Predictors Of Multidrug Resistant Tuberculosis Addis Ababa, Ethiopia

Report
Predictors of Multidrug Resistant Tuberculosis Among Adult
Tuberculosis Patients in Saint Peter Hospital, Addis Ababa,
Ethiopia: Case control study
By : Ermias D, Muluken Dessalegn
Amref Health Africa
PLAN OF PRESENTATION
Background
Methodology
Results and
Discussions
Conclusions and
Recommandation
s
Conclusio
n and
Recomma
ndation
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BACKGROUND
• Multidrug resistant TB (MDR-TB ) is caused by bacteria that are
resistant to the most effective anti-TB drugs (Isoniazid and
Rifampicin)
• According WHO(2013) estimates
 Half million new MDR-TB cases in the world emerge every year
 Only 3% get treatment
 150,000 persons die every year
 Ethiopia is – 7th among 22 high TB Burden countries
 15th among 27 MDR-TB
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Cont……..
• MDR-TB-is a major threat for successful TB control in Ethiopia and
others
• Very expensive
• Treatment requires prolonged chemotherapy using second line
• Drugs toxicity and less effective
• Did not receive major attention ( though burden cases are high )
• Understanding factors for MDR-TB is important for prevention and
control strategy
• Therefore, the aim of this study to look at the predictors of MDR TB
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Methodology
Study design, area, and Population
Area: St. Peter Hospital
 The only largest TB referral center in Ethiopia
Design: Hospital based unmatched case-control study design
• Conducted from Feb- March 2014
Population : All patients who were clinically diagnosed as TB at St. Peter
hospital
Cases (MDR-TB) : Tuberculosis patients with culture-proved mycobacterium
tuberculosis resistant at least to both Isoniazid (INH) and Rifampicin (RIF)
Controls (Non-MDR-TB): Tuberculosis patients with smear positive
mycobacterium tuberculosis who turned smear negative to the recent result
after 2nd, 5th,or 6th month of treatment course.
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Sample size determination
Calculated by EPI Info using the assumption for case control study design
 Confidence interval 95% , Case to controls ration 1, Power -80%,
 Percentage HIV cases among Non MDR-TB:26%
 Odds ratio worth detecting :2.5 , and assuming a non-response rate of 10%
 Total sample size :206( Cases=103 and control=103)
Ethical clearance
•
Approved by DMU and GAMBY College of medical sciences IRB
•
Ethical clearance -St. Peter hospital research center
•
Informed verbal consent
•
Anonymous, and Confidentiality was maintained
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Study variables





Socio-demographic:

Age, Sex, Religion, Marital status, Educational status
Environmental factors

type of living houses, use of tape water, social support, prison
history, and use of separated cocking room
Behavioral variables

Smoking, Alcohol use, chat chewing, history of drug use other
substance use type
TB treatment/ history related factors

History of Tb, TB site, type of TB and DOTS follow up, Family
history of TB and MDR-TB, Treatment category
Co–morbidity:

HIV Staus
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Data collection and analysis
Measurement tools and
Data Collection
Statistical Analysis
•
 A pretested structured
questionnaire
• Study subjects selection: by
•
Data was entered, coded and cleaned by
Epi Info
•
Analysis by SPSS V-20
•
The analysis had two stages
reviewing medical charts
 Bivariate analysis -(cross tabs, COR)
As safety precautions to prevent
 Multivaraite:logistic Regression
the risk of TB,
•
A significant (p < 0.05 and OR: 95% Cis)
 data collectors used the N-95
respiratory mask
 Patients wear surgical mask
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RESULT & DISCUSSION
Socio-demographic factors
 Sex : 52% cases and 38 % controls were females
 Age: The mean of age among cases: 30.5 (±9.26) and
controls 34.73(±11.28) years
 Income: 41% cases and 67 % controls earn less than or
equal to 500 ETB(25$)
 Employment: About 86% of cases and 61% of controls
were unemployed
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Table 1: Bivariate analysis of variables
Characteristics
Sex
Male
Female
Occupation
Employed
status
Not employed
Monthly
≤500
Income(b
501-1000
1001-2000
≥2000
Residence
AA
Out of AA
History of
Yes
pervious TB
No
HIV status
Yes
No
episodes of
One
pervious TB
Two and more
MDRTB
49(47.6%)
54(52.4%)
14(13.6%)
89(86.4%)
42(40.8%)
28(27.2%)
17(16.5%)
16(15.5%)
80(77.7%)
23(22.3%)
96 (93.2%)
7(6.8%)
19(18.4%)
84(81.6%)
34(33.0%)
69(67.0%)
Non MDR TB
64(62.1%)
39(37.9%)
40(38.8%)
63(61.2%)
69(67.0%)
14(13.6%)
9(8.7%)
11(10.7%)
61(59.2%)
42(40.8%)
25 (24.3%)
78(75.7%
48(46.6%)
55(53.4%)
90(87.4%)
13(12.6%)
COR,95%CI
1
1.808(1.04,3.15)
1
4.036(2.03,8.04)
0.418(0.18,.987)
1.375(0.51,3.74)
1.30(0.43,3.96)
1
2.39(1.30,4.40)
1
42.79(17.57,104.17)
1
0.26(0.14,0.49)
1
1
14.0573(6.89,28.63)
Pulmonary
92(93.9%)
21(80.8%)
3.651(1.017,13.104)
Extra pulmonary
6(6.1%)
5(19.2%)
1
Treatment
category
Category I
Category II
Category III
Category IV
48(46.6%
39(37.9%)
5(4.9%)
11(10.7%)
96(94.1%
2(2.0%)
3(2.9%)
1(1.0%)
1
39.00(9.03,168.37)
3.33(0.76,14.54)
2.82(1.27,175.44)
0.045
Ever Drug
interrupted
Yes
No
24(23.3%)
79(76.7%)
10(9.7%)
93(90.3%)
2.82(1.27,6.26)
1
0.011
Type of TB site
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p- value
0.036
0.001
0.047
0.005
0.00
0.00
0.0047
Table 2: Multivariate Analysis
Variables
Sex
History of pervious
TB
Occupational status
Income
Residence
HIV status
Episodes of TB
Type of TB site
Category of
treatment
Drug Interrupted for
at least once
Factors
Male
Female
Yes
No
Employed
Not employed
≤500
501-1000
1001-2000
≥2000
AA
Out of AA
Yes
No
one
More than one
Pulmonary
Extra pulmonary
TB
category I
Category II
Category III
Category IV
Yes
No
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Cases
49(47.6%)
54(52.4%)
96(93.2%)
7(6.8%)
14(13.6%)
89(86.4%)
42(40.8%)
28(27.2%)
17(16.5%)
16(15.5%)
80(77.7%)
23(22.3%)
19(18.4%)
84(81.6%)
34(33.0%)
9(67.0%)
92(93.9%)
6(6.1%)
Controls
64(62.1%)
39(37.9%)
25(24.3%)
78(75.7%)
40(38.8%)
63(61.2%)
69(67.0%)
14(13.6%)
9(8.7%)
11(10.7%)
61(59.2%)
42(40.8%)
48(46.6%)
55(53.4%)
90(87.4%)
13(12.6%)
21(80.8%)
5(19.2%)
COR(95%CI)
1
1.808(1.04,3.15)
42.79(17.57,10.17)
1
1
4.04(2.03,8.04)
0.42(0.18,0.99)
1.38(0.51,3.74)
1.30(0.43,3.96)
1
1
2.39(1.30,4.40)
0.26(.138,.487)
1
1
14.06(6.89,28.63)
3.651(1.017,13.10)
1
AOR(95%CI)
1
3.05(0.94,9.84)
20.35(5.13,80.58)
1
1
0.47(0.12,1.92)
1.2(0.28,5.22)
0.56(.09,3.36)
1.37(0.20,9.19)
1
1
2.04(0.65,6.38)
0.065(0.01,0.28)
1
1
15.67(4.18,58.71)
6.83(1.16,40.17)
1
48(46.6%)
39(37.9%)
5(4.9%)
11(10.7%)
24(23.3)
79(76.7%)
96(94.1%)
2(2.0%)
3(2.9%)
1(1.0%)
10(9.7%)
93(90.3%)
1
39.0(9.03,168.37)
3.33(0.76,14.54)
22.00(2.76,17.4)
2.82(1.27,6.26)
1
1
16.14(2.40,108.56)
2.49(0.29,21.38)
7.77(0.55,109.3)
0.25(0.058,1.11)
1
11
Result & Discussion cont ….
• Previous history of tuberculosis and TB episode
 The odds of MDR-TB were higher among those who had history of previous TB
and more than one episode (AOR :20 &15, respectively)
This might be due to:
 the previous treatment outcome, default, treatment failure, or relapse
 or the patient may have had MDR-TB initially
• Consistent with
 Study done in Uganda, South Africa also showed that multiple/previous
TB episodes and treatment failure were significantly associated with
MDR-TB
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Result & Discussion cont ….
Treatment category
 Individuals who had category II treatment was higher among
MDR TB than Non-MDR-TB (AOR95%CI=16 (2.40,
108.56)
 This might be related to:
• Patients who fall to this group are individuals who had previous TB
treatment, relapse ,defaulters, or treatment failures
• Already they took first line combination of anti TB drug except
streptomycin on previous TB infection and they might have already
had MDR-TB at initiation of the category II regimen
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Result & Discussion cont ….
Type of TB
•
The odds of MDR-TB was 6 times higher among those who have
pulmonary TB than extra pulmonary
• This might be due to:
 Smear-positive pulmonary TB individuals have a high bacterial load and
may not respond to the treatment within a short period of time
 Or
 Might be associated with diagnostic difficulties
 Extra pulmonary MDR-TB the bacterial load is lower and difficult
for definite diagnosis comparing to pulmonary MDR-TB
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Conclusion and Recommendations
• History of previous TB, TB episode more than one time,
pulmonary type of TB, individuals who were treated with the
Category II regimen were predictors for MDR-TB
• The measures in controlling MDR-TB should give emphasize
those predictor factors
• Improving the diagnostic laboratory centers
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