Helsinki Computed Tomography Scoring System Can Independently Predict Long-Term Outcome in Traumatic Brain Injury

Predictors of outcomes 3 to 12 months after traumatic brain injury: a systematic review and meta-analysis

The exact factors predicting outcomes following traumatic brain injury (TBI) remain elusive. In this systematic review and meta-analysis, we examined factors influencing outcomes in adult patients with TBI, from 3 months to 1 year after injury. A search of four electronic databases-PubMed, Scopus, Web of Science, and ScienceDirect-yielded 29 studies for review and 16 for meta-analysis, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. In patients with TBI of any severity, mean differences were observed in age (8.72 years; 95% confidence interval [CI], 4.77-12.66 years), lymphocyte count (-0.15 109/L; 95% CI, -0.18 to -0.11), glucose levels (1.20 mmol/L; 95% CI, 0.73-1.68), and haemoglobin levels (-0.91 g/dL; 95% CI, -1.49 to -0.33) between those with favourable and unfavourable outcomes. The prevalence rates of unfavourable outcomes were as follows: abnormal cisterns, 65.7%; intracranial pressure above 20 mmHg, 52.9%; midline shift of 5 mm or more, 63%; hypotension, 71%; hypoxia, 86.8%; blood transfusion, 70.3%; and mechanical ventilation, 90%. Several predictors were strongly associated with outcome. Specifically, age, lymphocyte count, glucose level, haemoglobin level, severity of TBI, pupillary reaction, and type of injury were identified as potential predictors of long-term outcomes.

Computed tomography findings as early predictors of long-term language impairment in patients with traumatic brain injury

This study aims to assess the relationship between computed tomography (CT) findings, during the acute phase of hospitalization, and long-term language impairment in people with traumatic brain injury (TBI). Another aim was to assess the receptive and expressive abilities of subjects with TBI based on the location of the injury. This is a retrospective observational study including 49 participants with TBI due to war injuries. The Arabic Diagnostic Aphasia Battery (A-DAB-1) was administered to the participants and the Helsinki CT score was computed to quantify brain damage. The results showed that the Helsinki CT score was negatively correlated with the total score of the A-DAB-1 (r = -0.544, p-value < 0.0001). Simple linear regression supported such findings and reflected an inversely proportional relationship between both variables (p-value < 0.0001). When compared with subjects having right hemisphere damage, subjects with left hemisphere and bilateral brain damage performed more poorly on language tasks respectively as follows: A-DAB-1 overall score (92.08-66.08-70.28, p-value = 0.021), Content of descriptive speech (9.57-6.69-7.22, p-value = 0.034), Verbal fluency (6.57-3.54-3.89, p-value = 0.002), Auditory comprehension (9.71-7.54-7.78, p-value = 0.039), Complex auditory commands (9.71-7.65-7.56, p-value = 0.043), Repetition (9.75-7.08-7.61, p-value = 0.036), Naming (9.93-7.15-8.11, p-value = 0.046). Following TBI, CT findings on admission can significantly predict long-term language abilities, with left side lesions inducing poorer outcomes.

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

PURPOSE

Despite advances in modern medicine, traumatic brain injuries (TBIs) are still a major medical problem. Early diagnosis of TBI is crucial for clinical decision-making and prognosis. This study aims to compare the predictive value of Helsinki, Rotterdam, and Stockholm CT scores in predicting the 6-month outcomes in blunt TBI patients.

METHODS

This cohort study was conducted on blunt TBI patients of 15 years or older. All of them were admitted to the surgical emergency department of Shahid Beheshti Hospital in Kashan, Iran from 2020 to 2021 and had abnormal trauma-related findings on brain CT images. The patients' demographic data such as age, gender, history of comorbid conditions, mechanism of trauma, Glasgow coma scale, CT images, length of hospital stay, and surgical procedures were recorded. The Helsinki, Rotterdam, and Stockholm CT scores were simultaneously determined according to the existing guidelines. The included patients' 6-month outcome was determined using the Glasgow outcome scale extended. M Data were analyzed by SPSS software version 16.0. Sensitivity, specificity, negative/positive predictive value and the area under the receiver operating characteristic curve were calculated for each test. The Kappa agreement coefficient and Kuder Richardson-20 were used to compare the scoring systems.

RESULTS

Altogether 171 TBI patients met the inclusion and exclusion criteria, with the mean age of (44.9 ± 20.2) years. Most patients were male (80.7%), had traffic related injuries (83.1%) and mild TBIs (64.3%). Patients with lower Glasgow coma scale had higher Helsinki, Rotterdam, and Stockholm CT scores and lower Glasgow outcome scale extended scores. Among all the scoring systems, the Helsinki and Stockholm scores showed the highest agreement in predicting patients' outcomes (kappa = 0.657, p < 0.001). The Rotterdam scoring system had the highest sensitivity (90.1%) in predicting death of TBI patients, whereas the Helsinki scoring system had the highest sensitivity (89.8%) in predicting the 6-month outcome in TBI patients.

CONCLUSION

The Rotterdam scoring system was superior in predicting death in TBI patients, whereas the Helsinki scoring system was more sensitive in predicting the 6-month outcome.

Impact of Intracranial Hypertension on Outcome of Severe Traumatic Brain Injury Pediatric Patients: A 15-Year Single Center Experience

Background: Intracranial hypertension (IC-HTN) is significantly associated with higher risk for an unfavorable outcome in pediatric trauma. Intracranial pressure (ICP) monitoring is widely becoming a standard of neurocritical care for children. Methods: The present study was designed to evaluate influences of IC-HTN on clinical outcomes of pediatric TBI patients. Demographic, injury severity, radiologic characteristics were used as possible predictors of IC-HTN or of functional outcome. Results: A total of 118 pediatric intensive care unit (PICU) patients with severe TBI (sTBI) were included. Among sTBI cases, patients with GCS < 5 had significantly higher risk for IC-HTN and for mortality. Moreover, there was a statistically significant positive correlation between IC-HTN and severity scoring systems. Kaplan−Meier analysis determined a significant difference for good recovery among patients who had no ICP elevations, compared to those who had at least one episode of IC-HTN (log-rank chi-square = 11.16, p = 0.001). A multivariable predictive logistic regression analysis distinguished the ICP-monitored patients at risk for developing IC-HTN. The model finally revealed that higher ISS and Helsinki CT score increased the odds for developing IC-HTN (p < 0.05). Conclusion: The present study highlights the importance of ICP-guided clinical practices, which may lead to increasing percentages of good recovery for children.

Prognostic Value of Different Computed Tomography Scoring Systems in Patients With Severe Traumatic Brain Injury Undergoing Decompressive Craniectomy

OBJECTIVE

In this study, we investigate the preoperative and postoperative computed tomography (CT) scores in severe traumatic brain injury (TBI) patients undergoing decompressive craniectomy (DC) and compare their predictive accuracy.

METHODS

Univariate and multivariate logistic regression analyses were used to determine the relationship between CT score (preoperative and postoperative) and mortality at 30 days after injury. The discriminatory power of preoperative and postoperative CT score was assessed by the area under the receiver operating characteristic curve (AUC).

RESULTS

Multivariate logistic regression analysis adjusted for the established predictors of TBI outcomes showed that preoperative Rotterdam CT score (odds ratio [OR], 3.60; 95% confidence interval [CI], 1.13-11.50; P = 0.030), postoperative Rotterdam CT score (OR, 4.17; 95% CI, 1.63-10.66; P = 0.003), preoperative Stockholm CT score (OR, 3.41; 95% CI, 1.42-8.18; P = 0.006), postoperative Stockholm CT score (OR, 4.50; 95% CI, 1.60-12.64; P = 0.004), preoperative Helsinki CT score (OR, 1.44; 95% CI, 1.03-2.02; P = 0.031), and postoperative Helsinki CT score (OR, 2.55; 95% CI, 1.32-4.95; P = 0.005) were significantly associated with mortality. The performance of the postoperative Rotterdam CT score was superior to the preoperative Rotterdam CT score (AUC, 0.82-0.97 vs 0.71-0.91). The postoperative Stockholm CT score was superior to the preoperative Stockholm CT score (AUC, 0.76-0.94 vs 0.72-0.92). The postoperative Helsinki CT score was superior to the preoperative Helsinki CT score (AUC, 0.88-0.99 vs 0.65-0.87).

CONCLUSIONS

In conclusion, assessing the CT score before and after DC may be more precise and efficient for predicting early mortality in severe TBI patients who undergo DC.

Rubiano A, G. Kolias A, Silva Paiva W. Evaluation of Computed Tomography Scoring Systems in the Prediction of Short-Term Mortality in Traumatic Brain Injury Patients from a Low- to Middle-Income Country

The present study aims to evaluate the accuracy of the prognostic discrimination and prediction of the short-term mortality of the Marshall computed tomography (CT) classification and Rotterdam and Helsinki CT scores in a cohort of TBI patients from a low- to middle-income country. This is a post hoc analysis of a previously conducted prospective cohort study conducted in a university-associated, tertiary-level hospital that serves a population of >12 million in Brazil. Marshall CT class, Rotterdam and Helsinki scores, and their components were evaluated in the prediction of 14-day and in-hospital mortality using Nagelkerk's pseudo-R² and area under the receiver operating characteristic curve. Multi-variate regression was performed using known outcome predictors (age, Glasgow Coma Scale, pupil response, hypoxia, hypotension, and hemoglobin values) to evaluate the increase in variance explained when adding each of the CT classification systems. Four hundred forty-seven patients were included. Mean age of the patient cohort was 40 (standard deviation, 17.83) years, and 85.5% were male. Marshall CT class was the least accurate model, showing pseudo-R² values equal to 0.122 for 14-day mortality and 0.057 for in-hospital mortality, whereas Rotterdam CT scores were 0.245 and 0.194 and Helsinki CT scores were 0.264 and 0.229. The AUC confirms the best prediction of the Rotterdam and Helsinki CT scores regarding the Marshall CT class, which presented greater discriminative ability. When associated with known outcome predictors, Marshall CT class and Rotterdam and Helsinki CT scores showed an increase in the explained variance of 2%, 13.4%, and 21.6%, respectively. In this study, Rotterdam and Helsinki scores were more accurate models in predicting short-term mortality. The study denotes a contribution to the process of external validation of the scores and may collaborate with the best risk stratification for patients with this important pathology.

Chinese Admission Warning Strategy for Predicting the Hospital Discharge Outcome in Patients with Traumatic Brain Injury

Objective: To develop and validate an admission warning strategy that incorporates the general emergency department indicators for predicting the hospital discharge outcome of patients with traumatic brain injury (TBI) in China. Methods: This admission warning strategy was developed in a primary cohort that consisted of 605 patients with TBI who were admitted within 6 h of injury. The least absolute shrinkage and selection operator and multivariable logistic regression analysis were used to develop the early warning strategy of selected indicators. Two sub-cohorts consisting of 180 and 107 patients with TBI were used for the external validation. Results: Indicators of the strategy included three categories: baseline characteristics, imaging and laboratory indicators. This strategy displayed good calibration and good discrimination. A high C-index was reached in the internal validation. The multicenter external validation cohort still showed good discrimination C-indices. Decision curve analysis (DCA) showed the actual needs of this strategy when the possibility threshold was 0.01 for the primary cohort, and at thresholds of 0.02–0.83 and 0.01–0.88 for the two sub-cohorts, respectively. In addition, this strategy exhibited a significant prognostic capacity compared to the traditional single predictors, and this optimization was also observed in two external validation cohorts. Conclusions: We developed and validated an admission warning strategy that can be quickly deployed in the emergency department. This strategy can be used as an ideal tool for predicting hospital discharge outcomes and providing objective evidence for early informed consent of the hospital discharge outcome to the family members of TBI patients.

External validation of the NeuroImaging Radiological Interpretation System and Helsinki computed tomography score for mortality prediction in patients with traumatic brain injury treated in the intensive care unit: a Finnish intensive care consortium study

BACKGROUND

Admission computed tomography (CT) scoring systems can be used to objectively quantify the severity of traumatic brain injury (TBI) and aid in outcome prediction. We aimed to externally validate the NeuroImaging Radiological Interpretation System (NIRIS) and the Helsinki CT score. In addition, we compared the prognostic performance of the NIRIS and the Helsinki CT score to the Marshall CT classification and to a clinical model.

METHODS

We conducted a retrospective multicenter observational study using the Finnish Intensive Care Consortium database. We included adult TBI patients admitted in four university hospital ICUs during 2003-2013. We analyzed the CT scans using the NIRIS and the Helsinki CT score and compared the results to 6-month mortality as the primary outcome. In addition, we created a clinical model (age, Glasgow Coma Scale score, Simplified Acute Physiology Score II, presence of severe comorbidity) and combined clinical and CT models to see the added predictive impact of radiological data to conventional clinical information. We measured model performance using area under curve (AUC), Nagelkerke's R² statistics, and the integrated discrimination improvement (IDI).

RESULTS

A total of 3031 patients were included in the analysis. The 6-month mortality was 710 patients (23.4%). Of the CT models, the Helsinki CT displayed best discrimination (AUC 0.73 vs. 0.70 for NIRIS) and explanatory variation (Nagelkerke's R² 0.20 vs. 0.15). The clinical model displayed an AUC of 0.86 (95% CI 0.84-0.87). All CT models increased the AUC of the clinical model by + 0.01 to 0.87 (95% CI 0.85-0.88) and the IDI by 0.01-0.03.

CONCLUSION

In patients with TBI treated in the ICU, the Helsinki CT score outperformed the NIRIS for 6-month mortality prediction. In isolation, CT models offered only moderate accuracy for outcome prediction and clinical variables outweighing the CT-based predictors in terms of predictive performance.

Serum Caspase-1 as an Independent Prognostic Factor in Traumatic Brain Injured Patients

BACKGROUND

The objectives of this study were to assess the association between serum caspase 1 levels and known clinical and radiological prognostic factors and determine whether caspase 1was a more powerful predictor of outcome after traumatic brain injury (TBI) than clinical indices alone, to determine the association between the serum levels of caspase 1 and the 6-month outcome, and to evaluate if there is any association between caspase 1 with clinical and radiological variables.

METHODS

This prospective and observational study was conducted in a university hospital and included patients with TBI who required hospital admission. Serum samples were collected at hospital admission and 24 h after TBI. Caspase 1 levels were determined by enzyme-linked immunosorbent assay. Receiver operating characteristic curves were obtained to test the potential of caspase 1 to predict mortality (Glasgow Outcome Scale Extended score of 1) and unfavorable outcome (Glasgow Outcome Scale Extended scores of 1-4). Multivariate logistic regression was used to assess the effect of serum caspase 1 levels, adjusted by known clinical and radiological prognostic indices, on the outcome.

RESULTS

One hundred thirty-two patients and 33 healthy controls were included. We obtained 6-month outcome in 118 patients. On admission, the mean serum levels of caspase 1 were higher in patients with TBI compared with controls (157.9 vs. 108.5 pg/mL; p < 0.05) but not at 24 h after TBI. Serum caspase 1 levels on admission were higher in patients with unfavorable outcomes (189.5 vs. 144.1 pg/mL; p = 0.009). Similarly, serum caspase 1 levels on admission were higher in patients who died vs. patients who survived (213.6 vs. 146.8 pg/mL; p = 0.03). A logistic regression model showed that the serum caspase 1 level on admission was an independent predictor of 6-month unfavorable outcomes (odds ratio 1.05; 95% confidence interval 1-1.11; p = 0.05). Caspase 1 levels were higher in patients with severe TBI compared with those with moderate TBI, those with mild TBI, and healthy controls (p < 0.001). We did not find any correlation between caspase 1 and the radiological variables studied.

CONCLUSIONS

In this cohort of patients with TBI, we show that serum caspase 1 protein levels on admission are an independent prognostic factor after TBI. Serum caspase 1 levels on admission are higher in patients who will present unfavorable outcomes 6 months after TBI. Caspase 1 levels on admission are associated with the injury severity determined by the Glasgow Coma Scale.

Admission Levels of Interleukin 10 and Amyloid β 1-40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury

Background: Blood biomarkers may enhance outcome prediction performance of head computed tomography scores in traumatic brain injury (TBI).

Objective: To investigate whether admission levels of eight different protein biomarkers can improve the outcome prediction performance of the Helsinki computed tomography score (HCTS) without clinical covariates in TBI.

Materials and methods: Eighty-two patients with computed tomography positive TBIs were included in this study. Plasma levels of β-amyloid isoforms 1–40 (Aβ40) and 1–42 (Aβ42), glial fibrillary acidic protein, heart fatty acid-binding protein, interleukin 10 (IL-10), neurofilament light, S100 calcium-binding protein B, and total tau were measured within 24 h from admission. The patients were divided into favorable (Glasgow Outcome Scale—Extended 5–8, n = 49) and unfavorable (Glasgow Outcome Scale—Extended 1–4, n = 33) groups. The outcome was assessed 6–12 months after injury. An optimal predictive panel was investigated with the sensitivity set at 90–100%.

Results: The HCTS alone yielded a sensitivity of 97.0% (95% CI: 90.9–100) and specificity of 22.4% (95% CI: 10.2–32.7) and partial area under the curve of the receiver operating characteristic of 2.5% (95% CI: 1.1–4.7), in discriminating patients with favorable and unfavorable outcomes. The threshold to detect a patient with unfavorable outcome was an HCTS > 1. The three best individually performing biomarkers in outcome prediction were Aβ40, Aβ42, and neurofilament light. The optimal panel included IL-10, Aβ40, and the HCTS reaching a partial area under the curve of the receiver operating characteristic of 3.4% (95% CI: 1.7–6.2) with a sensitivity of 90.9% (95% CI: 81.8–100) and specificity of 59.2% (95% CI: 40.8–69.4).

Conclusion: Admission plasma levels of IL-10 and Aβ40 significantly improve the prognostication ability of the HCTS after TBI.

Prediction of quality of life by Helsinki computed tomography scoring system in patients with traumatic brain injury

PURPOSE

The aim of this study is to assess the association between the Computed Tomography (CT) findings on admission, according to the Helsinki computed tomography CT score, and patient's Quality of Life (QoL) following traumatic brain injury (TBI) in Lebanon.

METHODS

A retrospective study was performed on 49 males suffering from war induced TBI. Participants were stratified into two groups based on the date of injury. Helsinki CT score was calculated for CT scans of participants. Outcomes were assessed using QoL scales including the Project for the Epidemiological Analysis of Critical Care Patients scale (PAEEC).

RESULTS

Correlation analysis showed that QoL, up to 4 years post-TBI, was significantly associated with Helsinki CT classification. Group 1 of subjects living with TBI for 1-2 years revealed a correlation coefficient r = 0.536, p-value = 0.027, whereas, group 2 including subjects who are injured since 3-4 years, had a correlation coefficient r = 0.565, p-value = 0.001.

CONCLUSION

The present study showed that patients with traumatic brain injury experienced significant quality of life deterioration up to 4 years post-TBI. Our findings propose the important role of Helsinki score in predicting the quality of life among patients with TBI.

Determinants affecting the prognosis of decompressive craniectomy for traumatic brain injury

Objective:

This research was designed to investigate the prognostic determinants of patients with traumatic brain injury (TBI) undergoing decompressive craniectomy (DC).

Methods:

The present study was a retrospective single center research including a total of 112 patients undergoing DC for TBI in Liaocheng People’s Hospital between January 2017 and December 2018. The results were measured by Extended Glasgow Outcome Sale (GOSE). The prognostic determinants were identified by univariate and binary logistic regression analysis between the deaths and survivors or favorable and unfavorable outcomes.

Results:

At the six-month follow-up, the mortality was 45.5% including 37 (33.0%) patients died within 30 days. The independent prognostic factors of 30-day mortality were age (p=0.033), D-dimer level at admission (p=0.032) and postoperative hypernatremia (p=0.014). Seventy five patients survived more than 30 days after DC, among which 27 (36.0%) patients had unfavorable prognosis (GOSE 1-4) and 48 (64.0%) patients presented favorable prognosis (GOSE 5-8). After 30 days from DC, the occurrence of post-traumatic hydrocephalus(PTH) (p= 0.008) was associated with unfavorable prognosis.

Conclusions:

Although DC is an effective treatment for TBI patients, the mortality and morbidity risk remain high. A combination of age, D-dimer level at admission and postoperative hypernatremia may be a good prognostic factor for 30-day mortality. Developing an accurate therapy strategy to prevent and control PTH may be beneficial to the 6-month prognosis for TBI patients undergoing DC.

Prognostic performance of computerized tomography scoring systems in civilian penetrating traumatic brain injury: an observational study

Background

The prognosis of penetrating traumatic brain injury (pTBI) is poor yet highly variable. Current computerized tomography (CT) severity scores are commonly not used for pTBI prognostication but may provide important clinical information in these cohorts.

Methods

All consecutive pTBI patients from two large neurotrauma databases (Helsinki 1999–2015, Stockholm 2005–2014) were included. Outcome measures were 6-month mortality and unfavorable outcome (Glasgow Outcome Scale 1–3). Admission head CT scans were assessed according to the following: Marshall CT classification, Rotterdam CT score, Stockholm CT score, and Helsinki CT score. The discrimination (area under the receiver operating curve, AUC) and explanatory variance (pseudo-R²) of the CT scores were assessed individually and in addition to a base model including age, motor response, and pupil responsiveness.

Results

Altogether, 75 patients were included. Overall 6-month mortality and unfavorable outcome were 45% and 61% for all patients, and 31% and 51% for actively treated patients. The CT scores’ AUCs and pseudo-R²s varied between 0.77–0.90 and 0.35–0.60 for mortality prediction and between 0.85–0.89 and 0.50–0.57 for unfavorable outcome prediction. The base model showed excellent performance for mortality (AUC 0.94, pseudo-R² 0.71) and unfavorable outcome (AUC 0.89, pseudo-R² 0.53) prediction. None of the CT scores increased the base model’s AUC (p > 0.05) yet increased its pseudo-R² (0.09–0.15) for unfavorable outcome prediction.

Conclusion

Existing head CT scores demonstrate good-to-excellent performance in 6-month outcome prediction in pTBI patients. However, they do not add independent information to known outcome predictors, indicating that a unique score capturing the intracranial severity in pTBI may be warranted.

Electronic supplementary material

The online version of this article (10.1007/s00701-019-04074-1) contains supplementary material, which is available to authorized users.

Validation of prognostic models in intensive care unit-treated pediatric traumatic brain injury patients

OBJECTIVE

There are few specific prognostic models specifically developed for the pediatric traumatic brain injury (TBI) population. In the present study, the authors tested the predictive performance of existing prognostic tools, originally developed for the adult TBI population, in pediatric TBI patients requiring stays in the ICU.

METHODS

The authors used the Finnish Intensive Care Consortium database to identify pediatric patients (< 18 years of age) treated in 4 academic ICUs in Finland between 2003 and 2013. They tested the predictive performance of 4 classification systems-the International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) TBI model, the Helsinki CT score, the Rotterdam CT score, and the Marshall CT classification-by assessing the area under the receiver operating characteristic curve (AUC) and the explanatory variation (pseudo-R2 statistic). The primary outcome was 6-month functional outcome (favorable outcome defined as a Glasgow Outcome Scale score of 4-5).

RESULTS

Overall, 341 patients (median age 14 years) were included; of these, 291 patients had primary head CT scans available. The IMPACT core-based model showed an AUC of 0.85 (95% CI 0.78-0.91) and a pseudo-R2 value of 0.40. Of the CT scoring systems, the Helsinki CT score displayed the highest performance (AUC 0.84, 95% CI 0.78-0.90; pseudo-R2 0.39) followed by the Rotterdam CT score (AUC 0.80, 95% CI 0.73-0.86; pseudo-R2 0.34).

CONCLUSIONS

Prognostic tools originally developed for the adult TBI population seemed to perform well in pediatric TBI. Of the tested CT scoring systems, the Helsinki CT score yielded the highest predictive value.