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Related Concept Videos

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Correlations

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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Correlation and Causation01:27

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Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
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Correlation01:09

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In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
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Correlation and Regression00:53

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In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
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The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable x and the dependent variable y.
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Cranial Bones: Superior and Posterior View01:14

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The superior view of the cranium shows the frontal and paired parietal bones.
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Persistent Left Superior Vena Cava: Imaging Correlation.

Andrés M Pineda, Saqib A Gowani1, Christos G Mihos

  • 1Hartford Hospital, University of Connecticut, 85 Seymour Street, Hartford, CT 06106 USA. saqibgowani@gmail.com.

The Journal of Invasive Cardiology
|May 2, 2018
PubMed
Summary
This summary is machine-generated.

A persistent left superior vena cava (SVC) was identified in a heart failure patient, alongside severe mitral regurgitation and aortic stenosis. This congenital condition was isolated, with no other cardiac abnormalities detected.

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Area of Science:

  • Cardiology
  • Medical Imaging
  • Congenital Heart Disease

Background:

  • Persistent left superior vena cava (PLSVC) is a rare congenital anomaly.
  • Patients with PLSVC may present with various cardiovascular complications.
  • Understanding the anatomical variations is crucial for patient management.

Observation:

  • Transthoracic echocardiography (TEE) revealed a persistent left SVC.
  • Dilated coronary sinus, severe mitral regurgitation, and aortic stenosis were observed.
  • Computed tomography (CT) confirmed an isolated PLSVC.

Findings:

  • The study identified a persistent left SVC in a heart failure patient.
  • Associated findings included a dilated coronary sinus, severe mitral regurgitation, and aortic stenosis.
  • CT imaging excluded anomalous pulmonary vein drainage and other congenital heart diseases.

Implications:

  • Accurate diagnosis of PLSVC is essential for appropriate treatment planning.
  • TEE and CT are valuable tools for characterizing cardiovascular anomalies.
  • This case highlights the importance of comprehensive imaging in heart failure patients with suspected congenital defects.