A protocol for the development of a prediction model in mild traumatic brain injury with CT scan abnormality: which patients are safe for discharge?

Autor: Carl Marincowitz, Fiona E. Lecky, William Townend, Victoria Allgar, Andrea Fabbri, Trevor A. Sheldon
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: Diagnostic and Prognostic Research, Vol 2, Iss 1, Pp 1-8 (2018)
Druh dokumentu: article
ISSN: 2397-7523
DOI: 10.1186/s41512-018-0027-4
Popis: Abstract Background Head injury is an extremely common clinical presentation to hospital emergency departments (EDs). Ninety-five percent of patients present with an initial Glasgow Coma Scale (GCS) score of 13–15, indicating a normal or near-normal conscious level. In this group, around 7% of patients have brain injuries identified by CT imaging but only 1% of patients have life-threatening brain injuries. It is unclear which brain injuries are clinically significant, so all patients with brain injuries identified by CT imaging are admitted for monitoring. If risk could be accurately determined in this group, admissions for low-risk patients could be avoided and resources could be focused on those with greater need. This study aims to (a) estimate the proportion of GCS13–15 patients with traumatic brain injury identified by CT imaging admitted to hospital who clinically deteriorate and (b) develop a prognostic model highly sensitive to clinical deterioration which could help inform discharge decision making in the ED. Methods A retrospective case note review of 2000 patients with an initial GCS13–15 and traumatic brain injury identified by CT imaging (2007–2017) will be completed in two English major trauma centres. The prevalence of clinically significant deterioration including death, neurosurgery, intubation, seizures or drop in GCS by more than 1 point will be estimated. Candidate prognostic factors have been identified in a previous systematic review. Multivariable logistic regression will be used to derive a prognostic model, and its sensitivity and specificity to the outcome of deterioration will be explored. Discussion This study will potentially derive a statistical model that predicts clinically relevant deterioration and could be used to develop a clinical risk tool guiding the need for hospital admission in this group.
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