Displaying publications 21 - 22 of 22 in total

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  1. The association between the reflux symptoms index and nasal symptoms among patients with non-allergic rhinitis
    Hamizan AW, Choo YY, Loh PV, Abd Talib NF, Mohd Ramli MF, Zahedi FD, et al.
    J Laryngol Otol, 2021 Feb;135(2):142-146.
    PMID: 33494850 DOI: 10.1017/S0022215120002492
    BACKGROUND: Laryngopharyngeal reflux symptoms assessed with the reflux symptom index can overlap with non-allergic rhinitis symptoms. This study aims to explore the association between the reflux symptom index and nasal symptoms in non-allergic rhinitis patients.

    METHODS: A cross-sectional study was conducted on consecutive adults with non-allergic rhinitis. The reflux symptom index (score of more than 13 = laryngopharyngeal reflux) and nasal symptoms (categorised as mild (total score of 0-3), moderate (4-7) or severe (8-12)) were assessed.

    RESULTS: The study included 227 participants (aged 58.64 ± 12.39 years, 59.5 per cent female). The reflux symptom index scores increased with total nasal symptom scores (mild vs moderate vs severe, 8.61 ± 6.27 vs 12.94 ± 7.4 vs 16.40 ± 8.10; p < 0.01). Logistic regression indicated that laryngopharyngeal reflux is more likely in patients with severe nose block (odds ratio 5.47 (95 per cent confidence interval = 2.16-13.87); p < 0.01).

    CONCLUSION: Laryngopharyngeal reflux symptoms are associated with nasal symptom severity, and nasal symptoms should be primarily treated. Those with predominant nose block and laryngopharyngeal reflux symptoms are more likely to have laryngopharyngeal reflux.

  2. Water quality assessment and analysis of spatial patterns and temporal trends
    Gazzaz NM, Yusoff MK, Juahir H, Ramli MF, Aris AZ
    Water Environ Res, 2013 Aug;85(8):751-66.
    PMID: 24003601
    This study investigated relationships of a water quality index (WQI) with multiple water quality variables (WQVs), explored variability in water quality over time and space, and established linear and non-linear models predictive of WQI from raw WQVs. Data were processed using Spearman's rank correlation analysis, multiple linear regression, and artificial neural network modeling. Correlation analysis indicated that from a temporal perspective, the WQI, temperature, and zinc, arsenic, chemical oxygen demand, sodium, and dissolved oxygen concentrations increased, whereas turbidity and suspended solids, total solids, nitrate nitrogen (NO3-N), and biochemical oxygen demand concentrations decreased with year. From a spatial perspective, an increase with distance of the sampling station from the headwater was exhibited by 10 WQVs: magnesium, calcium, dissolved solids, electrical conductivity, temperature, NO3-N, arsenic, chloride, potassium, and sodium. At the same time, the WQI; Escherichia coli bacteria counts; and suspended solids, total solids, and dissolved oxygen concentrations decreased with distance from the headwater. Lastly, regression and artificial neural network models with high prediction powers (81.2% and 91.4%, respectively) were developed and are discussed.
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