Randolph A G, Guyatt G H, Calvin J E, Doig G, Richardson W S
Department of Anesthesia and Pediatrics, Children's Hospital and Harvard Medical School, Boston, MA, USA.
Crit Care Med. 1998 Sep;26(9):1603-12. doi: 10.1097/00003246-199809000-00036.
Clinical prediction rules and models are developed by applying statistical techniques to find combinations of predictors that categorize a heterogeneous group of patients into subgroups of risk. Our goal is to teach clinicians how to evaluate the validity, results, and applicability of articles describing clinical prediction tools. CLINICAL EXAMPLE: An article describing a rule to predict the need for intensive care unit care admission in patients presenting to the emergency room with chest pain.
Valid clinical prediction tools are developed by completely following up a representative group of patients, by evaluating all potential predictors and testing the independent contribution of each predictor variable, and by ensuring that the outcomes were independent of the predictors. To evaluate the results of an article describing a clinical prediction tool, clinicians need to know what the prediction tool is, how well it categorizes patients into different levels of risk, and what the confidence intervals are around the risk estimates. Valid prediction tools are not applicable in every patient population. Before patient care application, the clinician should ensure that the tool maintains its prediction power in a new sample of patients, that the patients are similar to patients used to test the tool, and that the tool has been shown to improve clinical decision-making.
There has been an increase in the development and validation of clinical prediction rules and models. It is important to evaluate the validity and reliability of these prediction tools before application.
临床预测规则和模型是通过应用统计技术来找出预测因素的组合，从而将一组异质性患者分类为不同风险亚组而开发的。我们的目标是教导临床医生如何评估描述临床预测工具的文章的有效性、结果及适用性。临床实例：一篇描述用于预测因胸痛就诊于急诊室的患者入住重症监护病房需求的规则的文章。
有效的临床预测工具是通过对一组具有代表性的患者进行完整随访、评估所有潜在预测因素并测试每个预测变量的独立贡献，以及确保结果独立于预测因素而开发的。为了评估一篇描述临床预测工具的文章的结果，临床医生需要知道该预测工具是什么、它将患者分类到不同风险水平的效果如何，以及风险估计周围的置信区间是多少。有效的预测工具并非适用于每一个患者群体。在将其应用于患者护理之前，临床医生应确保该工具在新的患者样本中保持其预测能力，确保患者与用于测试该工具的患者相似，并且该工具已被证明能改善临床决策。
临床预测规则和模型的开发及验证有所增加。在应用之前评估这些预测工具的有效性和可靠性很重要。
