1. Predictors of Multidrug Resistant Tuberculosis Among Adult Tuberculosis Patients in Saint Peter Hospital, Addis Ababa, Ethiopia: Case control study By : Ermias D, Muluken Dessalegn
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2. Results and Discussions Conclusions and Recommandations
PLAN OF PRESENTATION 1
Background 2
Methodology 3
Results and Discussions 4
Conclusions and Recommandations
Conclusion and Recommandation
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3. 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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4. 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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5. 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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6. 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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7. 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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8. Data collection and analysis
Measurement tools and Data Collection
Statistical Analysis
Data was entered, coded and cleaned by Epi Info
Analysis by SPSS V-20
The analysis had two stages
Bivariate analysis -(cross tabs, COR)
Multivaraite:logistic Regression
A significant (p < 0.05 and OR: 95% Cis)
A pretested structured questionnaire
Study subjects selection: by reviewing medical charts
As safety precautions to prevent the risk of TB,
data collectors used the N-95 respiratory mask
Patients wear surgical mask
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9. 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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10. Table 1: Bivariate analysis of variables
Characteristics
MDRTB
Non MDR TB
COR,95%CI
p- value
Sex
Male
49(47.6%)
64(62.1%) 1
0.036
Female
54(52.4%)
39(37.9%)
1.808(1.04,3.15)
Occupation status
Employed
14(13.6%)
40(38.8%)
0.001
Not employed
89(86.4%)
63(61.2%)
4.036(2.03,8.04)
Monthly Income(b
≤500
42(40.8%)
69(67.0%)
0.418(0.18,.987)
0.047
28(27.2%)
1.375(0.51,3.74)
17(16.5%)
9(8.7%)
1.30(0.43,3.96)
≥2000
16(15.5%)
11(10.7%)
Residence AA
80(77.7%)
61(59.2%)
2.39(1.30,4.40)
0.005
Out of AA
23(22.3%)
History of pervious TB
Yes
96 (93.2%)
25 (24.3%)
42.79(17.57,104.17)
0.00 No
7(6.8%)
78(75.7%
HIV status
19(18.4%)
48(46.6%)
0.26(0.14,0.49)
84(81.6%)
55(53.4%)
episodes of pervious TB
One
34(33.0%)
90(87.4%)
Two and more
13(12.6%)
(6.89,28.63)
0.0047
Type of TB site
Pulmonary
92(93.9%)
21(80.8%)
3.651(1.017,13.104)
Extra pulmonary
6(6.1%)
5(19.2%)
0.045
Treatment category
Category I
48(46.6%
96(94.1%
Category II
Category III
Category IV
5(4.9%)
2(2.0%)
3(2.9%)
1(1.0%)
39.00(9.03,168.37)
3.33(0.76,14.54)
2.82(1.27,175.44)
Ever Drug interrupted
24(23.3%)
10(9.7%)
2.82(1.27,6.26)
0.011
79(76.7%)
93(90.3%)
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11. Table 2: Multivariate Analysis
Variables
Factors
Cases
Controls
COR(95%CI)
AOR(95%CI)
Sex
Male
49(47.6%)
64(62.1%) 1
Female
54(52.4%)
39(37.9%)
1.808(1.04,3.15)
3.05(0.94,9.84)
History of pervious TB
Yes
96(93.2%)
25(24.3%)
42.79(17.57,10.17)
20.35(5.13,80.58) No
7(6.8%)
78(75.7%)
Occupational status
Employed
14(13.6%)
40(38.8%)
Not employed
89(86.4%)
63(61.2%)
4.04(2.03,8.04)
0.47(0.12,1.92)
Income
≤500
42(40.8%)
69(67.0%)
0.42(0.18,0.99)
1.2(0.28,5.22)
28(27.2%)
1.38(0.51,3.74)
0.56(.09,3.36)
17(16.5%)
9(8.7%)
1.30(0.43,3.96)
1.37(0.20,9.19)
≥2000
16(15.5%)
11(10.7%)
Residence AA
80(77.7%)
61(59.2%)
Out of AA
23(22.3%)
2.39(1.30,4.40)
2.04(0.65,6.38)
HIV status
19(18.4%)
48(46.6%)
0.26(.138,.487)
0.065(0.01,0.28)
84(81.6%)
55(53.4%)
Episodes of TB
one
34(33.0%)
90(87.4%)
More than one
9(67.0%)
13(12.6%)
14.06(6.89,28.63)
15.67(4.18,58.71)
Type of TB site
Pulmonary
92(93.9%)
21(80.8%)
3.651(1.017,13.10)
6.83(1.16,40.17)
Extra pulmonary TB
6(6.1%)
5(19.2%)
Category of treatment
category I
96(94.1%)
Category II
2(2.0%)
39.0(9.03,168.37)
16.14(2.40,108.56)
Category III
5(4.9%)
3(2.9%)
3.33(0.76,14.54)
2.49(0.29,21.38)
Category IV
1(1.0%)
22.00(2.76,17.4)
7.77(0.55,109.3)
Drug Interrupted for at least once
24(23.3)
10(9.7%)
2.82(1.27,6.26)
0.25(0.058,1.11)
79(76.7%)
93(90.3%)
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12. 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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13. 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, )
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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14. 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
The other explanation might be associated with diagnostic difficulties.
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15. 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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