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Multidrug-resistant tuberculosis (MDR-TB) is caused by M. tuberculosis (Mtb) with resistance to the first-line anti-TB medicines isoniazid (INH) and rifampicin (RIF). In Western Kenya, there is reported low prevalence of drug resistant strains among HIV tuberculosis patients, creating a need to determine factors associated with drug resistance patterns among presumptive MDR-TB patients. To determine factors associated with drug resistance patterns among presumptive MDR-TB patients in western Kenya. Three hundred and ninety (3 9 0) sputum sample isolates from among presumptive multidrug TB patients, were analyzed for TB drug resistance as per Ministry of Health (MoH) TB program diagnostic algorithm. Frequency and percentages were used to summarize categorical data while median and interquartile range (IQR) were used for continuous data. Multivariable logistic regression was carried out to identify factors associated with TB drug resistance. Out of 390 participants enrolled, 302/390 (77.4 %) were males, with a median age of 34 years. The HIV-infected were 118/390 (30.3 %). Samples included 322 (82.6 %) from presumptive patients, while 68/390 (17.4 %) were either lost to follow-up patients, failures to first-line treatment or newly diagnosed cases. A total of 64/390 (16.4 %) of the isolates had at least some form of drug resistance. Out of 390, 14/390 (3.6 %) had MDR, 12 (3.1 %) were RIF mono-resistance, 34 (8.7 %) had INH, while 4 (1 %) had ethambutol resistance. The category of previously treated patients (those who received or are currently on TB treatment) had a 70 % reduced likelihood of resistance (aOR: 0.30; 95 % CI: 0.13-0.70). In contrast, older age was associated with an increased likelihood of resistance to INH and RIF, with an adjusted odds ratio of 1.04 per year (95 % CI: 1.00-1.08). Prompt MDR-TB diagnosis is essential for appropriate patient care, management, and disease prevention and control. We recommend active surveillance on drug resistant TB in these regions to detect drug resistance patterns for rapid disease management.
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Diagnostic network optimization (DNO) is an analytical approach that enables use of available country data to inform evidence-based decision-making to optimize access to diagnostic services. A DNO methodology was developed using available data sources and a commercial supply chain optimization software. In collaboration with Ministries of Health and partners, the approach was applied in Kenya, India and the Philippines to map TB diagnostic networks, identify misalignments, and determine optimal network design to increase patient access to TB diagnostic services and improve device utilization. The DNO analysis was successfully applied to evaluate and inform TB diagnostic services in Kenya, India and the Philippines as part of national strategic planning for TB. The analysis was tailored to each country's specific objectives and allowed evaluation of factors such as the number and placement of different TB diagnostics, design of sample referral networks and integration of early infant diagnosis for HIV at national and sub-national levels and across public and private sectors. Our work demonstrates the value of DNO as an innovative approach to analysing and modelling diagnostic networks, particularly suited for use in low-resource settings, as an open-access approach that can be applied to optimize networks for any disease.
Assuntos
Serviços de Diagnóstico , Encaminhamento e Consulta , Humanos , Filipinas/epidemiologia , Quênia/epidemiologia , ÍndiaRESUMO
BACKGROUND: Development of rapid biomarker-based tests that can diagnose tuberculosis using non-sputum samples is a priority for tuberculosis control. We aimed to compare the diagnostic accuracy of the novel Fujifilm SILVAMP TB LAM (FujiLAM) assay with the WHO-recommended Alere Determine TB-LAM Ag test (AlereLAM) using urine samples from HIV-positive patients. METHODS: We did a diagnostic accuracy study at five outpatient public health facilities in Uganda, Kenya, Mozambique, and South Africa. Eligible patients were ambulatory HIV-positive individuals (aged ≥15 years) with symptoms of tuberculosis irrespective of their CD4 T-cell count (group 1), and asymptomatic patients with advanced HIV disease (CD4 count <200 cells per µL, or HIV clinical stage 3 or 4; group 2). All participants underwent clinical examination, chest x-ray, and blood sampling, and were requested to provide a fresh urine sample, and two sputum samples. FujiLAM and AlereLAM urine assays, Xpert MTB/RIF Ultra assay on sputum or urine, sputum culture for Mycobacterium tuberculosis, and CD4 count were systematically carried out for all patients. Sensitivity and specificity of FujiLAM and AlereLAM were evaluated against microbiological and composite reference standards. FINDINGS: Between Aug 24, 2020 and Sept 21, 2021, 1575 patients (823 [52·3%] women) were included in the study: 1031 patients in group 1 and 544 patients in group 2. Tuberculosis was microbiologically confirmed in 96 (9·4%) of 1022 patients in group 1 and 18 (3·3%) of 542 patients in group 2. Using the microbiological reference standard, FujiLAM sensitivity was 60% (95% CI 51-69) and AlereLAM sensitivity was 40% (31-49; p<0·001). Among patients with CD4 counts of less than 200 cells per µL, FujiLAM sensitivity was 69% (57-79) and AlereLAM sensitivity was 52% (40-64; p=0·0218). Among patients with CD4 counts of 200 cells per µL or higher, FujiLAM sensitivity was 47% (34-61) and AlereLAM sensitivity was 24% (14-38; p=0·0116). Using the microbiological reference standard, FujiLAM specificity was 87% (95% CI 85-89) and AlereLAM specificity was 86% (95 CI 84-88; p=0·941). FujiLAM sensitivity varied by lot number from 48% (34-62) to 76% (57-89) and specificity from 77% (72-81) to 98% (93-99). INTERPRETATION: Next-generation, higher sensitivity urine-lipoarabinomannan assays are potentially promising tests that allow rapid tuberculosis diagnosis at the point of care for HIV-positive patients. However, the variability in accuracy between FujiLAM lot numbers needs to be addressed before clinical use. FUNDING: ANRS and Médecins Sans Frontières.
Assuntos
Infecções por HIV , Mycobacterium tuberculosis , Tuberculose , Humanos , Feminino , Masculino , Tuberculose/diagnóstico , Tuberculose/urina , Contagem de Linfócito CD4 , Infecções por HIV/complicações , Infecções por HIV/diagnóstico , Sensibilidade e Especificidade , Lipopolissacarídeos/urina , População Africana , África do SulRESUMO
Background: A recent tuberculosis prevalence survey in Kenya found that the country is home to nearly twice as many patients with tuberculosis as previously estimated. Kenya has prioritized identifying and treating the unnotified or missing cases of tuberculosis. This requires a better understanding of patient care seeking and system weaknesses. Methods: A patient-pathway analysis (PPA) was completed to assess the alignment between patient care seeking and the availability of tuberculosis diagnostic and treatment services at the national level and for all 47 counties at the subnational level in Kenya. Results: It was estimated that more than half of patients initiate care in the public sector. Nationally, just under half of patients encountered tuberculosis diagnostic and treatment capacity where they initiated care. Overall, there was distinct variation in diagnostic and treatment availability across counties and facility levels. Discussion: The PPA results emphasized the need for a differentiated approach to tuberculosis care, by county, and the distinct need for better referral systems. The majority of Kenyans actively sought care; improving diagnostic and treatment capacity in the formal and informal private sector, as well as in the public sector, could help identify the majority of missing cases.