Predictors of Upper Gastrointestinal Bleeding after Myocardial Infarction: Identifying High-Risk Patients

Several predictors are identified for upper gastrointestinal bleeding after myocardial infarction, emphasizing the importance of early risk stratification and targeted interventions to prevent hemorrhagic complications and improve patient outcomes.

March 2022
Predictors of Upper Gastrointestinal Bleeding after Myocardial Infarction: Identifying High-Risk Patients

Dual antiplatelet therapy (DAPT) with aspirin and a P2Y12 inhibitor is the default antithrombotic strategy after acute myocardial infarction (MI), regardless of invasive or conservative treatment. This strategy improves ischemic outcomes, but is offset by an increased risk of bleeding .

In recent decades, the prognostic importance of hemorrhagic episodes has been well established, as several studies have demonstrated a strong association between hemorrhage and mortality. The goal of future antithrombotic strategies now goes beyond ischemic protection, but also focuses on bleeding reduction.

The most common location of spontaneous bleeding at the non-access site is the gastrointestinal tract. Of these, upper gastrointestinal bleeding (UGIB) is common and of particular interest, as it can be prevented to some extent, for example, through the prophylactic use of proton pump inhibitors (PPIs), non-aspirin strategies, or Helicobacter eradication. pylori.

The European Society of Cardiology (ESC) recommends PPIs in patients at higher than average risk of gastrointestinal (GI) bleeding defined as a history of gastric ulcer/bleeding, anticoagulant therapy, chronic use of nonsteroidal anti-inflammatory drugs (NSAIDs)/corticosteroids, or two or older than 65 years or older, dyspepsia, gastroesophageal reflux disease, H. pylori infection, or chronic alcohol consumption.

Currently, the predictors and associated cardiovascular outcomes of UGIB after acute myocardial infarction are insufficiently understood.

First, the available data are derived from smaller studies with selected patient populations that commonly include all types of GI bleeding, and data from larger unselected MI populations are sparse.

Second, when exploring predictors, traditional risk prediction with logistic regression may miss important aspects due to inferior performance with respect to complex and/or nonlinear relationships.

Therefore, using comprehensive data from multiple mandatory national registries, our objectives were to (i) determine the 1-year incidence of UGIB, (ii) establish ischemic outcomes associated with UGIB, and (iii) identify the strongest predictors. from HDA. in patients with acute myocardial infarction.

For the latter objective, we use two different approaches: traditional logistic regression that includes variables based on prior knowledge and machine learning (ML) that includes all available data of possible interest.

Goals

Of all spontaneous bleeding complications in patients with acute myocardial infarction (MI), upper gastrointestinal bleeding (UGIB) is common and of specific interest, as it could be prevented with various prophylactic measures. Our objective was to determine the incidence, associated outcomes, and predictors of UGIB after acute myocardial infarction.

Methods and results

All patients with acute myocardial infarction enrolled in the SWEDEHEART registry (Swedish web system for the improvement and development of evidence-based care in cardiac diseases evaluated according to recommended therapies) from January 2007 to June 2016 and discharged alive with any antithrombotic treatment (n = 149,477) were followed with respect to UGIB for 1 year.

Associated outcomes were determined using Cox proportional hazards regression with UGIB as a time-dependent covariate, adjusting for baseline characteristics, invasive treatment, and medical treatment at discharge. Predictors of UGIB were determined using logistic regression and machine learning models.

At 1 year, UGIB had occurred in 2230 patients (cumulative incidence 1.5%) and was significantly associated with an increased risk of death from any cause [hazard ratio (HR) 2.86, confidence interval (CI) 95% CI: 2.58–3.16] and stroke (HR 1.80, 95% CI: 1.32 to 2.45) but not with recurrent MI (HR 1.17, 95% CI: 0.97 to 1.42).

The most important predictors of UGIB were hemoglobin, age, systolic blood pressure, blood glucose, smoking, previous upper gastrointestinal bleeding, and antithrombotic and gastroprotective treatment.

Conclusion

After acute myocardial infarction, readmission for UGIB is common and significantly associated with poor prognosis. Using machine learning in addition to traditional logistic regression, new predictors of UGIB, such as blood glucose and smoking, were identified.

Incidence, predictors and associated outcomes after acute myocardial infarction.

Eight predictors of upper gastrointestinal bleeding after a heart attack

Researchers at Karolinska Institutet in Sweden have identified eight main factors that increase the risk of a common bleeding complication after a heart attack. Some of these factors are already known, but using machine learning techniques, researchers have found additional predictors, such as smoking, blood pressure, and blood glucose.

The results are published in the European Heart Journal - Cardiovascular Pharmacotherapy , and will be presented at the digital congress of the European Society of Cardiology.

"If we can identify patients at high risk of upper gastrointestinal bleeding after a heart attack, doctors will be able to take prophylactic measures to mitigate this risk," says the study’s corresponding author, Moa Simonsson, associate consultant at Karolinska University Hospital and student. PhD at Karolinska. Institutet Department of Clinical Sciences, Danderyd Hospital. "There are, for example, medications that combat bleeding complications, gut bacteria tests that can be used in risk groups, and other personalized treatment possibilities for heart attack patients at high risk of bleeding complications."

Bleeding in the upper gastrointestinal (GI) tract is one of the most common hemorrhagic complications after acute myocardial infarction. The condition requires many resources for hospitals, causes considerable suffering and increases the risk of death. Bleeding complications also limit the use of antithrombotics, which in turn may worsen cardiovascular prognosis.

A sharper focus on bleeding complications over the past two decades has led to several strategies to reduce the risk of upper gastrointestinal bleeding. Despite this, there are few studies on this complication that include a diverse population of heart attack patients.

1.5 percent of patients suffer gastrointestinal bleeding after a heart attack

For the current study, researchers obtained data on nearly 150,000 patients with acute myocardial infarction between 2007 and 2016 from the national SWEDEHEART registry. Of these patients, about 1.5 percent suffered gastrointestinal bleeding within a year of their heart attack. They also had a higher risk of death and stroke.

The researchers confirmed several factors known to increase the risk of upper gastrointestinal bleeding, including low levels of hemoglobin (a protein that helps carry oxygen in the blood), previous upper gastrointestinal bleeding, age, and intensive antithrombotic treatment.

Using an algorithm, they also identified new risk factors, such as smoking, blood pressure, blood glucose, and previous treatments for stomach disorders, such as ulcers and acid reflux.

"By combining traditional statistical models with machine learning methods, you can create unique opportunities to find key risk factors for previously unknown cardiovascular events," says co-author Philip Sarajlic, PhD student at the Department of Medicine, Solna, Karolinska Institutet. “This allows us to make effective use of valuable data from the medical quality registry by taking into account the complex relationships between risk factors and outcomes to further optimize current recommendations for patient care.”

The most important predictors in the best performing machine learning model, the random forest. For each of the 10 variables, a variable importance weight measure is presented, which is proportional to the increase in the random forest misclassification rate if the variable was removed from the model. The weights of greater importance indicate that the variable is more important when predicting upper gastrointestinal bleeding events.

Big clinical study to come

This fall, researchers will begin a major clinical study to investigate the importance of diagnosing and treating a common upper gastrointestinal tract infection.

"A pilot study last year showed a two-fold increase in the presence of Helicobacter pylori in heart attack patients," says the last author of the study, Robin Hofmann, researcher and consultant at the Department of Clinical Science and Education at Karolinska Institutet, Södersjukhuset. "We will now proceed with a large randomized study to determine whether systematic screening of heart attack patients for Hp infection and, where relevant, its treatment, can reduce bleeding complications and improve prognosis after heart attack."

The study was funded by grants from the Heart-Lung Foundation, the Swedish Research Council, Stockholm Region, and the Clinical Sciences Training Program (CSTP) of the Karolinska Institute. Two of the authors have reported potential conflicts of interest, including receipt of speaking and consulting fees from pharmaceutical companies (see study for details).

Clinical relevance

Given the prognostic consequences of ischemic and hemorrhagic complications, the optimal treatment strategy should balance the risk of these events. There are currently many alternatives to this individualized approach, but it is still unclear how best to stratify these risks. Several scores have been developed for the assessment of out-of-hospital bleeding risk, and Academic Research Consortium criteria for High Bleeding Risk have recently been proposed.

In addition to the known risk factors for major bleeding, the results of our study suggest the existence of additional specific predictors useful in the risk stratification of patients with UGIB, such as blood glucose, smoking, and previous UGIB.

If patients at high risk of UGIB could be identified , there are several prophylactic measures to reduce the risk of UGIB. First, general approaches that reduce the risk of bleeding probably also reduce the risk of UGIB.

Individualized therapy with shorter DAPT and reduction to a less potent P2Y12 inhibitor may reduce overall bleeding, while non-aspirin strategies may not only reduce overall bleeding but also offer a direct mechanism to reduce negative effect. of cyclooxygenase in the gastric mucosa. inhibition by acetylsalicylic acid.

Second, there are specific therapies to prevent UGIB through the use of PPIs or other gastroprotective drugs and testing and treatment strategies for active H. pylori. Controversy persists over the risks associated with long-term use of PPIs, including pneumonia, dementia, cardiovascular events, and deterioration in renal function, but PPI use has increased over the past decade in practice. possibly due to lack of data from large-scale randomized clinical trials.

Conclusions

During the first year after acute MI, readmission for UGIB is common and significantly associated with poor prognosis. By using ML techniques in addition to traditional logistic regression, beyond the known predictors of major bleeding, new predictors of UGIB such as blood glucose and smoking were identified.