead bacilli of previously treated
patients who had active TB disease [4]. Xpert
MTB/RIF assay results of this nature can lead to
baseless treatment of the patients, increase the
health care costs and delay in reaching the correct
diagnosis for the patients which can even lead to
death [4]. In this regard patients started on
medication based on wrong diagnosis due to false
positive TB results, may end up dying because of
wrong diagnosis, since the really problem remains
unknown and untreated. This calls for clinicians to
exercise caution when interpreting results from
previously treated TB patients [4].
Further the current study findings revealed that
there were 3(4.5%) false positive TB cases in male
cases, in the age category (20-39). These findings
concur with previous finding in Brazil where there
was 73.6% false TB positivity among male patients
[18]. These findings would be attributed to the fact
that males in this age category (20-39), exhibit
some characteristics which expose them to
recurrent episodes of TB disease, making them
vulnerable to false positivity because of harboring
deoxyribonucleic acid from the previous episodes
[18]. This characteristics include overcrowding
since most of these people are found in institutions
of learning, which are often crowded increasing
transmission of this air borne disease, peer pressure
which is common during this period leads them to
engage in irresponsible behavior like drug and
alcohol abuse coupled with the already depressed
immunity due to HIV makes the body vulnerable to
TB disease [18].
Conclusions
Xpert MTB/RIF assay positivity for Mycobacterial
DNA can remain detected for years after treatment
in the absence of viable organisms for culture [4].
Understanding such assay results is of paramount
importance given the huge global burden of
symptomatic patients who present for investigation
of active TB and have history of previous active
TB disease treatment. There was significant
association between previously treated TB patients
and TB false positivity. But TB false positivity was
not significantly associated with the MTB detection
levels, IPT status, gender or age of the patients.
Clinicians should wait confirmatory testing in
Xpert positive TB results for retreatment patients
before commencing them on treatment, they should
also take detailed history especially accurate
classification of the patient and this will lead to
proper patient management. GeneXpert should not
be used to follow up patients who are on treatment,
this is because the mycobacterial deoxyribonucleic
Arch Microbiol Immunology 2020; 4 (2): 57-65 10.26502/ami.93650045
Archives of Microbiology & Immunology Vol. 4 No. 2 – June 2020 64
acid will still be detected and the results will be
positive for MTB detection, therefore smear
microscopy still remains a major test in TB
treatment follow up. The findings of this study
have important policy implications which include
the gaps in TB management guidelines and the
need for revision and standardization to avoid
exposing patients to unwarranted treatment.
Recommendation
Studies should be conducted to monitor Xpert
MTB/RIF assay tuberculosis positive patients after
treatment completion to ascertain duration of
mycobacterial DNA survival, also clinicians should
be very careful when dealing with retreatment
patients to avoid baseless treatment which is not
only expensive but toxic.
Acknowledgement
The authors owe special gratitude to the staffs of
Central Reference Laboratory, Bahati
Comprehensive Care Centre staffs and all those
who directly or indirectly contributed to the success
of this study.
Competing interests
The authors declare that they have no competing
interests.
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Journal of Tuberculosis
Open Access | Research Article
Lucy Obonyo Nyang’au1*; Evans Amukoye2; Stanley Kangethe1; Jackson Onyuka1
1Mount Kenya University, Thika, Nairobi, Kenya
2Kenya Medical Research Institute, Nairobi, Kenya
ISSN: 2640-1193
MedDocs Publishers
2
Journal of Tuberculosis
Introduction
Mycobacterium Tuberculosis (MTB) is the causative agent of tuberculosis, which still remains a leading cause of mortality and morbidity globally [1]. Worldwide tuberculosis was top ten cause of death alongside Human Immunodeficiency Virus (HIV) in 2018 [2]. In 2018, 10.0 million people fell ill with tuberculosis; 1.2 million TB deaths were among HIV negative people while an additional 251,000 were among HIV positive people [2]. HIV co-infection has been associated with unusual presentations of TB such as smear negative and abnormal chest radiographs thus causing a diagnostic challenge, poor treatment outcome and subsequent increased mortality [3]. People living with HIV who have TB infection have a 5-10% annual risk of developing TB compared to 5-10% lifetime risk in HIV negative individuals [1]. Isoniazid Preventive Therapy (IPT) together with other interventions such as intensified case finding and infection control has been widely recommended to reduce the burden of TB in people living with HIV (PLHIV) [4].
Isoniazid preventive therapy has proven to be safe with minimal and less frequently reported side effects such as hepatotoxicity and gastrointestinal symptoms, studies have shown that IPT can lower TB incidence among people living with human immunodeficiency virus (PLHIV) by up to 70% if used with or without ART [4]. Taking isoniazid as a preventive measure is a cost effective and simple way that prevents TB if present to become inactive, the drug has been a standard for treatment of tuberculosis and preventive therapy due to its high potency, infrequent toxicity, low cost and non- bulk [4]. Treatment of Latent Tuberculosis Infection (LTBI) prevents its progression to active disease, both in HIV negative population and those infected with HIV [5]. Increasing uptake of isoniazid preventive therapy in HIV positive people prevents deaths and cases caused by tuberculosis [6]. Uptake of IPT has been relatively slow in most developing countries; it works synergistically with and independently of antiretroviral therapy (ART) to reduce tuberculosis morbidity, mortality and incidence among PLHIV [7,8].
Isoniazid preventive therapy involves provision of isoniazid tablets to those who meet the eligibility criteria [8]. The recommended dose is 10mg/Kg daily for children and up to 300mg/day for adults [8]. To end the global TB epidemic, it entails addressing the significant reservoir of TB infection, especially in PLHIV who have the highest risk of progression to TB disease [8]. Emphasis on TB prevention not only spares individuals the burden of TB associated morbidity and mortality but it also reduces the economic impact of the disease on the health system as a whole [9]. Isoniazid preventive therapy is protective towards progressing to active tuberculosis disease and retreatment tuberculosis patients are more prone to TB disease [1]. Although IPT is crucial and cost effective component of HIV care for adults and children and has been strongly recommended as an international standard of care for over a decade, it has remained highly underutilized [10]. Regular screening for TB disease among PLHIV is a standard of care and a critical component of HIV care and treatment because it can be effectively treated
Conclusion: Isoniazid preventive therapy is protective towards progressing to active tuberculosis disease and symptomatic previously treated Tuberculosis (TB) patients are more likely to have confirmed TB disease. There was no significant association between prevalence of tuberculosis, age and gender of the patients
especially when diagnosed early, hence therefore finding and treating people with TB disease and thus interrupting further transmission remains a top global healthy priority [8].
Materials and methods
Study design
This was a retrospective cohort study design conducted in Makadara sub-county, Nairobi, Kenya. Eligible HIV positive participants (with or without use of IPT) were recruited through cluster random sampling, only those who gave consent were enrolled in the study.
Inclusion and exclusion criteria
Patients who were HIV positive, on care, above 15 years, with signs and symptoms of tuberculosis, at one year post IPT, were included in the study upon consent. While patients with IPT and age records not clear, unable to consent, with other samples other than sputum were excluded from the study.
Sputum collection
Good quality spot and morning sputum samples were collected in 50ml sterile conical tubes; the samples were processed according to the standard operating procedures for GeneXpert MTB/RIF assay and culture using BACTEC MGIT 960 machine.
Laboratory methods
Identification of mycobacterium tuberculosis
Good quality sputa [11] and the reagent buffer were mixed according to the standard operating procedure and loaded into the Xpert MTB/RIF assay cartridge and test started on Xpert MTB/RIF assay machine platform[3]. The assay has internal quality controls which serve to verify that lysis of Mycobacterium tuberculosis has occurred, sample preparation is adequate and detect any inhibitor of polymerase chain reaction; this is accomplished by the sample processing control (SPC) [3]. Sample processing control must be positive when the result reads Mycobacterium tuberculosis not detected, while it can be negative or positive when the result is Mycobacterium tuberculosis detected. The system undertakes to measure fluorescence signal, rehydrating the beads and checking stability of the probe and dye. This is accomplished by the probe check control [3]. Upon completion of the test, results were either of the following; Mycobacterium tuberculosis not detected, Mycobacterium tuberculosis detected very Low, Low, Medium or High. In this case the rifampicin resistance can be either detected or not detected. The test results can also be in form of error or invalid, in this case the test must be repeated [3].
Culture of mycobacterium tuberculosis
Sputa were subjected to culture for the presence of Mycobacterium tuberculosis (MTB) on non-radiometric method Mycobacterium Growth Indicator Tube (MGIT) BACTEC 960. This was done according to manufacturer recommendations. Decontamination of the sputa was done using sodium hydroxide solution (40% w/v) combined with 2.9% sodium citrate solution and N-acetyl-L-cystein powder [12,17]. Sterile phosphate buffer was added and the organisms concentrated by centrifugation at 3,000 rpm for 15 minutes. The supernatant was decanted and the sediment suspended with phosphate buffer and inoculated in liquid MGIT media and incubated along with negative control (un-inoculated MGIT media) and positive control (H37Rv ATCC 27294) [12]. The inoculated MGIT tubes were incubated in the
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BACTEC MGIT 960 machine at 37 oC until the instrument flagged them positive. After a maximum of six weeks, the instrument flagged the tubes negative only if there was no growth at 37 oC [13]. Isolates from MGIT 960 were subjected to confirmative identification of MTB using BD MGIT TBc. Positive culture for MTB confirmed diagnosis of active disease [13,14].
Quality control
Un-inoculated Mycobacteria growth indicator tube (MGIT) (negative control), and H37Rv ATCC, 27294(positive control) were processed and included during the run. Purity of bacterial suspensions used was checked by culture on blood agar [15,16].
Statistical analysis
Data was entered and analyzed by SPSS version 20.0 statistical software. Pearson’s Chi-square test was applied to determine the differences in proportion for both groups in IPT status, type of patient and gender against the detection of MTB. Pearson’s Chi-square test was applied to determine the differences in proportion for both groups in IPT status, type of patients and demographics against TB. These results were presented by appropriate tabulations based on the determined variables, odds ratio (OR) with 95% confidence interval (CI) and the corresponding P- values. The threshold for statistical significance was set at P≤ 0.05.
Results
Prevalence of Tuberculosis (TB) in relation to Isoniazid Preventive Therapy (IPT) and patient treatment status
Of the 346 sputum samples subjected to Xpert MTB/RIF assay analysis, 10(6.5%) and 67(35.1%) had Mycobacterium tuberculosis(MTB) detected in IPT and non-IPT patients respectively, (OR 7.835[95% C.I =3.866-15.878]; P=0.0001) (Table 1), on the other hand new and retreatment patients recorded 57(18.2%) and 20(60.6%) detection of MTB respectively,(OR 0.145[95% C.I=0.068-0.308]; P=0.0001) (Table 1). This indicated a significant association between the IPT status of the patient and MTB detection; the non-IPT arm of patients was more prone to TB, than the IPT arm. On the other hand there was a significant association between MTB detection and patient treatment status; retreatment TB patients were more prone to TB disease than the new patients. Further findings revealed that detection of TB was high among the males of age category (20-39), 27(14.1%) from the Non- IPT arm, in the same age category females documented 16(8.4%) TB cases (Table 2). There was no significant association between prevalence of TB and the age or gender of the patients. Study findings also revealed that 145(93.5%) and 124(64.9%) samples were negative for MTB among IPT and Non-IPT patients while 256(81.8%) and 13(39.4%) samples were negative among new and retreatment patients.
Table 1: Mycobacterium tuberculosis results from Xpert MTB/RIF Assay among study patients
Variables
Total (N)
MTB Detected n (%)
MTB Not Detected n (%)
OR (95% CI)
P Value
IPT Status
IPT Patients
155
10 (6.5)
145 (93.5)
7.835 (3.866-15.878)
0.0001
Non-IPT Patients
191
67 (35.1)
124 (64.9)
Patient Treatment Status
New Patients
313
57 (18.2)
256 (81.8)
0.145 (0.068-0.308)
0.0001
RT Patients
33
20 (60.6)
13 (39.4)
Gender
Female
153
30 (19.6)
123 (80.4)
0.758 (0.452-1.271)
0.293
Male
193
47 (24.4)
146 (75.6)
Age(Years)
< 20
34
4 (11.8)
30 (88.2)
20 – 39
191
47 (24.6)
144 (75.4)
0.791 (0.62-2.333)
0.624
40 – 59
103
23 (22.3)
80 (77.7)
0.613 (0.423-3.899)
0.454
60 +
18
3 (16.7)
15 (83.3)
0.696 (0.332-0.78)
0.591
MTB: Mycobacterium Tuberculosis; RT: Retreatment; IPT: Isoniazid Preventive Therapy; OR: Odds Ratio;
CI: Confidence Interval
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MTB DETECTION
Total
IPT Status
Gender
MTB DETECTED
MTB NOT DETECTED
IPT Patients
Male
Age (Years)
60+
1(0.6%)
4 (2.6%)
5
40 – 59
2(1.3%)
19 (12.3%)
21
20 – 39
3(1.9%)
43 (27.7%)
46
< 20
0(0%)
8 (5.2%)
8
Sub-Total
6(3.9%)
74 (47.7%)
80
Female
Age (Years)
60+
1(0.6%)
4 (2.6%)
5
40 – 59
1(0.6%)
22 (14.2%)
23
20 – 39
1(0.6%)
33 (21.3%)
34
< 20
1(0.6%)
12 (7.7%)
13
Sub-Total
4(2.6%)
71 (45.8%)
75
Total
Age (Years)
60+
2(1.3%)
8 (5.2%)
10
40 – 59
3(1.9%)
41 (26.5%)
44
20 – 39
4(2.6%)
76(49%)
80
< 20
1(0.6%)
20(12.9%)
21
Total
10(6.5%)
145 (93.5%)
155
Non IPT patients
Male
Age (Years)
60+
1(0.5%)
3 (1.6%)
4
40 – 59
12(6.3%)
31 (16.2%)
43
20 – 39
27(14.1%)
35 (18.3%)
62
< 20
1(0.5%)
3 (1.6%)
4
Sub-Total
41(21.5%)
72 (37.7%)
113
Female
Age (Years)
60+
0(0%)
4 (2.1%)
4
40 – 59
8(4.2%)
8(4.2%)
16
20 – 39
16(8.4%)
33 (17.3%)
49
< 20
2(1%)
7 (3.7%)
9
Sub-Total
26(13.6%)
52 (27.2%)
78
Total
Age (Years)
60+
1(0.5%)
7( 3.7%)
8
40 – 59
20(10.5%)
39 (20.4%)
59
20 – 39
43(22.5%)
68 (35.6%)
111
< 20
3(1.6%)
10 5.2%)
13
Total
67(35.1%)
124 (64.9%)
191
Total
77
269
346
Table 2: Xpert MTB/RIF Assay Results in relation to IPT status, Gender and Age
IPT: Isoniazid Preventive Therapy; RIF: Rifampicin; MTB: Mycobacterium Tuberculosis
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Discussion
The current study findings indicate that there is significant association between the isoniazid preventive therapy(IPT) status of the patient and likelihood of developing active Tuberculosis disease (TB); the non-IPT arm of patients had a significantly high rate of tuberculosis(TB) cases (35.1%) compared to the IPT arm (6.5%), these study findings confirm with other previous findings that IPT protects against progressing to active TB in the risk populations, among them being people living with HIV. The current study findings were relatively higher than those observed in previous studies in South Africa (15.9%) [18], Zimbabwe (3.0%) [8], Indonesia (Hasan Sadikin hospital) (4.3%) [9] Ethiopia 16.32% [4], (27.8%) [19] (13.4%) [5], (8.8%) [1]. On the other hand the findings were comparable with results from a previous study conducted in Egypt (Al- Hussein university) (36.7 %) [20], but the findings were relatively low than previous study findings in Pakistan 49.46% [21], (98.7) [22].
The difference in the findings can be attributed to low uptake of isoniazid preventive therapy. The study findings further indicated significant difference in the number of TB cases among patient treatment status; retreatment patients had (60.6%) while new patients had (18.2%), there was a significantly high rate of TB cases among the retreatment cases. The current findings confirm with other previous studies that retreatment patients are significantly associated to TB disease. The current study findings are slightly high than those documented in Ethiopia (53.8%) [23], on the other hand these findings are markedly high than previous findings in a study conducted in Benin (6%) [24], this difference may be attributed to lack of patient compliance to TB drugs, treatment interruptions due to either (imprisonment, defaulting) and weak active case finding strategies which allow re-infection of the already cured people, HIV prevalence [23]. Further findings of the current study indicated that a high percentage of male patients of age category 20-39 years had TB (14.1%), further the findings were markedly lower than those recorded in Thailand (43.7%) [25]. On the other hand the study findings were comparable with those recorded in Ethiopia (14.2%) [19].
These finding would be attributed to the fact that in this age category (20-39), people are normally in institutions of learning, which are often crowded increasing transmission of this air borne disease. Also because of peer pressure which is common during this period, engaging in irresponsible behavior like drug abuse coupled with the already depressed immunity due to HIV makes the body vulnerable to TB disease [10]. The health service seeking behavior can also be attributed to the high TB cases in males of this age category (they tend to seek health services only when the condition is serious) and the mobility they exhibit; in African culture males are supposed to fend for the family thus they have to move seeking for menial jobs in the process they are exposed to conditions which predispose them to get TB [26]. 20-39 years is the productive age of an individual, TB disease being chronic will compromise productivity of this population in the sectors they offer their services and thus decrease a country’s gross domestic product which eventually will lead to an unstable economy [10]. In institutions of learning students will drop out because of either stigma from friends and the lecturers or the challenges which come along with the long TB treatment duration, this might lead to a country lacking work force because the productive population will lack the necessary skills because of lack of education, worse more because of stigma treatment defaulting is high and this might lead to increased mortality and morbidity [10]. One important limitation of this study is that it involved participants who consented to be part of the study; the non-participants would not be profiled.
Conclusions
IPT protects against development of active Tuberculosis (TB) disease in eligible patients, who harbor latent TB. Retreatment patients were significantly associated with TB because of either lack of adherence to medications during previous TB treatments or interruptions during treatment which lead to lack of treatment completion. Of the patients infected with the disease a high percentage (14.1%) was male of age 20-39 years and those patients from the non-IPT arm.
Recommendation
Call for intensified efforts towards increasing the uptake of isoniazid preventive therapy in patients who are eligible to curb progressing of latent tuberculosis to active disease, especially in vulnerable population like people living with HIV. Active case finding on index cases should be made routine to avoid re-infections for those already cured. In this case there should be a budget for purposes of tracing the contact cases in their homes. Through the ministry of health friendly health education should be put in place, mostly in social gatherings to inform the population on what is TB, how it is spread, prevented, diagnosed, treated and importance of seeking medical attention earlier to avoid complications and further spread of the disease. This should be done in such a way that the target should be males 20-39 years of age.
Acknowledgement
The authors sincerely thank Central Reference Laboratory, Bahati Comprehensive Care Centre staffs and all those who directly or indirectly contributed to the success of this study.
References
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4. Geremew D, Endalamaw A, Negash M, Eshetie S, Tessema B. The protective effect of isoniazid preventive therapy on tuberculosis incidence among HIV positive patients receiving ART in Ethiopian settings: a meta-analysis. BMC Infectious Diseases. 2019; 19:405.
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S. Challenges and opportunities to prevent tuberculosis in people living with HIV in low-income countries. International Journal of Tuberculosis and Lung Diseases. 2019; 23: 241-251.
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14. Aono A, Hirano K, Hamasaki S. Evaluation of BACTEC MGIT 960 medium for susceptibility testing of Mycobacterium tuberculosis to Pyrazinamide (PZA): Compared with the results of pyrazinamide assay and Kyokuto PZA test. Diagnostic Microbiology and Infectious Diseases. 2002; 44: 347-352.
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International Journal of Sciences:
Basic and Applied Research
(IJSBAR)
ISSN 2307-4531
(Print & Online)
http://gssrr.org/index.php?journal=JournalOfBasicAndApplied
---------------------------------------------------------------------------------------------------------------------------
First Line Anti-Tuberculosis Drug Resistance Among Human Immunodeficiency Virus Infected Patients Attending Maryland Comprehensive Care Centre Mathare 4a Nairobi Kenya Lucy Obonyo Nyang’aua*, Dr. Evans Amukoyeb, Prof. Zipporah Ng’ang’ac aInstitute of Tropical Medicine and Infectious Diseases (ITROMID), Jomo Kenyatta University of Agriculture and Technology (JKUAT), Box 4899-00200 Nairobi, Kenya. bCentre for Respiratory Diseases Research, Nairobi, Kenya (CRDR), Kenya Medical Research Institute.
cJomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi, Kenya czipnganga@gmail.com
alucynyangau@yahoo.com bevansamukoye@gmail.com Abstract TB is a major cause of death among people living with human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS). Multi drug resistant tuberculosis (MDR-TB) accounts for up to 14 % of all these T.B cases. İn this study; Sputa from patients with bacteriologically confirmed pulmonary tuberculosis (PTB) were cultured on Mycobacterium Growth Indicator Tube (MGIT) media. Strains of MTB complex from MGIT were subjected to drug susceptibility testing for isoniazid, Rifampicin, Streptomycin, and Ethambutol using the proportional method on (MGIT). The CD4 cell counts were obtained from the Maryland laboratory registers. The results show that the Median CD4 count was 286 . A total of 51 (37.0%) patients had CD4 count (200. ------------------------------------------------------------------------ * Corresponding author. E-mail address: lucynyangau@yahoo.com.
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International Journal of Sciences: Basic and Applied Research (IJSBAR) (2014) Volume 15, No 1, pp 661-668
Patientswith CD4 count 200 were fully sensitive to all anti-tuberculosis drugs tested. Resistance patterns among patients with CD4 count of200 the resistance pattern was isoniazid 10 (11.5%), ethambutol 7 (8.0%), rifampicin 4 (4.6%), and streptomycin 4 (4.6%) (Table 1). Three (5.9%), and 3 (3.4%) isolates from patients with CD4 count 200 respectively, had multidrug resistant TB (MDR TB) defined as resistant to both isoniazid and rifampicin. Our study concluded that there were no significant associations between the various resistant patterns and levels of CD4.
Keywords: Tuberculosis; First Line Drug Resistance; HIV; Kenya; Multi drug resistant tuberculosis
1. Introduction
TB is a major cause of death among people living with the human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS) [13]. Multi drug resistant tuberculosis (MDR-TB) accounts for up to 14 % of all T.B cases, with TB being the leading cause of death among people living with H.I.V/A.I.D.S [7]. Although there have been several well documented outbreaks of MDR-TB in institutional settings, little evidence indicates that H.I.V is associated with MDR-TB among the general population [10-17]. Most studies conducted in the general population have very little power, are not methodologically rigorous, and have many potential confounders [2]. The treatment of tuberculosis is becoming increasingly more complex and difficult to treat in H.I.V infected patients due to the rising incidence of MDR-TB [15-19]. As immune suppression progresses, disseminated and extra-pulmonary forms of T.B become more frequent [4]. Occurrence of drug resistant T.B does not correlate with the cluster of differentiation (CD4) counts, although TB is more commonly seen in severely immune-compromised patients [5].
Several recent studies showed that resistance to additional first-line drugs other than isoniazid and rifampicin, were independently associated with unfavorable treatment outcomes [7]. The risk of developing tuberculosis after an infectious contact has been estimated to be 5-15% / year in H.I.V infected patients [4]. H.I.V induced immune-suppression modifies the clinical presentation of T.B. In the early stages of immune- suppression, most tuberculosis patients with infection present in the same fashion as others with tuberculosis not infected with H.I.V [1]. As immune suppression progresses, disseminated and extra-pulmonary forms of tuberculosis become more frequent [1]. The treatment of tuberculosis is also becoming increasingly more complex and difficult in H.I.V infected patients due to the rising incidence of MDR-TB. MDR-TB and extremely drug resistant tuberculosis (XDR-TB) are associated with very high mortality rates and their transmission both in community and health care settings remains an ongoing challenge in resource limited settings and in countries with high rates of HIV co-infection [18].
The true magnitude of drug resistance is not well described [8]. There are several limitations to adequate assessment of this problem, especially in developing countries. In many areas there are few facilities for culture of mycobacterium tuberculosis and where they are antimicrobial susceptibility testing is not performed [13]. 662
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Standardized laboratory methodologies have not been followed uniformly and in some surveys small or unrepresentative populations have been sampled, thus difficult to accurately monitor trends [13].
This study was undertaken to determine M. tuberculosis resistance patterns against first-line drugs with respect to CD4 counts among patients attending Maryland comprehensive care centre.
2. Materials and Methods
2.1 Setting
The study was conducted in Mathare 4A, Nairobi the capital city of Kenya. The population of Mathare is nearly 180,000 and is steadily growing due to rural /urban migration. This poses a lot of problems socially and economically. A significant proportion of the residents of Mathare live below the poverty line, with high population densities. Mathare valley is approximately 6km to the north east of Nairobi’s central business district. It is bordered by Thika road to the north and Juja road to the south. The study was cross sectional, eligible patients (new and retreatment) randomly sampled during the intake period, who gave consent were enrolled for the study. The intake period was between April and November 2013.
2.2 Specimen Collection and Transport
A spot sample and one early morning sputum were collected in sterile 50 milliliters falcon tubes. Genexpert was done on the spot sample to confirm T.B diagnosis of suspected patients. Second samples from the MTB positive patients were then transported weekly by smith-line courier service, to central reference laboratory (CRL) for culture and drug susceptibility testing (DST). The CRL is located within the centre for respiratory diseases research, Kenya Medical Research Institute (CRDR-KEMRI) at Kenyatta National Hospital.
2.3 Culture of M. Tuberculosis and Drug Susceptibility Testing
Sputum culture and drug susceptibility testing (DST) for M. tuberculosis was conducted in the central reference laboratory. Primary culture of M. tuberculosis was performed using non radiometric method Mycobacterium growth indicator tube (MGIT) 960. The sputa were decontaminated with NAOH solution (40%w/v) combined with 2.9% sodium citrate solution and N-acetyl -L-cystein (NALC) powder. Sterile phosphate buffer was added and the organisms concentrated by centrifugation at 3,000rpm for 15 minutes. The supernatant was decanted and the sediment suspended with phosphate buffer and inoculated in liquid MGIT media and incubated along with a growth control and an external control H37Rv at 37 degrees centigrade in BACTEC 960 systems (BD Diagnostic Systems, Sparks, MD, USA). The MGIT tubes were incubated until the instrument flagged them positive. After a maximum of six weeks, the instrument flagged the tubes negative if there was no growth at 37 degrees centigrade. A positive culture of M. tuberculosis confirmed the diagnosis of active disease.
2.4 Sensitivity Testing of M. tuberculosis
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All culture positive tubes were tested for contamination before sensitivity tests using the standard method used in Kenya for drug susceptibility BACTEC MGIT 960 liquid culture system (Becton Dickson Company Sparks, MD, USA. A total of four first line drugs collectively referred to as SIRE Streptomycin (S)-1.00ug/ml; Isoniazid (H)-0.10ug/ml; Rifampicin (R)-1.00ug/ml and Ethambutol (E)-5.00ug/ml were tested for sensitivity. A control tube was matched with all the isolates tested. An external control of H37Rv was also set in all culturing and sensitivity testing processes. All readings were performed inside the machine and results were printed as susceptible, resistant or indeterminate.
3. Ethical Approval
The research proposal was approved and ethically cleared by the national ethical review committee (ERC) and Scientific Steering Committee (SSC) at the Kenya Medical Research Institute (KEMRI). Each patient who consented to enroll was required to complete an informed consent form.
4. Results
Of the 138 patients who had valid results for analysis, 79(57.2%) were male and 59(42.8%) were female. Analysis of CD4 count among the patients revealed that median CD4 count was 286 ranging between 2 and 859. A classification of CD4 was done using a cut-off of 200. A total of 51 (37.0%) patients had low CD4 count (200.
In this study, 42 (82.4%) of patients with CD4 count 200 were fully sensitive to all anti-tuberculosis drugs tested. Resistance patterns among patients with CD4 count of200 the resistance pattern was isoniazid 10 (11.5%), ethambutol 7 (8.0%), rifampicin 4 (4.6%), and streptomycin 4 (4.6%) (Table 1; table 1 is at the end of the paper). Three (5.9%), and 3 (3.4%) isolates from patients with CD4 count 200 respectively, had multidrug resistant TB (MDR TB) defined as resistant to at least both isoniazid and rifampicin. There were no significant associations between the various resistant patterns and levels of CD4
5. Discussion
HIV pandemic has changed tuberculosis from an endemic disease to a worldwide epidemic (WHO 2011). The risk of developing TB after an infectious contact has been estimated to be 5-15% /year in HIV infected patients compared to 5-10% during the lifetime of non HIV infected patients [3]. The risk of drug resistant TB is higher among those infected with H.I.V this is because of decreased immunity. T.B drug resistance is usually related to non adherence to therapy, severe immunodeficiency, diarrhea, and concurrent antifungal therapy [6]. Worldwide incidence of T.B is increasing, particularly in areas where H.I.V is prevalent [14].
The effect of CD4 count on T.B drug resistance is varied in various studies and it is often difficult to compare data because of relatively small patient numbers in previous studies and few documented data [9]. In the present study, Three (5.9%), and 3 (3.4%) isolates from patients with CD4 count 200 respectively, had multidrug resistant TB (MDR TB) defined as resistant to at least both isoniazid and rifampicin. The median CD4 count was 286 ranging between 2 and 859. This contrasts with a study carried out in South Africa’s Tugela Ferry from 2005 to 2007 and found that of the 272 MDR-TB and 382 XDR-TB cases, 90% and 98% were co-infected with HIV with median CD4 counts of 41 cells/μl and 36 cells/μl.
In another study carried out by Gandhi et al. in Kwazulu Natal South Africa, of the 1,539 patients tested, 542 (35%) had culture-positive TB, with MDR-TB in 221 (41%) of those with culture-positive TB. Of the MDR-TB cases, 53 (24%) had XDR-TB, of which all of the 44 patients who were tested for HIV were infected with HIV, with a median CD4 count of 63 cells/μl. The CD4 count does not predict the occurrence of drug resistant TB, because there were no significant associations between the various resistant patterns and levels of CD4.
Some studies show that CD4 count does not have significant effects on MDR TB development based on there being no difference found in sputum cultures of H.I.V positive and negative individuals with MDR TB [16-12]. Instead, these studies propose that MDR TB is greatly impacted by previous antibiotic treatment, with individuals who have had previous treatment being five times more likely to develop MDR TB [11].
6. Study limitations
This study was conducted over a limited period of seven months and survey was conducted only in Mathare. Similar studies should be undertaken in other regions.
7. Conclusion
The effects of CD4 count on T.B drug resistance are varied in various studies and it is often difficult to compare data because of relatively small patient numbers in previous studies. CD4 count does not have a direct effect in development of T.B drug resistance among the immune-compromised patients. Immediate detection of drug resistance cases through rapid identification and DST is a key element and this benefits interruption of disease transmission. Rapid diagnosis of drug resistant T.B will have several benefits: earlier treatment of patients which will save lives and reducing the time spent on ineffective patient treatment. Diagnosis of MDR-TB and XDR-T.B now requires the scaling up of culture and drug susceptibility testing capacity, which is limited in disease endemic countries where H.I.V rates are high, and the expanded use of technology assays for rapid determination of resistance.
Acknowledgement
We thank the Maryland comprehensive care center, particularly the hospital laboratory staff for their support throughout the study period. We also in a special way thank the patients for accepting to participate in the study and also for their patience throughout the study.
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International Journal of Sciences: Basic and Applied Research (IJSBAR) (2014) Volume 15, No 1, pp 661-668
Table 1: Presents Patterns of resistance to first line anti-tuberculosis drugs in relation to CD4 levels
Antibiotic
Total (n=138)
CD4=200 (n=87)
OR
95% CI
p value
N
%
N
%
N
%
Lower
Upper
Sensitivity to all
112
81.2%
42
82.4%
70
80.5%
1.13
0.46
2.77
0.784
Any resistance
Isoniazid (H)
16
11.6%
6
11.8%
10
11.5%
1.03
0.35
3.01
0.962
Rifampicin (R)
9
6.5%
5
9.8%
4
4.6%
2.26
0.58
8.82
0.290
Ethambutol (E)
11
8.0%
4
7.8%
7
8.0%
0.97
0.27
3.50
1.000
Streptomycin (S)
7
5.1%
3
5.9%
4
4.6%
1.30
0.28
6.04
0.709
Monoresistance TB
Isoniazid (H)
6
4.3%
1
2.0%
5
5.7%
0.33
0.04
2.89
0.413
Rifampicin (R)
2
1.4%
2
3.9%
0
0.0%
UD
UD
UD
0.135
Ethambutol (E)
4
2.9%
0
0.0%
4
4.6%
UD
UD
UD
0.296
Streptomycin (S)
3
2.2%
1
2.0%
2
2.3%
0.85
0.08
9.61
1.000
Multi drug resistance TB (MDR TB)
H+R
2
1.4%
1
2.0%
1
1.1%
1.72
0.11
28.11
1.000
H+R+E
2
1.4%
1
2.0%
1
1.1%
1.72
0.11
28.11
1.000
H+R+S
1
0.7%
0
0.0%
1
1.1%
UD
UD
UD
1.000
H+R+E+S
1
0.7%
1
2.0%
0
0.0%
UD
UD
UD
0.370
Total MDR TB
6
4.3%
3
5.9%
3
3.4%
1.75
0.34
9.01
0.670
Other resistant Patterns
H+E
2
1.4%
1
2.0%
1
1.1%
1.72
0.11
28.11
1.000
H+S
1
0.7%
0
0.0%
1
1.1%
UD
UD
UD
1.000
H+E+S
1
0.7%
1
2.0%
0
0.0%
UD
UD
UD
0.370
R+E
1
0.7%
0
0.0%
1
1.1%
UD
UD
UD
1.000
E+S
0
0.0%
0
0.0%
0
0.0%
R+S
0
0.0%
0
0.0%
0
0.0%
R+E+S
0
0.0%
0
0.0%
0
0.0%
Table 1: Patterns of resistance to first line anti-tuberculosis drugs in relation to CD4 levels
UD-Undefined
L.O. Nyang’au et al.
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International Journal of Sciences: Basic and Applied Research (IJSBAR) (2014) Volume 15, No 1, pp 661-668
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