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Fulltext Cross-sectional study exploring barriers to adverse drug reactions reporting in community pharmacy settings in Dhaka, Bangladesh

Amin MN, Khan TM, Dewan SM, Islam MS, Moghal MR, Ming LC

BMJ Open, 2016 08 03;6(8):e010912.
PMID: 27489151 DOI: 10.1136/bmjopen-2015-010912

OBJECTIVES: To assess community pharmacists'/pharmacy technicians' knowledge and perceptions about adverse drug reactions (ADRs) and barriers towards the reporting of such reactions in Dhaka, Bangladesh.
METHOD: A cross-sectional study was planned to approach potential respondents for the study. A self-administered questionnaire was delivered to community pharmacists/pharmacy technicians (N=292) practising in Dhaka, Bangladesh.
RESULTS: The overall response to the survey was 69.5% (n=203). The majority of the sample was comprised of pharmacy technicians (152, 74.9%) who possessed a diploma in pharmacy, followed by pharmacists (37, 18.2%) and others (12, 5.9%). Overall, 72 (35.5%) of the respondents disclosed that they had experienced an ADR at their pharmacy, yet more than half (105, 51.7%) were not familiar with the existence of an ADR reporting body in Bangladesh. Exploring the barriers to the reporting of ADRs, it was revealed that the top four barriers to ADR reporting were 'I do not know how to report (Relative Importance Index (RII)=0.998)', 'reporting forms are not available (0.996)', 'I am not motivated to report (0.997)' and 'Unavailability of professional environment to discuss about ADR (RII=0.939)'. In addition to these, a majority (141, 69.46%) were not confident about the classification of ADRs (RII=0.889) and were afraid of legal liabilities associated with reporting ADRs (RII=0.806). Moreover, a lack of knowledge about pharmacotherapy and the detection of ADRs was another major factor hindering their reporting (RII=0.731).
CONCLUSIONS: The Directorate of Drug Administration in Bangladesh needs to consider the results of this study to help it improve and simplify ADR reporting in Bangladeshi community pharmacy settings.
Multigene Expression Programming Based Forecasting the Hardened Properties of Sustainable Bagasse Ash Concrete

Amin MN, Khan K, Aslam F, Shah MI, Javed MF, Musarat MA, et al.

Materials (Basel), 2021 Sep 28;14(19).
PMID: 34640055 DOI: 10.3390/ma14195659

The application of multiphysics models and soft computing techniques is gaining enormous attention in the construction sector due to the development of various types of concrete. In this research, an improved form of supervised machine learning, i.e., multigene expression programming (MEP), has been used to propose models for the compressive strength (fc'), splitting tensile strength (fSTS), and flexural strength (fFS) of sustainable bagasse ash concrete (BAC). The training and testing of the proposed models have been accomplished by developing a reliable and comprehensive database from published literature. Concrete specimens with varying proportions of sugarcane bagasse ash (BA), as a partial replacement of cement, were prepared, and the developed models were validated by utilizing the results obtained from the tested BAC. Different statistical tests evaluated the accurateness of the models, and the results were cross-validated employing a k-fold algorithm. The modeling results achieve correlation coefficient (R) and Nash-Sutcliffe efficiency (NSE) above 0.8 each with relative root mean squared error (RRMSE) and objective function (OF) less than 10 and 0.2, respectively. The MEP model leads in providing reliable mathematical expression for the estimation of fc', fSTS and fFS of BA concrete, which can reduce the experimental workload in assessing the strength properties. The study's findings indicated that MEP-based modeling integrated with experimental testing of BA concrete and further cross-validation is effective in predicting the strength parameters of BA concrete.

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