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Original Research Article | OPEN ACCESS

Serological Prediction of infections in Diabetic Patients with Diabetes Ketoacidosis in Penang, Malaysia

Syed Wasif Gillani1 , Syed Azhar Syed Sulaiman1, Shameni Sundram2, Yelly Oktavia Sari3,4, Mirza Baig5, Mian Muhammad Shahid Iqbal6

1School of Pharmaceutical Sciences, Universiti Sains Malaysia, Pulau Pinang, Malaysia; 2Doctor, Hospital Pulau Pinang, 10990, Residential Street, Penang; 3Faculty of Pharmacy, Andalas University, Padang 25163, Indonesia; 4Discipline of Clinical Pharmacy, School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800 Penang; 5Department of Clinical Pharmacy, Aimst University, Kedah; 6School of Pharmacy and Health Sciences, International Medical University, Malaysia.

For correspondence:-  Syed Gillani   Email: wasifgillani@gmail.com   Tel:+60174203027

Received: 25 August 2011        Accepted: 4 July 2012        Published: 18 October 2012

Citation: Gillani SW, Syed Sulaiman SA, Sundram S, Sari YO, Baig M, Shahid Iqbal MM. Serological Prediction of infections in Diabetic Patients with Diabetes Ketoacidosis in Penang, Malaysia. Trop J Pharm Res 2012; 11(5):815-821 doi: 10.4314/tjpr.v11i5.16

© 2012 The authors.
This is an Open Access article that uses a funding model which does not charge readers or their institutions for access and distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0) and the Budapest Open Access Initiative (http://www.budapestopenaccessinitiative.org/read), which permit unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited..

Abstract

Purpose: To determine the prevalence and predictors of infection in diabetic patients with diabetic ketoacidosis (DKA) who were ≥18 years.
Methods: A retrospective cohort design was adopted for this study. A total of 967 diabetes ketoacidosis patients from Hospital Pulau Pinang for the 3-year period, Jan 2008 - Dec 2010, were identified and enrolled. The data were analysed, as appropriate, by Student t-test and ANOVA for the normally distributed data, Mann-Whitney U rank sum and Kruskall-Wallis tests for continuous, non-nominal data and Chi-square for dichotomous variables. Odd Ratios with 95% confidence interval (CI) were also presented where applicable.
Results: Of the total diabetes ketoacidosis patients, 112 (11.6 %) were cases without infection, 679 (70.2 %) bacterial infection cases and 176 (18.2 %) presumed viral infection cases. The mean white blood count (WBC) for all the patients was 18,177 ± 9,431 while 721 (74.6 %) had leukocytosis, defined by WBC ≥ 15,000/mm3. WBC differential, leukocytosis, as well as sex and body temperature were not significant predictors (p >.05) of bacterial infection. There was, however, a significant difference (p <.05) in terms of age within groups, as those > 57 years showed a higher rate of infection.
Conclusion: The infection rate in elderly patients with DKA is high and a majority of them lack clinical evidence. Age has a significant effect on the rate and prediction of infection. Leukocytosis is commonly found but severe ketoacidosis was more likely than the presence of infection.

Keywords: Diabetes mellitus, Diabetes ketoacidosis, Infections, Predictors, White blood cells

Impact Factor
Thompson Reuters (ISI): 0.523 (2021)
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