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Suntornsut P, Asadinia KS, Limato R, Tamara A, Rotty LWA, Bramanti R, Nusantara DU, Nelwan EJ, Khusuwan S, Suphamongkholchaikul W, Chamnan P, Piyaphanee W, Vu HTL, Nguyen YH, Nguyen KH, Pham TN, Le QM, Vu VH, Chau DM, Vo DETH, Harriss EK, van Doorn HR, Hamers RL, Lorencatto F, Atkins L, Limmathurotsakul D. Barriers and enablers to blood culture sampling in Indonesia, Thailand and Viet Nam: a Theoretical Domains Framework-based survey. BMJ Open 2024; 14:e075526. [PMID: 38373855 PMCID: PMC10882306 DOI: 10.1136/bmjopen-2023-075526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/21/2024] Open
Abstract
OBJECTIVE Blood culture (BC) sampling is recommended for all suspected sepsis patients prior to antibiotic administration. We examine barriers and enablers to BC sampling in three Southeast Asian countries. DESIGN A Theoretical Domains Framework (TDF)-based survey, comprising a case scenario of a patient presenting with community-acquired sepsis and all 14 TDF domains of barriers/enablers to BC sampling. SETTING Hospitals in Indonesia, Thailand and Viet Nam, December 2021 to 30 April 2022. PARTICIPANTS 1070 medical doctors and 238 final-year medical students were participated in this study. Half of the respondents were women (n=680, 52%) and most worked in governmental hospitals (n=980, 75.4%). OUTCOME MEASURES Barriers and enablers to BC sampling. RESULTS The proportion of respondents who answered that they would definitely take BC in the case scenario was highest at 89.8% (273/304) in Thailand, followed by 50.5% (252/499) in Viet Nam and 31.3% (157/501) in Indonesia (p<0.001). Barriers/enablers in nine TDF domains were considered key in influencing BC sampling, including 'priority of BC (TDF-goals)', 'perception about their role to order or initiate an order for BC (TDF-social professional role and identity)', 'perception that BC is helpful (TDF-beliefs about consequences)', 'intention to follow guidelines (TDF-intention)', 'awareness of guidelines (TDF-knowledge)', 'norms of BC sampling (TDF-social influence)', 'consequences that discourage BC sampling (TDF-reinforcement)', 'perceived cost-effectiveness of BC (TDF-environmental context and resources)' and 'regulation on cost reimbursement (TDF-behavioural regulation)'. There was substantial heterogeneity between the countries. In most domains, the lower (higher) proportion of Thai respondents experienced the barriers (enablers) compared with that of Indonesian and Vietnamese respondents. A range of suggested intervention types and policy options was identified. CONCLUSIONS Barriers and enablers to BC sampling are varied and heterogenous. Cost-related barriers are more common in more resource-limited countries, while many barriers are not directly related to cost. Context-specific multifaceted interventions at both hospital and policy levels are required to improve diagnostic stewardship practices.
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Affiliation(s)
- Pornpan Suntornsut
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Koe Stella Asadinia
- Oxford University Clinical Research Unit Indonesia, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia
| | - Ralalicia Limato
- Oxford University Clinical Research Unit Indonesia, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, Oxford University, Oxford, UK
| | - Alice Tamara
- Oxford University Clinical Research Unit Indonesia, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia
| | | | | | | | - Erni J Nelwan
- Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia
- Department of Internal Medicine, Cipto Mangunkusumo National General Hospital, Jakarta, Indonesia
| | | | | | | | - Watcharapong Piyaphanee
- Hospital for Tropical Diseases, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | | | - Yen Hai Nguyen
- Oxford University Clinical Research Unit, Ha Noi, Viet Nam
| | | | | | | | | | | | | | - Elinor K Harriss
- Bodleian Health Care Libraries, University of Oxford, Oxford, UK
| | - Hindrik Rogier van Doorn
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, Oxford University, Oxford, UK
- Oxford University Clinical Research Unit, Ha Noi, Viet Nam
| | - Raph Leonardus Hamers
- Oxford University Clinical Research Unit Indonesia, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, Oxford University, Oxford, UK
| | | | - Lou Atkins
- Centre for Behaviour Change, University College London, London, UK
| | - Direk Limmathurotsakul
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, Oxford University, Oxford, UK
- Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
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Revell AD, Wang D, Wood R, Morrow C, Tempelman H, Hamers RL, Alvarez-Uria G, Streinu-Cercel A, Ene L, Wensing AMJ, DeWolf F, Nelson M, Montaner JS, Lane HC, Larder BA. Computational models can predict response to HIV therapy without a genotype and may reduce treatment failure in different resource-limited settings. J Antimicrob Chemother 2013; 68:1406-14. [PMID: 23485767 DOI: 10.1093/jac/dkt041] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
OBJECTIVES Genotypic HIV drug-resistance testing is typically 60%-65% predictive of response to combination antiretroviral therapy (ART) and is valuable for guiding treatment changes. Genotyping is unavailable in many resource-limited settings (RLSs). We aimed to develop models that can predict response to ART without a genotype and evaluated their potential as a treatment support tool in RLSs. METHODS Random forest models were trained to predict the probability of response to ART (≤400 copies HIV RNA/mL) using the following data from 14 891 treatment change episodes (TCEs) after virological failure, from well-resourced countries: viral load and CD4 count prior to treatment change, treatment history, drugs in the new regimen, time to follow-up and follow-up viral load. Models were assessed by cross-validation during development, with an independent set of 800 cases from well-resourced countries, plus 231 cases from Southern Africa, 206 from India and 375 from Romania. The area under the receiver operating characteristic curve (AUC) was the main outcome measure. RESULTS The models achieved an AUC of 0.74-0.81 during cross-validation and 0.76-0.77 with the 800 test TCEs. They achieved AUCs of 0.58-0.65 (Southern Africa), 0.63 (India) and 0.70 (Romania). Models were more accurate for data from the well-resourced countries than for cases from Southern Africa and India (P < 0.001), but not Romania. The models identified alternative, available drug regimens predicted to result in virological response for 94% of virological failures in Southern Africa, 99% of those in India and 93% of those in Romania. CONCLUSIONS We developed computational models that predict virological response to ART without a genotype with comparable accuracy to genotyping with rule-based interpretation. These models have the potential to help optimize antiretroviral therapy for patients in RLSs where genotyping is not generally available.
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Affiliation(s)
- A D Revell
- The HIV Resistance Response Database Initiative (RDI), London, UK
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Revell AD, Wang D, Harrigan R, Hamers RL, Wensing AMJ, Dewolf F, Nelson M, Geretti AM, Larder BA. Modelling response to HIV therapy without a genotype: an argument for viral load monitoring in resource-limited settings. J Antimicrob Chemother 2010; 65:605-7. [PMID: 20154024 DOI: 10.1093/jac/dkq032] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
In the absence of widespread access to individualized laboratory monitoring, which forms an integral part of HIV patient management in resource-rich settings, the roll-out of highly active antiretroviral therapy (HAART) in resource-limited settings has adopted a public health approach based on standard HAART protocols and clinical/immunological definitions of therapy failure. The cost-effectiveness of HIV-1 viral load monitoring at the individual level in such settings has been debated, and questions remain over the long-term and population-level impact of managing HAART without it. Computational models that accurately predict virological response to HAART using baseline data including CD4 count, viral load and genotypic resistance profile, as developed by the Resistance Database Initiative, have significant potential as an aid to treatment selection and optimization. Recently developed models have shown good predictive performance without the need for genotypic data, with viral load emerging as by far the most important variable. This finding provides further, indirect support for the use of viral load monitoring for the long-term optimization of HAART in resource-limited settings.
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Affiliation(s)
- A D Revell
- The HIV Resistance Response Database Initiative, London, UK.
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Hamers RL, Schuurman R, van Vugt M, Derdelinckx I, Rinke de Wit TF. [AIDS treatment in Africa: the risk of antiretroviral resistance]. Ned Tijdschr Geneeskd 2007; 151:2666-2671. [PMID: 18179083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
--In recent years, implementation of antiretroviral therapy in developing countries with a high prevalence of HIV-1 has been recognised as a public health priority. Consequently, the availability ofantiretroviral combination therapy for people with HIV is increasing rapidly in sub-Saharan Africa. --HIV treatment programmes are implemented according to the standardised, simplified public health guidelines developed by the World Health Organization (WHO). --However, the implementation of treatment programmes in Africa is hindered by several factors, including the lack of adequate immunological and virological laboratory monitoring, insufficient support for adherence to therapy, vulnerable health care systems and the use of suboptimal drug combinations. --These suboptimal treatment conditions increase the risk that resistant virus strains will emerge that are less susceptible to standard first-line combination therapy, thus threatening the long-term success of the treatment programmes. --The WHO has initiated HIVResNet, an international expert advisory board that has developed a global strategy for surveillance and prevention of antiretroviral drug resistance. --The Dutch initiative known as 'PharmAccess African studies to evaluate resistance' (PASER) is contributing to this strategy by creating a surveillance network in sub-Saharan Africa.
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Affiliation(s)
- R L Hamers
- Academisch Medisch Centrum/Universiteit van Amsterdam, Stichting PharmAccess International, Center for Poverty-related Communicable Diseases, Amsterdam
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