RESULTS: Prediction in two and three state classification systems with several thresholds are provided. Our prediction method achieved the accuracy level upto 90% for training and 88% for test data sets. Three state prediction results provide a maximum 65% accuracy for training and 63% for the test data. Applicability of neural networks for ASA prediction has been confirmed with a larger data set and wider range of state thresholds. Salient differences between a linear and exponential network for ASA prediction have been analysed.
AVAILABILITY: Online predictions are freely available at: http://www.netasa.org. Linux ix86 binaries of the program written for this work may be obtained by email from the corresponding author.
METHOD: This retrospective study utilised the Malaysian National Cardiovascular Disease- ACS (NCVD-ACS) registry. Consecutive patient data of those ≥80 years old admitted with ACS at 24 participating hospitals from 2008 to 2017 (n = 3162) were identified. Demographics, in-hospital intervention, and evidence-based pharmacotherapies over the 10-years were examined and compared across groups of interests using the Chi-square test. Multivariate logistic regression was used to calculate the adjusted odds ratio of receiving individual therapies according to patients' characteristics.
RESULTS: Octogenarians made up 3.8% of patients with ACS in the NCVD-ACS registry (mean age = 84, SD ± 3.6) from 2008 until 2017. The largest ethnic group was Chinese (44%). Most octogenarians (95%) have multiple cardiovascular risk factors, with hypertension (82%) being the main. Non-ST-elevation myocardial infarction (NSTEMI) predominated (38%, p