GFAP point-of-care measurement for prehospital diagnosis of intracranial hemorrhage in acute coma.

BACKGROUND: Prehospital triage and treatment of patients with acute coma is challenging for rescue services, as the underlying pathological conditions are highly heterogenous. Recently, glial fibrillary acidic protein (GFAP) has been identified as a biomarker of intracranial hemorrhage. The aim of this prospective study was to test whether prehospital GFAP measurements on a point-of-care device have the potential to rapidly differentiate intracranial hemorrhage from other causes of acute coma. METHODS: This study was conducted at the RKH Klinikum Ludwigsburg, a tertiary care hospital in the northern vicinity of Stuttgart, Germany. Patients who were admitted to the emergency department with the prehospital diagnosis of acute coma (Glasgow Coma Scale scores between 3 and 8) were enrolled prospectively. Blood samples were collected in the prehospital phase. Plasma GFAP measurements were performed on the i-STAT Alinity® (Abbott) device (duration of analysis 15 min) shortly after hospital admission. RESULTS: 143 patients were enrolled (mean age 65 ± 20 years, 42.7% female). GFAP plasma concentrations were strongly elevated in patients with intracranial hemorrhage (n = 51) compared to all other coma etiologies (3352 pg/mL [IQR 613-10001] vs. 43 pg/mL [IQR 29-91.25], p < 0.001). When using an optimal cut-off value of 101 pg/mL, sensitivity for identifying intracranial hemorrhage was 94.1% (specificity 78.9%, positive predictive value 71.6%, negative predictive value 95.9%). In-hospital mortality risk was associated with prehospital GFAP values. CONCLUSION: Increased GFAP plasma concentrations in patients with acute coma identify intracranial hemorrhage with high diagnostic accuracy. Prehospital GFAP measurements on a point-of-care platform allow rapid stratification according to the underlying cause of coma by rescue services. This could have major impact on triage and management of these critically ill patients.

Cutoff of the reverse shock index multiplied by the Glasgow coma scale for predicting in-hospital mortality in adult patients with trauma: a retrospective cohort study.

BACKGROUND: Early identification of patients at risk of potential death and timely transfer to appropriate healthcare facilities are critical for reducing the number of preventable trauma deaths. This study aimed to establish a cutoff value to predict in-hospital mortality using the reverse shock index multiplied by the Glasgow Coma Scale (rSIG). METHODS: This multicenter retrospective cohort study used data from 23 emergency departments in South Korea between January 2011 and December 2020. The outcome variable was the in-hospital mortality. The relationship between rSIG and in-hospital mortality was plotted using the shape-restricted regression spline method. To set a cutoff for rSIG, we found the point on the curve where mortality started to increase and the point where the slope of the mortality curve changed the most. We also calculated the cutoff value for rSIG using Youden's index. RESULTS: A total of 318,506 adult patients with trauma were included. The shape-restricted regression spline curve showed that in-hospital mortality began to increase when the rSIG value was less than 18.86, and the slope of the graph increased the most at 12.57. The cutoff of 16.5, calculated using Youden's index, was closest to the target under-triage and over-triage rates, as suggested by the American College of Surgeons, when applied to patients with an rSIG of 20 or less. In addition, in patients with traumatic brain injury, when the rSIG value was over 25, in-hospital mortality tended to increase as the rSIG value increased. CONCLUSIONS: We propose an rSIG cutoff value of 16.5 as a predictor of in-hospital mortality in adult patients with trauma. However, in patients with traumatic brain injury, a high rSIG is also associated with in-hospital mortality. Appropriate cutoffs should be established for this group in the future.

Establishment of a model to predict mortality after decompression craniotomy for traumatic brain injury.

BACKGROUND: The mortality rate of patients with traumatic brain injury (TBI) is still high even while undergoing decompressive craniectomy (DC), and the expensive treatment costs bring huge economic burden to the families of patients. OBJECTIVE: The aim of this study was to identify preoperative indicators that influence patient outcomes and to develop a risk model for predicting patient mortality by a retrospective analysis of TBI patients undergoing DC. METHODS: A total of 288 TBI patients treated with DC, admitted to the First Affiliated Hospital of Shantou University Medical School from August 2015 to April 2021, were used for univariate and multivariate logistic regression analysis to determine the risk factors for death after DC in TBI patients. We also built a risk model for the identified risk factors and conducted internal verification and model evaluation. RESULTS: Univariate and multivariate logistic regression analysis identified four risk factors: Glasgow Coma Scale, age, activated partial thrombin time, and mean CT value of the superior sagittal sinus. These risk factors can be obtained before DC. In addition, we also developed a 3-month mortality risk model and conducted a bootstrap 1000 resampling internal validation, with C-indices of 0.852 and 0.845, respectively. CONCLUSIONS: We developed a risk model that has clinical significance for the early identification of patients who will still die after DC. Interestingly, we also identified a new early risk factor for TBI patients after DC, that is, preoperative mean CT value of the superior sagittal sinus (p < .05).

Comparison of nine trauma scoring systems in prediction of inhospital outcomes of pediatric trauma patients: a multicenter study.

Hereby, we aimed to comprehensively compare different scoring systems for pediatric trauma and their ability to predict in-hospital mortality and intensive care unit (ICU) admission. The current registry-based multicenter study encompassed a comprehensive dataset of 6709 pediatric trauma patients aged ≤ 18 years from July 2016 to September 2023. To ascertain the predictive efficacy of the scoring systems, the area under the receiver operating characteristic curve (AUC) was calculated. A total of 720 individuals (10.7%) required admission to the ICU. The mortality rate was 1.1% (n = 72). The most predictive scoring system for in-hospital mortality was the adjusted trauma and injury severity score (aTRISS) (AUC = 0.982), followed by trauma and injury severity score (TRISS) (AUC = 0.980), new trauma and injury severity score (NTRISS) (AUC = 0.972), Glasgow coma scale (GCS) (AUC = 0.9546), revised trauma score (RTS) (AUC = 0.944), pre-hospital index (PHI) (AUC = 0.936), injury severity score (ISS) (AUC = 0.901), new injury severity score (NISS) (AUC = 0.900), and abbreviated injury scale (AIS) (AUC = 0.734). Given the predictive performance of the scoring systems for ICU admission, NTRISS had the highest predictive performance (AUC = 0.837), followed by aTRISS (AUC = 0.836), TRISS (AUC = 0.823), ISS (AUC = 0.807), NISS (AUC = 0.805), GCS (AUC = 0.735), RTS (AUC = 0.698), PHI (AUC = 0.662), and AIS (AUC = 0.651). In the present study, we concluded the superiority of the TRISS and its two derived counterparts, aTRISS and NTRISS, compared to other scoring systems, to efficiently discerning individuals who possess a heightened susceptibility to unfavorable consequences. The significance of these findings underscores the necessity of incorporating these metrics into the realm of clinical practice.

Validation of the Scandinavian guidelines for minor and moderate head trauma in children: protocol for a pragmatic, prospective, observational, multicentre cohort study.

INTRODUCTION: Mild traumatic brain injury is common in children and it can be challenging to accurately identify those in need of urgent medical intervention. The Scandinavian guidelines for management of minor and moderate head trauma in children, the Scandinavian Neurotrauma Committee guideline 2016 (SNC16), were developed to aid in risk stratification and decision-making in Scandinavian emergency departments (EDs). This guideline has been validated externally with encouraging results, but internal validation in the intended healthcare system is warranted prior to broad clinical implementation. OBJECTIVE: We aim to validate the diagnostic accuracy of the SNC16 to predict clinically important intracranial injuries (CIII) in paediatric patients suffering from blunt head trauma, assessed in EDs in Sweden and Norway. METHODS AND ANALYSIS: This is a prospective, pragmatic, observational cohort study. Children (aged 0-17 years) with blunt head trauma, presenting with a Glasgow Coma Scale of 9-15 within 24 hours postinjury at an ED in 1 of the 16 participating hospitals, are eligible for inclusion. Included patients are assessed and managed according to the clinical management routines of each hospital. Data elements for risk stratification are collected in an electronic case report form by the examining doctor. The primary outcome is defined as CIII within 1 week of injury. Secondary outcomes of importance include traumatic CT findings, neurosurgery and 3-month outcome. Diagnostic accuracy of the SNC16 to predict endpoints will be assessed by point estimate and 95% CIs for sensitivity, specificity, likelihood ratio, negative predictive value and positive predictive value. ETHICS AND DISSEMINATION: The study is approved by the ethical board in both Sweden and Norway. Results from this validation will be published in scientific journals, and a tailored development and implementation process will follow if the SNC16 is found safe and effective. TRIAL REGISTRATION NUMBER: NCT05964764.

Refining outcome prediction after traumatic brain injury with machine learning algorithms.

Outcome after traumatic brain injury (TBI) is typically assessed using the Glasgow outcome scale extended (GOSE) with levels from 1 (death) to 8 (upper good recovery). Outcome prediction has classically been dichotomized into either dead/alive or favorable/unfavorable outcome. Binary outcome prediction models limit the possibility of detecting subtle yet significant improvements. We set out to explore different machine learning methods with the purpose of mapping their predictions to the full 8 grade scale GOSE following TBI. The models were set up using the variables: age, GCS-motor score, pupillary reaction, and Marshall CT score. For model setup and internal validation, a total of 866 patients could be included. For external validation, a cohort of 369 patients were included from Leuven, Belgium, and a cohort of 573 patients from the US multi-center ProTECT III study. Our findings indicate that proportional odds logistic regression (POLR), random forest regression, and a neural network model achieved accuracy values of 0.3-0.35 when applied to internal data, compared to the random baseline which is 0.125 for eight categories. The models demonstrated satisfactory performance during external validation in the data from Leuven, however, their performance were not satisfactory when applied to the ProTECT III dataset.

General surgeon performed emergency craniotomies in regional Queensland hospitals: a 20-year state-wide study on patient outcomes.

BACKGROUND: Traumatic brain injuries account for up to 50% of trauma related deaths and if surgical intervention is indicated, consensus suggests a maximum of 4 hours to surgical decompression. The occurrence and outcomes of craniotomies performed by non-neurosurgeons in regional Queensland hospitals have never been reported previously in the literature. METHODS: A retrospective review was performed at all regional Queensland hospitals without an on-site neurosurgical service from January 2001 to December 2022 to identify patients undergoing emergency craniotomy. Data recorded included basic demographics, history of anti-coagulant use, mechanism of injury, type of haemorrhage, Glasgow Coma Score and Glasgow Outcome Scale (GOS) on discharge. Radiological parameters measured included midline shift and maximal coronal depth of haematoma. The primary aim of this study was to assess the clinical and radiological outcomes of patients who underwent a craniotomy performed by general surgeons. RESULTS: Over the past 20 years there have been 23 emergency decompressive procedures (one excluded) performed in regional Queensland. Preoperative imaging demonstrated 9 extradural haematomas and 13 subdural haematomas. Six of 17 transferred cases required reoperation after transfer to a neurosurgical centre. Survival was observed in 9 of 22 cases, with 'good' functional outcome (GOS ≥3) observed in 7 cases. In no cases were rurally performed burr holes effective. DISCUSSION: Qualitatively, a larger craniotomy may be associated with better clinical and radiological outcomes. Although rare occurrences, our results demonstrate that general surgeon performed craniotomies are frequently efficacious in producing radiological and/or clinical improvement and should be considered as a potentially lifesaving procedure.

Utilizing ultra-early continuous physiologic data to develop automated measures of clinical severity in a traumatic brain injury population.

Determination of prognosis in the triage process after traumatic brain injury (TBI) is difficult to achieve. Current severity measures like the Trauma and injury severity score (TRISS) and revised trauma score (RTS) rely on additional information from the Glasgow Coma Scale (GCS) and the Injury Severity Score (ISS) which may be inaccurate or delayed, limiting their usefulness in the rapid triage setting. We hypothesized that machine learning based estimations of GCS and ISS obtained through modeling of continuous vital sign features could be used to rapidly derive an automated RTS and TRISS. We derived variables from electrocardiograms (ECG), photoplethysmography (PPG), and blood pressure using continuous data obtained in the first 15 min of admission to build machine learning models of GCS and ISS (ML-GCS and ML-ISS). We compared the TRISS and RTS using ML-ISS and ML-GCS and its value using the actual ISS and GCS in predicting in-hospital mortality. Models were tested in TBI with systemic injury (head abbreviated injury scale (AIS) ≥ 1), and isolated TBI (head AIS ≥ 1 and other AIS ≤ 1). The area under the receiver operating characteristic curve (AUROC) was used to evaluate model performance. A total of 21,077 cases (2009-2015) were in the training set. 6057 cases from 2016 to 2017 were used for testing, with 472 (7.8%) severe TBI (GCS 3-8), 223 (3.7%) moderate TBI (GCS 9-12), and 5913 (88.5%) mild TBI (GCS 13-15). In the TBI with systemic injury group, ML-TRISS had similar AUROC (0.963) to TRISS (0.965) in predicting mortality. ML-RTS had AUROC (0.823) and RTS had AUROC 0.928. In the isolated TBI group, ML-TRISS had AUROC 0.977, and TRISS had AUROC 0.983. ML-RTS had AUROC 0.790 and RTS had AUROC 0.957. Estimation of ISS and GCS from machine learning based modeling of vital sign features can be utilized to provide accurate assessments of the RTS and TRISS in a population of TBI patients. Automation of these scores could be utilized to enhance triage and resource allocation during the ultra-early phase of resuscitation.

A Retrospective Study to Compare the Glasgow Coma Score, Pediatric Trauma Score, and Injury Severity Score and Outcomes in 118 Pediatric Trauma Patients at a Single Emergency Center in Turkey.

BACKGROUND The main causes of accidental trauma in children include road traffic accidents (RTAs) and falling from height (FFH). Rapid and accurate assessment of severity of injury is required to guide effective management. This retrospective study aimed to compare the Glasgow Coma Score (GCS), Pediatric Trauma Score (PTS), and Injury Severity Score (ISS) and outcomes for 118 pediatric trauma patients at a single Emergency Department (ED) in Turkey. MATERIAL AND METHODS Patients admitted to Ankara City Hospital due to high-energy trauma between November 1, 2019 and April 30, 2020 were analyzed retrospectively. Data for 118 patients with trauma by major mechanisms, aged 0-17, were collected. Demographic characteristics, trauma-related characteristics, outcomes, and GCS, PTS, and ISS values were compared. It was examined whether there was a relationship between trauma severity and prognosis. In this context, trauma severity was defined by these scores. RESULTS Of the 118 admitted patients, 66 (55.9%) were discharged from the ED, 33 (28%) were transferred to the intensive care unit (ICU), and 19 (16.1%) were admitted to non-ICU departments in the hospital. With hospitalization, patients with thoracic trauma (P<0.001; OR 11.1; 95% CI 3.0-40) and patients with abdominal trauma (P=0.003; OR 4.0; 95% CI 1.5-10.8) were discharged significantly less frequently than patients with other types of trauma. Patients with low ISS (P<0.001) and high PTS (P<0.001) were discharged more often. The relationship between diagnosis and hospitalization was significant (P<0.001). CONCLUSIONS RTA and FFH are the leading trauma mechanisms in children. Boys experience more trauma. ISS and PTS provide accurate predictions of severe and poor prognosis in pediatric trauma cases.

Predictive value of the Trauma Rating Index in Age, Glasgow Coma Scale, Respiratory rate and Systolic blood pressure score (TRIAGES) for the short-term mortality of older patients with isolated traumatic brain injury: a retrospective cohort study.

OBJECTIVES: This study aimed to evaluate the effectiveness of the Trauma Rating Index in Age, Glasgow Coma Scale, Respiratory rate and Systolic blood pressure score (TRIAGES) in predicting 24-hour in-hospital mortality among patients aged 65 years and older with isolated traumatic brain injury (TBI). DESIGN: A retrospective, single-centre cohort study. SETTING: This study was conducted at a government-run tertiary comprehensive hospital. PARTICIPANTS: This study included 982 patients aged 65 years or older with isolated TBI, who were admitted to the emergency department between 1 January 2020 and 31 December 2021. INTERVENTIONS: None. PRIMARY OUTCOME: 24-hour in-hospital mortality was the primary outcome. RESULTS: Among the 982 patients, 8.75% died within 24 hours of admission. The non-survivors typically had higher TRIAGES and lower GCS scores. Logistic regression showed significant associations of both TRIAGES and GCS with mortality; the adjusted ORs were 1.98 (95% CI 1.74 to 2.25) for TRIAGES and 0.72 (95% CI 0.68 to 0.77) for GCS. Receiver operating characteristic (ROC) analysis indicated an area under the ROC curve of 0.86 for GCS and 0.88 for TRIAGES, with a significant difference (p=0.012). However, precision-recall curve (PRC) analysis revealed an area under the PRC of 0.38 for GCS and 0.47 for TRIAGES, without a significant difference (p=0.107). CONCLUSIONS: The TRIAGES system is a promising tool for predicting 24-hour in-hospital mortality in older patients with TBI, demonstrating comparable or slightly superior efficacy to the GCS. Further multicentre studies are recommended for validation.

Management of Head Trauma.

Traumatic brain injury (TBI) represents a heterogenous spectrum of disease. It is essential to rapidly assess a patient's neurologic status and implement measures to prevent secondary brain injury. Intracranial hypertension, a common sequela of TBI, is managed in a tiered and systematic fashion, starting with the least invasive and moving toward the most invasive. TBI has long-lasting effects on patients and their families and represents a substantial financial and social influence on society. Research regarding the prognosis and treatment of TBI is essential to limit the influence of this widespread disease.

Effect of low fibrinogen level on in-hospital mortality and 6-month functional outcome of TBI patients, a single center experience.

In patients affected by traumatic brain injury (TBI), hypofibrinogenemia within the initial hours of trauma can be expected due to vascular and inflammatory changes. In this study, we aimed to evaluate the effect of hypofibrinogenemia on the in-hospital mortality and 6-month functional outcomes of TBI patients, admitted to Rajaee Hospital, a referral trauma center in Shiraz, Iran. This study included all TBI patients admitted to our center who had no prior history of coagulopathy or any systemic disease, were alive on arrival, and had not received any blood product before admission. On admission, hospitalization, imaging, and 6-month follow-up information of included patients were extracted from the TBI registry database. The baseline characteristics of patients with fibrinogen levels of less than 150 mg/dL were compared with the cases with higher levels. To assess the effect of low fibrinogen levels on in-hospital mortality, a uni- and multivariate was conducted between those who died in hospital and survivors. Based on the 6-month GOSE score of patients, those with GOSE < 4 (unfavorable outcome) were compared with those with a favorable outcome. A total of 3049 patients (84.3% male, 15.7% female), with a mean age of 39.25 ± 18.87, met the eligibility criteria of this study. 494 patients had fibrinogen levels < 150 mg/dl, who were mostly younger and had lower average GCS scores in comparison to cases with higher fibrinogen levels. By comparison of the patients who died during hospitalization and survivors, it was shown that fibrinogen < 150 mg/dl is among the prognostic factors for in-hospital mortality (OR:1.75, CI: 1.32:2.34, P-value < 0.001), while the comparison between patients with the favorable and unfavorable functional outcome at 6-month follow-up, was not in favor of prognostic effect of low fibrinogen level (OR: 0.80, CI: 0.58: 1.11, P-value: 0.19). Hypofibrinogenemia is associated with in-hospital mortality of TBI patients, along with known factors such as higher age and lower initial GCS score. However, it is not among the prognostic factors of midterm functional outcome.

Identifying Age-Specific Risk Factors for Poor Outcomes After Trauma With Machine Learning.

INTRODUCTION: Risk stratification for poor outcomes is not currently age-specific. Risk stratification of older patients based on observational cohorts primarily composed of young patients may result in suboptimal clinical care and inaccurate quality benchmarking. We assessed two hypotheses. First, we hypothesized that risk factors for poor outcomes after trauma are age-dependent and, second, that the relative importance of various risk factors are also age-dependent. METHODS: A cohort study of severely injured adult trauma patients admitted to the intensive care unit 2014-2018 was performed using trauma registry data. Random forest algorithms predicting poor outcomes (death or complication) were built and validated using three cohorts: (1) patients of all ages, (2) younger patients, and (3) older patients. Older patients were defined as aged 55 y or more to maintain consistency with prior trauma literature. Complications assessed included acute renal failure, acute respiratory distress syndrome, cardiac arrest, unplanned intubation, unplanned intensive care unit admission, and unplanned return to the operating room, as defined by the trauma quality improvement program. Mean decrease in model accuracy (MDA), if each variable was removed and scaled to a Z-score, was calculated. MDA change ≥4 standard deviations between age cohorts was considered significant. RESULTS: Of 5489 patients, 25% were older. Poor outcomes occurred in 12% of younger and 33% of older patients. Head injury was the most important predictor of poor outcome in all cohorts. In the full cohort, age was the most important predictor of poor outcomes after head injury. Within age cohorts, the most important predictors of poor outcomes, after head injury, were surgery requirement in younger patients and arrival Glasgow Coma Scale in older patients. Compared to younger patients, head injury and arrival Glasgow Coma Scale had the greatest increase in importance for older patients, while systolic blood pressure had the greatest decrease in importance. CONCLUSIONS: Supervised machine learning identified differences in risk factors and their relative associations with poor outcomes based on age. Age-specific models may improve hospital benchmarking and identify quality improvement targets for older trauma patients.

Patterns and outcomes of intracranial pressure monitoring in traumatic brain injury: An analysis of the National Inpatient Sample.

INTRODUCTION: Elevated intracranial pressure (ICP) can cause progressive neurological deterioration following traumatic brain injury (TBI). ICP can be monitored to guide subsequent treatment decisions. However, there is conflicting data in the literature regarding the utility of ICP monitoring. We aim to describe patterns and outcomes of ICP monitoring in the United States with the use of a nationwide healthcare database. METHODS: We performed a 5-year analysis of the Nationwide Inpatient Sample database. We identified all adult TBI patients with a Glasgow Coma Scale (GCS) measuring 3-8 using International Classification of Diseases diagnostic codes. Propensity score matching (1:2 ratio) was performed to control for demographics, injury parameters and comorbidities. Outcome measures included inpatient mortality, length of stay (LOS), cost of care, and discharge disposition. RESULTS: After propensity score matching, a cohort of 1664 patients was obtained (monitored, 555; non-monitored, 1109). Index outcomes with respect to monitor and no-monitor are as follows: inpatient mortality (35.1%, 42.4%, P <0.01), median LOS (15 days, 6 days, P<0.001), median total charge (289,797 USD, 154,223 USD, P <0.001), discharge home (7.9%, 19.3%, P <0.001) and discharge to another facility (53.9%, 35.4%, P <0.001). DISCUSSION: ICP monitoring in TBI patients is associated with decreased inpatient mortality and discharge to home, and it is associated with an increased hospital LOS, total charge, and chance of discharge to another facility. CONCLUSION: The risks and benefits of ICP monitoring should be seriously considered when managing adults with severe TBI.

PRECISION-TBI: a study protocol for a vanguard prospective cohort study to enhance understanding and management of moderate to severe traumatic brain injury in Australia.

INTRODUCTION: Traumatic brain injury (TBI) is a heterogeneous condition in terms of pathophysiology and clinical course. Outcomes from moderate to severe TBI (msTBI) remain poor despite concerted research efforts. The heterogeneity of clinical management represents a barrier to progress in this area. PRECISION-TBI is a prospective, observational, cohort study that will establish a clinical research network across major neurotrauma centres in Australia. This network will enable the ongoing collection of injury and clinical management data from patients with msTBI, to quantify variations in processes of care between sites. It will also pilot high-frequency data collection and analysis techniques, novel clinical interventions, and comparative effectiveness methodology. METHODS AND ANALYSIS: PRECISION-TBI will initially enrol 300 patients with msTBI with Glasgow Coma Scale (GCS) <13 requiring intensive care unit (ICU) admission for invasive neuromonitoring from 10 Australian neurotrauma centres. Demographic data and process of care data (eg, prehospital, emergency and surgical intervention variables) will be collected. Clinical data will include prehospital and emergency department vital signs, and ICU physiological variables in the form of high frequency neuromonitoring data. ICU treatment data will also be collected for specific aspects of msTBI care. Six-month extended Glasgow Outcome Scores (GOSE) will be collected as the key outcome. Statistical analysis will focus on measures of between and within-site variation. Reports documenting performance on selected key quality indicators will be provided to participating sites. ETHICS AND DISSEMINATION: Ethics approval has been obtained from The Alfred Human Research Ethics Committee (Alfred Health, Melbourne, Australia). All eligible participants will be included in the study under a waiver of consent (hospital data collection) and opt-out (6 months follow-up). Brochures explaining the rationale of the study will be provided to all participants and/or an appropriate medical treatment decision-maker, who can act on the patient's behalf if they lack capacity. Study findings will be disseminated by peer-review publications. TRIAL REGISTRATION NUMBER: NCT05855252.

Are there characteristic indicators for increased pressure in chronic subdural hematoma?

Chronic subdural hematoma (CSDH) is one of the most common neurosurgical disorders. However, no study has yet documented biomarkers indicating increased CSDH pressure. This study aimed to explore such indicators. A total of 50 patients underwent measurement for CSDH pressure during burr-hole irrigation. The mean hematoma pressure was 16.8 ± 7.6 cmH2O with no significant difference between new-onset and recurrent CSDHs. In 12 patients with a CSDH pressure ≥25 cmH2O, further analyses were carried out. Eight of them had bilateral CSDHs. All six patients with a CSDH pressure ≥28 cmH2O suffered headaches before surgery. Two out of three patients with a CSDH pressure ≥29 cmH2O felt nauseous. In statistical analyses, headache was positively correlated with a high CSDH pressure, whereas age and hematoma thickness were negatively correlated with it. Patients' sex, initial Glasgow coma scale score, motor weakness, midline shift on computed tomography scans, and administration of anticoagulants/antiplatelet agents, showed no significant correlation. When patients with bilateral CSDHs are not older adults and suffering headaches, an increased CSDH pressure should be assumed. For such patients, a prompt hematoma evacuation is indicated.

Diffuse axonal injury on magnetic resonance imaging and its relation to neurological outcomes in pediatric traumatic brain injury.

OBJECTIVE: Diffuse axonal injury (DAI), a frequent consequence of pediatric traumatic brain injury (TBI), presents challenges in predicting long-term recovery. This study investigates the relationship between the severity of DAI and neurological outcomes in children. METHODS: We conducted a retrospective analysis of 51 pediatric TBI patients diagnosed with DAI using Adam's classification. Neurological function was assessed at 2, 3, and 6 weeks, and 12 months post-injury using the Pediatric Glasgow Outcome Scale-Extended (PGOSE). RESULTS: PGOSE scores significantly improved over time across all DAI grades, suggesting substantial recovery potential even in initially severe cases. Despite indicating extensive injury, patients with DAI grades II and III demonstrated significant improvement, achieving a good recovery by 12 months. Although the initial Glasgow Coma Scale (GCS) score did not show a statistically significant association with long-term outcomes in our limited sample, these findings suggest that the severity of DAI alone may not fully predict eventual recovery. CONCLUSIONS: Our study highlights the potential for significant neurological recovery in pediatric patients with DAI, emphasizing the importance of long-term follow-up and individualized rehabilitation programs. Further research with larger cohorts and extended follow-up periods is crucial to refine our understanding of the complex relationships between DAI severity, injury mechanisms, and long-term neurological outcomes in children.

Clinical characteristics and outcomes of traumatic brain injury in patients admitted to surgical ward of Jimma Medical Center, Southwest Ethiopia: a prospective observational follow-up study.

OBJECTIVE: To assess the Clinical Characteristics and Outcomes of Traumatic Brain Injury in Patients Admitted to the Surgical Ward of Jimma Medical Center, Southwest Ethiopia from January to July 2022. DESIGN AND SETTING: A hospital-based prospective observational study was conducted among 175 patients admitted with Traumatic Brain Injury at Jimma Medical Center from January to July 2022. Data were collected by structured questionnaires and a convenient sampling technique was used. For data entry, Epidata V.4.6.0.5 software was used and exported to Stata V.14.0.2 for analysis. The Cox regression model was fitted to evaluate the predictors of mortality and variables with a p value <0.05 at 95% CI were taken as statistically significant predictors. RESULTS: The incidence of in-hospital mortality was 22 (12.6%). The mean length of hospital stay was 6 days. In-hospital complications were recorded in 32.0% of patients. A Glasgow Coma Scale (GCS) score of <8 on admission (adjusted HR (AHR)=6.2, 95% CI 0.75 to 51), hyperthermia (AHR: 1.7, 95% CI 1.02 to 3.05) and lack of prehospital care (AHR: 3.2, 95% CI 2.2 to 8.07) were predictors of mortality in patients with traumatic brain injury. CONCLUSION: In-hospital mortality was recorded in over one-tenth of patients with traumatic brain injury. The GCS score of <8 on admission, hyperthermia and lack of prehospital care positively affected the outcome of patients with traumatic brain injury. Screening of patients for hyperthermia and antipsychotics should be strengthened to reduce death. However, a multicentred study is needed for further evidence. Giving priority to the patients with those predictors will decrease the number of deaths.

Clinical Epidemiology of Extracranial Injuries in Severe Pediatric Traumatic Brain Injury in South America.

BACKGROUND: Severe traumatic brain injury (TBI) is a leading cause of pediatric mortality, with a disproportionate burden on low- and middle-income countries. The impact of concomitant extracranial injury (ECI) on these patients remains unclear. This study is the first to characterize the epidemiology and clinical course of severe pediatric TBI with extracranial injuries in any South American country. METHODS: We conducted a secondary analysis of baseline data collected prior to implementation of a clinical trial on TBI care in Argentina, Paraguay, and Chile from September 2019 to July 2020. Patients ≤18 years with CT evidence of TBI, and a Glasgow coma scale (GCS) score ≤8 were recruited. Patients were initially stratified by highest non-head abbreviated injury scale (AIS): isolated TBI (AIS=0), minor extracranial injury (MEI; AIS=1-2), and serious extracranial injury (SEI; AIS≥3). Patients were subsequently stratified by mechanism of injury. Intergroup differences were compared using ANOVA, two-tailed unpaired t-tests, and chi-square tests. RESULTS: Among the 116 children included, 33 % (n = 38) had an isolated TBI, 34 % (n = 39) had MEI, and 34 % (n = 39) had SEI. Facial (n = 53), thoracic (n = 44), and abdominal (n = 31) injuries were the most common ECIs. At discharge, there were no significant differences in median GCS, GOS, or GOS-extended between groups. Patients with SEI had a longer hospital LOS than those with isolated TBI (median 28.0 (IQR 10.6-40.1) vs 11.9 (IQR 8.7-20.7) days, p = 0.013). The most common mechanisms of injury were road traffic injuries (RTIs) (n = 50, 43 %) and falls (n = 35, 30 %). Patients with RTI-associated TBIs were more likely to be older (median 11.0 (IQR 3.0-14.0) vs 2.0 (IQR 0.8-7.0) years, p<0.001) and more likely to have an ECI (86% vs 54 %, respectively; p = 0.003). ICU and Hospital LOS for RTI patients (median 10.5 (IQR 6.1-21.1) and 24.1 (IQR 11.5-40.4) days) were longer than those of fall patients (median 6.1 (IQR 2.6-8.9) and 13.7 (IQR 7.7-24.5) days). CONCLUSIONS: Extracranial injuries are common in South American patients with severe TBI. Severe ECI is more frequently associated with RTIs and can result in a higher rate of surgical procedures and LOS. Further strategies are needed to characterize the prevention and treatment of severe pediatric TBI in the South American context.

Identification and management of low-risk isolated traumatic brain injury patients initially treated at a rural level IV trauma center.

STUDY OBJECTIVE: Our goal was to determine if low-risk, isolated mild traumatic brain injury (TBI) patients who were initially treated at a rural emergency department may have been safely managed without transfer to the tertiary referral trauma center. METHODS: This was a retrospective observational analysis of isolated mild TBI patients who were transferred from a rural Level IV Trauma Center to a regional Level I Trauma Center between 2018 and 2022. Patients were risk-stratified according to the modified Brain Injury Guidelines (mBIG). Data abstracted from the electronic medical record included patient presentation, management, and outcomes. RESULTS: 250 patients with isolated mild TBI were transferred out to the Level I Trauma Center. Fall was the most common mechanism of injury (69.2%). 28 patients (11.2%) were categorized as low-risk (mBIG1). No mBIG1 patients suffered a progression of neurological injury, had worsening of intracranial hemorrhage on repeat head CT, or required neurosurgical intervention. 12/28 (42.9%) of mBIG1 patients had a hospital length of stay of 2 days or less, typically for observation. Those with longer lengths of stay were due to medical complications, such as sepsis, or difficulty in arranging disposition. CONCLUSION: We propose that patients who meet mBIG1 criteria may be safely observed without transfer to a referral Level I Trauma Center. This would be of considerable benefit to patients, who would not need to leave their community, and would improve resource utilization in the region.