Infection rates and correlates of Non-Tuberculous Mycobacteria ...

Prime Journal of Social Science (PJSS) ISSN: 2315-5051. Vol. 4(7), pp. 1128-1134, July 31st, 2015 www.primejournal.org/PJSS © Prime Journals

Full Length Research

Infection rates and correlates of Non-Tuberculous Mycobacteria among Tuberculosis retreatment cases In Kenya Limo Jacqueline*,2,3, Bii Christine4, Musa Otieno Ngayo4, Galgalo Tura2, Mutua Daniel5, Nkirote Rose1, and Nyerere Andrew3 *National Tuberculosis Reference Laboratory, (NTRL), Ministry of Health, Nairobi Kenya. Kenyatta National Hospital Complex off Ngong Road, P.O. Box 20750 - 00200, Nairobi, Kenya. Email: [email protected] 1 National Tuberculosis Reference Laboratory, (NTRL), Ministry of Health, Nairobi, Kenya. 2 Field Epidemiology Laboratory Training Programme, Ministry of Health, Nairobi, Kenya. 3 Institute of Tropical Medicine and Infectious Diseases, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya 4 Centre of Microbiology and Research, Kenya Medical Research Institute, Nairobi, Kenya 5 Hain Life science, Nairobi, Kenya Accepted 22nd July, 2015 Kenya is ranked among top African countries with high TB cases coupled with high HIV/AIDS burden. The TB problem has been compounded by the emergence of non-Tuberculous mycobacteria (NTM) as opportunistic infections in the HIV/AIDS patients, and their treatment is not directly analogous to that of TB. This cross sectional study characterized and identified the correlates of NTM among TB retreatment patients attending NTRL. The TB retreatment patients with BACTEC MGIT culture positive samples were consented and enrolled into the study. The patients’ health record and structured interviews were used to gather information associated with NTM infection.The median (IQR) age of the 210 TB retreatment patients’ enrolled was 35 (28 75) years. Majority 53.8% were females, 32.2% were aged ≥40 years, 18% were smokers, 22% HIV positive. About 37% had respiratory symptoms while 36.2% had animal contact. Eighty nine 89 (42.4%) of them were infected with NTM with M. intracellulare 47/75 (67%) being the most responsible for NTM infection. Female gender OR 1.8 (95%CI 1.1 to 3.1), Eastern region OR 2.2 (95%CI 1.1 to 4.6), Central region OR 2.3 (95%CI 1.1 to 5.1), animal contact OR 1.7 (95%CI 1.1 to 2.7) and livestock keeping OR 1.6 (95%CI 1.06 to 2.6) were associated with NTM infection.Infection due to NTM among TB retreatment cases is high in Kenya and missed diagnosis jeopardizes proper management. Involvement of NTM during management of clinical pulmonary TB is important in planning for prevention and treatment of TB in Kenya especially among patients with animal contacts. Key words: Infection rates, Non-Tuberculous Mycobacteria, HIV/AIDS, Kenya

INTRODUCTION Mycobacterial infections are among the leading causes of disease in humans. In developing countries, the high incidence of tuberculosis overshadows the occurrence of non-tuberculous mycobacterial (NTM) infections. This trend is however fast changing. The incidence of NTM infections is increasing as a result of the growing number of immunodeficient patients (Ferreira et al., 2002), the use of contaminated endoscopic medical devices, and cosmetic procedures (Duarte et al., 2009).Pulmonary disease caused by NTM has gained increased attention

globally with increased incidences being reported (Thomson, 2010; Hoefslootet al., 2013). By 2014 estimated prevalence rate of pulmonary disease caused by NTM was 33–65 per 100,000 (Morimoto et al., 2014). Globally, patients with acid-fast bacilli (AFB) positive specimensare generally presumed to be infected with Mycobacterium tuberculosis (MTB) and are treated with anti-tuberculosis agents and some, placed in isolation rooms. Increased isolation of NTM causing mycobacterial diseases implies that more patients with AFB positive

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samples have received inappropriate or unnecessary empirical anti-tuberculous treatment (Hsueh et al., 2006). Due to this inappropriate treatment and high treatment failure (Zheng and Fanta, 2013), the mortality of NTM caused lung disease is on the increased (Itoet al., 2012). Therefore, efficient detection and regular monitoring of NTM is crucial. In Kenya, information on the extent of the burden of pulmonary disease from NTM is lacking due to limitations in tools for mycobacterial species identification (Muwongeet al., 2011). The ubiquitous distribution of NTM contributes to the difficulties in interpreting positive culture results. Further, it is not mandatory to report NTM disease to the Kenyan government thus, knowledge about the epidemiology and distribution of NTM causing pulmonary disease is limited in Kenya. We evaluated the contribution and the correlates of NTM among TB retreatment patients in Kenya attending the National Tuberculosis Reference Laboratory, (NTRL) located in Nairobi Kenya. METHODOLOGY Study design and sample collection This cross sectional study was done among samples from consenting TB retreatment patients received at the NTRL in Nairobi Kenya. This is a Kenyan government owned facility performing TB culture and drug susceptibility test. The facility is mandated with the development of national policy in relation to TB laboratory protocols/procedures, quality assurance planning and coordination of TB diagnostic in the satellite sites country wide. The NTRL laboratory also offers specialized TB testing with modern sensitive and specific techniques such as the BACTEC-MGIT 960TM (Becton Dickinson Diagnostic Instrument Systems) machine and Hain molecular TB/MDR TB test. Samples from TB retreatment patients are received from all over the country. Initial authority was obtained from the County TB/Leprosy coordinators (CTLCs)of various TB treatment sites where informed consent to participate in this study and samples were received. Patients meeting the inclusion c criteria; consenting age (above 18 years); currently receiving TB retreatment and, patients whose samples had positive growth from the BACTEC MGIT were consecutively selected until the sample size was reached. A total of 210 TB retreatment patients samples were randomly selected and enrolled into the study between October 2014 and March 2015. This study was approved by Ethical Review Committee of Jaramogi Oginga Odinga Teaching and Referral Hospital. This research adhered to the STROBE guidelines for observational studies as outlined at: http://www.strobestatement.org. Patients’ demographic data Patient health records were reviewed to gather social demographic information including age, gender,

residence, occupation, education level, alcohol intake, any other respiratory symptom, HIV status, CD4 count and Body mass index (BMI). Further, a case investigation form was used to collect information on history of diabetes mellitus, history of smoking, history of animal contact, livestock keeping and farming. Sample collection and transportation At least 2 ml of three sputum specimens (spot, early morning, spot) were collected from 210 participants with suspected TB under the supervision of trained and competent medical staff (Wolinsky, 1992). The patients were requested to cough so that expectoration would come from as deep down the chest as possible, and spit into a sterile 50 ml blue cap tubes. The samples were refrigerated at 4℃, awaiting transportation in cool boxes to National Tuberculosis Reference Laboratory. The samples were processed within 7 days of collection in order to minimize loss of viability of the mycobacteria. Sample pre-processing For respiratory samples, N-acetyl-L-cysteine (NALC)NaOH solution (5% NaOH+ 0.5% NALC) was added to the sample to liquefy and decontaminate the mucous sputum. The solution was centrifuged at 3,000 ×g for 18 minutes at 4℃, and the supernatant was discarded. Phosphate buffered saline 1 mL was added after the sediment had been vortexed. Microscopic examination of specimens Microscopic examination for detection of Mycobacterium was done after staining specimens with carbol-fuchsin using the ZN method (Ebersole, 1992). A TB suspect was considered to be ZN smear positive if at least one of the three specimens showed pink/red rod shaped bacteria on microscopy. Mycobacterial culture The processed samples (0.2 mL) were used to inoculate 3% Ogawa medium (Eiken, Tokyo, Japan) and were cultured for 8 weeks in an incubator at 35-37℃ under 510% CO2. Samples (0.5 mL each) were also used to inoculate MGIT medium (Becton Dickinson, Sparks, MD, USA) after mixing with PANTA/supplement according to the manufacturer's protocol. The tubes were then incubated for 6 weeks in the BACTEC MGIT 960 system (Becton Dickinson). If fluorescence was detected in the tube, the test was considered positive. The mycobacterial isolates were identified as M. tuberculosis complex or species of NTM using Hain’s GenoType® Mycobacterium CM and GenoType® Mycobacterium AS Molecular Genetic Assays, following manufacturer’s instructions. NTM identification Cultures with positive growth on the BACTEC MGIT and

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Table 1: Baseline Characteristics of the study population

Characteristic (N = 210)

Unit

Frequency

%

Gender

Female

113

53.8

Aged group {Median (IQR) 35 (28 - 75)}

≥40 (years)

76

32.2

Education Level Marital status Occupation Body Mass Index {Median (IQR) 18.6 (17.5 - 21.2)} Smoking Alcohol consumpton HIV serostatus CD4 (for 46 HIV positive) {Median (IQR) 212.5 (77.5 - 312)} Respiratory sympotoms History of Diabetes Mellitus Region of origin Animal contact Livestock keeping

Secondary/High school Married Farming

106 163 83

51 77.6 40

≤ 18 (kg/m2) Underweight

104

49.5

Yes Yes Positive

40 31 46

18 14.8 22

≤ 350 cells/mm3

31

77.5

Yes Yes Central* Yes Yes

77 54 58 76 71

37 25.7 28 36.2 34

N - Number; % - Percentage' * Central - Embu, Kiambu, Muranga, Thika and Gatudnu

presence of AFB but that were negative for MTB complex using the SD-Bioline assay were sub-cultured in Lowenstein Jensen (LJ) media. Those that subsequently grew on LJ medium were considered to be NTMs and were characterized with the PCR based Genotype CM/AS assays. Thus, the individuals in this study who visited the TB testing centers were divided into four groups: MTB cases, NTM cases, NMY (not mycobacterium thoughpositive for AFB) cases and those negative for AFB due to lack of bacterial growth or growth of contaminants. Data analysis Descriptive statistics were used to summarize data. The overall NTM prevalence was determined for the entire patient’s population. In bivariate analyses, prevalence ratios (PR) and 95% confidence intervals (CI) for the association between NTM infection and demographic or behavioral characteristics was calculated using poisson regression. In multivariate analyses, a manual backward elimination approach was utilized to reach the most parsimonious model, including factors that were independently associated with BV infection at the significance level of p ≤0.05. All statistical analyses were performed using STATA v 13 (StataCorp LP, Texas, USA).

RESULTS Characteristics of study population Table 1 summarizes the characteristics of the study population. Out of the 210 TB retirement patients enrolled in the study, their mean age was 38.09 (SD 14.2) years and a median (IQR) range of 35 (28 to 75) years. Majority of these patients were females (53.8%), were aged ≥40 years (32.2%), and had secondary/high school education (51%) while 77.6% were married. About 40% of them were farmers, with 49.5% being underweight with a BMI of ≤ 18Kg/m2. About 18% were chain smokers, 14.8% consumed alcohol, and 22% were HIV seropositive. Other 37% had respiratory symptoms, 25.7% history of diabetes mellitus. Majority 28% were from central part of Kenya while, 36.2% and 34% had animal contact and kept livestock respectively. Prevalence of NTM causing Mycobacterium Out of the 210 patients samples analyzed, 89 (42.4%) were positive for NTM species while the rest 121 (57.6%) had M. tuberculosis. A total of nine different mycobacterium species were found causing NTM among these patients. These included 47/89 (52.8) M. intracellulare, 12/89 (13.4%) M. absessus, 8/89 (8.9%) M. africanum, 6/89 (6.7%) M. bovis, 6/89 (6.7%) M. fortuitum, 4/89 (4.5%), M. sacrofuloceum 4/75 (5%), 3/89


Figure 1: The prevalence of NTM causing mycobacterium species

(3.4%) M. kansasii, 2/89 (2.2%) M. interjectum and 1/89 (1.2%) M. xenopi (Figure 1). Correlates for NTM infection The appendix summarizes the factors associated with NTM infection among TB retreatment cases in Kenya. In the bivariate analyses, female gender was more likely to be infected with NTM than males (PR 1.8, 95% CI 1.1 to 3.1). Patients residing in the Eastern (PR 2.2, 95% CI 1.1 to 4.6) and Nairobi (PR 2.3, 95% CI 1.1 to 5.1) areas of Kenya were more likely to be infected with NTM compared to those residing in the Western regions of Kenya. Patients who had animals contact were more likely to be infected with NTM compared to those who had no animal contacts (PR 1.7, 95% CI 1.1 to 2.7). Further, those patients who kept livestock were more likely to be infected with NTM than those who did not keep livestock (PR 1.6, 95% CI 1.06 to 2.6). Lastly patients who were farmers (PR 1.6, 95% CI 0.9 to 2.7), who had tertiary level education (PR 2.2, 95% CI 0.9 to 5.5) those HIV positive (PR 1.8, 95% CI 1.1 to 3.1) and those who had respiratory symptoms (PR 1.8, 95% CI 1.1 to 3.1) were near likely to be infected with NTM. DISCUSSION Although success in TB elimination efforts has reduced incidence of M. tuberculosis related diseases in Kenya, there is an apparent increase in non-tuberculous mycobacterial disease. Kenya and many countries, there are no nationally representative data about the prevalence of NTM related diseases (Billingeret al., 2009). The current study therefore provides vital information that will contribute significantly in the management of pulmonary infections in Kenya.Nearly

half (42.4%) of the patients being retreated for TB were infected with NTM. This significantly high prevalence of NTM among patients with pulmonary disease is worrying due to initial inappropriate management. Low NTM prevalence rates have been reported elsewhere; in Iran, Tabarsiet al., (2009) reported a prevalence of 11.4% NTM among patients with multiple drug resistance histories.In Thailand, Srisuwanvilaiet al. 2008 reported a NTM prevalence of 11%. In Nigeria, 15% of patients who sought clinical treatment for tuberculosis were caused by NTM (Aliyu et al., 2013). Other studies have reported high NTM infection. In Taiwan, Sun et al. (2009) showed 43.3% NTM prevalence while Makarovaet al. (2009) showed a higher NTM prevalence of 65.4%. In this study majority of MTB complex cases were caused by M. tuberculosiswith a few cases caused by M. africanum(8.9%) and 6.7% by M. bovis. This observation mirrors studies in Nigeria by Aliyuet al., (2013) that showed M. tuberculosiswith a few cases caused by M. africanum, and only one case by M. bovis causing MTB complex. Similarly, results in the order of contribution of M. tuberculosis, M. africanumand M. bovisforming MTB complex has been reported in many other African countries such as Ghana, Mali,Cameroun, and Burkina Faso (Addoet al., 2007; Niobe-Eyangohet al., 2003,Traoreet al., 2012; Gomgnimbouet al., 2012). The NTM complex were caused majorly by M. intracellulare(52.8%), followed by M. absessus, M. fortuitum, M. sacrofuloceum, M. kansasii, M. interjectum and M. xenopi. These findings are similar to those found in Japan (Ito et al., 2012), in East Asia (Simons et al., 2011), in South American (Hoefslootet al., 2013) in Nigeria (Aliyuet al., 2013), in Canada and European countries (Marraset al., 2007; Cassidyet al., 2009).

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Female gender was a strong predictor for NTM infection in the current study. This finding is similar to that of Cassidyet al., (2009) in Oregon, US which showed a strong association of NTM frequent infection in womenthan men. Our findings are in line with published reports from institutional cases series and experts who believe the epidemiology of this disease has changed during the lastseveral decades to affect women more frequently than men (Griffithet al., 2007; Kim et al., 2009). Region of origin was a strong risk factor associated with NTM infection. Eastern and Nairobi parts of Kenya are generally dusty (Eastern) and crowded (Nairobi). These regions are characterized with a pocket of poor nutrition, poor hygienic measures in the surrounding environment which have been shown to increase the risk for NTM disease (Marraset al., 2002; Gupta et al., 2009). Higher risks for environmentally acquired pulmonary mycobacterial infections have been previously reported for individuals with occupational exposures to dust (Tiwari et al., 2007). Most regions of Eastern Kenya and pockets of Nairobi are characterized by crowding and hot dusty environment which could explain high prevalence rates in these regions. Animals contact and livestock keeping was a significant risk factor for NTM infection in this study.NTM are ubiquitous opportunistic pathogens. Humans and their agronomic animals are literally surrounded by NTM thus in developing countries, the dietary habit of people, close physical contact between humans and animals, and inadequate disease control measures in animals and humans facilitate the transmission of the disease between animals and humans (Ameni et al., 2013). Other risk factors that we either did not measure or did not found associated with NTM infection includes: prior tuberculosis,chronic obstructive pulmonary disease, lung damage dueto occupational exposures to dusts (e.g., mining), cystic fibrosis, cystic fibrosis mutation, a-1antitrypsindeficiency (Ameniet al., 2013). Fishexposure riskfor infections with M. marinum infection while children aged below 5 years are at risk forcervical lymphadenitis caused more typically by M. avium(WHO, 2011).Immunodeficiency, due to HIV-infection or immunosuppressiondue to cancer or chemotherapy is risk factor for M. avium(WHO, 2009). In conclusion, the high prevalence (42.2%) of clinical pulmonary TB due to NTM associated with region and animal contact presents a novel public health challenge. NTM needs to be considered when planning for prevention andmanagement of pulmonary TB patients since NTM susceptibility toTB regimens areknown to vary from M. tuberculosis. ACKNOWLEDGEMENTS This work was carried out at the National Tuberculosis Reference Laboratory, (NTRL), in Nairobi Kenya. The work was funded by Field Epidemiology Laboratory Training Programme, Ministry of Health, Nairobi, Kenya.

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Appendix: Factors associated with NTM infection

Participants characteristics Age Group < 20 21-30 31-40 >41 Gender Female Male Marital status Married Not Married* Occupation Employment Farming Housewife Student/Unemployed Education Level Primary Secondary Tertiarry Non-Formal Education Smoking Yes No Alcohol consumpsion Yes No HIV status Positive Negative Respiratory Symptoms Yes No History of Diabetes Mellitus Yes No Religion Central Eastern Nairobi Reiftvalley Western Animal Contact Yes No Keep Livestock Yes No

Sample size

NTB infection N %

Bivariate PR (95% CI)

Multivariate PR (95% CI)

10 60 64 76

3 22 20 30

30 36.7 31.3 39.5

0.9(0.32-2.6) 0.9 (0.5 - 1.6) 0.7 (0.4 - 1.3) Referent

Referent

113 97

42 33

37.2 34

1.8 (1.1 - 3.1) Referent

NS Referent

163 47

56 19

34.4 40.4

0.8 (0.4 - 1.3) Referent

NS Referent

46 83 17 64

10 41 4 20

21.7 49.4 23.5 31.3

0.6 (0.3 - 1.4) 1.6 (0.9 - 2.7) 0.7 (0.2-2.2) Referent

91 106 4 9

32 37 3 3

35.2 34.9 75 33.3

1.1 (0.6-1.8) 1 (0.5-1.8) 2.2(0.9-5.5) Referent

Referent

40 170

17 58

42.5 34.1

1.2(0.71-2.1) Referent

NS Referent

31 179

11 64

35.5 35.8

0.9(0.5-1.8) Referent

NS Referent

46 164

23 52

50 31.7

1.5(0.94-2.5) Referent

NS Referent

77 133

36 39

46.8 29.3

1.5(0.9-2.4) Referent

1.95(0.99-2.5) Referent

54 156

20 55

37 35.3

1.3(0.61-1.71) Referent

NS Referent

57 51 31 20 51

23 21 14 7 10

40.4 41.2 45.2 35 19.6

2.1(0.97-4.3) 2.2(1.1-4.6) 2.3(1.1-5.1) 1.7(0.67-4.68) Referent

Referent

76 134

38 37

50 27.6

1.7(1.1-2.7) Referent

NS Referent

71 139

35 40

49.3 28.8

1.6(1.06-2.6) Referent

NS Referent

NS

NS Referent

NS

NS

N - Number; % - Percentage; PR - Prevalence ratio; CI - confidence interval; ND - Not Done; NS - Not significant * Not Married (Single, Separeted, Divorced, Widowed); Central - Embu, Kiambu, Muranga, Thika and Gatundu Eastern - Kitui, Machakos, Marsabit, Meru, Wajir, and Kajiado; Rift Valley - Nakuru and Narok