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The influence of weather in the forecasting of STEMI occurrence
Session:
Comunicações Orais - Sessão 11 - Síndromes Coronárias Agudas
Speaker:
Vitor Hugo Pereira
Congress:
CPC 2023
Topic:
E. Coronary Artery Disease, Acute Coronary Syndromes, Acute Cardiac Care
Theme:
13. Acute Coronary Syndromes
Subtheme:
13.7 Acute Coronary Syndromes - Other
Session Type:
Comunicações Orais
FP Number:
---
Authors:
Vitor Hugo Pereira; Joao Serafim; Carlos Braga; Patricio Costa
Abstract
<p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="font-size:12pt"><span style="font-family:NewsGotT">Forecasting applied to health data is expanding, but its application to ST-elevation myocardial infarction (STEMI) incidence data has not been explored. Although several works study seasonal and circadian patterns and the influence of the weather in the occurrence of acute myocardial infarction (AMI), none have been conducted in Portugal, to our knowledge.</span></span></span></span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="font-size:12pt"><span style="font-family:NewsGotT">This study aimed to develop predictive models of STEMI incidence in our region. Additionally, our purpose was to find temporal patterns of STEMI onset and assess the relationship between weather variables and STEMI occurrence.</span></span></span></span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="font-size:12pt"><span style="font-family:NewsGotT">Clinical data from 2011 to 2021 on STEMI incidence was collected from our hospital. Meteorological data were obtained for the same region and period. The frequencies of STEMI onset by month, day of the week and time of the day were registered. A time series analysis was performed. ARIMA and Neural Network Autoregression (NNAR) forecasting models were applied to the STEMI time series. Moreover, cross-correlation functions between MI and meteorological time series were explored.</span></span></span></span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="font-size:12pt"><span style="font-family:NewsGotT">A total of 3391 cases were enrolled. There were significant differences in the monthly and circadian distribution of STEMI incidence (p < 0.001), being winter months and morning hours the most frequent. No weekly variation was found. NNAR model was more accurate in predicting STEMI incidence than ARIMA model (MAPE: 11.24 vs. 17.26). For a certain period, our region temperature and solar radiation were inversely related to the number of STEMI cases, but higher air humidity was associated with more events. </span></span></span></span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="font-size:12pt"><span style="font-family:NewsGotT">There is a seasonal and circadian pattern for STEMI onset. Colder, wetter, and less sunny periods are associated with higher STEMI incidence. Neural network models seem more suitable than ARIMA for STEMI incidence forecasting. </span></span></span></span></span></p>
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