<< An Evidence-Based Approach To Imaging Of Acute Neurological Conditions

Critical Appraisal Of The Literature

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Critical Appraisal Of The Literature

Critical Appraisal Of The Literature

A large number of studies have examined indications for neuroimaging as well as the test characteristics (including sensitivity, specificity, and positive and negative likelihood ratios) of the available imaging modalities. This article focuses on large, multicenter, prospective trials whenever possible; unfortunately, however, strong evidence is lacking for many of the clinical questions addressed.

Principles Of Evidence-Based Medicine

Imaging studies for neurological emergencies share a common problem in that the gold-standard for diagnosis is often another imaging study, and there is no clear, independent means of settling discrepancies. It is unclear what strategy should be used when two imaging studies yield divergent results. For example, if CT is compared to MR for evaluation of acute intracranial hemorrhage, which test should serve as the gold standard? Given a negative CT in the context of a positive MR, is the CT a false negative or the MR a false positive? Alternative gold standards may include clinical follow-up for mortality, readmission, neurosurgical intervention, or neurological outcome. When evaluating a study's relevance to clinical practice, the strength of the gold standard must be considered.

Another important concept when interpreting the results of a study is "point estimate" versus "95% confidence interval." Take the example of a study with a point estimate sensitivity of 99% and a confidence interval of 66-100%. The 95% confidence interval indicates that the sensitivity of the test has a 95% chance of lying between the extreme values of 66% and 100%. While the likelihood of the test having either of these extreme values is low, it cannot be ruled out on the basis of the data. Small studies will often have broad 95% confidence intervals for their results, while larger studies usually have narrower confidence intervals. For a test to be reliable for ruling out a disease process, it must have both high sensitivity and a narrow confidence interval. To rule in pathology, the specificity must be high and the confidence interval narrow. The lower boundary of the confidence interval can be considered a "worst case scenario" for the test characteristic.

Another means of reporting a test's ability to "rule in" or "rule out" pathology is the likelihood ratio (LR). The likelihood ratio positive (LR+) is the factor by which the likelihood of disease increases when the test result is positive. The likelihood ratio negative (LR-) is the factor by which the likelihood of disease decreases when the test result is negative. The pretest probability multiplied by the LR (positive or negative) yields the post-test probability.

Positive and negative predictive values are not emphasized in this review because they are heavily influenced by disease prevalence and must be used cautiously in clinical practice.

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