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Fulltext A retrospective study to evaluate the effect of type 2 diabetes mellitus on the severity of periodontal disease. A preliminary investigation

Ismail, N., Mohd Ali, S. S., Swaminathan, D.

Ann Dent, 2013;20(1):8-12.
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A preliminary investigation to assess the relationship
in the severity of periodontal disease in diabetics when
compared with non-diabetic subjects. Materials and
Methods: A retrospective, comparative study using
periodontal case notes of 40 subjects (20 Type 2 diabetics,
20 non-diabetics) who were selected based on the
inclusion and exclusion criteria. Severity of periodontal
disease was assessed through number of periodontal
pocket ≥5mm. The results were compared between
subjects whose age, gender and plaque scores are matched
with the test group. Data obtained was then analyzed by
SPSS Version 12. Results: When comparisons were made
between test (Type 2 diabetic) and control (non-diabetic)
groups, there were no significant difference (p>0.05) in
the severity of periodontal disease. However, there was
a clinically mean difference between the two groups.
Conclusions: This preliminary investigation indicated
that the severity of chronic periodontitis, as indicated in
periodontal pocketing, increased in diabetic patients when
compared to non-diabetics clinically, although it was not
statistically significant. The finding of this investigation
was thus not conclusive as it was only a retrospective
study using patients’ case notes. However, the results
are now being further investigated with a proper clinical
trial which examines periodontal parameters and diabetic
status (HbA1c) of the subjects to determine the association
between periodontal disease and diabetes mellitus.
Convergence of tuberculosis and diabetes mellitus: time to individualise pharmaceutical care

Gnanasan S, Ting KN, Wong KT, Mohd Ali S, Muttalif AR, Anderson C

Int J Clin Pharm, 2011 Feb;33(1):44-52.
PMID: 21365392 DOI: 10.1007/s11096-010-9452-3

OBJECTIVE: To assess the feasibility of providing a pharmacist-led pharmaceutical care service to patients with tuberculosis and diabetes mellitus.
SETTING: The study was conducted at a tertiary hospital in the northern region of Peninsular Malaysia. Methods Action research methodology was used.
MAIN OUTCOME MEASURE: Pharmaceutical care issues.
RESULTS: The prevalence of diabetes mellitus among newly diagnosed tuberculosis patients was 15% (53/352). Out of 53 patients identified, 35 participated in the study. Patients' ages ranged between 29 and 73 years (mean of 52 ± 10 years). The male: female ratio was 1.7:1. Pharmaceutical care issues identified by pharmacists were nonadherence, uncontrolled diabetes mellitus, adverse drug reactions and individual patient's medication related problems. Pharmacists were able to intervene and resolve some of the pharmaceutical care issues.
CONCLUSION: Pharmacists played an important role in integrating the provision of care for tuberculosis and diabetes mellitus by providing individualised pharmaceutical care management. There still remains a need to address logistic barriers that impinged on the ability to conduct the pharmaceutical care service to its full potential.
Fulltext Automatic Artifact Removal in EEG of Normal and Demented Individuals Using ICA-WT during Working Memory Tasks

Al-Qazzaz NK, Hamid Bin Mohd Ali S, Ahmad SA, Islam MS, Escudero J

Sensors (Basel), 2017 Jun 08;17(6).
PMID: 28594352 DOI: 10.3390/s17061326

Characterizing dementia is a global challenge in supporting personalized health care. The electroencephalogram (EEG) is a promising tool to support the diagnosis and evaluation of abnormalities in the human brain. The EEG sensors record the brain activity directly with excellent time resolution. In this study, EEG sensor with 19 electrodes were used to test the background activities of the brains of five vascular dementia (VaD), 15 stroke-related patients with mild cognitive impairment (MCI), and 15 healthy subjects during a working memory (WM) task. The objective of this study is twofold. First, it aims to enhance the recorded EEG signals using a novel technique that combines automatic independent component analysis (AICA) and wavelet transform (WT), that is, the AICA-WT technique; second, it aims to extract and investigate the spectral features that characterize the post-stroke dementia patients compared to the control subjects. The proposed AICA-WT technique is a four-stage approach. In the first stage, the independent components (ICs) were estimated. In the second stage, three-step artifact identification metrics were applied to detect the artifactual components. The components identified as artifacts were marked as critical and denoised through DWT in the third stage. In the fourth stage, the corrected ICs were reconstructed to obtain artifact-free EEG signals. The performance of the proposed AICA-WT technique was compared with those of two other techniques based on AICA and WT denoising methods using cross-correlation X C o r r and peak signal to noise ratio ( P S N R ) (ANOVA, p ˂ 0.05). The AICA-WT technique exhibited the best artifact removal performance. The assumption that there would be a deceleration of EEG dominant frequencies in VaD and MCI patients compared with control subjects was assessed with AICA-WT (ANOVA, p ˂ 0.05). Therefore, this study may provide information on post-stroke dementia particularly VaD and stroke-related MCI patients through spectral analysis of EEG background activities that can help to provide useful diagnostic indexes by using EEG signal processing.

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