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Mastering Medical Statistics: Elevate Your Clinical Decision Making

2025/1/15
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Adam Badenoch
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Gavin Nimon
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Gavin Nimon: 我认为医学统计在现代医疗保健中起着至关重要的作用。它是循证医学的基础,使我们能够做出明智的决定,无论是选择最佳治疗方案、评估干预措施的有效性,还是了解患者的风险和益处。在今天的AussieMedEd节目中,我们将探讨医学统计的世界,研究它如何影响临床指南,帮助我们批判性地评估研究论文,并为日常临床实践提供信息。我们还将讨论其他研究设计、样本量的重要性以及如何在研究论文中发现潜在的偏差。 在节目的最后,我还想谈谈人工智能在数据分析中的作用,以及它可能带来的好处和陷阱。 Adam Badenoch: 我同意Gavin的观点。医学统计对于医疗专业人员至关重要,因为它为我们提供了评估研究结果、做出明智的临床决策以及改进医疗实践的工具。理解数据的类型(数值型或分类型)以及如何对数据进行分类和描述是理解医学统计的基础。数据可以分为数值型(离散型或连续型)和分类型(名义型或有序型)。连续型数据通常用中心趋势(均值、中位数、众数)和数据分布(范围、四分位数间距、方差)来描述。均值利用所有数据点的信息,但容易受极端值影响;中位数忽略了数据两端的值,因此更稳健。 在假设检验中,零假设通常是两组之间没有差异,检验旨在判断数据是否与零假设一致。p值表示在零假设为真的情况下观察到数据的概率,p值越低,拒绝零假设的信心越高。样本量大小会影响p值,0.05的显著性阈值是人为设定的。为了保持研究的完整性,需要在研究开始前定义临床重要性的差异和分析方法,并坚持使用预先设定的显著性阈值。置信区间提供了一系列可能的值,这些值包含了真实总体值,并能反映效应量的大小。 在解读医学研究中的统计数据时,最常见的陷阱是假设研究设计良好且结论有效。研究设计是影响研究质量的最重要因素,随机对照试验优于观察性研究。发表偏倚是指发表阳性结果的研究比阴性结果的研究更多,这会影响Meta分析的结果。系统综述是对文献的系统性检索,而Meta分析则整合多个研究的结果,得出平均效应。前瞻性注册研究,公开宣布研究计划,可以避免p值寻觅等问题。敏感性分析可以帮助评估研究结果的稳健性。CONSORT工具和清单可以帮助设计和评估研究。t检验和卡方检验是常用的统计检验方法。 将证据整合到临床实践中需要多方面努力,包括与同事沟通、参与质量改进项目以及考虑组织变革等。人工智能在数据分析方面具有巨大潜力,但也存在引入偏差的风险。为了确保人工智能分析结果的可靠性,需要公开发布代码、数据和输出结果以便进行验证。对于连续型变量且服从正态分布的数据,可以使用t检验或线性回归模型进行分析。

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Join host Dr Gavin Nimon (Orthopaedic Surgeon)) as he unlocks the mysteries of medical statistics and take your clinical decision-making skills to new heights with insights from Dr. Adam Badenoch, an anaesthetist with a Master's in Biostatistics. Discover how essential concepts like central tendency, distribution, and variance can transform your understanding of medical research. Dr. Badenoch explains the significance of numerical and categorical data, and sheds light on how outliers can alter the mean and median, equipping you with the tools needed to critically assess statistical evidence in healthcare.Venture into the complex world of hypothesis testing, where we explore the importance of the null hypothesis and the scrutiny needed before changing clinical practices. Dr. Badenoch demystifies the role of p-values and addresses common criticisms such as the arbitrary 0.05 significance threshold and publication bias. By emphasizing the necessity of defining clinical importance and analysis methods at the outset of studies, this discussion urges a thoughtful balance between scientific integrity and interpretation.Our episode culminates with an insightful look into research study design and the indispensable role of statistical tools in evaluating studies. Learn about confidence intervals and their power to reveal the range of plausible values for true population parameters, standing in contrast to p-values. We also touch on the challenges of implementing evidence-based medicine in practice, with a nod to the potential and pitfalls of artificial intelligence in data analysis. This episode is a must for healthcare professionals aiming to refine their statistical acumen and apply evidence-based insights effectively.

Aussie Med Ed is sponsored by OPC Health, an Australian supplier of prosthetics, orthotics, clinic equipment, compression garments, and more. Rehabilitation devices for doctors, physiotherapists, orthotists, podiatrists, and hand therapists. If you'd like to know what OPC Health offers.

Visit opchealth. com. au )and view their range online.

Aussie Med Ed is sponsored by -HealthShare is a digital health company, that provides solutions for patients, General Practitioners and Specialists across Australia.

Aussie Med Ed is sponsored by Avant  Medical Indemnity: They state that they offer holistic support to help the doctor practice safely and believe they have extensive cover that's continually evolving to meet your needs in the ever changing regulatory environment.