Policy to practice: impact of GeneXpert MTB/RIF implementation on the TB spectrum of care in Lilongwe, Malawi

Chawla, Kashmira S.; Kanyama, Cecilia; Mbewe, Abineli; Matoga, Mitch; Hoffman, Irving; Ngoma, Jonathan; Hosseinipour, Mina C.

doi:10.1093/trstmh/trw030

Cited by 20 publications

(13 citation statements)

References 33 publications

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“…A study in Malawi evaluating the impact of Xpert roll-out on TB diagnosis and treatment showed only a small contribution to case detection. This low diagnostic impact was attributed to operational challenges and other gaps in the continuum of care such as difficulty in sputum transportation and slow turnaround time in high volume settings [10]. Results from our surveys of community health centers and from field notes reveal additional detail regarding operational challenges and gaps in the TB diagnostic cascade of care that impact Xpert effectiveness.…”

Section: Discussionmentioning

confidence: 93%

Challenges with scale-up of GeneXpert MTB/RIF® in Uganda: a health systems perspective

Nalugwa

Shete

Nantale

et al. 2020

BMC Health Serv Res

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Background: Many high burden countries are scaling-up GeneXpert® MTB/RIF (Xpert) testing for tuberculosis (TB) using a hub-and-spoke model. However, the effect of scale up on reducing TB has been limited. We sought to characterize variation in implementation of referral-based Xpert TB testing across Uganda, and to identify health system factors that may enhance or prevent high-quality implementation of Xpert testing services. Methods: We conducted a cross-sectional study triangulating quantitative and qualitative data sources at 23 community health centers linked to one of 15 Xpert testing sites between November 2016 and May 2017 to assess health systems infrastructure for hub-and-spoke Xpert testing. Data sources included a standardized site assessment survey, routine TB notification data, and field notes from site visits. Results: Challenges with Xpert implementation occurred at every step of the diagnostic evaluation process, leading to low overall uptake of testing. Of 2192 patients eligible for TB testing, only 574 (26%) who initiated testing were referred for Xpert testing. Of those, 54 (9.4%) were Xpert confirmed positive just under half initiated treatment within 14 days (n = 25, 46%). Gaps in required infrastructure at 23 community health centers to support the huband-spoke system included lack of refrigeration (n = 14, 61%) for sputum testing and lack of telephone/mobile communication (n = 21, 91%). Motorcycle riders responsible for transporting sputum to Xpert sites operated variable with trips once, twice, or three times a week at 10 (43%), nine (39%) and four (17%) health centers, respectively. Staff recorded Xpert results in the TB laboratory register at only one health center and called patients with positive results at only two health centers. Of the 15 Xpert testing sites, five (33%) had at least one non-functioning module. The median number of tests per day was 3.57 (IQR 2.06-4.54), and 10 (67%) sites had error/invalid rates > 5%. Conclusions: Although Xpert devices are now widely distributed throughout Uganda, health system factors across the continuum from test referral to results reporting and treatment initiation preclude effective implementation of Xpert testing for patients presenting to peripheral health centers. Support for scale up of innovative technologies should include support for communication, coordination and health systems integration.

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Section: Discussionmentioning

confidence: 93%

Challenges with scale-up of GeneXpert MTB/RIF® in Uganda: a health systems perspective

Nalugwa

Shete

Nantale

et al. 2020

BMC Health Serv Res

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“…In that study, this was mostly because of operational challenges of GXP performance, such as sputum collection and slow turnaround time in a busy hospital setting. 19 As can be anticipated, GXP was more commonly performed in PTB compared with EXTB or PTB + EXTB patients. However, even for PTB, the overall GXP sensitivity remained less than 60%, with HIV-infected patients significantly less likely to have a positive result (45%) than HIV-uninfected patients (100%).…”

Section: Discussionmentioning

confidence: 74%

Utilization and Clinical Value of Diagnostic Modalities for Tuberculosis in a High HIV Prevalence Setting

Gati

Chetty

Wilson

et al. 2018

The American Journal of Tropical Medicine and Hygiene

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Human immunodeficiency virus (HIV) infection is a major risk factor for the development of active tuberculosis (TB), one of the deadliest infectious diseases globally. The high mortality associated with the disease can be reduced by early diagnosis and prompt antituberculous treatment initiation. Facilities in TB-endemic regions are increasing the use of nucleic acid amplification (e.g., GeneXpert), which provides rapid results but may have suboptimal sensitivity in HIV-associated TB. Our objective was to evaluate the current practices for TB diagnosis at Edendale Hospital, a large regional hospital in KwaZulu-Natal, South Africa-a TB-endemic region with high HIV prevalence. In this cross-sectional study, all adult inpatients newly started on TB treatment at Edendale were identified over a 6-week period. Demographics, clinical information, diagnostic test results, and outcomes were documented. Pulmonary TB (PTB), extrapulmonary TB (EXTB), and PTB + EXTB were defined as disease evidence in the lungs, other organs, or both, respectively. Ninety-four cases were identified, of which 83% were HIV-associated. Only 30% of all TB patients were microbiologically confirmed, consisting of 7/16 (44%) HIV-uninfected and 21/78 (27%) HIV-infected TB patients. Smear microscopy and mycobacterial culture were seldom ordered. Ultrasound was performed in about one-third of suspected EXTB cases and was valuable in identifying abdominal TB. In this clinical setting with a high incidence of HIV-associated TB, TB diagnosis was more commonly based on clinical assessment and imaging results than on mycobacterial gold standard test confirmation.

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“…This was likely due to the replacement of smear‐microscopy with the Xpert MTB/RIF assay, which is a more sensitive tool in detecting TB, specifically among HIV co‐infected patients . Yet despite Xpert, empiric therapy continued to play a role (18% in 2016), likely due to extra‐pulmonary TB and programmatic factors, as was also reported from other settings . Third, diagnosis in secondary‐level health care was also associated with HIV‐associated TB, probably because sicker patients with HIV co‐infection were more likely to access and health workers to refer complicated cases (e.g.…”

Section: Discussionmentioning

confidence: 98%

Decreased risk of HIV‐associated TB during antiretroviral therapy expansion in rural Eswatini from 2009 to 2016: a cohort and population‐based analysis

Kerschberger

Schomaker

Telnov

et al. 2019

Tropical Med Int Health

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Objectives This paper assesses patient‐ and population‐level trends in TB notifications during rapid expansion of antiretroviral therapy in Eswatini which has an extremely high incidence of both TB and HIV. Methods Patient‐ and population‐level predictors and rates of HIV‐associated TB were examined in the Shiselweni region in Eswatini from 2009 to 2016. Annual population‐level denominators obtained from projected census data and prevalence estimates obtained from population‐based surveys were combined with individual‐level TB treatment data. Patient‐ and population‐level predictors of HIV‐associated TB were assessed with multivariate logistic and multivariate negative binomial regression models. Results Of 11 328 TB cases, 71.4% were HIV co‐infected and 51.8% were women. TB notifications decreased fivefold between 2009 and 2016, from 1341 to 269 cases per 100 000 person‐years. The decline was sixfold in PLHIV vs. threefold in the HIV‐negative population. Main patient‐level predictors of HIV‐associated TB were recurrent TB treatment (adjusted odds ratio [aOR] 1.40, 95% confidence interval [CI]: 1.19–1.65), negative (aOR 1.31, 1.15–1.49) and missing (aOR 1.30, 1.11–1.53) bacteriological status and diagnosis at secondary healthcare level (aOR 1.18, 1.06–1.33). Compared with 2009, the probability of TB decreased for all years from 2011 (aOR 0.69, 0.58–0.83) to 2016 (aOR 0.54, 0.43–0.69). The most pronounced population‐level predictor of TB was HIV‐positive status (adjusted incidence risk ratio 19.47, 14.89–25.46). Conclusions This high HIV‐TB prevalence setting experienced a rapid decline in TB notifications, most pronounced in PLHIV. Achievements in HIV‐TB programming were likely contributing factors.

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Policy to practice: impact of GeneXpert MTB/RIF implementation on the TB spectrum of care in Lilongwe, Malawi

Cited by 20 publications

References 33 publications

Challenges with scale-up of GeneXpert MTB/RIF® in Uganda: a health systems perspective

Challenges with scale-up of GeneXpert MTB/RIF® in Uganda: a health systems perspective

Utilization and Clinical Value of Diagnostic Modalities for Tuberculosis in a High HIV Prevalence Setting

Decreased risk of HIV‐associated TB during antiretroviral therapy expansion in rural Eswatini from 2009 to 2016: a cohort and population‐based analysis

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