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采用算法方法诊断继发性闭经:避免诊断错误。

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

机构信息

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

出版信息

Clin Chim Acta. 2013 Aug 23;423:56-61. doi: 10.1016/j.cca.2013.04.007. Epub 2013 Apr 12.

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.

摘要

育龄期妇女的继发性闭经可能表明存在未确诊的慢性疾病,而准确诊断潜在病因是进行适当治疗的关键。详细的临床评估和一些常见的实验室检查可以轻松识别继发性闭经最常见的原因。然而,一旦排除了这些原因,由于表现相似,并且适当的实验室检测和解释变得至关重要,因此更罕见的病理生理学可能难以诊断。在这些情况下,误诊很常见,这通常是由于实验室检测利用不当造成的,例如未能进行适当的检测、使用过时的检测方法,或者在存在干扰因素或合并症的情况下错误解读。因此,本综述中描述的继发性闭经实验室评估算法方法可以最大限度地降低诊断错误的风险,同时减少检测量、成本和诊断时间。

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