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Predictors of tamponade and constriction in patients with pericardial disease undergoing interventional and surgical
Taalaibek Kudaiberdiev1,2, Seitkhan Joshibayev3, Gulzada Imanalieva1
1Scientific Research Institute of Heart Surgery and Organ Transplantation, Bishkek, Kyrgyzstan.
Insights
Predictors of cardiac compression include large pericardial effusion, cardiac chamber collapse, and high NYHA class. A model using these factors accurately predicts compression in over 91% of cases, aiding diagnosis.
Area of Science:
- Cardiology
- Medical Diagnostics
Background:
- Pericardial disease can lead to cardiac compression, such as tamponade or constriction.
- Identifying predictors is crucial for timely diagnosis and management.
Purpose of the Study:
- To define predictors of cardiac compression development.
- To evaluate the diagnostic value of clinical, electrocardiographic, echocardiographic, and perioperative parameters.
Main Methods:
- Logistic regression analysis of data from 243 patients with pericardial disease.
- Included patients with (n=123) and without (n=120) signs of compression.
- Analyzed clinical, laboratory, ECG, chest-X-ray, echocardiographic, and perioperative data.
Main Results:
- Large effusion (>20 mm), cardiac chamber collapse, and NYHA class >3 were independent predictors of compression.
- A model incorporating these three variables predicted compression in 91.7% of cases.
- ROC analysis showed significant diagnostic value for each predictor, with large effusion having high sensitivity and specificity.
Conclusions:
- Large effusion (>20 mm), cardiac chamber collapse, and high NYHA class are independent predictors of cardiac compression.
- A predictive model using these factors demonstrates high accuracy.
- These predictors offer valuable diagnostic insights for cardiac compression in pericardial disease.
Objective:
The aim of our study was to define predictors of cardiac compression development including clinical, electrocardiographic, echocardiographic, chest-X-ray and perioperative parameters and their diagnostic value.
Methods:
Overall 243 patients with pericardial disease, among them 123 with compression (tamponade, constriction) and 120 without signs of compression were included in the study. Clinical, laboratory, electrocardiographic, chest-X-Ray, echocardiographic and perioperative data were included in the logistic regression analysis to define predictors of tamponade/constriction development.
Results:
Logistic regression analysis demonstrated large effusion (> 20 mm) (OR 5.393, 95%CI 1.202-24.199, p = 0.028), cardiac chamber collapse (OR 31.426, 95%CI 1.609-613-914, p = 0.023) and NYHA class > 3 (OR 8.671, 95%CI 1.730-43.451, p = 0.009) were multivariable predictors of compression development. The model including these three variables allowed predicting compression in 91.7% of cases. ROC analyses demonstrated that all three variables had significant diagnostic value with sensitivity of 75.6% and specificity of 74.2% for large effusion, low sensitivity and high specificity for cardiac chamber collapse (35% and 92%) and NYHA class (32.5% and 94.2%).
Conclusion:
The independent predictors of compression development are presence of large effusion > 20 mm, cardiac chamber collapse and high NYHA class. The model including all three parameters allows correctly predicting compression in 91.4% of cases. The diagnostic accuracy of each parameter is characterized by high sensitivity and specificity of large effusion, high specificity of cardiac chamber collapse and NYHA class.
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