Weather Impact on Acute Myocardial Infarction Hospital Admissions With a New Model for Prediction: A Nationwide Study

Introduction: Cardiovascular disease is one of the leading causes of mortality worldwide. Acute myocardial infarction (AMI) is associated with weather change. The study aimed to investigate if weather change was among the risk factors of coronary artery disease to influence AMI occurrence in Taiwan and to generate a model to predict the probabilities of AMI in specific weather and clinical conditions.Method: This observational study utilized the National Health Insurance Research Database and daily weather reports from Taiwan Central Weather Bureau to evaluate the discharge records of patients diagnosed with AMI from various hospitals in Taiwan between January 1, 2008 and December 31, 2011. Generalized additive models (GAMs) were used to estimate the effective parameters on the trend of the AMI incidence rate with respect to the weather and health factors in the time-series data and to build a model for predicting AMI probabilities.Results: A total of 40,328 discharges were listed. The minimum temperature, maximum wind speed, and antiplatelet therapy were negatively related to the daily AMI incidence; however, a drop of 1° when the air temperature was below 15°C was associated with an increase of 1.6% of AMI incidence. By using the meaningful parameters including medical and weather factors, an estimated GAM was built. The model showed an adequate correlation in both internal and external validation.Conclusion: An increase in AMI occurrence in colder weather has been evidenced in the study, but the influence of wind speed remains uncertain. Our analysis demonstrated that the novel GAM model can predict daily onset rates of AMI in specific weather conditions.

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Hospital Admissions for Acute Myocardial Infarction Before and After Lockdown According to Regional Prevalence of COVID-19 and Patient Profile

SSRN Electronic Journal ◽

10.2139/ssrn.3619808 ◽

2020 ◽

Author(s):

Jules Mesnier ◽

Yves Cottin ◽

Pierre Coste ◽

Emile Ferrari ◽

Francois Schiele ◽

...

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Hospital Admissions ◽

Patient Profile ◽

Before And After

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The Use of Odd and Even Class Wind Speed Time Series of Distribution Histogram to Estimate Weibull Parameters

International Journal of Renewable Energy Development ◽

10.14710/ijred.7.2.139-150 ◽

2018 ◽

Vol 7 (2) ◽

pp. 139-150 ◽

Cited By ~ 1

Author(s):

Adekunlé Akim Salami ◽

Ayité Sénah Akoda Ajavon ◽

Mawugno Koffi Kodjo ◽

Seydou Ouedraogo ◽

Koffi-Sa Bédja

Keyword(s):

Time Series ◽

Wind Speed ◽

Time Series Data ◽

Empirical Method ◽

Likelihood Method ◽

Series Data ◽

New Approach ◽

Weibull Parameters ◽

Distribution Histogram ◽

Mean Wind Speed

In this article, we introduced a new approach based on graphical method (GPM), maximum likelihood method (MLM), energy pattern factor method (EPFM), empirical method of Justus (EMJ), empirical method of Lysen (EML) and moment method (MOM) using the even or odd classes of wind speed series distribution histogram with 1 m/s as bin size to estimate the Weibull parameters. This new approach is compared on the basis of the resulting mean wind speed and its standard deviation using seven reliable statistical indicators (RPE, RMSE, MAPE, MABE, R2, RRMSE and IA). The results indicate that this new approach is adequate to estimate Weibull parameters and can outperform GPM, MLM, EPF, EMJ, EML and MOM which uses all wind speed time series data collected for one period. The study has also found a linear relationship between the Weibull parameters K and C estimated by MLM, EPFM, EMJ, EML and MOM using odd or even class wind speed time series and those obtained by applying these methods to all class (both even and odd bins) wind speed time series. Another interesting feature of this approach is the data size reduction which eventually leads to a reduced processing time.Article History: Received February 16th 2018; Received in revised form May 5th 2018; Accepted May 27th 2018; Available onlineHow to Cite This Article: Salami, A.A., Ajavon, A.S.A., Kodjo, M.K. , Ouedraogo, S. and Bédja, K. (2018) The Use of Odd and Even Class Wind Speed Time Series of Distribution Histogram to Estimate Weibull Parameters. Int. Journal of Renewable Energy Development 7(2), 139-150.https://doi.org/10.14710/ijred.7.2.139-150

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Daylight saving time does not seem to be associated with number of percutaneous coronary interventions for acute myocardial infarction in the Netherlands

Netherlands Heart Journal ◽

10.1007/s12471-021-01566-7 ◽

2021 ◽

Author(s):

L. Derks ◽

◽

S. Houterman ◽

G. S. C. Geuzebroek ◽

P. van der Harst ◽

...

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

The Netherlands ◽

Incidence Rate ◽

Hospital Admissions ◽

Control Period ◽

Daylight Saving Time ◽

Daylight Saving ◽

Percutaneous Coronary ◽

Acute Mi

Abstract Background In multiple studies, the potential relationship between daylight saving time (DST) and the occurrence of acute myocardial infarction (MI) has been investigated, with mixed results. Using the Dutch Percutaneous Coronary Intervention (PCI) registry facilitated by the Netherlands Heart Registration, we investigated whether the transitions to and from DST interact with the incidence rate of PCI for acute MI. Methods We assessed changes in hospital admissions for patients with ST-elevation myocardial infarction (STEMI) or non-STEMI (NSTEMI) undergoing PCI between 1 January 2015 and 31 December 2018. We compared the incidence rate of PCI procedures during the first 3 or 7 days after the transition with that during a control period (2 weeks before transition plus second week after transition). Incidence rate ratio (IRR) was calculated using Poisson regression. Potential gender differences were also investigated. Results A total of 80,970 PCI procedures for STEMI or NSTEMI were performed. No difference in incidence rate a week after the transition to DST in spring was observed for STEMI (IRR 0.95, 95% confidence interval (CI) 0.87–1.03) or NSTEMI (IRR 1.04, 95% CI 0.96–1.12). After the transition from DST in autumn, the IRR was also comparable with the control period (STEMI: 1.03, 95% CI 0.95–1.12, and NSTEMI: 0.98, 95% CI 0.91–1.06). Observing the first 3 days after each transition yielded similar results. Gender-specific results were comparable. Conclusion Based on data from a large, nationwide registry, there was no correlation between the transition to or from DST and a change in the incidence rate of PCI for acute MI.

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Abstract 11133: The Incidence and Predicting Factors of Heart Failure After First Acute Myocardial Infarction: A Population[[Unable to Display Character: ‐]]Based Study in Taiwan

Circulation ◽

10.1161/circ.130.suppl_2.11133 ◽

2014 ◽

Vol 130 (suppl_2) ◽

Author(s):

Cheng-Han Lee ◽

Yi-Heng Li ◽

Ching-Lan Cheng ◽

Jyh-Hong Chen ◽

Yea-Huei Kao Yang

Keyword(s):

Myocardial Infarction ◽

Heart Failure ◽

Acute Myocardial Infarction ◽

Coronary Revascularization ◽

Temporal Trends ◽

Population Based ◽

Research Database ◽

Index Hospitalization ◽

Predicting Factors ◽

One Year

Background: Early coronary revascularization and medical therapy advancement improve the survival of patients (pts) with acute myocardial infarction (AMI). However, survivors of AMI are at heightened risk of developing heart failure (HF) and there is a paucity of information regarding this issue in Asian countries. This study described the temporal trends in the incidence of HF after the first AMI and the predicting factors of HF development in Taiwan. Methods: We conducted a nationwide population-based cohort study by using 1999 to 2009 National Health Insurance Research Database. Pts aged≧18 years, with no history of HF, who hospitalized with a first AMI between January 2002 and December 2008 were identified and followed up for one year. The primary outcome was HF. We evaluated the incidence of HF during the index hospitalization, 30 days, 6 months, and one year after the discharge. The predicting factors of HF were identified by Cox proportional hazard model. Results: Overall, 42,011 first AMI pts (mean age 64.4 ± 13.8 years; male 75.0%) from 2002 to 2008 were identified. The HF incidence during the index hospitalization was 14.8%. After exclusion of HF during the hospitalization, the overall HF prevalence at 30 days, 6 months, and 1 year was 9.6%, 14.2%, and 16.8%, respectively. The HF prevalence at 1 year declined from 17.9% to 14.9% (p<0.05) from 2002 to 2008. The independent predicting factors of HF after the first AMI were elder age (≧65 years) (adjusted HR 1.81, 95% CI 1.51-2.18), diabetes mellitus (adjusted HR 1.30, 95% CI 1.21-1.41), chronic kidney disease (adjusted HR 1.41, 95% CI 1.20-1.65), use of loop diuretics within 30 days after the discharge (adjusted HR 2.21, 95% CI 2.00-2.43), and recurrent AMI (adjusted HR 2.43, 2.16-2.74). Conclusions: Survivors of AMI without prior HF remain at risk of developing HF in Taiwan and most episodes occur within 6 months after AMI. Five important clinical factors of HF were identified that may help us for risk stratification.

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Morbidity and pollution: Model specification analysis for time-series data on hospital admissions

Journal of Environmental Economics and Management ◽

10.1016/0095-0696(82)90025-0 ◽

1982 ◽

Vol 9 (4) ◽

pp. 311-327 ◽

Cited By ~ 9

Author(s):

Ronald J Krumm ◽

Philip E Graves

Keyword(s):

Time Series ◽

Hospital Admissions ◽

Time Series Data ◽

Model Specification ◽

Series Data ◽

Specification Analysis

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Prediction of mortality in hospital survivors of STEMI: External validation of a novel acute myocardial infarction prognostic score

Cardiovascular Revascularization Medicine ◽

10.1016/j.carrev.2018.05.008 ◽

2019 ◽

Vol 20 (2) ◽

pp. 96-100 ◽

Cited By ~ 5

Author(s):

Arthur Shiyovich ◽

Tamir Bental ◽

Ygal Plakht ◽

Hana Vaknin-Assa ◽

Gabriel Greenberg ◽

...

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Prognostic Score ◽

External Validation ◽

Prediction Of Mortality

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Abstract P84: The Impact of a Potential Nationwide Comprehensive Smoking Ban on Acute Myocardial Infarction Hospitalizations

Circulation Cardiovascular Quality and Outcomes ◽

10.1161/circoutcomes.4.suppl_1.ap84 ◽

2011 ◽

Vol 4 (suppl_1) ◽

Author(s):

Mouaz H Al-Mallah ◽

Owais Khawaja ◽

Fadi Alqaisi ◽

David Nerenz ◽

W Douglas Weaver

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Hospital Admissions ◽

Meta Analysis ◽

Cost Savings ◽

Smoking Ban ◽

Disease States ◽

Established Risk Factor ◽

Department Of Health ◽

The Impact

Introduction: Smoking is a well established risk factor for acute myocardial infarction (AMI). The potential impact of a nationwide comprehensive smoking ban (CSB) legislation on the incidence of AMI hospital admissions is not known. The aim of this analysis is to determine the impact of a nationwide CSB legislation on the incidence of AMI hospitalizations. Methods: We contacted the department of health at states with no CSB law for information on the total number of AMI discharges (ICD-9-CM 410), length of stay and charges in dollars for 2007. Expected decrease in the number of AMI in the year following a potential implementation of a nationwide CSB was calculated by multiplying the current number of AMI by the pooled relative risk reduction (RRR) obtained from a recent published meta analysis (RR 0.89). Results: In 2007, 37 States had CSB laws. There were 169,043 AMI hospitalizations in states without CSB. A nationwide smoking ban would result in 18,596 less AMI hospitalizations in the year following such a ban. This is associated with more than 92 million dollars in direct cost savings. Conclusion: A nationwide CSB legislation would result in significant reduction in the number of AMI hospitalizations. This is associated with significant cost saving. Further studies are needed to evaluate the impact of CSB on admission from other disease states.

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