METHODS: Surveys were conducted in April 2009. Analysis data from the Asia cohort were collected in March 2009 from 12 centres in Cambodia, India, Indonesia, Malaysia, and Thailand. Data from the IeDEA Southern Africa cohort were finalized in February 2008 from 10 centres in Malawi, Mozambique, South Africa and Zimbabwe.
RESULTS: Survey responses reflected inter-regional variations in drug access and national guidelines. A total of 1301 children in the TREAT Asia and 4561 children in the IeDEA Southern Africa cohorts met inclusion criteria for the cross-sectional analysis. Ten percent of Asian and 3.3% of African children were on second-line ART at the time of data transfer. Median age (interquartile range) in months at second-line initiation was 120 (78-145) months in the Asian cohort and 66 (29-112) months in the southern African cohort. Regimens varied, and the then current World Health Organization-recommended nucleoside reverse transcriptase combination of abacavir and didanosine was used in less than 5% of children in each region.
CONCLUSIONS: In order to provide life-long ART for children, better use of current first-line regimens and broader access to heat-stable, paediatric second-line and salvage formulations are needed. There will be limited benefit to earlier diagnosis of treatment failure unless providers and patients have access to appropriate drugs for children to switch to.
METHODS: On Ambae Island, blood samples were collected from 231 and 282 individuals in 2003 and 2007, respectively. Parasite prevalence was determined by microscopy. Antibodies to three Plasmodium falciparum (PfSE, PfMSP-119, and PfAMA-1) and three Plasmodium vivax (PvSE, PvMSP-119, and PvAMA-1) antigens, as well as the Anopheles-specific salivary antigen gSG6, were detected by ELISA. Age-specific seroprevalence was analysed using a reverse catalytic modelling approach to estimate seroconversion rates (SCRs).
RESULTS: Parasite rate decreased significantly (P
METHOD: This study was conducted using an exploratory qualitative approach on purposely selected healthcare providers at primary healthcare clinics. Twenty focus group discussions and three in-depth interviews were conducted using a semi-structured interview guide. Consent was obtained prior to interviews and for audio-recordings. Interviews were transcribed verbatim and thematically analysed, guided by the Consolidated Framework for Implementation Research (CFIR), a framework comprised of five major domains promoting implementation theory development and verification across multiple contexts.
RESULTS: The study revealed via CFIR that most primary healthcare providers were receptive towards any proposed changes or intervention for the betterment of NCD care management. However, many challenges were outlined across four CFIR domains-intervention characteristics, outer setting, inner setting, and individual characteristics-that included perceived barriers to implementation. Perception of issues that triggered proposed changes reflected the current situation, including existing facilitating aspects that can support the implementation of any future intervention. The importance of strengthening the primary healthcare delivery system was also expressed.
CONCLUSION: Understanding existing situations faced at the primary healthcare setting is imperative prior to implementation of any intervention. Healthcare providers' receptiveness to change was explored, and using CFIR framework, challenges or perceived barriers among healthcare providers were identified. CFIR was able to outline the clinics' setting, individual behaviour and external agency factors that have direct impact to the organisation. These are important indicators in ensuring feasibility, effectiveness and sustainability of any intervention, as well as future scalability considerations.
METHODS: This cross sectional study was conducted in December 2019 in cardiology ward of a 1000-bed tertiary care hospital of Bangladesh. Patients admitted in the ward with the diagnosis of myocardial infarction were included in the study. Socio demographic data, clinical features and patients' health seeking behavior was collected in a structured questionnaire from the patients. Median with interquartile range (IQR) of pre hospital delay were calculated and compared between different groups. Chi-square (χ2) test and binary logistic regression were used to estimate the determinants of pre-hospital delay and effect of pre-hospital delay on in-hospital mortality.
RESULTS: Three hundred thirty-seven patients was enrolled in the study and their median (IQR) pre-hospital delay was 9.0 (13.0) hours. 39.5% patients admitted in the specialized hospital within 6 h. In logistic regression, determinants of pre-hospital delay were patients age (for health care system may reduce this unexpected delay.