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Related Concept Videos

Gastritis-II: Pathophysiology01:17

Gastritis-II: Pathophysiology

286
Gastritis is marked by disruption of the mucosal barrier that usually protects the stomach tissue from digestive juices and manifests in acute and chronic forms.
In acute gastritis, the gastric mucosa becomes swollen and red and undergoes superficial erosion. Superficial ulceration may lead to bleeding.
In chronic gastritis, persistent or repeated insults lead to chronic inflammatory changes and, eventually, thinning or atrophy of the gastric tissue.
Gastritis can stem from various causes, each...
286
Esophageal Varices-I: Introduction01:24

Esophageal Varices-I: Introduction

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Esophageal varices are dilated, tortuous veins which are found mainly in the submucosa of the lower esophagus but which may also appear higher up or extend into the stomach. They develop due to increased pressure in the portal venous system, often as a result of liver cirrhosis. This condition scars and damages the liver, impeding normal blood flow through the portal vein. To compensate, blood seeks alternative pathways, forming fragile new vessels (varices) in the esophagus and stomach. These...
95
Gastritis III: Clinical Manifestations and Management01:23

Gastritis III: Clinical Manifestations and Management

188
The clinical manifestations of gastritis can vary depending on the cause and type of gastritis, but some common symptoms may include the following.
Clinical manifestations of acute gastritis
The patient with acute gastritis may have a rapid onset of symptoms, such as epigastric pain or discomfort, dyspepsia, anorexia, hiccups, or nausea and vomiting, which can last from a few hours to a few days. Erosive or hemorrhagic gastritis may cause bleeding, which may manifest as blood in vomit or as...
188
Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

Blood Studies for Cardiovascular System I: Cardiac Biomarkers

119
Cardiac biomarkers are enzymes, proteins, and hormones released into the blood when cardiac cells are injured. They are powerful tools for triaging.
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
119
Esophageal Varices-II: Clinical Features and Management01:28

Esophageal Varices-II: Clinical Features and Management

57
Esophageal varices often manifest as gastrointestinal bleeding episodes, presenting symptoms like hematemesis (vomiting of blood), hematochezia (passing fresh blood via the rectum), and melena (black, tarry stools). Other signs can include weight loss, anorexia, abdominal discomfort, jaundice, pruritus, altered mental status, and muscle cramps.
In the initial assessment, a thorough review of the patient's medical history is vital to identify risk factors such as liver disease, alcohol...
57
Peptic Ulcer Disease I: Introduction01:30

Peptic Ulcer Disease I: Introduction

148
Peptic Ulcer Disease (PUD) is characterized by mucosal excavation in the esophagus, stomach, pylorus, or duodenum. It can manifest as acute or chronic based on the extent and duration of mucosal involvement.
An acute ulcer, marked by superficial erosion and minimal inflammation, swiftly resolves upon identifying and addressing the underlying cause. In contrast, a chronic ulcer persists, potentially eroding through the muscular wall and forming fibrous tissue.
Peptic ulcers can also be...
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Risk Factors for Gastrointestinal Bleeding in Patients With Acute Myocardial Infarction: Multicenter Retrospective

Yanqi Kou1, Shicai Ye1, Yuan Tian1,2

  • 1Department of Gastroenterology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.

Journal of Medical Internet Research
|January 30, 2025
PubMed
Summary
This summary is machine-generated.

A machine learning model effectively predicts gastrointestinal bleeding in acute myocardial infarction patients, identifying key risk factors like red blood cell count and coronary heart disease for early intervention.

Keywords:
acute myocardial infarctiongastrointestinal bleedingin-hospitalmachine learningprediction model

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Area of Science:

  • Cardiology
  • Medical Informatics
  • Machine Learning in Healthcare

Background:

  • Gastrointestinal bleeding (GIB) is a serious complication for acute myocardial infarction (AMI) patients, impacting prognosis.
  • Early identification of high-risk individuals is crucial for improved outcomes and clinical decision-making.

Purpose of the Study:

  • Develop and validate a machine learning (ML) model to predict in-hospital GIB in AMI patients.
  • Identify key risk factors for GIB in this population.
  • Assess the model's clinical utility for risk stratification and decision support.

Main Methods:

  • Retrospective cohort study of 1910 AMI patients (training/testing) and external validation using MIMIC-IV data.
  • Boruta algorithm for predictor identification; 7 ML algorithms trained and evaluated.
  • Model performance assessed using AUC, accuracy, sensitivity, specificity, F1-score, and decision curve analysis.

Main Results:

  • Random Forest (RF) model achieved AUC of 0.77 (training/testing) and 0.75 (validation).
  • Key predictors included red blood cell count, hemoglobin, maximal myoglobin, hematocrit, and coronary heart disease (CHD).
  • CHD identified as an independent risk factor for GIB (OR 2.79).

Conclusions:

  • The ML-based RF model offers a robust, clinically applicable tool for predicting in-hospital GIB in AMI patients.
  • The model utilizes readily available data for early risk stratification and personalized prevention.
  • No significant difference in short-term survival was observed between patients with and without GIB.