PDF(Pubmed)
Abstract：
Hospitalized persons with suspected pulmonary tuberculosis (PTB) are placed in airborne isolation to prevent nosocomial infection, as recommended by the Centers for Disease Control and Prevention (CDC). There is significant evidence that clinicians overuse this resource due to an abundance of caution when confronted with a patient with possible PTB. Many researchers have developed predictive tools based on clinical and radiographic data to assist clinicians in deciding which patients to place in respiratory isolation. We assessed the isolation practices for an urban hospital serving a large immigrant population and then retrospectively applied seven previously derived prediction models of isolation of PTB to our population. Our current clinical practice results in 76% of patients with PTB being placed in isolation on admission. However, 208 patients without PTB were placed in isolation unnecessarily for a total of 584 days. Four models had sensitivities greater than 90%, and two models had sensitivities of 100%. The use of these models would have potentially saved more than 150 days of patient isolation per year.
摘要：
疑似肺结核(PTB)的住院人员被安置在空气隔离中，以防止医院感染，根据疾病控制和预防中心（CDC）的建议。有大量证据表明，临床医生在面对可能患有PTB的患者时，由于非常谨慎，因此过度使用了这种资源。许多研究人员已经开发了基于临床和影像学数据的预测工具，以帮助临床医生决定将哪些患者置于呼吸隔离中。我们评估了为大量移民人口服务的城市医院的隔离做法，然后回顾性地将七个先前得出的PTB隔离预测模型应用于我们的人群。我们目前的临床实践导致76％的PTB患者在入院时被隔离。然而,208名没有PTB的患者被不必要地隔离，总共584天。四个模型的灵敏度大于90%，两个模型的敏感性为100%。使用这些模型可能每年节省超过150天的患者隔离时间。
