Dataset Information

Acute myocardial infarction: Circadian, daily, monthly and seasonal patterns of occurrence in diabetics.

ABSTRACT:

Background

Illustrating the temporal pattern of acute myocardial infarction (AMI), as a major cause of mortality, may help with disease prevention and better treatment. Therefore, the aim of our study was to investigate the circadian, daily, monthly and seasonal patterns of AMI occurrence in patients with diabetes mellitus, and other likely associated factors.

Methods

This cross-sectional study was performed on 142 diabetic patients admitted to the Imam Ali cardiovascular hospital, Kermanshah, Iran with a diagnosis of ST-segment elevation myocardial infarction (STEMI) from March 2018 to February 2019. Data were collected using a checklist developed based on the study goals. One-way Analysis of Variance (ANOVA) and Chi-Square test (or Fishers҆ Exact test) were used to assess the differences between subgroups. Multiple logistic regression model was constructed to evaluate independent predictors of the AMI occurrence.

Result

Out of the 142 diabetic patients, 90 (63.4%) were male. The mean age of the patients was (mean ± SD) 62.81 ± 10.21 years. Occurrence of STEMI was the most common during winter (p = 0.001). Prior angina, prior congestive heart failure (CHF), prior stroke, High-density lipoprotein (HDL), and Creatine Phosphokinase (CPK) were significantly associated with seasonal pattern of STEMI (p-value < 0.05). Angiotensin receptor blockers (ARBs) use was associated with an increased odds of the AMI occurrence in winter (OR = 8.32; P = 0.027).

Conclusion

The present study of Iranian patients with diabetes revealed that AMI occurred more frequently during the winter compared to the other seasons. ARBs use was associated with an increased odd of the AMI occurrence in winter.

Supplementary information

The online version contains supplementary material available at 10.1007/s40200-021-00813-3.

SUBMITTER: Rouzbahani M

PROVIDER: S-EPMC8212248 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Publications

Acute myocardial infarction: Circadian, daily, monthly and seasonal patterns of occurrence in diabetics.

Rouzbahani Mohammad M Azimivghar Javad J Moghadam Reza Heidari RH Montazeri Nafiseh N Janjani Parisa P Rai Alireza A Rad Etrat Javadi EJ Naderipour Arsalan A Salehi Nahid N

Journal of diabetes and metabolic disorders 20210520 1

<h4>Background</h4>Illustrating the temporal pattern of acute myocardial infarction (AMI), as a major cause of mortality, may help with disease prevention and better treatment. Therefore, the aim of our study was to investigate the circadian, daily, monthly and seasonal patterns of AMI occurrence in patients with diabetes mellitus, and other likely associated factors.<h4>Methods</h4>This cross-sectional study was performed on 142 diabetic patients admitted to the Imam Ali cardiovascular hospital ...[more]

PMID: 34222090

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Project description:ObjectiveThe onset of acute myocardial infarction (AMI) shows characteristic circadian variations involving a definite morning peak and a less-defined night-time peak. However, the factors influencing the circadian patterns of AMI onset and their influence on morning and night-time peaks have not been fully elucidated.Design, setting and participantsAn analysis of patients registered between 1998 and 2008 in the Osaka Acute Coronary Insufficiency Study, which is a prospective, multicentre observational study of patients with AMI in the Osaka region of Japan. The present study included 7755 consecutive patients with a known time of AMI onset.Main outcomes and measuresA mixture of two von Mises distributions was used to examine whether a circadian pattern of AMI had uniform, unimodal or bimodal distribution, and the likelihood ratio test was then used to select the best circadian pattern among them. The hierarchical likelihood ratio test was used to identify factors affecting the circadian patterns of AMI onset. The Kaplan-Meier method was used to estimate survival curves of 1-year mortality according to AMI onset time.ResultsThe overall population had a bimodal circadian pattern of AMI onset characterised by a high and sharp morning peak and a lower and less-defined night-time peak (bimodal p<0.001). Although several lifestyle-related factors had a statistically significant association with the circadian patterns of AMI onset, serum triglyceride levels had the most prominent association with the circadian patterns of AMI onset. Patients with triglyceride ≥150 mg/dL on admission had only one morning peak in the circadian pattern of AMI onset during weekdays, with no peaks detected on weekends, whereas all other subgroups had two peaks throughout the week.ConclusionsThe circadian pattern of AMI onset was characterised by bimodality. Notably, several lifestyle-related factors, particularly serum triglyceride levels, had a strong relation with the circadian pattern of AMI onset.Trial registration numberUMIN000004575.

Project description:BackgroundPreclinical data suggest that an acute inflammatory response following myocardial infarction (MI) accelerates systemic atherosclerosis. Using combined positron emission and computed tomography, we investigated whether this phenomenon occurs in humans.Methods and resultsOverall, 40 patients with MI and 40 with stable angina underwent thoracic 18F-fluorodeoxyglucose combined positron emission and computed tomography scan. Radiotracer uptake was measured in aortic atheroma and nonvascular tissue (paraspinal muscle). In 1003 patients enrolled in the Global Registry of Acute Coronary Events, we assessed whether infarct size predicted early (≤30 days) and late (>30 days) recurrent coronary events. Compared with patients with stable angina, patients with MI had higher aortic 18F-fluorodeoxyglucose uptake (tissue-to-background ratio 2.15±0.30 versus 1.84±0.18, P<0.0001) and plasma C-reactive protein concentrations (6.50 [2.00 to 12.75] versus 2.00 [0.50 to 4.00] mg/dL, P=0.0005) despite having similar aortic (P=0.12) and less coronary (P=0.006) atherosclerotic burden and similar paraspinal muscular 18F-fluorodeoxyglucose uptake (P=0.52). Patients with ST-segment elevation MI had larger infarcts (peak plasma troponin 32 300 [10 200 to >50 000] versus 3800 [1000 to 9200] ng/L, P<0.0001) and greater aortic 18F-fluorodeoxyglucose uptake (2.24±0.32 versus 2.02±0.21, P=0.03) than those with non-ST-segment elevation MI. Peak plasma troponin concentrations correlated with aortic 18F-fluorodeoxyglucose uptake (r=0.43, P=0.01) and, on multivariate analysis, independently predicted early (tertile 3 versus tertile 1: relative risk 4.40 [95% CI 1.90 to 10.19], P=0.001), but not late, recurrent MI.ConclusionsThe presence and extent of MI is associated with increased aortic atherosclerotic inflammation and early recurrent MI. This finding supports the hypothesis that acute MI exacerbates systemic atherosclerotic inflammation and remote plaque destabilization: MI begets MI.Clinical trial registrationURL: https://www.clinicaltrials.gov. Unique identifier: NCT01749254.

Project description:BackgroundEarly identification of the occurrence of arrhythmia in patients with acute myocardial infarction plays an essential role in clinical decision-making. The present study attempted to use machine learning (ML) methods to build predictive models of arrhythmia after acute myocardial infarction (AMI).MethodsA total of 2084 patients with acute myocardial infarction were enrolled in this study. (All data is available on Github: https://github.com/wangsuhuai/AMI-database1.git) . The primary outcome is whether tachyarrhythmia occurred during admission containing atrial arrhythmia, ventricular arrhythmia, and supraventricular tachycardia. All data is randomly divided into a training set (80%) and an internal testing set (20%). Apply three machine learning algorithms: decision tree, random forest (RF), and artificial neural network (ANN) to learn the training set to build a model, then use the testing set to evaluate the prediction performance, and compare it with the model built by the Global Registry of Acute Coronary Events (GRACE) risk variable set.ResultsThree ML models predict the occurrence of tachyarrhythmias after AMI. After variable selection, the artificial neural network (ANN) model has reached the highest accuracy rate, which is better than the model constructed using the Grace variable set. After applying SHapley Additive exPlanations (SHAP) to make the model interpretable, the most important features are abnormal wall motion, lesion location, bundle branch block, age, and heart rate. Among them, RBBB (odds ratio [OR]: 4.21; 95% confidence interval [CI]: 2.42-7.02), ≥ 2 ventricular walls motion abnormal (OR: 3.26; 95% CI: 2.01-4.36) and right coronary artery occlusion (OR: 3.00; 95% CI: 1.98-4.56) are significant factors related to arrhythmia after AMI.ConclusionsWe used advanced machine learning methods to build prediction models for tachyarrhythmia after AMI for the first time (especially the ANN model that has the best performance). The current study can supplement the current AMI risk score, provide a reliable evaluation method for the clinic, and broaden the new horizons of ML and clinical research. Trial registration Clinical Trial Registry No.: ChiCTR2100041960.

Project description:ObjectivesThere are conflicting data on the relationship between the time of symptom onset during the 24-hour cycle (circadian dependence) and infarct size in ST-elevation myocardial infarction (STEMI). Moreover, the impact of this circadian pattern of infarct size on clinical outcomes is unknown. We sought to study the circadian dependence of infarct size and its impact on clinical outcomes in STEMI.MethodsWe studied 6,710 consecutive patients hospitalized for STEMI from 2006 to 2009 in a tropical climate with non-varying day-night cycles. We categorized the time of symptom onset into four 6-hour intervals: midnight-6:00 A.M., 6:00 A.M.-noon, noon-6:00 P.M. and 6:00 P.M.-midnight. We used peak creatine kinase as a surrogate marker of infarct size.ResultsMidnight-6:00 A.M patients had the highest prevalence of diabetes mellitus (P = 0.03), more commonly presented with anterior MI (P = 0.03) and received percutaneous coronary intervention less frequently, as compared with other time intervals (P = 0.03). Adjusted mean peak creatine kinase was highest among midnight-6:00 A.M. patients and lowest among 6:00 A.M.-noon patients (2,590.8±2,839.1 IU/L and 2,336.3±2,386.6 IU/L, respectively, P = 0.04). Midnight-6:00 A.M patients were at greatest risk of acute heart failure (P<0.001), 30-day mortality (P = 0.03) and 1-year mortality (P = 0.03), while the converse was observed in 6:00 A.M.-noon patients. After adjusting for diabetes, infarct location and performance of percutaneous coronary intervention, circadian variations in acute heart failure incidence remained strongly significant (P = 0.001).ConclusionWe observed a circadian peak and nadir in infarct size during STEMI onset from midnight-6:00A.M and 6:00A.M.-noon respectively. The peak and nadir incidence of acute heart failure paralleled this circadian pattern. Differences in diabetes prevalence, infarct location and mechanical reperfusion may account partly for the observed circadian pattern of infarct size and acute heart failure.

Dataset Information

Acute myocardial infarction: Circadian, daily, monthly and seasonal patterns of occurrence in diabetics.

Background

Methods

Result

Conclusion

Supplementary information

Publications

Acute myocardial infarction: Circadian, daily, monthly and seasonal patterns of occurrence in diabetics.

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