Skip to main content
Top
Published in:

09-05-2024 | Central Nervous System Trauma | Original Article

Development and validation of a nomogram for predicting mortality in patients with acute severe traumatic brain injury: A retrospective analysis

Authors: Haosheng Wang, Yehong Liu, Jun Yuan, Yuhai Wang, Ying Yuan, Yuanyuan Liu, Xu Ren, Jinxu Zhou

Published in: Neurological Sciences | Issue 10/2024

Login to get access

Abstract

Background

Recent evidence links the prognosis of traumatic brain injury (TBI) to various factors, including baseline clinical characteristics, TBI specifics, and neuroimaging outcomes. This study focuses on identifying risk factors for short-term survival in severe traumatic brain injury (sTBI) cases and developing a prognostic model.

Methods

Analyzing 430 acute sTBI patients from January 2018 to December 2023 at the 904th Hospital's Neurosurgery Department, this retrospective case–control study separated patients into survival outcomes: 288 deceased and 142 survivors. It evaluated baseline, clinical, hematological, and radiological data to identify risk and protective factors through univariate and Lasso regression. A multivariate model was then formulated to pinpoint independent prognostic factors, assessing their relationships via Spearman's correlation. The model's accuracy was gauged using the Receiver Operating Characteristic (ROC) curve, with additional statistical analyses for quantitative factors and model effectiveness. Internal validation employed ROC, calibration curves, Decision Curve Analysis (DCA), and Clinical Impact Curves (CIC) to assess model discrimination, utility, and accuracy. The International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) and Corticosteroid Randomization After Significant Head injury (CRASH) models were also compared through multivariate regression.

Results

Factors like unilateral and bilateral pupillary non-reactivity at admission, the derived neutrophil to lymphocyte ratio (dNLR), platelet to lymphocyte ratio (PLR), D-dimer to fibrinogen ratio (DFR), infratentorial hematoma, and Helsinki CT score were identified as independent risk factors (OR > 1), whereas serum albumin emerged as a protective factor (OR < 1). The model showed superior predictive performance with an AUC of 0.955 and surpassed both IMPACT and CRASH models in predictive accuracy. Internal validation confirmed the model's high discriminative capability, clinical relevance, and effectiveness.

Conclusions

Short-term survival in sTBI is significantly influenced by factors such as pupillary response, dNLR, PLR, DFR, serum albumin levels, infratentorial hematoma occurrence, and Helsinki CT scores at admission. The developed nomogram accurately predicts sTBI outcomes, offering significant clinical utility.
Literature
2.
go back to reference Maas AIR et al (2017) Traumatic brain injury: integrated approaches to improve prevention, clinical care, and research. Lancet Neurol 16(12):987–1048PubMedCrossRef Maas AIR et al (2017) Traumatic brain injury: integrated approaches to improve prevention, clinical care, and research. Lancet Neurol 16(12):987–1048PubMedCrossRef
3.
go back to reference Dewan MC et al (2018) Estimating the global incidence of traumatic brain injury. J Neurosurg 130(4):1080–1097PubMedCrossRef Dewan MC et al (2018) Estimating the global incidence of traumatic brain injury. J Neurosurg 130(4):1080–1097PubMedCrossRef
5.
go back to reference Sobuwa S et al (2014) Predicting outcome in severe traumatic brain injury using a simple prognostic model. S Afr Med J 104(7):492–494PubMedCrossRef Sobuwa S et al (2014) Predicting outcome in severe traumatic brain injury using a simple prognostic model. S Afr Med J 104(7):492–494PubMedCrossRef
6.
go back to reference Gómez PA et al (2014) Validation of a prognostic score for early mortality in severe head injury cases. J Neurosurg 121(6):1314–1322PubMedCrossRef Gómez PA et al (2014) Validation of a prognostic score for early mortality in severe head injury cases. J Neurosurg 121(6):1314–1322PubMedCrossRef
7.
go back to reference Lingsma HF et al (2010) Early prognosis in traumatic brain injury: from prophecies to predictions. Lancet Neurol 9(5):543–554PubMedCrossRef Lingsma HF et al (2010) Early prognosis in traumatic brain injury: from prophecies to predictions. Lancet Neurol 9(5):543–554PubMedCrossRef
8.
go back to reference Tasaki O et al (2009) Prognostic indicators and outcome prediction model for severe traumatic brain injury. J Trauma 66(2):304–308PubMed Tasaki O et al (2009) Prognostic indicators and outcome prediction model for severe traumatic brain injury. J Trauma 66(2):304–308PubMed
9.
go back to reference Perel P et al (2008) Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients. BMJ 336(7641):425–429PubMedCrossRef Perel P et al (2008) Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients. BMJ 336(7641):425–429PubMedCrossRef
10.
go back to reference Maas AI et al (2007) Prognosis and clinical trial design in traumatic brain injury: the IMPACT study. J Neurotrauma 24(2):232–238PubMedCrossRef Maas AI et al (2007) Prognosis and clinical trial design in traumatic brain injury: the IMPACT study. J Neurotrauma 24(2):232–238PubMedCrossRef
11.
go back to reference Cremer OL et al (2006) Prognosis following severe head injury: Development and validation of a model for prediction of death, disability, and functional recovery. J Trauma 61(6):1484–1491PubMedCrossRef Cremer OL et al (2006) Prognosis following severe head injury: Development and validation of a model for prediction of death, disability, and functional recovery. J Trauma 61(6):1484–1491PubMedCrossRef
12.
go back to reference Edwards P et al (2005) Final results of MRC CRASH, a randomised placebo-controlled trial of intravenous corticosteroid in adults with head injury-outcomes at 6 months. Lancet 365(9475):1957–1959PubMedCrossRef Edwards P et al (2005) Final results of MRC CRASH, a randomised placebo-controlled trial of intravenous corticosteroid in adults with head injury-outcomes at 6 months. Lancet 365(9475):1957–1959PubMedCrossRef
13.
go back to reference Moorthy D et al (2021) Prediction of Outcome Based on Trauma and Injury Severity Score, IMPACT and CRASH Prognostic Models in Moderate-to-Severe Traumatic Brain Injury in the Elderly. Asian J Neurosurg 16(3):500–506PubMedPubMedCentralCrossRef Moorthy D et al (2021) Prediction of Outcome Based on Trauma and Injury Severity Score, IMPACT and CRASH Prognostic Models in Moderate-to-Severe Traumatic Brain Injury in the Elderly. Asian J Neurosurg 16(3):500–506PubMedPubMedCentralCrossRef
14.
go back to reference Chen L et al (2022) Performance of the IMPACT and Helsinki models for predicting 6-month outcomes in a cohort of patients with traumatic brain injury undergoing cranial surgery. Front Neurol 13:1031865PubMedPubMedCentralCrossRef Chen L et al (2022) Performance of the IMPACT and Helsinki models for predicting 6-month outcomes in a cohort of patients with traumatic brain injury undergoing cranial surgery. Front Neurol 13:1031865PubMedPubMedCentralCrossRef
15.
go back to reference Steyerberg EW et al (2008) Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics. PLoS Med 5(8):e165 (discussion e165)PubMedPubMedCentralCrossRef Steyerberg EW et al (2008) Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics. PLoS Med 5(8):e165 (discussion e165)PubMedPubMedCentralCrossRef
16.
go back to reference Lang L et al (2023) An independently validated nomogram for individualised estimation of short-term mortality risk among patients with severe traumatic brain injury: a modelling analysis of the CENTER-TBI China Registry Study. EClinicalMedicine 59:101975PubMedPubMedCentralCrossRef Lang L et al (2023) An independently validated nomogram for individualised estimation of short-term mortality risk among patients with severe traumatic brain injury: a modelling analysis of the CENTER-TBI China Registry Study. EClinicalMedicine 59:101975PubMedPubMedCentralCrossRef
17.
go back to reference Nasrallah F et al (2023) PREdiction and Diagnosis using Imaging and Clinical biomarkers Trial in Traumatic Brain Injury (PREDICT-TBI) study protocol: an observational, prospective, multicentre cohort study for the prediction of outcome in moderate-to-severe TBI. BMJ Open 13(4):e067740PubMedPubMedCentralCrossRef Nasrallah F et al (2023) PREdiction and Diagnosis using Imaging and Clinical biomarkers Trial in Traumatic Brain Injury (PREDICT-TBI) study protocol: an observational, prospective, multicentre cohort study for the prediction of outcome in moderate-to-severe TBI. BMJ Open 13(4):e067740PubMedPubMedCentralCrossRef
18.
19.
go back to reference Marshall LF et al (1991) A new classification of head injury based on computerized tomography. J Neurosurg 75(Supplement):S14–S20CrossRef Marshall LF et al (1991) A new classification of head injury based on computerized tomography. J Neurosurg 75(Supplement):S14–S20CrossRef
20.
go back to reference Maas AI et al (2005) Prediction of outcome in traumatic brain injury with computed tomographic characteristics: a comparison between the computed tomographic classification and combinations of computed tomographic predictors. Neurosurgery 57(6):1173–82 (discussion 1173–82)PubMedCrossRef Maas AI et al (2005) Prediction of outcome in traumatic brain injury with computed tomographic characteristics: a comparison between the computed tomographic classification and combinations of computed tomographic predictors. Neurosurgery 57(6):1173–82 (discussion 1173–82)PubMedCrossRef
21.
go back to reference Raj R et al (2014) Predicting outcome in traumatic brain injury: development of a novel computerized tomography classification system (Helsinki computerized tomography score). Neurosurgery 75(6):632–46 (discussion 646–7)PubMedCrossRef Raj R et al (2014) Predicting outcome in traumatic brain injury: development of a novel computerized tomography classification system (Helsinki computerized tomography score). Neurosurgery 75(6):632–46 (discussion 646–7)PubMedCrossRef
22.
go back to reference Frodsham KM et al (2020) Day-of-injury computed tomography and longitudinal rehabilitation outcomes: a comparison of the marshall and rotterdam computed tomography scoring methods. Am J Phys Med Rehabil 99(9):821–829PubMedPubMedCentralCrossRef Frodsham KM et al (2020) Day-of-injury computed tomography and longitudinal rehabilitation outcomes: a comparison of the marshall and rotterdam computed tomography scoring methods. Am J Phys Med Rehabil 99(9):821–829PubMedPubMedCentralCrossRef
23.
go back to reference Nelson DW et al (2010) Extended analysis of early computed tomography scans of traumatic brain injured patients and relations to outcome. J Neurotrauma 27(1):51–64PubMedCrossRef Nelson DW et al (2010) Extended analysis of early computed tomography scans of traumatic brain injured patients and relations to outcome. J Neurotrauma 27(1):51–64PubMedCrossRef
24.
go back to reference Liao B et al (2023) The prognostic value of systemic immune-inflammation index in patients with aneurysmal subarachnoid hemorrhage: a systematic review. Neurosurg Rev 46(1):219PubMedCrossRef Liao B et al (2023) The prognostic value of systemic immune-inflammation index in patients with aneurysmal subarachnoid hemorrhage: a systematic review. Neurosurg Rev 46(1):219PubMedCrossRef
25.
go back to reference Luo S et al (2022) The clinical value of neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and D-dimer-to-fibrinogen ratio for predicting pneumonia and poor outcomes in patients with acute intracerebral hemorrhage. Front Immunol 13:1037255PubMedPubMedCentralCrossRef Luo S et al (2022) The clinical value of neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and D-dimer-to-fibrinogen ratio for predicting pneumonia and poor outcomes in patients with acute intracerebral hemorrhage. Front Immunol 13:1037255PubMedPubMedCentralCrossRef
26.
go back to reference Nasr IW, Chun Y, Kannan S (2019) Neuroimmune responses in the developing brain following traumatic brain injury. Exp Neurol 320:112957PubMedCrossRef Nasr IW, Chun Y, Kannan S (2019) Neuroimmune responses in the developing brain following traumatic brain injury. Exp Neurol 320:112957PubMedCrossRef
28.
go back to reference Jo S et al (2020) The prognostic value of platelet-to-lymphocyte ratio on in-hospital mortality in admitted adult traffic accident patients. PLoS ONE 15(6):e0233838PubMedPubMedCentralCrossRef Jo S et al (2020) The prognostic value of platelet-to-lymphocyte ratio on in-hospital mortality in admitted adult traffic accident patients. PLoS ONE 15(6):e0233838PubMedPubMedCentralCrossRef
29.
go back to reference Chen L et al (2022) Systemic immune inflammation index and peripheral blood carbon dioxide concentration at admission predict poor prognosis in patients with severe traumatic brain injury. Front Immunol 13:1034916PubMedCrossRef Chen L et al (2022) Systemic immune inflammation index and peripheral blood carbon dioxide concentration at admission predict poor prognosis in patients with severe traumatic brain injury. Front Immunol 13:1034916PubMedCrossRef
30.
go back to reference Ge X et al (2022) Red cell distribution width to platelet count ratio: a promising routinely available indicator of mortality for acute traumatic brain injury. J Neurotrauma 39(1–2):159–171PubMedCrossRef Ge X et al (2022) Red cell distribution width to platelet count ratio: a promising routinely available indicator of mortality for acute traumatic brain injury. J Neurotrauma 39(1–2):159–171PubMedCrossRef
31.
go back to reference Li W, Deng W (2022) Platelet-to-lymphocyte ratio predicts short-term mortality in patients with moderate to severe traumatic brain injury. Sci Rep 12(1):13976PubMedPubMedCentralCrossRef Li W, Deng W (2022) Platelet-to-lymphocyte ratio predicts short-term mortality in patients with moderate to severe traumatic brain injury. Sci Rep 12(1):13976PubMedPubMedCentralCrossRef
32.
go back to reference Mao B et al (2022) The predictive role of systemic inflammation response index in the prognosis of traumatic brain injury: A propensity score matching study. Front Neurol 13:995925PubMedPubMedCentralCrossRef Mao B et al (2022) The predictive role of systemic inflammation response index in the prognosis of traumatic brain injury: A propensity score matching study. Front Neurol 13:995925PubMedPubMedCentralCrossRef
33.
go back to reference Wang R et al (2021) A prognostic model incorporating red cell distribution width to platelet ratio for patients with traumatic brain injury. Ther Clin Risk Manag 17:1239–1248PubMedPubMedCentralCrossRef Wang R et al (2021) A prognostic model incorporating red cell distribution width to platelet ratio for patients with traumatic brain injury. Ther Clin Risk Manag 17:1239–1248PubMedPubMedCentralCrossRef
34.
go back to reference Carney N et al (2017) Guidelines for the management of severe traumatic brain injury. Fourth Edition Neurosurg 80(1):6–15CrossRef Carney N et al (2017) Guidelines for the management of severe traumatic brain injury. Fourth Edition Neurosurg 80(1):6–15CrossRef
35.
go back to reference Steyerberg EW et al (2019) Case-mix, care pathways, and outcomes in patients with traumatic brain injury in CENTER-TBI: a European prospective, multicentre, longitudinal, cohort study. Lancet Neurol 18(10):923–934PubMedCrossRef Steyerberg EW et al (2019) Case-mix, care pathways, and outcomes in patients with traumatic brain injury in CENTER-TBI: a European prospective, multicentre, longitudinal, cohort study. Lancet Neurol 18(10):923–934PubMedCrossRef
36.
go back to reference Leary OP et al (2021) Computer-assisted measurement of traumatic brain hemorrhage volume is more predictive of functional outcome and mortality than standard ABC/2 method: an analysis of computed tomography imaging data from the progesterone for traumatic brain injury experimental clinical treatment phase-III trial. J Neurotrauma 38(5):604–615 Leary OP et al (2021) Computer-assisted measurement of traumatic brain hemorrhage volume is more predictive of functional outcome and mortality than standard ABC/2 method: an analysis of computed tomography imaging data from the progesterone for traumatic brain injury experimental clinical treatment phase-III trial. J Neurotrauma 38(5):604–615
37.
go back to reference Vijian K et al (2020) Initial leucocytosis and other significant indicators of poor outcome in severe traumatic brain injury: an observational study. Chin Neurosurg J 6:5PubMedPubMedCentralCrossRef Vijian K et al (2020) Initial leucocytosis and other significant indicators of poor outcome in severe traumatic brain injury: an observational study. Chin Neurosurg J 6:5PubMedPubMedCentralCrossRef
38.
go back to reference Deepika A et al (2015) Comparison of predictability of Marshall and Rotterdam CT scan scoring system in determining early mortality after traumatic brain injury. Acta Neurochir (Wien) 157(11):2033–2038PubMedCrossRef Deepika A et al (2015) Comparison of predictability of Marshall and Rotterdam CT scan scoring system in determining early mortality after traumatic brain injury. Acta Neurochir (Wien) 157(11):2033–2038PubMedCrossRef
39.
go back to reference Chen JY et al (2023) The establishment and validation of a prediction model for traumatic intracranial injury patients: a reliable nomogram. Front Neurol 14:1165020PubMedPubMedCentralCrossRef Chen JY et al (2023) The establishment and validation of a prediction model for traumatic intracranial injury patients: a reliable nomogram. Front Neurol 14:1165020PubMedPubMedCentralCrossRef
40.
go back to reference Dijkland SA et al (2020) Prognosis in moderate and severe traumatic brain injury: a systematic review of contemporary models and validation studies. J Neurotrauma 37(1):1–13PubMedCrossRef Dijkland SA et al (2020) Prognosis in moderate and severe traumatic brain injury: a systematic review of contemporary models and validation studies. J Neurotrauma 37(1):1–13PubMedCrossRef
41.
go back to reference Thelin EP et al (2017) Evaluation of novel computerized tomography scoring systems in human traumatic brain injury: An observational, multicenter study. PLoS Med 14(8):e1002368PubMedPubMedCentralCrossRef Thelin EP et al (2017) Evaluation of novel computerized tomography scoring systems in human traumatic brain injury: An observational, multicenter study. PLoS Med 14(8):e1002368PubMedPubMedCentralCrossRef
42.
go back to reference Biuki NM et al (2023) Comparison of the predictive value of the Helsinki, Rotterdam, and Stockholm CT scores in predicting 6-month outcomes in patients with blunt traumatic brain injuries. Chin J Traumatol 26(6):357–362PubMedPubMedCentralCrossRef Biuki NM et al (2023) Comparison of the predictive value of the Helsinki, Rotterdam, and Stockholm CT scores in predicting 6-month outcomes in patients with blunt traumatic brain injuries. Chin J Traumatol 26(6):357–362PubMedPubMedCentralCrossRef
43.
go back to reference Neugebauer H et al (2013) Space-occupying cerebellar infarction: complications, treatment, and outcome. Neurosurgical Focus FOC 34(5):E8CrossRef Neugebauer H et al (2013) Space-occupying cerebellar infarction: complications, treatment, and outcome. Neurosurgical Focus FOC 34(5):E8CrossRef
44.
go back to reference Petr O et al (2023) Link between both infratentorial and supratentorial intracranial pressure burdens and final outcome in patients with infratentorial brain injury. J Neurosurg 139(5):1430–1438PubMedCrossRef Petr O et al (2023) Link between both infratentorial and supratentorial intracranial pressure burdens and final outcome in patients with infratentorial brain injury. J Neurosurg 139(5):1430–1438PubMedCrossRef
45.
go back to reference Su TM et al (2023) Head trauma associated with supra- and infratentorial epidural hematoma: diagnostic and surgical considerations. World Neurosurg 176:e273–e280PubMedCrossRef Su TM et al (2023) Head trauma associated with supra- and infratentorial epidural hematoma: diagnostic and surgical considerations. World Neurosurg 176:e273–e280PubMedCrossRef
46.
go back to reference Jang JW et al (2011) Traumatic epidural haematoma of the posterior cranial fossa. Br J Neurosurg 25(1):55–61PubMedCrossRef Jang JW et al (2011) Traumatic epidural haematoma of the posterior cranial fossa. Br J Neurosurg 25(1):55–61PubMedCrossRef
47.
go back to reference Bernard F et al (2008) Serum albumin level as a predictor of outcome in traumatic brain injury: potential for treatment. J Trauma 64(4):872–875PubMed Bernard F et al (2008) Serum albumin level as a predictor of outcome in traumatic brain injury: potential for treatment. J Trauma 64(4):872–875PubMed
48.
go back to reference Luo HC et al (2019) Comparison of admission serum albumin and hemoglobin as predictors of outcome in children with moderate to severe traumatic brain injury: A retrospective study. Medicine (Baltimore) 98(44):e17806PubMedCrossRef Luo HC et al (2019) Comparison of admission serum albumin and hemoglobin as predictors of outcome in children with moderate to severe traumatic brain injury: A retrospective study. Medicine (Baltimore) 98(44):e17806PubMedCrossRef
50.
go back to reference Garwe T et al (2016) Hypoalbuminemia at admission is associated with increased incidence of in-hospital complications in geriatric trauma patients. Am J Surg 212(1):109–115PubMedCrossRef Garwe T et al (2016) Hypoalbuminemia at admission is associated with increased incidence of in-hospital complications in geriatric trauma patients. Am J Surg 212(1):109–115PubMedCrossRef
51.
go back to reference Corrigan F et al (2016) Neurogenic inflammation after traumatic brain injury and its potentiation of classical inflammation. J Neuroinflammation 13(1):264PubMedPubMedCentralCrossRef Corrigan F et al (2016) Neurogenic inflammation after traumatic brain injury and its potentiation of classical inflammation. J Neuroinflammation 13(1):264PubMedPubMedCentralCrossRef
52.
go back to reference Sorby-Adams AJ et al (2017) The role of neurogenic inflammation in blood-brain barrier disruption and development of cerebral oedema following acute central nervous system (CNS) injury. Int J Mol Sci 18(8):1788PubMedPubMedCentralCrossRef Sorby-Adams AJ et al (2017) The role of neurogenic inflammation in blood-brain barrier disruption and development of cerebral oedema following acute central nervous system (CNS) injury. Int J Mol Sci 18(8):1788PubMedPubMedCentralCrossRef
53.
go back to reference Rodoman GV et al (2006) Serum albumin in systemic inflammatory reaction syndrome. Anesteziol Reanimatol 2:62–64 Rodoman GV et al (2006) Serum albumin in systemic inflammatory reaction syndrome. Anesteziol Reanimatol 2:62–64
54.
go back to reference Healey C et al (2003) Improving the Glasgow Coma Scale score: motor score alone is a better predictor. J Trauma 54(4):671–8 (discussion 678–80)PubMedCrossRef Healey C et al (2003) Improving the Glasgow Coma Scale score: motor score alone is a better predictor. J Trauma 54(4):671–8 (discussion 678–80)PubMedCrossRef
55.
go back to reference Ross SE et al (1998) Efficacy of the motor component of the Glasgow Coma Scale in trauma triage. J Trauma 45(1):42–44PubMedCrossRef Ross SE et al (1998) Efficacy of the motor component of the Glasgow Coma Scale in trauma triage. J Trauma 45(1):42–44PubMedCrossRef
56.
go back to reference Hoffmann M et al (2012) Pupil evaluation in addition to Glasgow Coma Scale components in prediction of traumatic brain injury and mortality. Br J Surg 99(Suppl 1):122–130PubMed Hoffmann M et al (2012) Pupil evaluation in addition to Glasgow Coma Scale components in prediction of traumatic brain injury and mortality. Br J Surg 99(Suppl 1):122–130PubMed
57.
go back to reference Sulhan S et al (2020) Neuroinflammation and blood-brain barrier disruption following traumatic brain injury: Pathophysiology and potential therapeutic targets. J Neurosci Res 98(1):19–28PubMedCrossRef Sulhan S et al (2020) Neuroinflammation and blood-brain barrier disruption following traumatic brain injury: Pathophysiology and potential therapeutic targets. J Neurosci Res 98(1):19–28PubMedCrossRef
58.
go back to reference Loane DJ, Faden AI (2010) Neuroprotection for traumatic brain injury: translational challenges and emerging therapeutic strategies. Trends Pharmacol Sci 31(12):596–604PubMedPubMedCentralCrossRef Loane DJ, Faden AI (2010) Neuroprotection for traumatic brain injury: translational challenges and emerging therapeutic strategies. Trends Pharmacol Sci 31(12):596–604PubMedPubMedCentralCrossRef
59.
go back to reference Winkler EA et al (2016) Cerebral edema in traumatic brain injury: pathophysiology and prospective therapeutic targets. Neurosurg Clin N Am 27(4):473–488PubMedCrossRef Winkler EA et al (2016) Cerebral edema in traumatic brain injury: pathophysiology and prospective therapeutic targets. Neurosurg Clin N Am 27(4):473–488PubMedCrossRef
60.
go back to reference Nimmerjahn A, Kirchhoff F, Helmchen F (2005) Resting microglial cells are highly dynamic surveillants of brain parenchyma in vivo. Science 308(5726):1314–1318PubMedCrossRef Nimmerjahn A, Kirchhoff F, Helmchen F (2005) Resting microglial cells are highly dynamic surveillants of brain parenchyma in vivo. Science 308(5726):1314–1318PubMedCrossRef
61.
go back to reference Kumar A, Loane DJ (2012) Neuroinflammation after traumatic brain injury: opportunities for therapeutic intervention. Brain Behav Immun 26(8):1191–1201PubMedCrossRef Kumar A, Loane DJ (2012) Neuroinflammation after traumatic brain injury: opportunities for therapeutic intervention. Brain Behav Immun 26(8):1191–1201PubMedCrossRef
62.
go back to reference Aungst SL et al (2014) Repeated mild traumatic brain injury causes chronic neuroinflammation, changes in hippocampal synaptic plasticity, and associated cognitive deficits. J Cereb Blood Flow Metab 34(7):1223–1232PubMedPubMedCentralCrossRef Aungst SL et al (2014) Repeated mild traumatic brain injury causes chronic neuroinflammation, changes in hippocampal synaptic plasticity, and associated cognitive deficits. J Cereb Blood Flow Metab 34(7):1223–1232PubMedPubMedCentralCrossRef
63.
go back to reference Loane DJ et al (2014) Novel mGluR5 positive allosteric modulator improves functional recovery, attenuates neurodegeneration, and alters microglial polarization after experimental traumatic brain injury. Neurotherapeutics 11(4):857–869PubMedPubMedCentralCrossRef Loane DJ et al (2014) Novel mGluR5 positive allosteric modulator improves functional recovery, attenuates neurodegeneration, and alters microglial polarization after experimental traumatic brain injury. Neurotherapeutics 11(4):857–869PubMedPubMedCentralCrossRef
64.
go back to reference Mezquita L et al (2021) Predicting immunotherapy outcomes under therapy in patients with advanced NSCLC using dNLR and its early dynamics. Eur J Cancer 151:211–220PubMedCrossRef Mezquita L et al (2021) Predicting immunotherapy outcomes under therapy in patients with advanced NSCLC using dNLR and its early dynamics. Eur J Cancer 151:211–220PubMedCrossRef
65.
go back to reference Xiu WJ et al (2022) ALB-dNLR Score Predicts Mortality in Coronary Artery Disease Patients After Percutaneous Coronary Intervention. Front Cardiovasc Med 9:709868PubMedPubMedCentralCrossRef Xiu WJ et al (2022) ALB-dNLR Score Predicts Mortality in Coronary Artery Disease Patients After Percutaneous Coronary Intervention. Front Cardiovasc Med 9:709868PubMedPubMedCentralCrossRef
66.
go back to reference Fan W et al (2023) Prognostic value of a novel dNLR-PNI score in patients with acute coronary syndrome undergoing percutaneous coronary intervention. Perfusion 38(5):973–982PubMedCrossRef Fan W et al (2023) Prognostic value of a novel dNLR-PNI score in patients with acute coronary syndrome undergoing percutaneous coronary intervention. Perfusion 38(5):973–982PubMedCrossRef
68.
go back to reference Nascimento M et al (2020) B-Cell activating factor secreted by neutrophils is a critical player in lung inflammation to cigarette smoke exposure. Front Immunol 11:1622PubMedPubMedCentralCrossRef Nascimento M et al (2020) B-Cell activating factor secreted by neutrophils is a critical player in lung inflammation to cigarette smoke exposure. Front Immunol 11:1622PubMedPubMedCentralCrossRef
69.
go back to reference Abdul-Muneer PM et al (2016) Role of matrix metalloproteinases in the pathogenesis of traumatic brain injury. Mol Neurobiol 53(9):6106–6123PubMedCrossRef Abdul-Muneer PM et al (2016) Role of matrix metalloproteinases in the pathogenesis of traumatic brain injury. Mol Neurobiol 53(9):6106–6123PubMedCrossRef
70.
go back to reference Nagase H, Visse R, Murphy G (2006) Structure and function of matrix metalloproteinases and TIMPs. Cardiovasc Res 69(3):562–573PubMedCrossRef Nagase H, Visse R, Murphy G (2006) Structure and function of matrix metalloproteinases and TIMPs. Cardiovasc Res 69(3):562–573PubMedCrossRef
71.
go back to reference Yong VW (2005) Metalloproteinases: mediators of pathology and regeneration in the CNS. Nat Rev Neurosci 6(12):931–944PubMedCrossRef Yong VW (2005) Metalloproteinases: mediators of pathology and regeneration in the CNS. Nat Rev Neurosci 6(12):931–944PubMedCrossRef
72.
go back to reference Abdul Muneer PM et al (2012) The mechanisms of cerebral vascular dysfunction and neuroinflammation by MMP-mediated degradation of VEGFR-2 in alcohol ingestion. Arterioscler Thromb Vasc Biol 32(5):1167–1177PubMedPubMedCentralCrossRef Abdul Muneer PM et al (2012) The mechanisms of cerebral vascular dysfunction and neuroinflammation by MMP-mediated degradation of VEGFR-2 in alcohol ingestion. Arterioscler Thromb Vasc Biol 32(5):1167–1177PubMedPubMedCentralCrossRef
73.
go back to reference Wang X et al (2002) Secretion of matrix metalloproteinase-2 and -9 after mechanical trauma injury in rat cortical cultures and involvement of MAP kinase. J Neurotrauma 19(5):615–625PubMedCrossRef Wang X et al (2002) Secretion of matrix metalloproteinase-2 and -9 after mechanical trauma injury in rat cortical cultures and involvement of MAP kinase. J Neurotrauma 19(5):615–625PubMedCrossRef
74.
go back to reference Turner RJ, Sharp FR (2016) Implications of MMP9 for blood brain barrier disruption and hemorrhagic transformation following ischemic stroke. Front Cell Neurosci 10:56PubMedPubMedCentralCrossRef Turner RJ, Sharp FR (2016) Implications of MMP9 for blood brain barrier disruption and hemorrhagic transformation following ischemic stroke. Front Cell Neurosci 10:56PubMedPubMedCentralCrossRef
75.
go back to reference Semple JW, Italiano JE Jr, Freedman J (2011) Platelets and the immune continuum. Nat Rev Immunol 11(4):264–274PubMedCrossRef Semple JW, Italiano JE Jr, Freedman J (2011) Platelets and the immune continuum. Nat Rev Immunol 11(4):264–274PubMedCrossRef
77.
78.
go back to reference Ciferri S et al (2000) Platelets release their lysosomal content in vivo in humans upon activation. Thromb Haemost 83(1):157–164PubMedCrossRef Ciferri S et al (2000) Platelets release their lysosomal content in vivo in humans upon activation. Thromb Haemost 83(1):157–164PubMedCrossRef
79.
go back to reference Wang Y et al (2018) Platelet activation and antiplatelet therapy in sepsis: A narrative review. Thromb Res 166:28–36PubMedCrossRef Wang Y et al (2018) Platelet activation and antiplatelet therapy in sepsis: A narrative review. Thromb Res 166:28–36PubMedCrossRef
80.
go back to reference Dewar DC et al (2013) Changes in the epidemiology and prediction of multiple-organ failure after injury. J Trauma Acute Care Surg 74(3):774–779PubMedCrossRef Dewar DC et al (2013) Changes in the epidemiology and prediction of multiple-organ failure after injury. J Trauma Acute Care Surg 74(3):774–779PubMedCrossRef
81.
go back to reference Nydam TL et al (2011) Refractory postinjury thrombocytopenia is associated with multiple organ failure and adverse outcomes. J Trauma 70(2):401–6 (discussion 406–7)PubMed Nydam TL et al (2011) Refractory postinjury thrombocytopenia is associated with multiple organ failure and adverse outcomes. J Trauma 70(2):401–6 (discussion 406–7)PubMed
82.
go back to reference Liu J et al (2019) Systemic immune-inflammation index, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio can predict clinical outcomes in patients with metastatic non-small-cell lung cancer treated with nivolumab. J Clin Lab Anal 33(8):e22964PubMedPubMedCentralCrossRef Liu J et al (2019) Systemic immune-inflammation index, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio can predict clinical outcomes in patients with metastatic non-small-cell lung cancer treated with nivolumab. J Clin Lab Anal 33(8):e22964PubMedPubMedCentralCrossRef
83.
go back to reference Stojkovic Lalosevic M et al (2019) Combined Diagnostic Efficacy of Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), and Mean Platelet Volume (MPV) as Biomarkers of Systemic Inflammation in the Diagnosis of Colorectal Cancer. Dis Markers 2019:6036979PubMedPubMedCentralCrossRef Stojkovic Lalosevic M et al (2019) Combined Diagnostic Efficacy of Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), and Mean Platelet Volume (MPV) as Biomarkers of Systemic Inflammation in the Diagnosis of Colorectal Cancer. Dis Markers 2019:6036979PubMedPubMedCentralCrossRef
84.
go back to reference Chen T, Yang M (2020) Platelet-to-lymphocyte ratio is associated with cardiovascular disease in continuous ambulatory peritoneal dialysis patients. Int Immunopharmacol 78:106063PubMedCrossRef Chen T, Yang M (2020) Platelet-to-lymphocyte ratio is associated with cardiovascular disease in continuous ambulatory peritoneal dialysis patients. Int Immunopharmacol 78:106063PubMedCrossRef
85.
go back to reference Nakae R et al (2019) A retrospective study of the effect of fibrinogen levels during fresh frozen plasma transfusion in patients with traumatic brain injury. Acta Neurochir (Wien) 161(9):1943–1953PubMedCrossRef Nakae R et al (2019) A retrospective study of the effect of fibrinogen levels during fresh frozen plasma transfusion in patients with traumatic brain injury. Acta Neurochir (Wien) 161(9):1943–1953PubMedCrossRef
86.
go back to reference Nakae R et al (2020) Age-related differences in the time course of coagulation and fibrinolytic parameters in patients with traumatic brain injury. Int J Mol Sci 21(16):5613PubMedPubMedCentralCrossRef Nakae R et al (2020) Age-related differences in the time course of coagulation and fibrinolytic parameters in patients with traumatic brain injury. Int J Mol Sci 21(16):5613PubMedPubMedCentralCrossRef
87.
go back to reference Nakae R et al (2021) Time course of coagulation and fibrinolytic parameters in pediatric traumatic brain injury. J Neurosurg Pediatr 28(5):526–532PubMedCrossRef Nakae R et al (2021) Time course of coagulation and fibrinolytic parameters in pediatric traumatic brain injury. J Neurosurg Pediatr 28(5):526–532PubMedCrossRef
88.
go back to reference Nakae R et al (2022) Coagulopathy and traumatic brain injury: overview of new diagnostic and therapeutic strategies. Neurol Med Chir (Tokyo) 62(6):261–269PubMedCrossRef Nakae R et al (2022) Coagulopathy and traumatic brain injury: overview of new diagnostic and therapeutic strategies. Neurol Med Chir (Tokyo) 62(6):261–269PubMedCrossRef
89.
go back to reference Wabl R et al (2018) Long-term and delayed functional recovery in patients with severe cerebrovascular and traumatic brain injury requiring tracheostomy. J Neurosurg 131(1):114–121PubMedCrossRef Wabl R et al (2018) Long-term and delayed functional recovery in patients with severe cerebrovascular and traumatic brain injury requiring tracheostomy. J Neurosurg 131(1):114–121PubMedCrossRef
Metadata
Title
Development and validation of a nomogram for predicting mortality in patients with acute severe traumatic brain injury: A retrospective analysis
Authors
Haosheng Wang
Yehong Liu
Jun Yuan
Yuhai Wang
Ying Yuan
Yuanyuan Liu
Xu Ren
Jinxu Zhou
Publication date
09-05-2024
Publisher
Springer International Publishing
Published in
Neurological Sciences / Issue 10/2024
Print ISSN: 1590-1874
Electronic ISSN: 1590-3478
DOI
https://doi.org/10.1007/s10072-024-07572-y

Keynote series | Spotlight on menopause

Menopause can have a significant impact on the body, with effects ranging beyond the endocrine and reproductive systems. Learn about the systemic effects of menopause, so you can help patients in your clinics through the transition.   

Prof. Martha Hickey
Dr. Claudia Barth
Dr. Samar El Khoudary
Developed by: Springer Medicine
Watch now

Advances in Alzheimer's

Alzheimer's research and care is changing rapidly. Keep up with the latest developments from key international conferences, together with expert insights on how to integrate these advances into practice.

This content is intended for healthcare professionals outside of the UK.

Supported by:
  • Lilly
Developed by: Springer Healthcare IME
Learn more