Fragmented understanding: exploring the practice and meaning of informed consent in clinical trials in Ho Chi Minh City, Vietnam.

BACKGROUND: The informed consent process in clinical trials has been extensively studied to inform the development processes which protect research participants and encourage their autonomy. However, ensuring a meaningful informed consent process is still of great concern in many research settings due to its complexity in practice and interwined socio-cultural factors. OBJECTIVES: This study explored the practices and meaning of the informed consent process in two clinial trials conducted by Oxford University Clinical Research Unit in collaboration with the Hospital for Tropical Diseases in Ho Chi Minh City, Vietnam. METHODS: We used multiple data collection methods including direct observervations, in-depth interviews with study physicians and trial participants, review of informed consent documents from 2009 to 2018, and participant observation with patients' family members. We recruited seven physicians and twenty-five trial participants into the study, of whom five physicians and thirteen trial participants completed in-depth interviews, and we held twenty-two direct observation sessions. RESULTS: We use the concept "fragmented understanding" to describe the nuances of understanding about the consent process and unpack underlying reasons for differing understandings. CONCLUSIONS: Our findings show how practices of informed consent and different understanding of the trial information are shaped by trial participants' characteristics and the socio-cultural context in which the trials take place.

Predictors of treatment failures of plasmodium falciparum malaria in Vietnam: a 4-year single-centre retrospective study.

BACKGROUND: Drug-resistant falciparum malaria is an increasing public health burden. This study examined the magnitude of Plasmodium falciparum infection and the patterns and predictors of treatment failure in Vietnam. METHODS: Medical records of all 443 patients with malaria infection admitted to the Hospital for Tropical Diseases between January 2015 and December 2018 were used to extract information on demographics, risk factors, symptoms, laboratory tests, treatment, and outcome. RESULTS: More than half (59.8%, 265/443, CI 55.1-64.4%) of patients acquired Plasmodium falciparum infection of whom 21.9% (58/265, CI 17.1-27.4%) had severe malaria, while 7.2% (19/265, CI 4.6-10.9%) and 19.2% (51/265, CI 14.7-24.5%) developed early treatment failure (ETF) and late treatment failure (LTF) respectively. Among 58 patients with severe malaria, 14 (24.1%) acquired infection in regions where artemisinin resistance has been documented including Binh Phuoc (11 patients), Dak Nong (2 patients) and Gia Lai (1 patient). Under treatment with intravenous artesunate, the median (IQR) parasite half-life of 11 patients coming from Binh Phuoc was 3 h (2.3 to 8.3 h), two patients coming from Dak Nong was 2.8 and 5.7 h, and a patient coming from Gia Lai was 6.5 h. Most patients (98.5%, 261/265) recovered completely. Four patients with severe malaria died. Severe malaria was statistically associated with receiving treatment at previous hospitals (P < 0.001), hepatomegaly (P < 0.001) and number of inpatient days (P < 0.001). Having severe malaria was a predictor of ETF (AOR 6.96, CI 2.55-19.02, P < 0.001). No predictor of LTF was identified. CONCLUSIONS: Plasmodium falciparum remains the prevalent malaria parasite. Despite low mortality rate, severe malaria is not rare and is a significant predictor of ETF. To reduce the risk for ETF, studies are needed to examine the effectiveness of combination therapy including parenteral artesunate and a parenteral partner drug for severe malaria. The study alerts the possibility of drug-resistant malaria in Africa and other areas in Vietnam, which are known as non-endemic areas of anti-malarial drug resistance. A more comprehensive study using molecular technique in these regions is required to completely understand the magnitude of drug-resistant malaria and to design appropriate control strategies.

Computer-aided prognosis of tuberculous meningitis combining imaging and non-imaging data.

Tuberculous meningitis (TBM) is the most lethal form of tuberculosis. Clinical features, such as coma, can predict death, but they are insufficient for the accurate prognosis of other outcomes, especially when impacted by co-morbidities such as HIV infection. Brain magnetic resonance imaging (MRI) characterises the extent and severity of disease and may enable more accurate prediction of complications and poor outcomes. We analysed clinical and brain MRI data from a prospective longitudinal study of 216 adults with TBM; 73 (34%) were HIV-positive, a factor highly correlated with mortality. We implemented an end-to-end framework to model clinical and imaging features to predict disease progression. Our model used state-of-the-art machine learning models for automatic imaging feature encoding, and time-series models for forecasting, to predict TBM progression. The proposed approach is designed to be robust to missing data via a novel tailored model optimisation framework. Our model achieved a 60% balanced accuracy in predicting the prognosis of TBM patients over the six different classes. HIV status did not alter the performance of the models. Furthermore, our approach identified brain morphological lesions caused by TBM in both HIV and non-HIV-infected, associating lesions to the disease staging with an overall accuracy of 96%. These results suggest that the lesions caused by TBM are analogous in both populations, regardless of the severity of the disease. Lastly, our models correctly identified changes in disease symptomatology and severity in 80% of the cases. Our approach is the first attempt at predicting the prognosis of TBM by combining imaging and clinical data, via a machine learning model. The approach has the potential to accurately predict disease progression and enable timely clinical intervention.

Pharmacokinetics and Pharmacodynamics of Intensive Antituberculosis Treatment of Tuberculous Meningitis.

The most effective antituberculosis drug treatment regimen for tuberculous meningitis is uncertain. We conducted a randomized controlled trial comparing standard treatment with a regimen intensified by rifampin 15 mg/kg and levofloxacin for the first 60 days. The intensified regimen did not improve survival or any other outcome. We therefore conducted a nested pharmacokinetic/pharmacodynamic study in 237 trial participants to define exposure-response relationships that might explain the trial results and improve future therapy. Rifampin 15 mg/kg increased plasma and cerebrospinal fluid (CSF) exposures compared with 10 mg/kg: day 14 exposure increased from 48.2 hour·mg/L (range 18.2-93.8) to 82.5 hour·mg/L (range 8.7-161.0) in plasma and from 3.5 hour·mg/L (range 1.2-9.6) to 6.0 hour·mg/L (range 0.7-15.1) in CSF. However, there was no relationship between rifampin exposure and survival. In contrast, we found that isoniazid exposure was associated with survival, with low exposure predictive of death, and was linked to a fast metabolizer phenotype. Higher doses of isoniazid should be investigated, especially in fast metabolizers.