Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Statistics
  • Help & Advice
University of Warwick

The Library

  • Login

Modelling treatment, age- and gender-specific recovery in acute injury studies

Tools
- Tools
+ Tools

Akacha, Mouna, Hutton, Jane L. and Lamb, S. E. (Sallie E.) (2010) Modelling treatment, age- and gender-specific recovery in acute injury studies. Working Paper. University of Warwick. Centre for Research in Statistical Methodology, Coventry.

[img]
Preview
PDF
WRAP_Akacha_10-09w.pdf - Published Version - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader

Download (512Kb)
Official URL: http://www2.warwick.ac.uk/fac/sci/statistics/crism...

Abstract

Background: Acute injury studies often measure physical ability repeatedly over time through scores that have a finite range. This can result in a faster score change at the beginning of the study than towards the end, motivating the investigation of the rate of change. Additionally, the bounds of the score and their dependence on covariates are often of interest. Methods: We argue that transforming bounded data is not satisfactory in some settings. Motivated by the Collaborative Ankle Support Trial (CAST), which investigated different methods of immobilisation for severe ankle sprains, we developed a model under the assumption that the recovery rate at a specific time is proportional to the current score and the remaining score. This model enables a direct interpretation of the covariate effects. We have re-analyzed the CAST data using these improved methods, and explored novel relationships between age, gender and recovery rate. Results: We confirm that using below knee cast is advantageous compared with a tubular bandage in relation with the recovery rate. An age and gender effect on the recovery rate and the maximum achievable score is demonstrated, with older female patients recovering less fast (age-effect: -0.21, 95% confidence interval (CI) [-0.28,- 0.14]; gender effect: -0.06, CI [-0.12,-0.004]) and achieving a lower maximum score (age-effect: -8.07, CI [-11.68,-4.01]; gender-effect: -5.34, CI [-8.18, -2.50]) than younger male patients. Conclusions: Our model is able to accurately model repeated measurements on the original scale, while accounting for the bounded nature of a score. We demonstrate that recovery in acute injury trials can differ substantially by age and gender. Older female patients are less likely to recover well from a sprain.

Item Type: Working or Discussion Paper (Working Paper)
Subjects: Q Science > QA Mathematics
R Medicine > R Medicine (General)
Divisions: Faculty of Science > Statistics
Faculty of Medicine > Warwick Medical School
Library of Congress Subject Headings (LCSH): Medical statistics, Wounds and injuries -- Mathematical models, Medical rehabilitation -- Mathematical models
Series Name: Working papers
Publisher: University of Warwick. Centre for Research in Statistical Methodology
Place of Publication: Coventry
Date: May 2010
Volume: Vol.2010
Number: No.9
Number of Pages: 12
Status: Not Peer Reviewed
Access rights to Published version: Open Access
References: [1] Mahony F, Barthel D. Functional evaluation: the Barthel index. Maryland State Medical Journal. 1965;14:56{61. [2] Vernon H, Mior S. The Neck Disability Index: a study of reliability and validity. Journal of Manipulative and Physiological Therapeutics. 1991;14:409{415. [3] Roos E, Brandsson S, Karlsson J. Validation of the foot and ankle outcome score for ankle ligament reconstruction. Foot & Ankle International. 2001;22(10):788{ 794. [4] Lamb SE, Nakash RA, Withers EJ, Clark M, Marsh JL, Wilson S, et al. Clinical and cost effectiveness of mechanical support for severe ankle sprains: Design of a randomised controlled trial in the emergency department. BMC Musculoskeletal Disorders. 2005;6:1471{2474. [5] Lamb SE, Marsh JL, Hutton JL, Nakash RA, Cooke MW. Mechanical supports for acute, severe ankle sprains: a pragmatic, multi-centre, randomised controlled trial. Lancet. 2009;373:575{581. [6] Cooke MW, Marsh JL, Clark M, Nakash RA, Jarvis RM, Hutton JL, et al. Treatment of severe ankle sprain: A pragmatic randomised controlled trial comparing the clinical effectiveness and cost-effectiveness of three types of mechanical ankle support with tubular bandage. The CAST trial. Health Technology Assessment. 2009;13: No.13. [7] Karlsson J, Peterson L. Evaluation of ankle joint function: the use of a scoring scale. The Foot. 1991;1:15{19. [8] Avci S, Sayli U. Comparison of the results of short-term rigid and semi-rigid cast immobilization for the treatment of grade 3 inversion injuries of the ankle. Injury. 1998;29:581{584. [9] Linde F, Hvass I, Juergensen U, Madsen F. Early mobilizing treatment in lateral ankle sprains. Course and risk factors for chronic painful or function-limiting ankle. Scandinavian Journal of Rehabilitation Medicine. 1986;18:17{21. [10] Schapp GR, de Keizer G, Marti K. Inversion trauma of the ankle. Archives of Orthopaedic and Trauma Surgery. 1989;108:273{275. [11] Sherman M, Le Cessie S. A comparison between bootstrap methods and generalized estimating equations for correlated outcomes in generalized linear models. Communications in Statistics - Simulation and Communication. 1997;26:901{925. [12] Little RJA, Rubin DB. Statistical analysis with missing data. Wiley Interscience; 2002. [13] Molenberghs G, Kenward MG. Missing data in clinical studies. Wiley; 2007. [14] Akacha M, Hutton JL. Analysing the rate of change in a longitudinal study with missing data, taking into account the number of contact attempts;. Available at: http://www2.warwick.ac.uk/fac/sci/statistics/crism/research/2010/. [15] Nakash RA, Hutton JL, Lamb SE, Gates S, Fisher J. Response and non-response to postal questionnaire follow-up in a clinical trial - A qualitative study of the patient's perspective. Journal of Evaluation in Clinical Practice. 2008;14:226{235. [16] Davidian M, Giltinan DM. Nonlinear models for repeated measurement data. Chapman & Hall; 1995. [17] SAS/STAT Users Guide, Version 8. Cary, NC: SAS Institute Inc.; 1999. [18] Molenberghs G, Verbeke G. Models for discrete longitudinal data. Springer; 2005. [19] Davidian M, Giltinan DM. Some general estimation methods for non-linear mixed models. Journal of Biopharmaceutical Statistics. 1993;3:23{55. [20] Vonesh EF, Chinchilli VM. Linear and nonlinear models for the analysis of repeated measurements. Marcel Dekker, Inc.; 1997. [21] Bridgman SA, Clement D, Downing A, Walley G, Phair I, Maulli N. Population based epidemiology of ankle sprains attending accident and emergency units in the West Midlands of England, and a survey of UK practice for severe ankle sprains. Emergency Medicine Journal. 2003;20:508{510.
URI: http://wrap.warwick.ac.uk/id/eprint/35073

Request changes to a record

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...
twitter

Email us: publications@warwick.ac.uk
Contact Details
About Us