scholarly journals Prognostic Value of Admission Parameters in a Machine Learning Predictive Model in Patients With Severe Traumatic Brain Injury and Acute Subdural Hematomas

Neurosurgery ◽  
2019 ◽  
Vol 66 (Supplement_1) ◽  
Author(s):  
Kevin John ◽  
Aaron McPheters ◽  
Andrew Donovan ◽  
Nicolas K Khattar ◽  
Jacob R Shpilberg ◽  
...  

Abstract INTRODUCTION Acute subdural hematoma (aSDH) in the context of severe traumatic brain injury (TBI) is a neurosurgical emergency. Predictive models have been used in an attempt to modulate the morbidity and mortality of patient outcomes. We used machine learning (ML) to identify admission risk factors predictive of long-term morbidity in the severe TBI patient population with aSDH. METHODS Between 2013 and 2016, 85 patients with severe TBI and aSDH were included in the analysis. Random forest, ML architecture, was used to create a predictive model of long-term morbidity stratification. About 46 patients were included in the high morbidity group [Glasgow Outcome Scale (GOS) 1-2] and 39 patients were in the low morbidity group (GOS 3-5). We included 30 admission input variables including medical and surgical co-morbidities, neurological examination, laboratory values, and radiographic findings. RESULTS The predictive model showed a 78% precision. The highest scoring input variable was the pupillary examination in predicting high vs low morbidity (bilaterally unreactive vs symmetrically reactive; P < .0001). GCS on admission was higher in the low morbidity group (4 [3-7] vs 7 [3-7]; P < .0101). Rotterdam scores were higher in the high-morbidity group (3 [3-5] vs 4 [4-5]; P < .0032). GCS motor examination on admission was higher in the low-morbidity group (5 [1-5] vs. 2 [1-5]; P < .0106). The basal cisterns were found to be more patent in patients with the low-morbidity group (P = .0012). CONCLUSION ML is an efficient tool that can provide a reasonable level of accuracy in predicting long-term morbidity in patients with severe TBI and aSDH. Monitoring these admission criteria can help with risk-stratification of patients into higher and low risk tracks. Integration of ML into the treatment algorithm may allow the development of more refined guidelines to guide goal-directed therapy.

2020 ◽  
Author(s):  
Xiangyi Yin ◽  
Jie Wu ◽  
Lihui Zhou ◽  
Chunyan Ni ◽  
Minyan Xiao ◽  
...  

Abstract Background: Tracheostomy is very common in patients with severe traumatic brain injury (TBI), and long-term nursing care are needed for those patients. We aimed to evaluate the effects of hospital-community-home (HCH) nursing in those patients. Methods: Tracheostomy patients with severe TBI needing long-term care were included. All patients underwent two months long follow-up. Glasgow coma score (GCS), Karnofsky, Self-Anxiety Scale (SAS) (SAS) and Barthel assessment at the discharge and two months after discharge were evaluated. The tracheostomy related complications were recorded and compared.Results: A total of 60 patients were included. There weren’t significant differences between two groups in the GCS, Karnofsky, SAS and Barthel index at discharge((all p>0.05), the GCS, Karnofsky and Barthel index was all significantly increased after two months follow-up for two groups (all p<0.05), and the GCS, Karnofsky and Barthel index at two months follow-up in HCH group was significantly higher than that of control group(all p<0.05), but the SAS at two months follow-up in HCH group was significantly less than that of control group(p=0.009). The incidence of block of artificial tracheal cannula and readmission in HCH group were significant less than that of control group (all p<0.05).Conclusion: HCH nursing care is feasible in tracheostomy patients with severe TBI, future studies are needed to further evaluate the role of HCH nursing care.


2021 ◽  
Author(s):  
Caroline Lindblad ◽  
Elisa Pin ◽  
David Just ◽  
Faiez Al Nimer ◽  
Peter Nilsson ◽  
...  

Abstract Background: Severe traumatic brain injury (TBI) is associated with blood-brain barrier (BBB) disruption and a subsequent neuroinflammatory process. We aimed to perform a multiplex screening of brain enriched and inflammatory proteins in blood and cerebrospinal fluid (CSF) in order to study their role in BBB disruption, neuroinflammation and long-term functional outcome in TBI patients and healthy controls. Methods: We conducted a prospective, observational study on 90 severe TBI patients and 15 control subjects. Clinical outcome data, Glasgow Outcome Score, was collected after 6-12 months. We utilized a suspension bead antibody array analyzed on a FlexMap 3D Luminex platform to characterize 177 unique proteins in matched CSF and serum samples. In addition, we assessed BBB disruption using the CSF-serum albumin quotient (QA), and performed Apolipoprotein E-genotyping as the latter has been linked to BBB function in the absence of trauma. We employed pathway-, cluster-, and proportional odds regression analyses. Key findings were validated in blood samples from an independent TBI cohort.Results: TBI patients had an upregulation of structural and neuroinflammatory pathways in both CSF and serum. In total, 114 proteins correlated with QA, among which the top-correlated proteins were complement proteins. A cluster analysis revealed protein levels to be strongly associated with BBB integrity, but not carriage of the Apolipoprotein E4-variant. Among cluster-derived proteins, innate immune pathways were upregulated. Forty unique proteins emanated as novel independent predictors of clinical outcome, that individually explained ~10% additional model variance. Among proteins significantly different between TBI patients with intact or disrupted BBB, complement C9 in CSF (p = 0.014, DR2 = 7.4%) and complement factor B in serum (p = 0.003, DR2 = 9.2%) were independent outcome predictors also following step-down modelling. Conclusions: This represents the largest concomitant CSF and serum proteomic profiling study so far reported in TBI, providing substantial support to the notion that neuroinflammatory markers, including complement activation, predicts BBB disruption and long-term outcome. Individual proteins identified here could potentially serve to refine current biomarker modelling or represent novel treatment targets in severe TBI.


Critical Care ◽  
2021 ◽  
Vol 25 (1) ◽  
Author(s):  
Caroline Lindblad ◽  
Elisa Pin ◽  
David Just ◽  
Faiez Al Nimer ◽  
Peter Nilsson ◽  
...  

Abstract Background Severe traumatic brain injury (TBI) is associated with blood–brain barrier (BBB) disruption and a subsequent neuroinflammatory process. We aimed to perform a multiplex screening of brain enriched and inflammatory proteins in blood and cerebrospinal fluid (CSF) in order to study their role in BBB disruption, neuroinflammation and long-term functional outcome in TBI patients and healthy controls. Methods We conducted a prospective, observational study on 90 severe TBI patients and 15 control subjects. Clinical outcome data, Glasgow Outcome Score, was collected after 6–12 months. We utilized a suspension bead antibody array analyzed on a FlexMap 3D Luminex platform to characterize 177 unique proteins in matched CSF and serum samples. In addition, we assessed BBB disruption using the CSF-serum albumin quotient (QA), and performed Apolipoprotein E-genotyping as the latter has been linked to BBB function in the absence of trauma. We employed pathway-, cluster-, and proportional odds regression analyses. Key findings were validated in blood samples from an independent TBI cohort. Results TBI patients had an upregulation of structural CNS and neuroinflammatory pathways in both CSF and serum. In total, 114 proteins correlated with QA, among which the top-correlated proteins were complement proteins. A cluster analysis revealed protein levels to be strongly associated with BBB integrity, but not carriage of the Apolipoprotein E4-variant. Among cluster-derived proteins, innate immune pathways were upregulated. Forty unique proteins emanated as novel independent predictors of clinical outcome, that individually explained ~ 10% additional model variance. Among proteins significantly different between TBI patients with intact or disrupted BBB, complement C9 in CSF (p = 0.014, ΔR2 = 7.4%) and complement factor B in serum (p = 0.003, ΔR2 = 9.2%) were independent outcome predictors also following step-down modelling. Conclusions This represents the largest concomitant CSF and serum proteomic profiling study so far reported in TBI, providing substantial support to the notion that neuroinflammatory markers, including complement activation, predicts BBB disruption and long-term outcome. Individual proteins identified here could potentially serve to refine current biomarker modelling or represent novel treatment targets in severe TBI.


2015 ◽  
Vol 2015 ◽  
pp. 1-19 ◽  
Author(s):  
Torun Gangaune Finnanger ◽  
Alexander Olsen ◽  
Toril Skandsen ◽  
Stian Lydersen ◽  
Anne Vik ◽  
...  

Survivors of moderate-severe Traumatic Brain Injury (TBI) are at risk for long-term cognitive, emotional, and behavioural problems. This prospective cohort study investigated self-reported executive, emotional, and behavioural problems in the late chronic phase of moderate and severe TBI, if demographic characteristics (i.e., age, years of education), injury characteristics (Glasgow Coma Scale score, MRI findings such as traumatic axonal injury (TAI), or duration of posttraumatic amnesia), symptoms of depression, or neuropsychological variables in the first year after injury predicted long-term self-reported function. Self-reported executive, emotional, and behavioural functioning were assessed among individuals with moderate and severe TBI (N=67, age range 15–65 years at time of injury) 2–5 years after TBI, compared to a healthy matched control group(N=72). Results revealed significantly more attentional, emotional regulation, and psychological difficulties in the TBI group than controls. Demographic and early clinical variables were associated with poorer cognitive and emotional outcome. Fewer years of education and depressive symptoms predicted greater executive dysfunction. Younger age at injury predicted more aggressive and rule-breaking behaviour. TAI and depressive symptoms predicted Internalizing problems and greater executive dysfunction. In conclusion, age, education, TAI, and depression appear to elevate risk for poor long-term outcome, emphasising the need for long-term follow-up of patients presenting with risk factors.


2020 ◽  
Author(s):  
Xiangyi Yin ◽  
Jie Wu ◽  
Lihui Zhou ◽  
Chunyan Ni ◽  
Minyan Xiao ◽  
...  

Abstract Background Tracheostomy is very common in patients with severe traumatic brain injury (TBI), and long-term nursing care are needed for those patients. We aimed to evaluate the effects of hospital-community-home (HCH) nursing in those patients. Methods Tracheostomy patients with severe TBI were included. Glasgow coma score (GCS), Karnofsky, Self-Anxiety Scale (SAS) and Barthel assessment at the discharge and two months after discharge were evaluated. Results A total of 60 patients were included. There weren’t significant differences between two groups in the GCS, Karnofsky, SAS and Barthel index at discharge((all p > 0.05), the GCS, Karnofsky and Barthel index was all significantly increased after two months follow-up for two groups (all p < 0.05), and the GCS, Karnofsky and Barthel index at two months follow-up in HCH group was significantly higher than that of control group(all p < 0.05), but the SAS at two months follow-up in HCH group was significantly less than that of control group(p = 0.009). The incidence of block of artificial tracheal cannula and readmission in HCH group were significant less than that of control group (all p < 0.05). Conclusion HCH nursing care is feasible in tracheostomy patients with severe TBI, future studies are needed to further evaluate the role of HCH nursing care.


2020 ◽  
Author(s):  
Caroline Lindblad ◽  
Elisa Pin ◽  
David Just ◽  
Faiez Al Nimer ◽  
Peter Nilsson ◽  
...  

Abstract Background: Severe traumatic brain injury (TBI) is associated with blood-brain barrier (BBB) disruption and a subsequent neuroinflammatory process. We aimed to perform a multiplex screening of brain enriched and inflammatory proteins in blood and cerebrospinal fluid (CSF) in order to study their role in BBB disruption, neuroinflammation and long-term functional outcome in TBI patients and healthy controls. Methods: We conducted a prospective, observational study on 90 severe TBI patients and 15 control subjects. Clinical outcome data, Glasgow Outcome Scale, was collected after 6-12 months. We utilized a suspension bead antibody array analyzed on a FlexMap 3D Luminex platform to characterize 177 unique proteins in matched CSF and serum samples. In addition, we assessed BBB disruption using the CSF-serum albumin quotient (QA), and performed Apolipoprotein E-genotyping as the latter has been linked to BBB function in the absence of trauma. We employed pathway-, cluster-, and proportional odds regression analyses.Results: TBI patients had an upregulation of structural and neuroinflammatory pathways in both CSF and serum. In total, 114 proteins correlated with QA, among which the top-correlated proteins were complement proteins. A cluster analysis revealed protein levels to be strongly associated with BBB integrity, but not carriage of the Apolipoprotein E4-variant. Among cluster-derived proteins, innate immune pathways were upregulated. Forty unique proteins emanated as novel independent predictors of clinical outcome, that individually explained ~10% additional model variance. Among proteins significantly different between TBI patients with intact or disrupted BBB, complement C9 in CSF (p = 0.014, ΔR2 = 7.4%) and complement factor B in serum (p = 0.003, ΔR2 = 9.2%) were independent outcome predictors also following step-down modelling. Conclusions: This represents the largest concomitant CSF and serum proteomic profiling study so far reported in TBI, providing substantial support to the notion that neuroinflammatory markers, including complement activation, predicts BBB disruption and long-term outcome. Individual proteins identified here could potentially serve to refine current biomarker modelling or represent novel treatment targets in severe TBI.


2021 ◽  
Vol 11 (8) ◽  
pp. 1044
Author(s):  
Cristina Daia ◽  
Cristian Scheau ◽  
Aura Spinu ◽  
Ioana Andone ◽  
Cristina Popescu ◽  
...  

Background: We aimed to assess the effects of modulated neuroprotection with intermittent administration in patients with unresponsive wakefulness syndrome (UWS) after severe traumatic brain injury (TBI). Methods: Retrospective analysis of 60 patients divided into two groups, with and without neuroprotective treatment with Actovegin, Cerebrolysin, pyritinol, L-phosphothreonine, L-glutamine, hydroxocobalamin, alpha-lipoic acid, carotene, DL-α-tocopherol, ascorbic acid, thiamine, pyridoxine, cyanocobalamin, Q 10 coenzyme, and L-carnitine alongside standard treatment. Main outcome measures: Glasgow Coma Scale (GCS) after TBI, Extended Glasgow Coma Scale (GOS E), Disability Rankin Scale (DRS), Functional Independence Measurement (FIM), and Montreal Cognitive Assessment (MOCA), all assessed at 1, 3, 6, 12, and 24 months after TBI. Results: Patients receiving neuroprotective treatment recovered more rapidly from UWS than controls (p = 0.007) passing through a state of minimal consciousness and gradually progressing until the final evaluation (p = 0.000), towards a high cognitive level MOCA = 22 ± 6 points, upper moderate disability GOS-E = 6 ± 1, DRS = 6 ± 4, and an assisted gait, FIM =101 ± 25. The improvement in cognitive and physical functioning was strongly correlated with lower UWS duration (−0.8532) and higher GCS score (0.9803). Conclusion: Modulated long-term neuroprotection may be the therapeutic key for patients to overcome UWS after severe TBI.


2002 ◽  
Vol 32 (4) ◽  
pp. 639-647 ◽  
Author(s):  
Kevin W Greve ◽  
Jeff Love ◽  
Elisabeth Sherwin ◽  
Matthew S Stanford ◽  
Charles Mathias ◽  
...  

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