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首页> 外文期刊>Orthopaedic Journal of Sports Medicine >How Accurate Are Patients at Diagnosing the Cause of Their Knee Pain With the Help of a Web-based Symptom Checker?
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How Accurate Are Patients at Diagnosing the Cause of Their Knee Pain With the Help of a Web-based Symptom Checker?

机译:借助基于网络的症状检查器,患者诊断膝痛原因的准确性如何?

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Background: Researching medical information is the third most popular activity online, and there are a variety of web-based symptom checker programs available. Purpose: This study evaluated a patient’s ability to self-diagnose their knee pain from a list of possible diagnoses supplied by an accurate symptom checker. Study Design: Cohort study (diagnosis); Level of evidence, 2. Methods: All patients older than 18 years who presented to the office of 7 different fellowship-trained sports medicine surgeons over an 8-month period with a complaint of knee pain were asked to participate. A web-based symptom checker for knee pain was used; the program has a reported accuracy of 89%. The symptom checker generates a list of potential diagnoses after patients enter symptoms and links each diagnosis to informative content. After exploring the informative content, patients selected all diagnoses they felt could explain their symptoms. Each patient was later examined by a physician who was blinded to the differential generated by the program as well as the patient-selected diagnoses. A blinded third party compared the diagnoses generated by the program with those selected by the patient as well as the diagnoses determined by the physician. The level of matching between the patient-selected diagnoses and the physician’s diagnoses determined the patient’s ability to correctly diagnose their knee pain. Results: There were 163 male and 165 female patients, with a mean age of 48 years (range, 18-76 years). The program generated a mean 6.6 diagnoses (range, 2-15) per patient. Each patient had a mean 1.7 physician diagnoses (range, 1-4). Patients selected a mean 2 diagnoses (range, 1-9). The patient-selected diagnosis matched the physician’s diagnosis 58% of the time. Conclusion: With the aid of an accurate symptom checker, patients were able to correctly identify the cause of their knee pain 58% of the time.
机译:背景:研究医学信息是在线上第三大最受欢迎的活动,并且有多种基于Web的症状检查程序可供选择。目的:这项研究从准确的症状检查者提供的一系列可能的诊断中评估了患者自我诊断膝盖疼痛的能力。研究设计:队列研究(诊断);证据级别:2。方法:所有18岁以上且在7个月内因膝关节疼痛而在7位不同的接受过研究金培训的运动医学外科医生的办公室就诊的患者均应参加。使用基于Web的膝盖疼痛症状检查器;该程序的报告准确性为89%。在患者输入症状后,症状检查器会生成潜在诊断的列表,并将每个诊断链接到内容丰富的内容。在探索了内容丰富的内容之后,患者选择了他们认为可以解释其症状的所有诊断。随后,每位患者均由医师检查,医师对程序产生的差异以及患者选择的诊断视而不见。盲目的第三方将程序生成的诊断与患者选择的诊断以及医师确定的诊断进行了比较。患者选择的诊断与医生的诊断之间的匹配程度决定了患者正确诊断膝盖疼痛的能力。结果:男性163例,女性165例,平均年龄48岁(范围18-76岁)。该程序每位患者平均产生6.6次诊断(范围2-15)。每个患者平均有1.7位医生诊断(范围1-4)。患者选择了平均2次诊断(范围1-9)。由患者选择的诊断在58%的时间内与医师的诊断相符。结论:借助准确的症状检查器,患者可以在58%的时间内正确识别出膝盖疼痛的原因。

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