The St.Emlyn’s Podcast

Understanding P Values: A Comprehensive Guide for Clinicians

Welcome to St Emlyn's blog, where we delve into the complex world of P values—a crucial element in medical research. For emergency medicine clinicians, understanding P values is essential for interpreting study results and applying them effectively in clinical practice. This post aims to demystify P values and enhance your critical appraisal skills.

What Are P Values?

P values are a measure of the probability that an observed difference could have occurred just by chance if the null hypothesis were true. The null hypothesis generally states that there is no difference between two treatments or interventions. Thus, a P value helps us determine whether the observed data is consistent with this hypothesis.

The Null Hypothesis and Significance Testing

To grasp P values fully, we start with the null hypothesis. In any trial, we begin with the premise that there is no difference between the treatments being tested. Our goal is to test this null hypothesis and ideally disprove it, a process known as significance testing.

When we calculate a P value, we express the probability of obtaining a result as extreme as the one observed, assuming the null hypothesis is true. For instance, a P value of 0.05 suggests a 5% chance that the observed difference is due to random variation alone.

The Magic of 0.05

The threshold of 0.05 has become a benchmark in research. A P value below this threshold is often considered statistically significant, while one above is not. However, this binary approach oversimplifies statistical analysis. The figure 0.05 is arbitrary and does not imply that results just above or below this threshold are vastly different in terms of practical significance.

Clinical vs. Statistical Significance

Distinguishing between statistical significance and clinical significance is crucial. A statistically significant result with a very small P value may not always translate into clinical importance. For example, a large study might find that a new treatment reduces blood pressure by 0.5 millimetres of mercury with a P value of 0.001. While statistically significant, such a small reduction may not be clinically relevant.

Conversely, a clinically significant finding might not reach the strict threshold of statistical significance, particularly in smaller studies. Therefore, it's essential to consider both the magnitude of the effect and its practical implications in clinical practice.

The Fragility Index

The fragility index is an alternative measure that addresses some limitations of P values. It calculates the number of events that would need to change to alter the study's results from statistically significant to non-significant. This index provides insight into the robustness of the findings. Surprisingly, even large trials can have a low fragility index, indicating that their results hinge on a small number of events.

Moving Beyond 0.05

Recognizing the limitations of the 0.05 threshold, some researchers advocate for more stringent criteria, such as a P value of 0.02, particularly in large randomized controlled trials (RCTs). This approach aims to reduce the likelihood of false-positive results and improve the reliability of findings. However, it also raises the bar for demonstrating the efficacy of new treatments, which can be a double-edged sword.

Multiple Testing and Bonferroni Adjustment

A significant challenge in research is multiple testing. Conducting numerous statistical tests increases the probability of finding at least one significant result purely by chance. This issue is particularly relevant in exploratory studies where multiple outcomes are assessed.

One method to address this problem is the Bonferroni adjustment, which adjusts the significance threshold based on the number of tests performed. While this approach helps control the risk of false positives, it can be overly conservative and reduce the power to detect true effects. Therefore, it should be used judiciously.

Interim Analysis in Clinical Trials

Interim analysis is a crucial aspect of clinical trials, allowing researchers to assess the effectiveness or harm of an intervention before the study's completion. However, performing multiple interim analyses can increase the risk of false-positive findings. To mitigate this risk, researchers use techniques like P value spending functions, which adjust the significance threshold for each interim analysis.

Additionally, the number of interim analyses should be limited and pre-specified in the study protocol. This ensures that decisions to stop a trial early are based on robust evidence and not on arbitrary or opportunistic analyses.

Effect Size and Confidence Intervals

P values alone do not provide a complete picture of the study results. It's equally important to consider the effect size, which measures the magnitude of the difference between treatments. A small P value might indicate statistical significance, but without a substantial effect size, the clinical relevance of the finding remains questionable.

Confidence intervals (CIs) complement P values by providing a range within which the true effect size is likely to lie. A 95% CI means that if the study were repeated multiple times, 95% of the calculated intervals would contain the true effect size. CIs offer valuable context for interpreting P values and understanding the precision of the estimated effect.

Practical Tips for Interpreting P Values

1. Understand the Null Hypothesis: Always start with a clear understanding of the null hypothesis and what the study aims to test.
2. Look Beyond the P Value: Consider the effect size, confidence intervals, and clinical significance of the findings.
3. Be Cautious with Multiple Testing: Recognize the increased risk of false positives with multiple comparisons and apply appropriate adjustments.
4. Assess the Fragility Index: Use the fragility index to gauge the robustness of the study's findings.
5. Consider Interim Analysis: Ensure that interim analyses are pre-planned and interpreted with caution to avoid bias.
6. Question the Threshold: Remember that the 0.05 threshold is not a magic number. Interpret P values in the context of the study design, sample size, and practical implications.

Conclusion

P values are a fundamental aspect of medical research, but their interpretation requires a nuanced understanding. By considering the null hypothesis, clinical significance, effect size, and confidence intervals, we can make more informed decisions based on the data. As emergency medicine clinicians, our goal is to apply research findings judiciously to improve patient care.

We hope this deep dive into P values has clarified their role and limitations in research. Remember, the journey to mastering statistical concepts is ongoing, and continuous learning is key. If you have any questions or thoughts, please share them in the comments below. Happy appraising, and stay curious!

St. Emlyn's January Roundup: Key Insights and Innovations

Hello and welcome to the St. Emlyn’s Podcast. I’m Simon Carley, joined by Rick Body. Today, we’re bringing you our January roundup, sharing the most intriguing and impactful content we've covered this month. From reflecting on 2018 to exploring new guidelines and innovations in emergency medicine, we have a lot to discuss. Let’s dive in!

Reflecting on 2018: Transformational Reads and Achievements

As we started January, we reflected on 2018, a year filled with significant achievements and insights. One standout discussion was our review of key books that left a lasting impact. A personal favorite of mine is "Why We Sleep" by Matthew Walker. This book has been transformational for me, influencing how I live and advise others on health, well-being, and performance. The insights on sleep’s importance in education, creativity, and overall health are profound.

Rick, did anything from our 2018 review resonate with you?

Rick Body: Absolutely, Simon. The variety of books we discussed was impressive. It was enlightening to hear about others' achievements in 2018 and their goals for 2019. This exercise really focused my mind on what I hope to achieve this year.

Goals for 2019: Innovations and Personal Aspirations

As we moved from reflections to aspirations, we set our sights on exciting projects for 2019. One major highlight is the AI incubator for emergency care. This initiative aims to support academic careers and foster partnerships between data and industry to enhance medical technologies. It’s an exhilarating time for advancements in emergency care.

Rick is incredibly busy with groundbreaking work, particularly in diagnostics in Manchester. His research and speaking engagements are making waves in the medical community. For more details on these projects, check out the blog where all the information is comprehensively covered.

New Year’s Resolutions: Insights from Liz Crowe

We explored New Year’s resolutions with Liz Crowe, who offered a fresh perspective on well-being and resolutions. Instead of focusing on all-or-nothing goals, Liz suggests starting small and seeking rewards rather than punishments. This approach makes significant lifestyle changes more manageable and sustainable. Committing to resolutions publicly or with a friend can enhance accountability and success.

Rick, do you have any New Year’s resolutions?

Rick Body: It’s challenging to pinpoint one or two, but Liz’s advice on avoiding binary thinking is crucial. Recognizing progress rather than dwelling on setbacks can make a big difference.

Tetanus Guidelines: New Insights and Practical Applications

In January, we delved into updated tetanus guidelines, highlighting significant changes. Previously, a single booster in your early 20s was deemed sufficient, but the new guidelines recommend a 10-year booster. This change stems from the recognition that immunity wanes over time. Interestingly, point-of-care testing is now available to detect active tetanus immunization, allowing for more tailored booster decisions.

These updates are crucial for emergency physicians to ensure compliance with current standards and provide optimal patient care. The blog post simplifies these guidelines, making them accessible and easy to understand.

Excellence in Emergency Medicine: Claire Richmond’s Contributions

We featured Claire Richmond, a hero in the emergency medicine community. Claire, who works with Sydney HEMS, delivered an inspiring keynote at the St. Emlyn’s live conference. Her talk focused on excellence, performance, training, and development in retrieval medicine. She emphasized the importance of honesty, feedback, and continuous improvement.

For those aspiring to achieve self-actualization in emergency medicine, Claire’s insights are invaluable. We’ve shared the video and podcast of her talk, and we highly recommend checking them out.

Prognosticating Cardiac Arrest Outcomes: Dan Horner’s Research

Another highlight of January was Professor Dan Horner’s discussion on serum neurofilament light chains, a promising tool for prognosticating cardiac arrest outcomes. This research, stemming from the TTM trial, suggests that these biomarkers can provide early predictions about patient outcomes. Early identification of patients likely to have poor neurological outcomes can significantly impact family discussions, treatment decisions, and overall management.

This research is groundbreaking and holds potential for future clinical applications, although it’s not yet ready for immediate practice.

Celebrating Evidence-Based Medicine: Critical Appraisal E-Book

We’re incredibly proud of our journal club series at St. Emlyn’s, which advocates for evidence-based medicine. This series highlights the latest research, making it accessible and understandable. To celebrate the contributions over the past year, we’ve compiled an e-book available for free download. This resource is a testament to our commitment to advancing medical knowledge and practice.

Pre-Medication for Ketamine Sedation: Exploring New Research

One of the intriguing studies we covered this month examined pre-medication with midazolam or haloperidol for ketamine sedation. The randomized control trial suggested that pre-medication could reduce complications like abnormal behaviors and emergence phenomena. However, it also increased recovery time, requiring more resources and nursing time.

While the findings are interesting, they haven’t convinced us to change our current practice. However, it’s essential to stay informed about such research to make informed decisions in clinical practice.

HEMS and Traumatic Cardiac Arrest: Evaluating Outcomes

We also discussed the role of HEMS in improving outcomes for traumatic cardiac arrest. The study from the UK highlighted the high-level interventions provided by HEMS teams. However, it raised questions about the overall impact on patient survival. Of the 263 patients attended, only seven survived, and all had achieved ROSC before HEMS arrival. This data suggests that while HEMS interventions are critical, their direct impact on survival needs further evaluation.

This topic is sure to spark debate, and we appreciate the transparency of HEMS services in sharing their data and encouraging open discussions.

Looking Ahead: Plans for the Future

As we wrap up January, we’re excited about the plans for the coming months. Simon is heading to Jeddah for a significant event, and we’re considering hosting another St. Emlyn’s live conference and teaching course. We’re exploring innovative formats for medical conferences and welcome your ideas on how we can make these events even more impactful.

Support St. Emlyn’s: Keeping Education Free and Accessible

Since 2012, we’ve funded the blog and podcast out of our own pockets, but as our audience has grown, so have the costs. If you find our content valuable, please consider making a small donation or subscribing for regular contributions. Your support helps us keep St. Emlyn’s free and accessible to all.

Thank you for your time and continued support. Stay tuned for more updates, and as always, enjoy your emergency medicine practice and take care!