MATERIALS AND METHODS: Two hundred retinal samples of right eye [57.0% females (n = 114) and 43.0% males (n = 86)] were selected from baseline visit. A custom-written software was used for vessel segmentation. Vessel segmentation is the process of transforming two-dimensional color images into binary images (i.e. black and white pixels). The circular area of approximately 2.6 optic disc radii surrounding the center of optic disc was cropped. The non-vessels fragments were removed. FracLac was used to measure the fractal dimension and vessel density of retinal vessels.
RESULTS: This study suggested that 14.1% of the region of interest (i.e. approximately 2.6 optic disk radii) comprised retinal vessel structure. Using correlation analysis, vessel density measurement and fractal dimension estimation are linearly and strongly correlated (R = 0.942, R(2) = 0.89, p
OBJECTIVE: The aim of this study was to evaluate the effectiveness of a Web-based continuing professional development (CPD) program on "general intention" of the health carers to perform daily mouth cleaning for stroke patients using the theory of planned behavior (TPB).
METHODS: A double-blind cluster randomized controlled trial was conducted among 547 stroke care providers across 10 hospitals in Malaysia. The centers were block randomized to receive either (1) test intervention (a Web-based CPD program on providing oral hygiene care to stroke patients using TPB) or (2) control intervention (a Web-based CPD program not specific to oral hygiene). Domains of TPB: "attitude," "subjective norm" (SN), "perceived behavior control" (PBC), "general intention" (GI), and "knowledge" related to providing oral hygiene care were assessed preintervention and at 1 month and 6 months postintervention.
RESULTS: The overall response rate was 68.2% (373/547). At 1 month, between the test and control groups, there was a significant difference in changes in scores of attitude (P=.004) and subjective norm (P=.01), but not in other TPB domains (GI, P=.11; PBC, P=.51; or knowledge, P=.08). At 6 months, there were significant differences in changes in scores of GI (P=.003), attitude (P=.009), SN (P
MATERIALS AND METHODS: A large scale survey of 13 centers in Malaysia was conducted involving 806 nurses in relation to oral hygiene care intentions and practices. In addition, information on personal and environmental factors was collected.
RESULTS: The response rate was 95.6% (778/806). The domains of the Theory of Planned Behavior were significantly associated with general intention to perform oral hygiene care: attitudes (β = 0.21, p
BACKGROUND: Oral hygiene care following stroke is important as the mouth can act as a reservoir for opportunistic infections that can lead to aspirational pneumonia.
DESIGN: A national cross-sectional survey was conducted in Malaysia among public hospitals where specialist stroke rehabilitation care is provided.
METHODS: All (16) hospitals were invited to participate, and site visits were conducted. A standardised questionnaire was employed to determine nurses' oral health knowledge for stroke care and existing clinical practices for oral hygiene care. Variations in oral health knowledge and clinical practices for oral hygiene care were examined.
RESULTS: Questionnaires were completed by 806 nurses across 13 hospitals. Oral health knowledge scores varied among the nurses; their mean score was 3.7 (SD 1.1) out of a possible 5.0. Approximately two-thirds (63.6%, n = 513) reported that some form of "mouth cleaning" was performed for stroke patients routinely. However, only a third (38.3%, n = 309) reported to perform or assist with the clinical practice of oral hygiene care daily. Their oral health knowledge of stroke care was associated with clinical practices for oral hygiene care (p
MATERIALS AND METHODS: A total of 84 patients with treatment-naïve invasive breast cancer were enrolled into this retrospective study. The tumour stroma ratio (TSR) was estimated from the amount of tumour stroma in the pathology specimen of the breast tumour. The MRI images of the patients were analysed based on Breast Imaging Reporting and Data Systems (ACR-BIRADS) for qualitative features which include T2- weighted, diffusion-weighted images (DWI) and dynamic contrast-enhanced (DCE) for kinetic features. The mean signal intensity (SI) of Short Tau Inversion Recovery (STIR), with the ratio of STIR of the lesion and pectoralis muscle (L/M ratio) and apparent diffusion coefficient (ADC) value, were measured for the quantitative features. Correlation tests were performed to assess the relationship between TSR and MRI features.
RESULTS: There was a significant correlation between the margin of mass, enhancement pattern, and STIR signal intensity of breast cancer and TSR. There were 54.76% (n = 46) in the low stromal group and 45.24% (n = 38) in the high stromal group. A significant association were seen between the margin of the mass and TSR (p = 0.034) between the L/M ratio (p <0.001), and between STIR SI of the lesion and TSR (p<0.001). The median L/M ratio was significantly higher in the high TSR group as compared to the lower TSR group (p < 0.001).
CONCLUSION: Breast cancer with high stroma had spiculated margins, lower STIR signal intensity, and a heterogeneous pattern of enhancement. Hence, in this preliminary study, certain MRI features showed a potential to predict TSR.
METHODS: Hospitalised adult patients on EID gentamicin were selected. We considered a DFP of between 2 and 8 h as appropriate. Data from two blood samples (2 and 6 h postdose) from each patient were used to estimate the duration of DFP (i.e. DFP method 1). DFP was also calculated for the same patient using an empirically estimated elimination rate constant (Ke ) and the same 6 h postdose concentration value (DFP method 2). Correlation between the two methods was made. An alternative graphical method to estimate DFP was attempted.
KEY FINDINGS: Correlation between Ke and age was favourable (r = -0.453; P = 0.001). Ke derived from this empirical relationship was used to estimate DFP method 2. DFP method 1 correlated well with DFP method 2 (r = 0.742; P