Title |
Clustering in surgical trials - database of intracluster correlations
|
---|---|
Published in |
Trials, January 2012
|
DOI | 10.1186/1745-6215-13-2 |
Pubmed ID | |
Authors |
Jonathan A Cook, Thomas Bruckner, Graeme S MacLennan, Christoph M Seiler |
Abstract |
Randomised trials evaluation of surgical interventions are often designed and analysed as if the outcome of individual patients is independent of the surgeon providing the intervention. There is reason to expect outcomes for patients treated by the same surgeon tend to be more similar than those under the care of another surgeon due to previous experience, individual practice, training, and infrastructure. Such a phenomenon is referred to as the clustering effect and potentially impacts on the design and analysis adopted and thereby the required sample size. The aim of this work was to inform trial design by quantifying clustering effects (at both centre and surgeon level) for various outcomes using a database of surgical trials. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 4 | 40% |
Egypt | 1 | 10% |
Unknown | 5 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 50% |
Scientists | 3 | 30% |
Practitioners (doctors, other healthcare professionals) | 2 | 20% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Australia | 1 | 2% |
Unknown | 58 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 17 | 29% |
Other | 7 | 12% |
Student > Ph. D. Student | 7 | 12% |
Student > Postgraduate | 5 | 8% |
Student > Master | 5 | 8% |
Other | 10 | 17% |
Unknown | 8 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 27 | 46% |
Mathematics | 5 | 8% |
Nursing and Health Professions | 2 | 3% |
Social Sciences | 2 | 3% |
Agricultural and Biological Sciences | 2 | 3% |
Other | 9 | 15% |
Unknown | 12 | 20% |