Decision tree analysis to predict the risk of intracranial haemorrhage after mild traumatic brain injury in patients taking DOACs

2021 ◽  
Author(s):  
Gianni Turcato ◽  
Arian Zaboli ◽  
Norbert Pfeifer ◽  
Antonio Maccagnani ◽  
Andrea Tenci ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Decision Tree ◽  
Mild Traumatic Brain Injury ◽  
Intracranial Haemorrhage ◽  
Decision Tree Analysis ◽  
Tree Analysis

Clinical Elements that Predict Outcome after Traumatic Brain Injury: A Prospective Multicenter Recursive Partitioning (Decision-Tree) Analysis

2005 ◽  
Vol 22 (10) ◽  
pp. 1040-1051 ◽  
Author(s):  
Allen W. Brown ◽  
James F. Malec ◽  
Robyn L. McClelland ◽  
Nancy N. Diehl ◽  
Jeffrey Englander ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Decision Tree ◽  
Recursive Partitioning ◽  
Decision Tree Analysis ◽  
Tree Analysis

A decision tree framework for understanding blast-induced mild Traumatic Brain Injury in a military medical database

2017 ◽  
Vol 14 (4) ◽  
pp. 389-398 ◽  
Author(s):  
Peter B Walker ◽  
Melissa L Mehalick ◽  
Amanda C Glueck ◽  
Anna E Tschiffely ◽  
Craig A Cunningham ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Personalized Medicine ◽  
Decision Tree ◽  
Mild Traumatic Brain Injury ◽  
Health Data ◽  
Decision Tree Classifier ◽  
Tree Classifier ◽  
Clustering Quality ◽  
Over Time

Personalized medicine is a ubiquitous term that has come to be used to describe a medical model that proposes the customization of healthcare, such that decisions and/or treatments are tailored to each individual patient. Under this type of clinical practice model, diagnostic and prognostic decisions are often based upon selecting the most appropriate therapy based on a patient’s genetic, demographic, and/or other pertinent information. The primary aim of this paper is to use a personalized medicine framework to better understand the relationship between neuropsychological testing and the progression of symptoms in a blast-induced mild Traumatic Brain Injury (mTBI) patient population. In this paper, we extended our earlier work on Constrained Spectral Partitioning (CSP), a graph-based approach that incorporates additional information from separate graphs to help improve the clustering quality on both graphs simultaneously. While our previous work demonstrated the effectiveness of this algorithm in its ability to accurately classify whether symptoms improved or declined over time, that work did not provide any insights into the progression of symptoms. Therefore, this paper sought to identify, from a clinical perspective, whether symptoms increased/decreased over time. To accomplish this, we developed a decision tree classifier to classify symptom progression based on the outputs from our CSP algorithm. We present results from four separate decision tree classifiers that illustrate the adaptability of these algorithms for utilization as decision rules for the treatment of patients following blast-induced mTBI. Decision tree classifier models are useful in the healthcare setting because patient health data (e.g., diagnosis of a condition or a type of treatment) can be imput into the model and, based on the health data variables, a resulting outcome can be suggested, and providers can use this outcome as information to direct their clinical treatment.

scholarly journals Exploratory Use of Decision Tree Analysis in Classification of Outcome in Hypoxic–Ischemic Brain Injury

2018 ◽  
Vol 9 ◽  
Author(s):  
Thanh G. Phan ◽  
Jian Chen ◽  
Shaloo Singhal ◽  
Henry Ma ◽  
Benjamin B. Clissold ◽  
...  
Keyword(s):  
Brain Injury ◽  
Decision Tree ◽  
Ischemic Brain Injury ◽  
Decision Tree Analysis ◽  
Ischemic Brain ◽  
Tree Analysis ◽  
Hypoxic Ischemic Brain Injury

scholarly journals Age is not associated with intracranial haemorrhage in patients with mild traumatic brain injury and oral anticoagulation

2016 ◽  
Vol 15 (1) ◽  
Author(s):  
Thomas C. Sauter ◽  
Stephan Ziegenhorn ◽  
Sufian S. Ahmad ◽  
Wolf E. Hautz ◽  
Meret E. Ricklin ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Mild Traumatic Brain Injury ◽  
Oral Anticoagulation ◽  
Intracranial Haemorrhage

scholarly journals S100B protein level for the detection of clinically significant intracranial haemorrhage in patients with mild traumatic brain injury: a subanalysis of a prospective cohort study

2020 ◽  
pp. emermed-2020-209583
Author(s):  
Julien Blais Lécuyer ◽  
Éric Mercier ◽  
Pier-Alexandre Tardif ◽  
Patrick M Archambault ◽  
Jean-Marc Chauny ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Cohort Study ◽  
Brain Injury ◽  
Mild Traumatic Brain Injury ◽  
Protein Level ◽  
Intracranial Haemorrhage ◽  
S100b Protein ◽  
Head Ct ◽  
Hospitalised Patients ◽  
Clinically Significant

BackgroundClinical assessment of patients with mild traumatic brain injury (mTBI) is challenging and overuse of head CT in the ED is a major problem. Several studies have attempted to reduce unnecessary head CTs following a mTBI by identifying new tools aiming to predict intracranial bleeding. Higher levels of S100B protein have been associated with intracranial haemorrhage following a mTBI in previous literature. The main objective of this study is to assess whether plasma S100B protein level is associated with clinically significant brain injury and could be used to reduce the number of head CT post-mTBI.MethodsStudy design: secondary analysis of a prospective multicentre cohort study conducted between 2013 and 2016 in five Canadian EDs. Inclusion criteria: non-hospitalised patients with mTBI with a GCS score of 13–15 in the ED and a blood sample drawn within 24 hours after the injury. Data collected: sociodemographic and clinical data were collected in the ED. S100B protein was analysed using ELISA. All CT scans were reviewed by a radiologist blinded to the biomarker results. Main outcome: the presence of clinically important brain injury.Results476 patients were included. Mean age was 41±18 years old and 150 (31.5%) were women. Twenty-four (5.0%) patients had a clinically significant intracranial haemorrhage. Thirteen patients (2.7%) presented a non-clinically significant brain injury. A total of 37 (7.8%) brain injured patients were included in our study. S100B median value (Q1–Q3) was: 0.043 µg/L (0.008–0.080) for patients with clinically important brain injury versus 0.039 µg/L (0.023–0.059) for patients without clinically important brain injury. Sensitivity and specificity of the S100B protein level, if used alone to detect clinically important brain injury, were 16.7% (95% CI 4.7% to 37.4%) and 88.5% (95% CI 85.2% to 91.3%), respectively.ConclusionPlasma S100B protein level was not associated with clinically significant intracranial lesion in patients with mTBI.

Rivaroxaban and intracranial haemorrhage after mild traumatic brain injury: A dangerous combination?

2015 ◽  
Vol 136 ◽  
pp. 73-78 ◽  
Author(s):  
Christopher Beynon ◽  
Anna Potzy ◽  
Oliver W. Sakowitz ◽  
Andreas W. Unterberg
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Mild Traumatic Brain Injury ◽  
Intracranial Haemorrhage

The Speech-Language Pathologists' Role in Mild Traumatic Brain Injury for Middle and High School–Age Children: Viewpoints on Guidelines From the Centers for Disease Control and Prevention

2019 ◽  
Vol 28 (3) ◽  
pp. 1363-1370 ◽  
Author(s):  
Jessica Brown ◽  
Katy O'Brien ◽  
Kelly Knollman-Porter ◽  
Tracey Wallace
Keyword(s):  
High School ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Disease Control ◽  
Mild Traumatic Brain Injury ◽  
School Age Children ◽  
School Age ◽  
Speech Language Pathologists ◽  
Control And Prevention ◽  
Centers For Disease Control

Purpose The Centers for Disease Control and Prevention (CDC) recently released guidelines for rehabilitation professionals regarding the care of children with mild traumatic brain injury (mTBI). Given that mTBI impacts millions of children each year and can be particularly detrimental to children in middle and high school age groups, access to universal recommendations for management of postinjury symptoms is ideal. Method This viewpoint article examines the CDC guidelines and applies these recommendations directly to speech-language pathology practices. In particular, education, assessment, treatment, team management, and ongoing monitoring are discussed. In addition, suggested timelines regarding implementation of services by speech-language pathologists (SLPs) are provided. Specific focus is placed on adolescents (i.e., middle and high school–age children). Results SLPs are critical members of the rehabilitation team working with children with mTBI and should be involved in education, symptom monitoring, and assessment early in the recovery process. SLPs can also provide unique insight into the cognitive and linguistic challenges of these students and can serve to bridge the gap among rehabilitation and school-based professionals, the adolescent with brain injury, and their parents. Conclusion The guidelines provided by the CDC, along with evidence from the field of speech pathology, can guide SLPs to advocate for involvement in the care of adolescents with mTBI. More research is needed to enhance the evidence base for direct assessment and treatment with this population; however, SLPs can use their extensive knowledge and experience working with individuals with traumatic brain injury as a starting point for post-mTBI care.

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