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  1. Ooi CG, Haizee HN, Kando OV, Lua GW, Philip H, Chan SP, et al.
    Med J Malaysia, 2002 Jun;57(2):195-200.
    PMID: 24326650
    We examined the prevalence of diabetes among inpatients in our hospital, the relationship of the diagnoses on admission to diabetes, and the frequency of testing for HbA1c as a marker of long-term glycaemic control, proteinuria, and hypercholesterolaemia. In addition, patients with raised laboratory plasma glucose without a know history of diabetes mellitus, were studied to see if these had been further evaluation. The overall prevalence of diabetes in our hospital was 25.% with the highest prevalence found (37.8%) on medical wards. 10.5% of admissions were due directly to diabetes and a further 58.9% of patients were admitted with illness which were significant related to diabetes. Overall testing rates for HbA31c, proteinuria, and hypercholesterolaemia were less than ideal (51.6, 73.4 and 45.% respectively). Less than 50% of patients without previously diagnosed diabetes but with high plasma glucose values had further evaluation for diabetes. In conclusion, this study has detected a high overall prevalence of diabetes among inpatients in an urban Malaysian hospital. Rates of testing for HbA51c, proteinuria, and hypercholesterolaemia, are disappointingly low, as is further evaluation of patients without known diabetes, but with elevated glucose values. More effective measures to improve the delivery of inpatient diabetes care are needed.
  2. Li L, An J, Zhou M, Qiao L, Zhu S, Yan R, et al.
    Environ Sci Technol, 2018 Dec 18;52(24):14216-14227.
    PMID: 30288976 DOI: 10.1021/acs.est.8b01211
    An integrated source apportionment methodology is developed by amalgamating the receptor-oriented model (ROM) and source-oriented numerical simulations (SOM) together to eliminate the weaknesses of individual SA methods. This approach attempts to apportion and dissect the PM2.5 sources in the Yangtze River Delta region during winter. First, three ROM models (CMB, PMF, ME2) are applied and compared for the preliminary SA results, with information from PM2.5 sampling and lab analysis during the winter seasons. The detailed source category contribution of SOM to PM2.5 is further simulated using the WRF-CAMx model. The two pieces of information from both ROM and SOM are then stitched together to give a comprehensive information on the PM2.5 sources over the region. With the integrated approach, the detailed contributing sources of the ambient PM2.5 at different receptors including rural and urban, coastal and in-land, northern and southern receptors are analyzed. The results are compared with previous data and shows good agreement. This integrative approach is more comprehensive and is able to produce a more profound and detailed understanding between the sources and receptors, compared with single models.
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