METHODS: This is a retrospective cohort study utilizing data from the National Cardiovascular Disease (NCVD)-PCI registry. The data collected (N = 28,007) were split into training set (n = 24,409) and testing set (n = 3598). Four predictive models (logistic regression [LR], random forest method, support vector machine [SVM], and artificial neural network) were developed and validated. The outcome on risk prediction were compared.
RESULTS: The demographic and clinical features of patients in the training and testing cohorts were similar. Patients had mean age ± standard deviation of 58.15 ± 10.13 years at admission with a male majority (82.66%). In over half of the procedures (50.61%), patients had chronic stable angina. Within 1 year of follow up mortality, target vessel revascularization (TVR), and composite event of mortality and TVR were 3.92%, 9.48%, and 12.98% respectively. LR was the best model in predicting mortality event within 1-year post-PCI (AUC: 0.820). SVM had the highest discrimination power for both TVR event (AUC: 0.720) and composite event of mortality and TVR (AUC: 0.720).
CONCLUSIONS: This study successfully identified optimal prediction models with the good discriminatory ability for mortality outcome and good discrimination ability for TVR and composite event of mortality and TVR with a simple machine learning framework.
OBJECTIVES & METHODOLOGY: This systematic narrative review examines articles published from 1990 to 2017, generated from Ovid, MEDLINE, CINAHL, and PubMed. The search was also supplemented by an examination of reference lists for related articles via Scopus. We included 105 articles.
FINDINGS: We found that the type of unmet needs in stroke survivors and the contributing factors were substantially different from their caregivers. The unmet needs in stroke survivors ranged from health-related needs to re-integration into the community; while the unmet needs in stroke caregivers ranged from information needs to support in caring for the stroke survivors and caring for themselves. Additionally, the unmet needs in both groups were associated with different factors.
CONCLUSION: More research is required to understand the unmet needs of stroke survivors and stroke caregivers to improve the overall post-stroke care services.
OBJECTIVES: This study examined the speech and hearing status of Malay-speaking children with CLP residing in Kuala Lumpur.
METHODS: Parents whose children were between the age of 5 and 7 years were recruited via the Cleft Lip and Palate Association of Malaysia (CLAPAM) registry. Parents completed a survey and the children completed a speech and hearing assessment at the Audiology and Speech Sciences Clinic, Universiti Kebangsaan Malaysia.
OUTCOMES: Speech measures include nasality rating, nasalance scores, articulation errors and speech intelligibility rating, while hearing measures include hearing thresholds and tympanometry results for each child.
RESULTS: Out of 118 registered members who fulfilled the inclusion criteria, 21 agreed to participate in the study. The overall speech and hearing status of children in this sample were poor. Only four (19%) participants had normal speech intelligibility rating and normal hearing bilaterally. In terms of overall cleft management, only four (19%) participants were seen by a cleft team while seven (33%) had never had their hearing tested prior to this study.
CONCLUSION: Participants in this sample had poor outcomes in speech and hearing and received uncoordinated and fragmented cleft care. This finding calls for further large scale research and collaborative efforts into improving and providing centralised, multidisciplinary care for children born with CLP.