Distribution patterns of drug resistance Mycobacterium tuberculosis among HIV negative and positive tuberculosis patients in Western Kenya

Abstract

Introduction Globally anti-tuberculosis drug resistance is one of the major challenges affecting control and prevention of tuberculosis. Kenya is ranked among 30 high burden TB countries globally. However, there is scanty information on second line antituberculosis drug resistance among tuberculosis patients. Therefore, this study aimed at determining Mycobacterium tuberculosis drug resistant strain distribution pattern in 10 counties of Western Kenya among HIV positive and negative patients. Method A cross-sectional study was conducted in Western Kenya, which comprises 10 counties. A multistage sampling method was used where a single sub-county was randomly selected followed by sampling one high volume health facility from each sub-county. Consenting study subjects with at least two smear positive sputum at the time of enrolment were randomly selected. The collected sputum was decontaminated with N-acetyl-l-cysteine-sodium hydroxide (NALC-NaOH) and then stained with Ziehl Neelsen Stain before visualizing the presence of bacilli under microscope at ×100 magnification with oil immersion. Further, the identified bacilli were cultured and susceptibility test carried out using known first and second line antimycobacterial tuberculosis. HIV testing was carried out using Determine® HIV-1/2 rapid test (Abbot Diagnostics, Maidenhead, United Kingdom). Those who had smear converted were dropped from the study. Finally, drug susceptibility pattern across the 10 counties of Western Kenya was evaluated. Results Our study showed that Mycobacterium tuberculosis drug resistance among HIV negative and positive cases in Western Kenya was prevalent in all the 10 counties surveyed. Based on the drug susceptibility tests, 53.2% and 42.7% of the study samples were resistant to at least one antituberculosis drug among HIV negative and HIV positive patients respectively. The data analysis revealed that among the HIV-positive and HIV-negative patients, resistance to INH was predominant (28.5%, and 23.6%, respectively), followed by RIF (16.4% and 14.6% respectively). Second-line drug resistant strains identified among HIV negative patients included Ethionamide (0.3%), Gatifloxacin (0.3%), Amikacin (0.3%) and Capreomycin (0.3%). There was no second line drug monoresistance among HIV positive TB patients. Multi/poly drug resistance were noted among HIV-negative patients in, INH + AMK (0.7%), INH + PZA (1%), INH + GFX (0.7%, INH + ETO (0.7%, STY + ETO (1%), ETH + ETO (1.0%), INH + KAN (0.7%) and INH + CAP (0.7%) strains/cases at 95% confidence interval. Among HIV positive patients INH + GFX (1.1%), INH + ETO (0.4%) and INH + KAN (0.4%) strains of M. tuberculosis were identified with a confidence interval of 95%. Geographical distribution patterns analysis of M. tuberculosis drug polyresistant strains across the 10 counties were recorded. Among HIV TB patients, resistant strains were identified in Nyamira (INH + GFX, INH + KAN), Bungoma ((ETO + STY), Busia (ETH + ETO and STY + ETO) Homabay (RIF + AMK. ETO + ETH and ETO + STY), Kisumu (ETH + ETO and PZA + ETO) and in Kakamega, Kisii and Vihiga (INH + KAN and RIF + AMK). There was no M. tuberculosis polyresistant strain identified in Migori and Siaya counties. Among HIV positive TB patients, M. tuberculosis resistant strains were identified in three counties, Nyamira (INH + KAN) Homabay (INH + GFX and INH + AMK) and Kakamega (INH + GFX). There was no polyresistant M. tuberculosis strain identified in Migori, Bungoma, Kisii, Vihiga, Busia, Siaya and Kisumu Counties. Discussion The distribution patterns of M. tuberculosis drug resistance among HIV negative and positive TB patients could be as a result of reported high prevalence of HIV in Western Kenya counties especially the area under study. Tuberculosis is one of the opportunistic diseases that have been shown to be the major cause of AIDS among HIV infected patients. Resent reports by National AIDS Control Council shows that Kisumu, Siaya, Homabay, Migori, Busia have the overall leading in HIV prevalence in Kenya. The low prevalence of drug resistant strains among HIV tuberculosis patients could be as a result of drug adherence attitude adopted by HIV patients, availability of continuous counselling and close follow up and notification by healthcare workers and community health volunteers. Conclusion Drug resistant M. tuberculosis strains prevalence is still high among HIV negative and positive patients in Western Kenya with the most affected being HIV negative TB patients. It is therefore probable that the existing control measures are not adequate to control transmission of drug resistant strains. Further, miss diagnosis or delayed diagnosis of TB patients could be contributing to the emergence of M. tuberculosis drug polyresistant strains. Recommendation Based on the result of this study, regular TB drug resistance surveillance should be conducted to ensure targeted interventions aimed at controlling increased transmission of the tuberculosis drug resistant strains among HIV/AIDS and HIV negative patients. There is also need for improved drug resistant infection control measures, timely and rapid diagnosis and enhanced and active screening strategies of tuberculosis among suspected TB patients need to be put in place. Further, studies using a larger patient cohort and from counties across the country would shed much needed insights on the true national prevalence of different variants of M. tuberculosis drug resistance.

Characteristics of TB/HIV Co-Infection and Patterns of Multidrug-Resistance Tuberculosis in the Northwest Amhara, Ethiopia

“…However, in the study, there was no RIF-mono resistant isolate found, and all RIF-related resistant cases were also resistant to INH-related which are known as MDR-TB cases, which has significant implications since practicing TB programs to use RIF-resistance as a surrogate marker for MDR-TB diagnosis and is an essential drug during the course of TB treatment. Compared to our findings, previous studies were reported higher rate of INH-mono resistant from Western Kenya (28.5%) 36 and RIF-mono resistant from Amhara region (6%), 34 Western Kenya (14.6%), 36 Tanzania (2.5%), 41 and Zambia (3%); 37 as well as lower rate of any mono-resistant to tested drugs from Russia (13.9%), 42 INH mono-resistant from Amhara region (2%) 34 and Zambia (9.8%), 37 and STR-mono resistant from Zambia (0.8%) 37 among TB patients.…”

“…Our study also revealed that the MDR-TB isolates among HIV-positive vs HIV-negative patients was found to be 5/36 (13.9%) vs 7/132 (5.3%), respectively. The proportion of MDR-TB among HIV-positive patients (22.2%) in our finding is higher than the previous finding from Western Kenya (12%), 36 and slightly lower than from North India (27.3%) 35 among HIV-positive patients.…”

“…The study was found a higher prevalence of TB/HIV co-infection (50/252, 19.8%), which is slightly in consistent with the other findings from the Amhara region (20% and 25.6%) 19 , 34 and North India (20%). 35 Higher rate of TB/HIV co-infection cases were reported from Addis Ababa, Ethiopia (57%), 8 Western Kenya (48%), 36 and Zambia (44%); 37 while a lower rate from Northwest Ethiopia (12%) 38 and Saudi Arabia (0.7%). 39 The higher rate of TB with HIV co-infected cases might be explained by impairing the host’s immune responses to both diseases, lengthening the time it takes for TB treatments to be effective by increasing the bacilli load, which could make the bacteria resistant to anti-TB drugs, and lead to MDR-TB.…”

Strain structure analysis of Mycobacterium tuberculosis circulating among HIV negative, positive and drug resistant TB patients attending chest clinics in Western Kenya

“…Additionally, there has been increased circulation of drug resistant M. tuberculosis of varying degrees ranging from mono resistant, multi resistant and poly resistant strains. Drug resistance structure of M. tuberculosis under study was reported by Ogwang et al, [ 30 ] thus this study intended to establish M. tuberculosis drug resistance strain structure through spacer oligonucleotide typing (Spoligotyping). Our findings indicate a circulation of diverse strains of M. tuberculosis in the study area.…”

“…Despite other studies associating TB drug resistance to Beijing lineage, this study did not find any correlation between the strain and resistance. Therefore, resistance in this case could be associated to poor drug adherence, failure in prompt diagnosis, migration, poverty and increased TB/HIV cross infection [ 30 ].…”