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Using an algorithmic approach to secondary amenorrhea: Avoiding diagnostic error. | LitMetric

Using an algorithmic approach to secondary amenorrhea: Avoiding diagnostic error.

Clin Chim Acta

Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, United States.

Published: August 2013

AI Article Synopsis

  • - Secondary amenorrhea in women may signal an undiagnosed chronic condition, and accurate diagnosis is crucial for effective treatment.
  • - Common lab tests can identify frequent causes, but rare conditions may be misdiagnosed due to similarities in symptoms and lab test errors.
  • - An algorithmic approach to lab evaluation can help reduce diagnostic mistakes, lower costs, and speed up the diagnosis process for secondary amenorrhea.

Article Abstract

Secondary amenorrhea in women of reproductive age may be an indication of an undiagnosed, chronic condition and appropriate treatment is dependent upon accurate diagnosis of the underlying etiology. A thorough clinical assessment and a few common laboratory tests can easily identify the most frequent causes of secondary amenorrhea. However, once these have been ruled out, the more uncommon pathophysiologies can be difficult to diagnose due to similarities in presentation and appropriate laboratory testing and interpretation become critical. In these cases, misdiagnosis is unfortunately common and often the result of poor laboratory utilization in the form of a failure to employ indicated tests, the use of obsolete tests, or erroneous interpretation in the face of interfering factors or co-morbidities. Consequently, the algorithmic approach to laboratory evaluation in the context of secondary amenorrhea described in this review can minimize the risk of diagnostic error as well was decrease test volume, cost, and time to diagnosis.

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Source
http://dx.doi.org/10.1016/j.cca.2013.04.007DOI Listing

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