METHODS: This was a cross sectional study involving 197 T2DM patients on insulin from two government primary health clinics in Gombak. Physician-patient interaction satisfaction was assessed using Skala Kepuasan Interaksi Perubatan (SKIP-11) consisting of 3 subdomains (Distress Relief, Rapport and Interaction Outcome). Medication adherence level was measured using a single item selfreport question. Data analysis for descriptive, inferential and multivariate analysis statistics were performed.
RESULTS: The mean age of the study participants was 57.12 (SD: 9.27). Majority were Malay, female, unemployed with mean BMI of 27.5. Majority reported full adherence (62.9%). High scores in the Interaction Outcome subdomain was associated with better adherence. Factors associated with high scores in this subdomain included patient education level, number of oral hypoglycaemic agent and type of insulin regime taken. This study also found that high scores in the Interaction Outcome domain is associated with lower HbA1c (p<0.05).
CONCLUSION: Physician-patient interaction satisfaction is an important factor in achieving better medication adherence which also leads to better glycaemic control in this group of patients. There is a need to identify strategies to improve satisfaction in this domain to improve patient adherence.
MATERIALS AND METHODS: A literature review was performed following the PRISMA guidelines. Systematic searches were performed in PubMed, Scopus, Cochrane and Embase databases from the earliest record up to September 2022. Related studies on deep learning models for radiotherapy toxicity prediction were selected based on predefined PICOS criteria.
RESULTS: Fourteen studies of radiotherapy-treated patients on different types of cancer [prostate (n=2), HNC (n=4), liver (n=2), lung (n=4), cervical (n=1), and oesophagus (n=1)] were eligible for inclusion in the systematic review. Information regarding patient characteristics and model development was summarized. Several approaches, such as ensemble learning, data augmentation, and transfer learning, that were utilized by selected studies were discussed.
CONCLUSION: Deep learning techniques are able to produce a consistent performance for toxicity prediction. Future research using large and diverse datasets and standardization of the study methodologies are required to improve the consistency of the research output.
Methods: Extraction of the human hair shaft proteins was performed using a newly developed alkaline solubilisation method. The extracts were profiled by 2-dimensional electrophoresis and resolved protein spots were identified by mass spectrometry and queried against the human hair database. The study was then followed-up by immunoblotting of the identified hair shaft keratin of interest using commercially available antibodies.
Results: Separation of the human hair shaft proteins by 2-dimensional electrophoresis generated improved and highly resolved profiles. Comparing the hair shaft protein profiles of 10 female with 10 male subjects and their identification by mass spectrometry and query of the human hair database showed significant altered abundance of truncated/processed type-II keratin peptides K81 (two spots), K83 (one spot) and K86 (three spots). The 2-dimensional electrophoresis profiling of 30 hair shaft samples taken from women of similar age range but from three distinctive ethnic subpopulations in Malaysia further showed significant altered abundance of one type-I and four type-II truncated/processed keratin peptides including K33b, K81, K83 and K86 (2 spots) between at least two of the ethnic groups. When a followed-up immunoblotting experiment was performed to detect the relative expression of the K86 peptides using commercialised antibodies, similar trends of expression were obtained. The present data, when taken together, demonstrated the potential use of keratin peptide signatures of the human hair shaft to distinguish gender and ethnicity although this needs to be further substantiated in a larger scale study.
METHOD: This cross-sectional study was conducted between April to June 2020 in Malaysia. Patients who have recovered from COVID-19 for at least 1 month and their family members who were tested with negative results, Malaysian and aged 18-65 years old were purposively sampled. Cold call method was employed to recruit patients while their family members were recruited by their recommendations. Telephone interviews were conducted with the participants after obtaining their verbal consent.
RESULTS: A total of 18 participants took part in this study. Three themes emerged from the interviews: (Ι) experience of stigmatization, (ΙΙ) perspective on disease disclosure, and (ΙΙΙ) suggestion on coping and reducing stigma. The participants expressed their experiences of being isolated, labelled, and blamed by the people surrounding them including the health care providers, neighbours, and staff at the service counters. Some respondents expressed their willingness to share their experience with others by emphasizing the importance of taking preventive measure in order to stop the chain of virus transmission and some of them chose to disclose this medical history for official purpose because of fear and lack of understanding among the public. As suggested by the respondents, the approaches in addressing social stigma require the involvement of the government, the public, health care provider, and religious leader.
CONCLUSION: Individuals recovered from COVID-19 and their families experienced social stigma. Fear and lack of public understanding of the COVID-19 disease were the key factors for non-disclosure. Some expressed their willingness to share their experience as they perceived it as method to increase public awareness and thereby reducing social stigma. Multifaceted approaches with the involvement of multiple parties including the government, non-governmental organization as well as the general public were recommended as important measures to address the issues of social stigma.
Methods: A cross-sectional study involving 503 drug naive subjects (163 males, aged 30-65 years old (mean age ± SD = 47.4 ± 8.3 years)) divided into MS, COB and NC groups. COB was defined as central obesity (waist circumference (WC) males ≥90 cm, females ≥80 cm) in the absence of MS according to the International Diabetes Federation 2006. Fasting blood levels of tPA and PAI-1were analyzed.
Results: MS and COB had significantly higher concentration of all biomarkers compared to NC. The MS group had significantly higher concentration of tPA and PAI-1 compared to COB. WC and HDL-c had significant correlation with all biomarkers (tPA p < 0.001, PAI-1 p < 0.001). Fasting plasma glucose and diastolic blood pressure were independent predictors after correcting for confounding factors.
Conclusion: Central obesity with or without MS both demonstrated enhanced prothrombogenesis. This suggests that simple obesity possibly increases the risk of coronary artery disease in part, via increased susceptibility to thrombogenesis.