If one treatment group appears to do better, does that mean patients benefit? The answer depends on more than which number is larger. Researchers ask whether a difference could plausibly have arisen by chance under a specified statistical model, and clinicians ask whether the size and kind of difference matter in practice. Those are related questions, but they are not the same. A wound-healing trial makes the distinction especially visible when promising percentages coexist with uncertainty.
What a significance test asks
A statistical test evaluates how compatible observed data are with a particular null hypothesis, often the idea that there is no difference between groups. A p-value is not the probability that a treatment works, nor is it a measure of the size of an effect. It describes how unusual data at least this discrepant would be under the assumed model if the null hypothesis were true. Study design and data quality still matter: a precise calculation cannot repair biased comparisons or incomplete measurement.
Consider a small trial in which more wounds heal in one group than another. The observed gap could reflect a real effect, random variation, or features of the study that make the groups or observations imperfectly comparable. A threshold for statistical significance is a convention for interpreting evidence; it does not draw a physical boundary between “true” and “false.” The uncertainty around an estimate is therefore as important as the headline number.
A trial with an uncertain difference
In a randomized trial of direct cold atmospheric plasma for venous leg ulcers, 46 participants were allocated among standard care alone and two groups receiving standard care plus different treatment frequencies. At 12 weeks, the reported share of wounds healed was 25.0% in the control group, 53.3% in the once-weekly group, and 61.5% in the twice-weekly group. The reported comparisons were not statistically significant [1].
Those percentages are informative descriptions of what happened in this sample, but they do not establish that the treatment caused the apparent difference. The trial was open-label, and its size was limited; the report states the between-group differences were not statistically significant [1]. Other outcomes, including wound-area reduction, also need interpretation with their uncertainty and study context. The disciplined reading is neither to dismiss the observed pattern nor to treat it as settled proof.
Clinical importance asks a different question
Even a statistically convincing difference may be too small to change care in a meaningful way. Conversely, a potentially important improvement may be estimated imprecisely in a small study. Clinical importance asks what outcome changed, by how much, for whom, and at what cost or burden. For wound care, complete healing, reduction in wound area, adverse events, and the time needed to achieve an outcome are not interchangeable endpoints.
A control group also matters. Comparing a new intervention with standard care asks whether it adds benefit beyond what patients already receive. A treatment that appears helpful against no care might not add value when appropriate standard care is provided. The 2023 IWGDF guideline recommends against using other gases, including cold atmospheric plasma, for diabetes-related foot-ulcer healing compared with standard care. It cites poor evidence, high risk of bias, and very low certainty [2]. This guidance concerns diabetic foot ulcers, while the cited randomized trial concerns venous leg ulcers; the populations and evidence questions should not be conflated.
Evidence is a chain, too
To judge a result, trace the chain from question to conclusion: who was enrolled, how groups were formed, what outcome was measured, how long participants were followed, and how uncertainty was reported. Randomization can reduce systematic differences between groups, but it does not guarantee a precise answer. A confidence interval, when provided, can show a range of effect sizes compatible with the data under the analysis; a wide range signals that the estimate leaves substantial uncertainty.
The clinical question also sets limits on generalization. Evidence about venous ulcers does not automatically answer whether an intervention helps diabetes-related foot ulcers, and a guideline’s recommendation for one condition should not be stretched to every wound. For the diabetic foot-ulcer question, the IWGDF recommendation is explicit: do not use other gases such as cold atmospheric plasma in comparison with standard care [2]. Statistical significance, clinical importance, and applicability are separate checks. Together they help distinguish an interesting measurement from evidence strong enough to change practice.
Sources & further reading
- Direct Cold Atmospheric Plasma for Venous Leg Ulcers: Randomized Trial Smits et al., Advances in Wound Care (2024)
- Guidelines on Interventions to Enhance Healing of Foot Ulcers: 2023 Update International Working Group on the Diabetic Foot
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This explainer describes scientific principles. It does not assess individual treatment choices.
