Decision-making in the diagnosis of tuberculous meningitis.
Decision-making in the diagnosis of tuberculous meningitis.
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DOI：
10.12688/wellcomeopenres.15611.1
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发表时间：
2020-01-01
影响因子：
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通讯作者：
Seddon, James A
中科院分区：
文献类型：
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作者：
Boyles, Tom H;Lynen, Lutgarde;Seddon, James A
结核性脑膜炎（TBM）是结核病（TB）中最具破坏性的一种，但诊断困难，延误治疗会增加死亡率。所有目前可用的测试是不完善的;从脑脊液（CSF）中培养结核分枝杆菌被认为是最准确的测试，但往往是阴性的，即使当疾病存在，并需要太长的时间是有用的立即决策。常用的快速检测是常规的Ziehl-Neelsen染色和核酸扩增检测，如Xpert MTB/RIF和Xpert MTB/RIF Ultra。虽然阳性结果通常会确认诊断，但阴性测试通常提供的证据不足，无法停止治疗。传统的诊断方法是根据TB的患病率、病史、检查、基本血液和CSF参数分析、成像和快速检测结果，使用经验和直觉确定TBM的概率。因此，治疗决定可能是可变的和不准确的，取决于临床医生的经验，并且测试的请求可能是不适当的。在这篇文章中，我们讨论了使用贝叶斯定理和阈值模型的决策方法，以改善测试和治疗决策的TBM。贝叶斯定理描述了根据检验结果将疾病的验前概率转化为验后概率的过程，阈值模型指导临床医生做出合理的检验和治疗决策。我们讨论了使用这些方法的优点和局限性，并建议新的诊断策略最终应在随机试验中进行测试。
Tuberculous meningitis (TBM) is the most devastating form of tuberculosis (TB) but diagnosis is difficult and delays in initiating therapy increase mortality. All currently available tests are imperfect; culture of Mycobacterium tuberculosis from the cerebrospinal fluid (CSF) is considered the most accurate test but is often negative, even when disease is present, and takes too long to be useful for immediate decision making. Rapid tests that are frequently used are conventional Ziehl-Neelsen staining and nucleic acid amplification tests such as Xpert MTB/RIF and Xpert MTB/RIF Ultra. While positive results will often confirm the diagnosis, negative tests frequently provide insufficient evidence to withhold therapy. The conventional diagnostic approach is to determine the probability of TBM using experience and intuition, based on prevalence of TB, history, examination, analysis of basic blood and CSF parameters, imaging, and rapid test results. Treatment decisions may therefore be both variable and inaccurate, depend on the experience of the clinician, and requests for tests may be inappropriate. In this article we discuss the use of Bayes' theorem and the threshold model of decision making as ways to improve testing and treatment decisions in TBM. Bayes' theorem describes the process of converting the pre-test probability of disease to the post-test probability based on test results and the threshold model guides clinicians to make rational test and treatment decisions. We discuss the advantages and limitations of using these methods and suggest that new diagnostic strategies should ultimately be tested in randomised trials.