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Related Concept Videos

Correlations02:20

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.
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
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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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Spearman's Rank Correlation Test01:20

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Spearman's rank correlation test, also known as Spearman's rho, is a nonparametric method for assessing the strength and direction of association between two variables. This test is particularly valuable when the data distribution is unknown or when the assumption of normality does not hold. Named after the English psychologist and statistician Dr. Charles Edward Spearman, it serves as the nonparametric counterpart to Pearson's correlation coefficient.
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Optical Frequency Domain Imaging of Ex vivo Pulmonary Resection Specimens: Obtaining One to One Image to Histopathology Correlation
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Needle electromyography and histopathologic correlation in myopathies.

Ugur Sener1, Jennifer Martinez-Thompson2, Ruple S Laughlin2

  • 1Mayo Clinic Neurology Department, 4500 San Pablo Road South, Jacksonville, Florida, 32224, USA.

Muscle & Nerve
|November 11, 2018
PubMed
Summary

Needle electromyography (EMG) can help diagnose myopathy. Specific EMG findings like fibrillation potentials and short-duration motor unit potentials (MUPs) correlate with muscle biopsy results, aiding in diagnosis.

Keywords:
EMGfibrillationsmuscle biopsymuscle pathologymyotonic dischargesshort motor unit potentials

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Area of Science:

  • Neurology
  • Clinical Neurophysiology

Background:

  • Needle electromyography (EMG) is crucial for diagnosing myopathies.
  • EMG findings can guide muscle biopsy interpretation.

Purpose of the Study:

  • To correlate specific needle EMG findings with muscle biopsy results.
  • To determine the diagnostic accuracy of EMG findings for myopathic changes.

Main Methods:

  • Retrospective chart review of 218 patients undergoing muscle biopsy.
  • Correlation of needle EMG findings with pathologic muscle biopsy results (inflammation, necrosis, splitting, vacuolar changes).
  • Calculation of sensitivity, specificity, and predictive values for EMG findings.

Main Results:

  • Short-duration motor unit potentials (MUPs) showed high sensitivity (83%-94%) but low specificity (34%-49%) for pathologic changes.
  • Fibrillation potentials were moderately sensitive (65%-74%) and specific (58%-81%) for inflammation, necrosis, splitting, or vacuolar changes.
  • Absence of fibrillation potentials had high negative predictive value (82%-93%) for certain myopathic changes.

Conclusions:

  • Fibrillation potentials and short-duration MUPs are predictive of muscle fiber necrosis, splitting, and vacuolar changes, common in inflammatory myopathies and muscular dystrophies.
  • The absence of fibrillation potentials suggests alternative myopathologic conditions, such as congenital myopathies.