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Evaluation of studies of treatment or prevention interventions. Part 2: applying the results of studies to your patients
  1. Nicky Cullum, RN, PhD
  1. Centre for Evidence Based Nursing Department of Health Studies University of York York, UK

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In the previous article in this users' guide series, we began to look at how a critical appraisal checklist could be used to help to decide whether a piece of research is sufficiently valid for its results to be applied to patients.1 This article continues the appraisal of the same study but focuses on its results to answer the questions:

What were the results?

  • How large was the treatment effect?

  • How precise is the estimate of treatment effect?

Will the results help me in caring for my patients?

  • Are my patients so different from those in the study that the results don't apply?

  • Is the treatment feasible in our setting?

  • Were all clinically important outcomes (harms as well as benefits) considered?

Review of the clinical scenario

You are a diabetes specialist nurse who, along with podiatrist colleagues, runs a foot care clinic for people with diabetes. A patient presents at the clinic with a full thickness plantar foot ulcer without any sign of arterial disease. The patient is enthusiastic to try an artificial skin replacement as she has read about them on the internet. You are unfamiliar with this type of wound covering, and your search for the best available evidence identified no systematic review and one randomised controlled trial (RCT).2 You are now getting to grips with this RCT before the patient's next visit.


The aim of this part of the appraisal is to help the reader to judge whether the results of an individual study are important. This decision takes into account the size of the treatment effect and whether the estimate of the treatment effect is precise.

How large was the treatment effect?

The effects of individual treatments are measured using one or more outcome measures. Previous EBN notebooks have described how outcome measures can be dichotomous (eg, yes or no, dead or alive, healed or …

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