MATERIALS AND METHODS: This is a prospective cross-sectional study on the data obtained from Hospital Universiti Sains Malaysia (Hospital USM) from Jun 2018 until May 2019. Blood samples were taken via a single prick from venous blood and sent separately using 1ml heparinised syringe and were analysed immediately in ED using BGA (Radiometer, ABL800 FLEX, Denmark) and another sample was sent to the central laboratory of Hospital USM and analysed by BCA (Architect, C8000, USA). Only patients who had potassium levels ≥5.0mmol/L on blood gas results were included. A total of 173 sample pairs were included. The correlation and agreement were evaluated using Passing and Bablok regression, Linear Regression and Bland-Altman test.
RESULT: Of the 173 sample pairs, the median of potassium level based on BGA and BCA were 5.50mmol/L (IQR: 1.00) and 5.90mmol/L (IQR: 0.95) respectively. There was significant correlation between two measurements (p<0.001, r: 0.36). The agreement between the two measurements showed within acceptable mean difference which was 0.27 mmol/L with 95% limit of agreement were 1.21mmol/L to 1.73mmol/L.
CONCLUSION: The result of blood gas can be used as a guide for initial treatment of hyperkalaemia in critical cases where time is of the essence. However, BCA result is still the definitive value.
Objectives: The objective of the present study was to demonstrate water quality modelling methodology in reviewing existing policies for Malaysian river catchments based on an example case study.
Methods: The MIKE 11 software developed by the Danish Hydraulic Institute was used to model the main pollutant point sources within the study area - sand mining and aquaculture. Water quality data were obtained for six river stations from 2000 to 2015. All sand mining and aquaculture locations and approximate production capacities were quantified by ground survey. Modelling of the sand washing effluents was undertaken with the advection-dispersion module due to the nature of the fine sediment. Modelling of the fates of aquaculture deposits required both advection-dispersion and Danish Hydraulic Institute ECO Lab modules to simulate the detailed interactions between water quality determinants.
Results: According to the Malaysian standard, biochemical oxygen command (BOD) and ammonium (NH4) parameters fell under Class IV at most of the river reaches, while the dissolved oxygen (DO) parameter varied between Classes II to IV. Total suspended solids (TSS) fell within Classes IV to V along the mid river reaches of the catchment.
Discussion: Comparison between corresponding constituents and locations showed that the water quality model reproduced the long-term duration exceedance for the main body of the curves. However, the water quality model underestimated the infrequent high concentration observations. A standard effluent disposal was proposed for the development of legislation and regulations by authorities in the district that could be replicated for other similar catchments.
Conclusions: Modelling pollutants enables observation of trends over the years and the percentage of time a certain class is exceeded for each individual pollutant. The catchment did not meet Class II requirements and may not be able to reach Class I without extensive improvements in the quality and reducing the quantity of both point and non-point effluent sources within the catchment.
Competing Interests: The authors declare no competing financial interests.
AIM: We investigated the association between air pollution exposure and IBD.
METHODS: The European Prospective Investigation into Cancer and Nutrition cohort was used to identify cases with Crohn's disease (CD) (n = 38) and ulcerative colitis (UC) (n = 104) and controls (n = 568) from Denmark, France, the Netherlands, and the UK, matched for center, gender, age, and date of recruitment. Air pollution data were obtained from the European Study of Cohorts for Air Pollution Effects. Residential exposure was assessed with land-use regression models for particulate matter with diameters of <10 μm (PM10), <2.5 μm (PM2.5), and between 2.5 and 10 μm (PMcoarse), soot (PM2.5 absorbance), nitrogen oxides, and two traffic indicators. Conditional logistic regression analyses were performed to calculate odds ratios (ORs) with 95 % confidence intervals (CIs).
RESULTS: Although air pollution was not significantly associated with CD or UC separately, the associations were mostly similar. Individuals with IBD were less likely to have higher exposure levels of PM2.5 and PM10, with ORs of 0.24 (95 % CI 0.07-0.81) per 5 μg/m(3) and 0.25 (95 % CI 0.08-0.78) per 10 μg/m(3), respectively. There was an inverse but nonsignificant association for PMcoarse. A higher nearby traffic load was positively associated with IBD [OR 1.60 (95 % CI 1.04-2.46) per 4,000,000 motor vehicles × m per day]. Other air pollutants were positively but not significantly associated with IBD.
CONCLUSION: Exposure to air pollution was not found to be consistently associated with IBD.