Physical Therapy Program, Sacred Heart University, Fairfield, CT, USA.
Department of Rehabilitation Sciences, University of Hartford, West Hartford, CT, USA.
Braz J Phys Ther. 2021 Jul-Aug;25(4):407-414. doi: 10.1016/j.bjpt.2020.12.001. Epub 2020 Dec 13.
There is considerable overlap between pain referral patterns from the lumbar disc, lumbar facets, the sacroiliac joint (SIJ), and the hip. Additionally, sciatic like symptoms may originate from the lumbar spine or secondary to extra-spinal sources such as deep gluteal syndrome (GPS). Given that there are several overlapping potential anatomic sources of symptoms that may be synchronous in patients who have low back pain (LBP), it may not be realistic that a linear deductive approach can be used to establish a diagnosis and direct treatment in this group of patients.
The objective of this theoretical clinical reasoning model is to provide a framework to help clinicians integrate linear and non-linear clinical reasoning approaches to minimize clinical reasoning errors related to logically fallacious thinking and cognitive biases.
This masterclass proposes a hypothesis-driven and probabilistic approach that uses clinical reasoning for managing LBP that seeks to eliminate the challenges related to using any single diagnostic paradigm.
This model integrates the why (mechanism of primary symptoms), where (location of the primary driver of symptoms), and how (impact of mechanical input and how it may or may not modulate the patient's primary complaint). The integration of these components individually, in serial, or simultaneously may help to develop clinical reasoning through reflection on and in action. A better understanding of what these concepts are and how they are related through the proposed model may help to improve the clinical conversation, academic application of clinical reasoning, and clinical outcomes.
腰椎间盘、腰椎小关节、骶髂关节(SIJ)和髋关节的疼痛牵涉模式有很大的重叠。此外,类似坐骨神经的症状可能源于腰椎,或继发于脊柱外的来源,如臀深部综合征(GPS)。鉴于腰痛(LBP)患者可能存在几个重叠的潜在解剖学症状来源,线性演绎方法可能无法用于确定诊断并指导治疗,这是现实情况。
本理论临床推理模型的目的是提供一个框架,帮助临床医生整合线性和非线性临床推理方法,以最大程度地减少与逻辑谬误思维和认知偏差相关的临床推理错误。
本大师班提出了一种假设驱动和概率方法,用于管理 LBP 的临床推理,旨在消除使用任何单一诊断范式的相关挑战。
该模型整合了“为什么(主要症状的机制)”、“在哪里(症状的主要驱动因素的位置)”和“如何(机械输入的影响以及它如何或可能不会调节患者的主要抱怨)”。这些组件的单独、连续或同时整合,可能有助于通过反思和行动来发展临床推理。通过提出的模型更好地理解这些概念是什么以及它们是如何相关的,可能有助于改善临床对话、临床推理的学术应用和临床结果。