Deduction, Induction and the Art of Clinical Reasoning in Medical Education: Systematic Review and Bayesian Proposal

Abstract Background Clinical reasoning is at the core of medical practice and entangled in a conceptual confusion. The duality theory in probability allows to evaluate its objective and subjective aspects. Objectives To conduct a systematic review of the literature about clinical reasoning in decision making in medical education and to propose a “reasoning based on the Bayesian rule” (RBBR). Methods A systematic review on PubMed was conducted (until February 27, 2022), following a strict methodology, by a researcher experienced in systematic review. The RBBR, presented in the discussion section, was constructed in his undergraduate dissertation in Philosophy at Minas Gerais Federal University. Heart failure was used as example. Results Of 3,340 articles retrieved, 154 were included: 24 discussing the uncertainty condition, 87 on vague concepts (case discussion, heuristics, list of cognitive biases, choosing wisely) subsumed under the term “art”, and 43 discussing the general idea of inductive or deductive reasoning. RBBR provides coherence and reproducibility rules, inference under uncertainty, and learning rule, and can incorporate those vague terms classified as “art”, arguments and evidence, from a subjective perspective about probability. Conclusions This systematic review shows that reasoning is grounded in uncertainty, predominantly probabilistic, and reviews possible errors of the hypothetico-deductive reasoning. RBBR is a two-step probabilistic reasoning that can be taught. The Bayes theorem is a linguistic tool, a general rule of reasoning, diagnosis, scientific communication and review of medical knowledge according to new evidence.

摘要
背景 临床推理（clinical reasoning）是医学实践的核心，却面临概念层面的混淆。概率对偶理论（duality theory in probability）可用于评估其客观与主观层面。
研究目的 针对医学教育中决策相关的临床推理文献开展系统综述（systematic review），并提出"基于贝叶斯法则的推理（reasoning based on the Bayesian rule，RBBR）"模型。
研究方法 由一名精通系统综述方法的研究者，遵循严格的研究流程，在PubMed数据库中开展系统综述（检索截止至2022年2月27日）。RBBR模型的构建源于该研究者在米纳斯吉拉斯联邦大学哲学专业的本科毕业论文，并在本次综述的讨论环节中予以呈现。本研究以心力衰竭作为示例。
研究结果 本次综述共检索到3340篇文献，最终纳入154篇：其中24篇探讨不确定性情境，87篇围绕被归入“临床技艺”范畴的模糊概念展开讨论（包括病例讨论、启发式思维（heuristics）、认知偏差（cognitive biases）、明智选择等），另有43篇探讨归纳推理（inductive reasoning）或演绎推理（deductive reasoning）的通用理念。RBBR模型可提供一致性与可重复性准则、不确定性情境下的推理方法以及学习规则，同时能够从概率的主观视角纳入被归类为“临床技艺”的模糊概念、论证与证据。
研究结论 本次系统综述表明，临床推理根植于不确定性，且本质上以概率为核心，同时本综述也梳理了假说-演绎推理（hypothetico-deductive reasoning）可能存在的谬误。RBBR模型是一种可教学的两步式概率推理方法。贝叶斯定理（Bayes theorem）作为一种语言学工具，是推理、诊断、科学传播以及依据新证据梳理医学知识的通用准则。