Publications by authors named "Norma Coffey"

Introduction: Patients  with corneal foreign bodies (CFBs) often present to the emergency department (ED). However, removal techniques vary among emergency physicians (EPs). A prospective, single-blinded, observational study was performed to compare slit-lamp-aided (SLA) versus non-slit-lamp-aided (NSLA) CFB removal by EPs.

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Aim: To compare the effectiveness of group follow-up with individual follow-up after participation in the Dose Adjustment for Normal Eating (DAFNE) structured education programme.

Methods: Cluster randomised controlled trial involving 437 adults with type 1 diabetes attending hospital diabetes clinics in Ireland. All participants received DAFNE at baseline.

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Background: This work aimed to assess the effects of the annual breast cancer awareness campaign on internet search activity, and to compare these effects with those of similar campaigns in prostate and lung cancer. We further aimed to assess overall levels of online activity relating to all three neoplasms between 2004 and 2009.

Methods: Google Insights for Search was employed to examine search trends for the term "breast cancer", across all Google domains between January 2004 and December 2009 (6 years).

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Purpose: Chronic Achilles tendon (AT) injuries are common, but kinematic studies confirming the exact mechanisms of injury and how orthoses are effective are lacking. Existing analysis often relies on discrete measures and provides an incomplete analysis because many of the data are discarded. Functional data analysis (FDA) views the entire dataset as a function, thus retaining the main features of the curve.

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Objectives: This paper examines the pitfalls that arise when an outlier is assessed using a criterion based on a fixed multiple of the standard deviation rather than an established statistical test. Although the former approach is statistically invalid, it is the favored method for identifying outliers in Ontario laboratory quality control protocols.

Design And Methods: Computer simulations are used to calculate the probability of a false positive result (classifying a valid observation as an outlier) when outlier criteria based on fixed multiples of the standard deviation are applied to samples containing no outliers.

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