Neuromuscular Disease: Evidence and Analysis in Clinical by Michael Benatar
By Michael Benatar
This quantity provides a severe appraisal of the neurological literature on neuromuscular sickness from an evidence-based standpoint. Writing in a readable, available sort, the writer considers, intimately, a huge variety of the broadcast literature appropriate not just to questions of therapy, but additionally to problems with prognosis and diagnosis. via a chain of questions and solutions pertaining to particular neuromuscular issues, each one bankruptcy evaluations the simplest to be had proof to demonstrate strengths and weaknesses of the information and make the reader conscious of the standard of scientific learn stories typically. Introductory chapters facilitate this studying strategy by means of elucidating the epidemiological and biostatistical concerns pertinent to prognosis, therapy, and analysis. A vast diversity of issues of the anterior horn mobilephone, nerve roots, peripheral nerves, neuromuscular junction, and muscle are significantly appraised and mentioned.
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Additional resources for Neuromuscular Disease: Evidence and Analysis in Clinical Neurology
The details of these methods will be explained elsewhere in this chapter, but for now it will suffice to understand that these forms of regression each employ a different mathematical formula to determine the best fit of the data. Of course, linear and logistic regression differ in other respects as well. In linear regression, the outcome variable is a normally distributed continuous variable. In logistic regression, the outcome variable is a binomially distributed dichotomous variable. To develop a better understand these analytic techniques, we shall now consider examples of both linear and logistic regression.
0917 × age at onset)] We can now use this formula to estimate the log odds of death for a person diagnosed with ALS at, for example, the age of 40. 7 There is, therefore, a 66% risk of death. For this estimate to have meaning, we have to know the time period over which this risk applies. To know this, we must return to the study in which the data was gathered for the logistic model. We see that death was determined over a 3-year study period. The 3-year risk of death, therefore, for a person diagnosed with ALS at the age of 40 is 66%.
Use of methodological standards in diagnostic test research: getting better but still not good. JAMA 1995;274:645–651. 2. England J, Gronseth G, Franklin G, et al. Distal symmetric polyneuropathy: A definition for clinical research: Report of the American Academy of Neurology, the American Association of Electrodiagnostic Medicine, and the American Academy of Physical Medicine and Rehabilitation. Neurology 2005; 64:199–207. 3. Bossuyt PM, Reitsma JB, Bruns DE, et al. Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative.