Surreal illustration of a heart intertwined with statistical graphs over a Norwegian fjord, symbolizing data analysis in cardiovascular health.

Decoding Heart Health: Are We Overlooking Key Factors in Heart Attack Statistics?

Avery Sinclair in Health & Wellness December 2025 • 5 min read.

"A critical look at incident acute myocardial infarction (AMI) trends and the importance of accurate data interpretation for better heart health strategies."

In the realm of cardiovascular health, accurate data is the cornerstone of effective prevention and treatment strategies. A recent article, ‘Trends in incident acute myocardial infarction in Norway: An updated analysis to 2014 using national data from the CVDNOR project,' published in the European Journal of Preventive Cardiology, has sparked a discussion among experts. This article, authored by Sulo et al., delves into the trends of acute myocardial infarction (AMI) in Norway, providing valuable insights into the state of heart health in the region.

However, a letter to the editor, penned by Jan Bruthans and Jan Bruthans Jr, raises critical questions about the methodologies used in the study. Their concerns revolve around the accuracy of AMI statistics, particularly regarding the inclusion of deaths and the classification of incident cases. These questions are not merely academic; they have significant implications for how we understand and address heart disease, one of the leading causes of mortality worldwide.

This article aims to dissect the arguments presented by Bruthans and Bruthans Jr, providing a comprehensive overview of the debate surrounding AMI data interpretation. By exploring the potential pitfalls in data collection and analysis, we hope to shed light on the importance of precise methodologies in cardiovascular research. Understanding these nuances is crucial for healthcare professionals, policymakers, and anyone interested in improving heart health outcomes.

The Heart of the Matter: Are AMI Statistics Overestimated?

Surreal illustration of a heart intertwined with statistical graphs over a Norwegian fjord, symbolizing data analysis in cardiovascular health.

The primary concern raised by Bruthans and Bruthans Jr. centers on the definition of ‘incident’ AMIs and how deaths are classified in relation to AMI statistics. The original study defined AMIs as hospitalizations for AMI according to specific discharge diagnoses (ICD-9 410 and ICD-10 I21, I22) and deaths with coronary heart disease (CHD) ICD-9 410-414 and ICD-10 I20-125 as the underlying cause in individuals who had not undergone AMI hospitalization in the previous seven years.

Bruthans and Bruthans Jr argue that including all deaths with CHD ICD-9 410-414 and ICD-10 I20-125 may lead to an overestimation of incident AMIs. Their reasoning is that while these deaths are undoubtedly related to coronary issues, they are not necessarily solely attributable to AMI. This distinction is crucial because misclassifying deaths can skew the data and lead to inaccurate conclusions about the true incidence of AMIs.

Here are the Key concerns in interpreting AMI incidence accurately:

Inclusion of CHD Deaths: Questioning whether all deaths coded as CHD should be classified as AMI, potentially overestimating new AMI cases.
Classification Accuracy: Highlighting the need to distinguish between deaths directly caused by AMI versus other coronary-related deaths.
Data Precision: Stressing the importance of accurate and precise data collection to avoid misleading conclusions about AMI incidence.

To illustrate, consider a patient with a history of heart disease who dies from a sudden cardiac arrest. While the underlying cause may be related to coronary issues, it might not be directly triggered by an AMI. Including such cases in the AMI statistics could inflate the numbers, leading to a misrepresentation of the actual incidence of new heart attacks. This is particularly relevant in regions with aging populations and a higher prevalence of chronic heart conditions.

The Path Forward: Enhancing Accuracy in Cardiovascular Data

The debate sparked by Bruthans and Bruthans Jr underscores the importance of rigorous methodologies in cardiovascular research. Accurate data collection and interpretation are essential for understanding the true burden of heart disease and developing effective prevention and treatment strategies. As the landscape of healthcare evolves, it is imperative that we continue to refine our approaches to data analysis, ensuring that our efforts are guided by the most precise and reliable information available.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: 10.1177/2047487318803240, Alternate LINK

Title: Trends In Incident Acute Myocardial Infarction In Norway: Could The Results Be Under- Or Overestimated?

Subject: Cardiology and Cardiovascular Medicine

Journal: European Journal of Preventive Cardiology

Publisher: Oxford University Press (OUP)

Authors: Jan Bruthans, Jan Bruthans

Published: 2018-10-05

Everything You Need To Know

What is an Acute Myocardial Infarction (AMI), and why is it important to understand its accurate incidence?

The term Acute Myocardial Infarction (AMI) refers to a heart attack, a critical condition where blood flow to the heart is blocked. The significance lies in its status as a leading cause of death globally, thus making the accurate tracking and understanding of AMI crucial for public health initiatives. The implications of misinterpreting AMI incidence include ineffective allocation of resources, misguided prevention strategies, and potentially compromised patient care.

How did the study by Sulo et al. define AMI cases, and what specific concerns were raised by Bruthans and Bruthans Jr. regarding this definition?

In the context, the authors, Sulo et al., defined AMIs based on hospitalizations recorded under specific International Classification of Diseases (ICD) codes: ICD-9 410 and ICD-10 I21, I22. Bruthans and Bruthans Jr. raise concerns that the methodologies might lead to an overestimation of AMI cases. This is important because of the need for precise methodologies in cardiovascular research. The implications are that if cases are misclassified, it can lead to inaccurate understanding of heart disease.

What is the key concern regarding the definition of 'incident' AMIs, as highlighted by Bruthans and Bruthans Jr.?

The main concern is the potential overestimation of AMI cases due to the inclusion of all deaths with Coronary Heart Disease (CHD) codes (ICD-9 410-414 and ICD-10 I20-I25), regardless of whether an AMI directly caused the death. Including all CHD-related deaths in AMI statistics could inflate the reported incidence. The importance is understanding the true burden of heart disease and for developing effective prevention and treatment strategies. The implications are that inaccurate data could mislead healthcare professionals.

What are the International Classification of Diseases (ICD) codes mentioned in this context, and why are they important?

The ICD-9 and ICD-10 are international systems used for classifying diseases and health problems, providing a standardized way to record diagnoses and causes of death. The specific codes mentioned (ICD-9 410-414, ICD-10 I20-I25) are used for Coronary Heart Disease (CHD) and the codes (ICD-9 410 and ICD-10 I21, I22) are for Acute Myocardial Infarction (AMI). They are essential for data collection. The implications are that accuracy in coding is important for understanding the true incidence of AMIs.

Why is it important to have precise methodologies in cardiovascular research when dealing with AMI statistics?

Precise data collection and interpretation are essential for understanding the true burden of heart disease, and to develop effective prevention and treatment strategies. The significance of precise methodologies in cardiovascular research involves ensuring that the data accurately reflects the incidence of AMIs. The implications are that data inaccuracies could lead to ineffective public health measures, misinformed clinical practices, and a failure to address the real challenges of heart disease.