METHODS: A user-friendly software was developed to accurately predict the individual size-specific dose estimation of paediatric patients undergoing computed tomography (CT) scans of the head, thorax, and abdomen. The software includes a calculation equation developed based on a novel SSDE prediction equation that used a population's pre-determined percentage difference between volume-weighted computed tomography dose index (CTDIvol) and SSDE with age. American Association of Physicists in Medicine (AAPM RPT 204) method (manual) and segmentation-based SSDE calculators (indoseCT and XXautocalc) were used to assess the proposed software predictions comparatively.
RESULTS: The results of this study show that the automated equation-based calculation of SSDE and the manual and segmentation-based calculation of SSDE are in good agreement for patients. The differences between the automated equation-based calculation of SSDE and the manual and segmentation-based calculation are less than 3%.
CONCLUSION: This study validated an accurate SSDE calculator that allows users to enter key input values and calculate SSDE.
IMPLICATION FOR PRACTICE: The automated equation-based SSDE software (PESSD) seems a promising tool for estimating individualised CT doses during CT scans.
METHOD: A facility-based cross-sectional study was conducted from February 2019 to June 2020 involving 217 participants who were visiting dermatology clinics to seek treatment for dandruff conditions. Information on the socio-demographic characteristics and hair care behaviors of the participants was obtained. Isolation and identification of Malassezia species from scalp scrapings using cultural and biochemical tests were carried out.
RESULTS: Out of the 217 participants with dandruff, 111 (51.15%) were positive for Malassezia fungi. One hundred forty (140) Malassezia isolates were collected from the 111 positive participants. Further study of the isolates yielded three etiologic species: Malassezia globosa (67.15%), M. furfur (21.70%), and M. restricta (12.15%). Demographic characteristics, namely gender (AOR = 2.605; 95%CI: 1.427 - 4.757) and age (AOR = 2.667; 95%CI: 1.046 - 6.795), as well as hair care behaviors, namely use of hair oil (AOR = 2.964; 95%CI: 1.288 - 6.820), were associated with the presence of Malassezia species. However, the use of anti-dandruff shampoo (AOR = 2.782; 95%CI: 1.301 - 10.993) was negatively associated with the presence of Malassezia species among the participants with dandruff conditions. These findings open opportunities to devise effective prevention, management, and control measures for Malassezia-based dandruff conditions.