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Better decisions through science: Exercise testing scores.

机译:通过科学做出更好的决策:练习测试成绩。

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Statistical tools can be used to create scores for assisting in the diagnosis of coronary artery disease and assessing prognosis. General practitioners and internists frequently function as gatekeepers, deciding which patients must be referred to the cardiologist. Therefore, they need to use the basic tools they have available (ie, history, physical examination and the exercise test) in an optimal fashion. Scores derived from multivariable statistical techniques considering clinical and exercise data have demonstrated superior discriminating power compared with diagnosis only using the ST segment response. In addition, by stratifying patients as to probability of disease and prognosis, they provide a more practical management strategy than a response of normal or abnormal. Although computers, as part of information management systems, can calculate complicated equations and derive these scores, physicians are reluctant to trust them. However, when represented as nomograms or simple additive discrete pieces of information, scores are more readily accepted. The scores have been compared with physician judgment and have been found to estimate the presence of coronary disease and prognosis as well as expert cardiologists and often better than nonspecialists. However, the discriminating power of specific variables from the medical history and exercise test remains unclear because of inadequate study design and differences in study populations. Should expired gases be substituted for estimated METs? Should ST/heart rate index be used instead of putting ST depression and heart rate separately into the models? Should right-sided chest leads and heart rate in recovery be considered? There is a need for further evaluation of these easily obtained variables to improve the accuracy of prediction algorithms, especially in women. The portability and reliability of scores must be ensured because access to specialized care must be safeguarded. Assessment of the clinical and exercise test data and application of the newer scores can empower the clinician to assure the cardiac patient access to appropriate and cost-effective cardiologic care.
机译:统计工具可用于创建评分,以帮助诊断冠状动脉疾病和评估预后。全科医生和内科医生经常担任看门人,决定哪些患者必须转介给心脏病专家。因此,他们需要以最佳方式使用其可用的基本工具(即历史记录,体格检查和运动测试)。与仅使用ST段反应进行诊断相比,从考虑临床和运动数据的多变量统计技术得出的分数已显示出卓越的辨别力。此外,通过对患者的疾病和预后进行分层,与正常或异常反应相比,他们提供了更实用的管理策略。尽管计算机作为信息管理系统的一部分,可以计算出复杂的方程式并得出这些分数,但医生仍然不愿意相信它们。但是,当用列线图或简单的附加离散信息表示时,分数更容易被接受。该分数已与医生的判断进行了比较,并被发现可以评估冠心病的存在和预后以及心脏病专家,并且通常比非专家更好。但是,由于研究设计不足和研究人群的差异,尚不清楚病历和运动测试对特定变量的区分能力。应该用过期的气体代替估算的MET吗?是否应该使用ST /心率指数,而不是将ST抑郁和心率分别放入模型中?是否应考虑右侧胸导联和恢复时的心率?需要进一步评估这些容易获得的变量,以提高预测算法的准确性,尤其是在女性中。必须确保分数的可移植性和可靠性,因为必须保障获得专业护理的机会。对临床和运动测试数据的评估以及更新分数的应用可以使临床医生确保心脏病患者获得适当且具有成本效益的心脏护理。

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