Use this URL to cite or link to this record in EThOS:
Title: Early identification and prediction of multiple organ failure following major trauma
Author: Hutchings, Lynn
ISNI:       0000 0004 5349 6679
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2014
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Restricted access.
Access from Institution:
Introduction: Trauma is the main cause of death in working-age adults in the UK. Multiple organ failure (MOF) is associated with a high proportion of late trauma deaths, and MOF survivors have poor long-term outcomes. Early prediction of patients at risk of MOF would assist treatment decisions and allow targeted interventions. Methods: A cohort of major trauma patients requiring intensive care unit (ICU) treatment at the John Radcliffe Hospital was identified. Data were obtained from the two national databases of the Trauma Audit Research Network and the Intensive Care National Audit and Research Centre, and from a local ICU database with hourly data recording. Literature review and questionnaire analysis of trauma clinicians identified candidate predictors of MOF, grouped into patient, injury, physiological, laboratory and management variables. MOF scoring systems were reviewed to determine the most appropriate for use in trauma patients. Prediction models of post-trauma MOF were developed using logistic regression at a range of times from 0 to 48 hours after injury. Models were internally validated using bootstrapping. Results: 517 adult trauma patients were identified from 2003-2011. Overall mortality was 14.9%, with 491 patients surviving more than 48 hours, and therefore being at risk of MOF development. For these 491 patients, MOF incidence depended on the definition, and ranged from 23% (Denver score) to 58% (SOFA score). MOF was associated with mortality, time to ICU admission, and length of ICU and hospital stay. MOF could be predicted with an accuracy of up to 81.3% at 2 hours post-injury, and 84.2% at 12 hours post-injury using small numbers of clinical variables. Age, head injury, abdominal injury, maximum heart rate and the need for vasopressors were strong predictors of all definitions of MOF. Conclusions: Post-trauma MOF can be predicted early after injury using combinations of clinical variables. Further validation of the identified variables on external populations would allow development of a clinical score to assist clinicians in trauma management.
Supervisor: Watkinson, P.; Young, J. D.; Willett, K. M. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Orthopaedics ; Organisation and evaluation of medical care ; Anaesthetics ; Medical Sciences ; Trauma ; multiple organ failure ; predictive model