scholarly journals Development of a Prognostic Model to Predict Mortality after Traumatic Brain Injury in Intensive Care Setting in a Developing Country

2021 ◽  
Vol 12 (02) ◽  
pp. 368-375
Author(s):  
Mini Jayan ◽  
Dhaval Shukla ◽  
Bhagavatula Indira Devi ◽  
Dhananjaya I. Bhat ◽  
Subhas K. Konar
Keyword(s):  
Traumatic Brain Injury ◽  
Intensive Care ◽  
Brain Injury ◽  
Hospital Mortality ◽  
Prognostic Model ◽  
Third Ventricle ◽  
The Third ◽  
Scan Data ◽  
Gcs Score ◽  
Basal Cisterns

Abstract Objectives We aimed to develop a prognostic model for the prediction of in-hospital mortality in patients with traumatic brain injury (TBI) admitted to the neurosurgery intensive care unit (ICU) of our institute. Materials and Methods The clinical and computed tomography scan data of consecutive patients admitted after a diagnosis TBI in ICU were reviewed. Construction of the model was done by using all the variables of Corticosteroid Randomization after Significant Head Injury and International Mission on Prognosis and Analysis of Clinical Trials in TBI models. The endpoint was in-hospital mortality. Results A total of 243 patients with TBI were admitted to ICU during the study period. The in-hospital mortality was 15.3%. On multivariate analysis, the Glasgow coma scale (GCS) at admission, hypoxia, hypotension, and obliteration of the third ventricle/basal cisterns were significantly associated with mortality. Patients with hypoxia had eight times, with hypotensions 22 times, and with obliteration of the third ventricle/basal cisterns three times more chance of death. The TBI score was developed as a sum of individual points assigned as follows: GCS score 3 to 4 (+2 points), 5 to 12 (+1), hypoxia (+1), hypotension (+1), and obliteration third ventricle/basal cistern (+1). The mortality was 0% for a score of “0” and 85% for a score of “4.” Conclusion The outcome of patients treated in ICU was based on common admission variables. A simple clinical grading score allows risk stratification of patients with TBI admitted in ICU.

scholarly journals Lactate Albumin Ratio is Associated with Mortality in Patients with Moderate to Severe Traumatic Brain Injury

2020 ◽  
Author(s):  
Ruoran Wang ◽  
Min He ◽  
Xiaofeng Ou ◽  
Xiaoqi Xie ◽  
Yan Kang
Keyword(s):  
Risk Factors ◽  
Traumatic Brain Injury ◽  
Logistic Regression ◽  
Brain Injury ◽  
Hospital Mortality ◽  
Prognostic Model ◽  
Multivariate Logistic Regression ◽  
Albumin Ratio ◽  
Severe Tbi ◽  
Auc Value

Abstract Background: Traumatic brain injury (TBI) is a serious public health issue all over the world. This study was designed to evaluate the prognostic value of lactate to albumin ratio (LAR) on moderate to severe traumatic brain injury.Methods: Clinical data of 273 moderate to severe TBI patients hospitalized in West China Hospital between May 2015 and January 2018 were collected. Multivariate logistic regression analyses were used to explore risk factors and construct prognostic model of in-hospital mortality in this cohort. Nomogram was drawn to visualize the prognostic model. Receiver operating characteristic (ROC) curve and calibration curve were respectively drawn to evaluate discriminative ability and stability of this model.Results: Non-survivors had higher LAR than survivors (1.0870 vs 0.5286, p<0.001). Results of multivariate logistic regression analysis showed that GCS (OR=0.818, p=0.008), blood glucose (OR=1.232, p<0.001), LAR (OR=1.883, p=0.012), and red blood cell distribution (RDW)-SD (OR=1.179, p=0.004) were independent risk factors of in-hospital mortality in included patients. These four factors were utilized to construct prognostic model. The area under the ROC curve (AUC) value of single lactate and LAR were 0.733 (95%Cl; 0.673-0.794) and 0.780 (95%Cl; 0.725-0.835), respectively. The AUC value of the prognostic model was 0.868 (95%Cl; 0.826-0.909), which was higher than that of LAR (Z=2.5143, p<0.05).Conclusions: LAR is a readily available prognostic marker of moderate to severe TBI patients. Prognostic model incorporating LAR is beneficial for clinicians to evaluate possible progression and make treatment decisions in these patients.

scholarly journals Medical necessity of routine admission of children with mild traumatic brain injury to the intensive care unit

2017 ◽  
Vol 19 (6) ◽  
pp. 668-674 ◽  
Author(s):  
Jared D. Ament ◽  
Krista N. Greenan ◽  
Patrick Tertulien ◽  
Joseph M. Galante ◽  
Daniel K. Nishijima ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Traumatic Brain Injury ◽  
Intensive Care ◽  
Brain Injury ◽  
Skull Fracture ◽  
Tertiary Care ◽  
Stepwise Logistic Regression ◽  
Mild Tbi ◽  
Misclassification Cost ◽  
Gcs Score

OBJECTIVEApproximately 475,000 children are treated for traumatic brain injury (TBI) in the US each year; most are classified as mild TBI (Glasgow Coma Scale [GCS] Score 13–15). Patients with positive findings on head CT, defined as either intracranial hemorrhage or skull fracture, regardless of severity, are often transferred to tertiary care centers for intensive care unit (ICU) monitoring. This practice creates a significant burden on the health care system. The purpose of this investigation was to derive a clinical decision rule (CDR) to determine which children can safely avoid ICU care.METHODSThe authors retrospectively reviewed patients with mild TBI who were ≤ 16 years old and who presented to a Level 1 trauma center between 2008 and 2013. Data were abstracted from institutional TBI and trauma registries. Independent covariates included age, GCS score, pupillary response, CT characteristics, and Injury Severity Score. A composite outcome measure, ICU-level care, was defined as cardiopulmonary instability, transfusion, intubation, placement of intracranial pressure monitor or other invasive monitoring, and/or need for surgical intervention. Stepwise logistic regression defined significant predictors for model inclusion with p < 0.10. The authors derived the CDR with binary recursive partitioning (using a misclassification cost of 20:1).RESULTSA total of 284 patients with mild TBI were included in the analysis; 40 (14.1%) had ICU-level care. The CDR consisted of 5 final predictor variables: midline shift > 5 mm, intraventricular hemorrhage, nonisolated head injury, postresuscitation GCS score of < 15, and cisterns absent. The CDR correctly identified 37 of 40 patients requiring ICU-level care (sensitivity 92.5%; 95% CI 78.5–98.0) and 154 of 244 patients who did not require an ICU-level intervention (specificity 63.1%; 95% CI 56.7–69.1). This results in a negative predictive value of 98.1% (95% CI 94.1–99.5).CONCLUSIONSThe authors derived a clinical tool that defines a subset of pediatric patients with mild TBI at low risk for ICU-level care. Although prospective evaluation is needed, the potential for improved resource allocation is significant.

scholarly journals Sepsis in Traumatic Brain Injury: Epidemiology and Outcomes

2019 ◽  
Vol 47 (2) ◽  
pp. 197-201
Author(s):  
Dustin Anderson ◽  
Demetrios J. Kutsogiannis ◽  
Wendy I. Sligl
Keyword(s):  
Traumatic Brain Injury ◽  
Intensive Care ◽  
Brain Injury ◽  
Hospital Mortality ◽  
Administrative Databases ◽  
Care Utilization ◽  
Apache Ii Score ◽  
Common Source ◽  
Icu Mortality ◽  
Co Morbidity

ABSTRACT:Background:Traumatic brain injury (TBI) is a leading cause of death and disability. Risk factors for in-hospital mortality include older age, co-morbidity, and TBI severity. Few studies have investigated the role of sepsis in individuals with TBI.Methods:We studied adult patients with TBI admitted to intensive care over a 5-year period. Patient characteristics were identified by linking clinical and administrative databases. Charts of individuals with TBI and sepsis were manually reviewed. Predictors of ICU and hospital mortality were identified using logistic regression modeling.Results:Four hundred eighty-six individuals with TBI were admitted to intensive care. Sixteen (3.3%) developed sepsis. Pneumonia was the most common source (94%). Staphylococcus aureus was the most common pathogen (75%). ICU lengths of stay (LOS) (12.2 days [interquartile range (IQR) 4.4–23.5] versus 3.7 days [IQR 1.7–8.2]; p < 0.001) and hospital LOS (28.0 days [IQR 11.8–41.4] versus 15.3 days [IQR 5.0–30.9]; p = 0.017) were longer in patients with TBI and sepsis. Sepsis was not associated with ICU (adjusted odds ratio [aOR] 0.51; 95%CI 0.12–2.27; p = 0.38) or hospital (aOR 0.78; 95% CI 0.21–2.96; p = 0.78) mortality, though age (aOR 1.02; 95% CI 1.00–1.04; p = 0.014 for hospital mortality), severe TBI (aOR 3.71; 95% CI 1.52–9.08; p = 0.004 for ICU mortality and 4.10; 95% CI 1.95–8.65; p < 0.001 for hospital mortality), and APACHE II score (aOR 1.19; 95% CI 1.11–1.28; p < 0.001 for ICU mortality and 1.22; 95% CI 1.14–1.31; p < 0.001 for hospital mortality) were.Conclusion:Sepsis in patients with TBI was not associated with mortality; however, sepsis was associated with increased health care utilization (ICU and hospital LOS).

scholarly journals Hemotransfusion and mechanical ventilation time are associated with intra-hospital mortality in patients with traumatic brain injury admitted to intensive care unit

2016 ◽  
Vol 74 (8) ◽  
pp. 644-649 ◽  
Author(s):  
Kelson James Almeida ◽  
Ânderson Batista Rodrigues ◽  
Luiz Euripedes Almondes Santana Lemos ◽  
Marconi Cosme Soares de Oliveira Filho ◽  
Brisa Fideles Gandara ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Traumatic Brain Injury ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Brain Injury ◽  
Hospital Mortality ◽  
Hospital Death ◽  
Factors Associated ◽  
Ventilation Time ◽  
Mechanical Ventilation Time

ABSTRACT Objective To identify the factors associated with the intra-hospital mortality in patients with traumatic brain injury (TBI) admitted to intensive care unit (ICU). Methods The sample included patients with TBI admitted to the ICU consecutively in a period of one year. It was defined as variables the epidemiological characteristics, factors associated with trauma and variables arising from clinical management in the ICU. Results The sample included 87 TBI patients with a mean age of 28.93 ± 12.72 years, predominantly male (88.5%). The intra-hospital mortality rate was of 33.33%. The initial univariate analysis showed a significant correlation of intra-hospital death and the following variables: the reported use of alcohol (p = 0.016), hemotransfusion during hospitalization (p = 0.036), and mechanical ventilation time (p = 0.002). Conclusion After multivariate analysis, the factors associated with intra-hospital mortality in TBI patients admitted to the intensive care unit were the administration of hemocomponents and mechanical ventilation time.

scholarly journals Decompressive Craniectomy for Traumatic Brain Injury: In-hospital Mortality-Associated Factors

2020 ◽  
Vol 11 (04) ◽  
pp. 601-608
Author(s):  
Fernando Celi ◽  
Giancarlo Saal-Zapata
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Hospital Mortality ◽  
Decompressive Craniectomy ◽  
Univariate Analysis ◽  
Midline Shift ◽  
Tomographic Images ◽  
Radiological Criteria ◽  
The Mean ◽  
Gcs Score

Abstract Objective Determine predictors of in-hospital mortality in patients with severe traumatic brain injury (TBI) who underwent decompressive craniectomy. Materials and Methods This retrospective study reviewed consecutive patients who underwent a decompressive craniectomy between March 2017 and March 2020 at our institution, and analyzed clinical characteristics, brain tomographic images, surgical details and morbimortality associated with this procedure. Results Thirty-three (30 unilateral and 3 bifrontal) decompressive craniectomies were performed, of which 27 patients were male (81.8%). The mean age was 52.18 years, the mean Glasgow coma scale (GCS) score at admission was 9, and 24 patients had anisocoria (72.7%). Falls were the principal cause of the trauma (51.5%), the mean anterior–posterior diameter (APD) of the bone flap in unilateral cases was 106.81 mm (standard deviation [SD] 20.42) and 16 patients (53.3%) underwent a right-sided hemicraniectomy. The temporal bone enlargement was done in 20 cases (66.7%), the mean time of surgery was 2 hours and 27 minutes, the skull flap was preserved in the subcutaneous layer in 29 cases (87.8%), the mean of blood loss was 636.36 mL,and in-hospital mortality was 12%. Univariate analysis found differences between the APD diameter (120.3 mm vs. 85.3 mm; p = 0.003) and the presence of midline shift > 5 mm (p = 0.033). Conclusion The size of the skull flap and the presence of midline shift > 5 mm were predictors of mortality. In the absence of intercranial pressure (ICP) monitoring, clinical and radiological criteria are mandatory to perform a decompressive craniectomy.

scholarly journals Trends in mortality after intensive care of patients with traumatic brain injury in Finland from 2003 to 2019: a Finnish Intensive Care Consortium study

2021 ◽  
Author(s):  
Teemu Luostarinen ◽  
Juho Vehviläinen ◽  
Matias Lindfors ◽  
Matti Reinikainen ◽  
Stepani Bendel ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Intensive Care ◽  
Brain Injury ◽  
Hospital Mortality ◽  
The Elderly ◽  
Case Mix ◽  
Multivariable Logistic Regression Analysis ◽  
Mechanically Ventilated ◽  
Severe Tbi

Abstract Background Several studies have suggested no change in the outcome of patients with traumatic brain injury (TBI) treated in intensive care units (ICUs). This is mainly due to the shift in TBI epidemiology toward older and sicker patients. In Finland, the share of the population aged 65 years and over has increased the most in Europe during the last decade. We aimed to assess changes in 12-month and hospital mortality of patients with TBI treated in the ICU in Finland. Methods We used a national benchmarking ICU database (Finnish Intensive Care Consortium) to study adult patients who had been treated for TBI in four tertiary ICUs in Finland during 2003–2019. We divided admission years into quartiles and used multivariable logistic regression analysis, adjusted for case-mix, to assess the association between admission year and mortality. Results A total of 4535 patients were included. Between 2003–2007 and 2016–2019, the patient median age increased from 54 to 62 years, the share of patients having significant comorbidity increased from 8 to 11%, and patients being dependent on help in activities of daily living increased from 7 to 15%. Unadjusted hospital and 12-month mortality decreased from 18 and 31% to 10% and 23%, respectively. After adjusting for case-mix, a reduction in odds of 12-month and hospital mortality was seen in patients with severe TBI, intracranial pressure monitored patients, and mechanically ventilated patients. Despite a reduction in hospital mortality, 12-month mortality remained unchanged in patients aged ≥ 70 years. Conclusion A change in the demographics of ICU-treated patients with TBI care is evident. The outcome of younger patients with severe TBI appears to improve, whereas long-term mortality of elderly patients with less severe TBI has not improved. This has ramifications for further efforts to improve TBI care, especially among the elderly.

scholarly journals Intracranial Densitometry-Augmented Machine Learning Enhances the Prognostic Value of Brain CT in Pediatric Patients With Traumatic Brain Injury: A Retrospective Pilot Study

2021 ◽  
Vol 9 ◽  
Author(s):  
Young-Tak Kim ◽  
Hakseung Kim ◽  
Choel-Hui Lee ◽  
Byung C. Yoon ◽  
Jung Bin Kim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Length Of Stay ◽  
Hospital Mortality ◽  
Outcome Measures ◽  
Prognostic Model ◽  
Pediatric Patients ◽  
Prognostic Models ◽  
Brain Ct

Background: The inter- and intrarater variability of conventional computed tomography (CT) classification systems for evaluating the extent of ischemic-edematous insult following traumatic brain injury (TBI) may hinder the robustness of TBI prognostic models.Objective: This study aimed to employ fully automated quantitative densitometric CT parameters and a cutting-edge machine learning algorithm to construct a robust prognostic model for pediatric TBI.Methods: Fifty-eight pediatric patients with TBI who underwent brain CT were retrospectively analyzed. Intracranial densitometric information was derived from the supratentorial region as a distribution representing the proportion of Hounsfield units. Furthermore, a machine learning-based prognostic model based on gradient boosting (i.e., CatBoost) was constructed with leave-one-out cross-validation. At discharge, the outcome was assessed dichotomously with the Glasgow Outcome Scale (favorability: 1–3 vs. 4–5). In-hospital mortality, length of stay (&gt;1 week), and need for surgery were further evaluated as alternative TBI outcome measures.Results: Densitometric parameters indicating reduced brain density due to subtle global ischemic changes were significantly different among the TBI outcome groups, except for need for surgery. The skewed intracranial densitometry of the unfavorable outcome became more distinguishable in the follow-up CT within 48 h. The prognostic model augmented by intracranial densitometric information achieved adequate AUCs for various outcome measures [favorability = 0.83 (95% CI: 0.72–0.94), in-hospital mortality = 0.91 (95% CI: 0.82–1.00), length of stay = 0.83 (95% CI: 0.72–0.94), and need for surgery = 0.71 (95% CI: 0.56–0.86)], and this model showed enhanced performance compared to the conventional CRASH-CT model.Conclusion: Densitometric parameters indicative of global ischemic changes during the acute phase of TBI are predictive of a worse outcome in pediatric patients. The robustness and predictive capacity of conventional TBI prognostic models might be significantly enhanced by incorporating densitometric parameters and machine learning techniques.

scholarly journals Performance of Modified Early Warning Score (MEWS) for Predicting In-Hospital Mortality in Traumatic Brain Injury Patients

2021 ◽  
Vol 10 (9) ◽  
pp. 1915
Author(s):  
Dong-Ki Kim ◽  
Dong-Hun Lee ◽  
Byung-Kook Lee ◽  
Yong-Soo Cho ◽  
Seok-Jin Ryu ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Hospital Mortality ◽  
Early Warning ◽  
Injury Severity ◽  
Characteristic Curve ◽  
Early Warning Score ◽  
Trauma Patients ◽  
Discrimination Ability ◽  
Gcs Score

The present study aimed to analyze and compare the prognostic performances of the Revised Trauma Score (RTS), Injury Severity Score (ISS), Shock Index (SI), and Modified Early Warning Score (MEWS) for in-hospital mortality in patients with traumatic brain injury (TBI). This retrospective observational study included severe trauma patients with TBI who visited the emergency department between January 2018 and December 2020. TBI was considered when the Abbreviated Injury Scale was 3 or higher. The primary outcome was in-hospital mortality. In total, 1108 patients were included, and the in-hospital mortality was 183 patients (16.3% of the cohort). Receiver operating characteristic curve analyses were performed for the ISS, RTS, SI, and MEWS with respect to the prediction of in-hospital mortality. The area under the curves (AUCs) of the ISS, RTS, SI, and MEWS were 0.638 (95% confidence interval (CI), 0.603–0.672), 0.742 (95% CI, 0.709–0.772), 0.524 (95% CI, 0.489–0.560), and 0.799 (95% CI, 0.769–0.827), respectively. The AUC of MEWS was significantly different from the AUCs of ISS, RTS, and SI. In multivariate analysis, age (odds ratio (OR), 1.012; 95% CI, 1.000–1.023), the ISS (OR, 1.040; 95% CI, 1.013–1.069), the Glasgow Coma Scale (GCS) score (OR, 0.793; 95% CI, 0.761–0.826), and body temperature (BT) (OR, 0.465; 95% CI, 0.329–0.655) were independently associated with in-hospital mortality after adjustment for confounders. In the present study, the MEWS showed fair performance for predicting in-hospital mortality in patients with TBI. The GCS score and BT seemed to have a significant role in the discrimination ability of the MEWS. The MEWS may be a useful tool for predicting in-hospital mortality in patients with TBI.

scholarly journals Age- and Severity-Related In-Hospital Mortality Trends and Risks of Severe Traumatic Brain Injury in Japan: A Nationwide 10-Year Retrospective Study

2021 ◽  
Vol 10 (5) ◽  
pp. 1072 ◽  
Author(s):  
Chiaki Toida ◽  
Takashi Muguruma ◽  
Masayasu Gakumazawa ◽  
Mafumi Shinohara ◽  
Takeru Abe ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Hospital Mortality ◽  
Mortality Risk ◽  
Injury Severity ◽  
Mortality Trend ◽  
Mortality Trends ◽  
Age Related ◽  
Severe Tbi ◽  
Gcs Score

Traumatic brain injury (TBI) is the major cause of mortality and morbidity in severely-injured patients worldwide. This retrospective nationwide study aimed to evaluate the age- and severity-related in-hospital mortality trends and mortality risks of patients with severe TBI from 2009 to 2018 to establish effective injury prevention measures. We retrieved information from the Japan Trauma Data Bank dataset between 2009 and 2018. The inclusion criteria for this study were patients with severe TBI defined as those with an Injury Severity Score ≥ 16 and TBI. In total, 31,953 patients with severe TBI (32.6%) were included. There were significant age-related differences in characteristics, mortality trend, and mortality risk in patients with severe TBI. The in-hospital mortality trend of all patients with severe TBI significantly decreased but did not improve for patients aged ≤ 5 years and with a Glasgow Coma Scale (GCS) score between 3 and 8. Severe TBI, age ≥ 65 years, fall from height, GCS score 3–8, and urgent blood transfusion need were associated with a higher mortality risk, and mortality risk did not decrease after 2013. Physicians should consider specific strategies when treating patients with any of these risk factors to reduce severe TBI mortality.

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