Machine learning versus classical electrocardiographic criteria for echocardiographic left ventricular hypertrophy in a pre-participation cohort.

BACKGROUND: Classical electrocardiographic (ECG) criteria for left ventricular hypertrophy (LVH) are well studied in older populations and patients with hypertension. Their utility in young pre-participation cohorts is unclear. AIMS: We aimed to develop machine learning models for detection of echocardiogram-diagnosed LVH from ECG, and compare these models with classical criteria. METHODS: Between November 2009 and December 2014, pre-participation screening ECG and subsequent echocardiographic data was collected from 17 310 males aged 16 to 23, who reported for medical screening prior to military conscription. A final diagnosis of LVH was made during echocardiography, defined by a left ventricular mass index >115 g/m2. The continuous and threshold forms of classical ECG criteria (Sokolow-Lyon, Romhilt-Estes, Modified Cornell, Cornell Product, and Cornell) were compared against machine learning models (Logistic Regression, GLMNet, Random Forests, Gradient Boosting Machines) using receiver-operating characteristics curve analysis. We also compared the important variables identified by machine learning models with the input variables of classical criteria. RESULTS: Prevalence of echocardiographic LVH in this population was 0.82% (143/17310). Classical ECG criteria had poor performance in predicting LVH. Machine learning methods achieved superior performance: Logistic Regression (area under the curve [AUC], 0.811; 95% confidence interval [CI], 0.738-0.884), GLMNet (AUC, 0.873; 95% CI, 0.817-0.929), Random Forest (AUC, 0.824; 95% CI, 0.749-0.898), Gradient Boosting Machines (AUC, 0.800; 95% CI, 0.738-0.862). CONCLUSIONS: Machine learning methods are superior to classical ECG criteria in diagnosing echocardiographic LVH in the context of pre-participation screening.

Awareness and Attitudes of Community-Dwelling Individuals in Singapore towards Participating in Advance Care Planning.

INTRODUCTION: Advance care planning (ACP) is an important aspect of end-of-life care that has been shown to improve patient autonomy in decision-making and reduce stress for surviving family members. Given the rapidly ageing population in Singapore, a greater emphasis on end-of-life care planning is needed. This study therefore sought to examine the awareness and attitudes of the general Singaporean community towards participating in ACP, which are not known hitherto. MATERIALS AND METHODS: A 24-item interviewer-administered questionnaire was constructed and administered via door-to-door survey amongst community-dwelling residents living in Housing and Development Board (HDB) flats across Singapore, selected via a two-stage stratified random sampling. RESULTS: Of the 406 completed surveys, 14.4% of respondents had heard of ACP (n = 58), mostly through the media (67.9%), from family and friends (21.4%) and healthcare providers (21.4%). Only 26.8% of those who had previously heard of ACP knew how to begin an ACP discussion and 12.5% of them had a prior ACP discussion. After education, the majority of respondents were willing to begin an ACP discussion (n = 236, 60.1%). Being of an older age, having a life threatening illness, and having more knowledge about ACP were significant factors associated with willingness to have an ACP discussion. Barriers included perceiving oneself as still healthy and preferring the family to make decisions instead. CONCLUSION: There is a low awareness but high expressed willingness to engage in an ACP discussion amongst the Singaporean community. More efforts are needed to educate the public about ACP, engage the family unit and correct the present misconceptions.

The effectiveness of a shared conference experience in improving undergraduate medical and nursing students' attitudes towards inter-professional education in an Asian country: a before and after study.

BACKGROUND: In recent years, increasing emphasis has been placed on the importance of collaboration within multi-disciplinary healthcare teams, so as to facilitate holistic patient care and thus allow improved treatment outcomes. There is hence an urgent need to educate healthcare undergraduates early in their professional careers on the importance of and complexities involved in cooperating with counterparts from other allied healthcare professions. In conjunction with this, a milestone student-led conference for undergraduate students, the 9th Student Medical-Nursing Education Conference (SMEC), was organised in 2013 to provide a unique opportunity for shared learning among the entire cohort of undergraduate medical and nursing students in Singapore matriculating in that year. METHODS: This study evaluated the effectiveness of the 9th SMEC 2013 as a shared conference experience in improving the attitudes of undergraduate medical and nursing students in Singapore towards inter-professional education (IPE). A 19-point Readiness for Inter-Professional Learning Scale (RIPLS) questionnaire comprising three subscales was administered to participants both before and after the conference. 352 responses were collected, giving a response rate of 75.1 %. Results were analysed using paired-samples t-tests with statistical significance set at p = 0.05. RESULTS: Improvements in overall scores for both medical and nursing students were reported for all three RIPLS subscales. Examining the RIPLS items individually, significant improvement in scores for both medical and nursing students was obtained in all 19 items. Prior exposure to IPE activities was not a predictor of improvement in IPE attitudes. CONCLUSION: The authors propose that student-led jointly-organised conference experiences are effective in improving healthcare students' attitudes towards IPE. This study provides valuable insights to facilitate the development of further IPE programs to allow for the rapid and effective promotion of cooperation and collaboration between students across various healthcare disciplines.