Validació d’un model predictiu per a la identificació de lesions intracranials en els pacients amb traumatisme cranial lleu assistits en el medi extrahospitalari

Portabella Serra, Anna
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The severity of traumatic brain injury (TBI) depends on the primary injury and subsequent complications. The Glasgow Coma Scale (GCS) is used to assess its initial severity. We talk about mild TBI when the GCS score ranges from 15-13 points. The clinical course of mild TBI is generally satisfactory, but there are several intracranial lesions that are subsidiary to neurosurgical treatment. In outpatient care, the assessment of GCS along with the detection of neurological signs suggest the presence of an intracranial lesion. A retrospective study by our research group identified the predictive factors of intracranial injury in mild TBI assisted by the Emergency Medical Service (EMS) of Manresa. Based on the identification of these factors, a predictive model of the likelihood of intracranial lesions was developed in patients with mild TBI assisted in the outpatient setting. The main objective of the current study is to determine the external validity of the model and to establish a cut-off point that optimizes the parameters of the intracranial injury diagnostic. Methodology Prospective and multicenter observational study of patients with mild TBI assisted by the Advanced Life Support Units of the EMS in the period October 2017 - May 2021. To collect the data of the study, the records of EMS assistance, Emergency Department (ED) reports, imaging tests and patients’ clinical history. The study variables were demographics, GCS, injury mechanism, type of pathway, neurological signs, antiplatelet/anticoagulant drugs, presence and type of intracranial lesions, destination of ED discharge, and clinical course 30 days after the event. Descriptive analysis of the demographic, clinical and care characteristics of patients with mild TBI. The incidence of intracranial lesions and the need for neurosurgery were determined. Univariate and multivariate logistic regression models were used to determine intracranial injury risk factors. Raw and adjusted odds ratios (ORs) were determined with a 95% confidence interval. The area under the ROC curve was used to assess the discrimination capacity of the multivariate predictive model. The level of statistical significance used was 5% bilateral (p <0.05). IBM SPSS Statistics for Windows version 26 (IBM Corp, Armonk, New York, USA) and R version 3.6.1 (R Foundation for Statistical Computing, Vienna, Austria) were used for statistical analysis ​
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