Long-term outcome in traumatic brain injury patients with midline shift: a secondary analysis of the Phase 3 COBRIT clinical trial

Physiological and radiological parameters predicting outcome from penetrating traumatic brain injury treated in the deployed military setting

INTRODUCTION

Penetrating traumatic brain injury (TBI) is the most common cause of death in current military conflicts, and results in significant morbidity in survivors. Identifying those physiological and radiological parameters associated with worse clinical outcomes following penetrating TBI in the austere setting may assist military clinicians to provide optimal care.

METHOD

All emergency neurosurgical procedures performed at a Role 3 Medical Treatment Facility in Afghanistan for penetrating TBI between 01 January 2016 and 18 December 2020 were analysed. The odds of certain clinical outcomes (death and functional dependence post-discharge) occurring following surgery were matched to existing agreed preoperative variables described in current US and UK military guidelines. Additional physiological and radiological variables including those comprising the Rotterdam criteria of TBI used in civilian settings were additionally analysed to determine their potential utility in a military austere setting.

RESULTS

55 casualties with penetrating TBI underwent surgery, all either by decompressive craniectomy (n=42) or craniotomy±elevation of skull fragments (n=13). The odds of dying in hospital attributable to TBI were greater with casualties with increased glucose on arrival (OR=70.014, CI=3.0399 to 1612.528, OR=70.014, p=0.008) or a mean arterial pressure <90 mm Hg (OR=4.721, CI=0.969 to 22.979, p=0.049). Preoperative hyperglycaemia was also associated with increased odds of being functionally dependent on others on discharge (OR=11.165, CI=1.905 to 65.427, p=0.007). Bihemispheric injury had greater odds of being functionally dependent on others at discharge (OR=5.275, CI=1.094 to 25.433, p=0.038).

CONCLUSIONS

We would recommend that consideration of these three additional preoperative clinical parameters (hyperglycaemia, hypotension and bihemispheric injury on CT) when managing penetrating TBI be considered in future updates of guidelines for deployed neurosurgical care.

Changes in neurologic status after traumatic brain injury in the Resuscitation Outcomes Consortium Hypertonic Saline trial

Objectives

Traumatic brain injury (TBI) is an important public health problem resulting in significant death and disability. Emergency medical services (EMS) personnel often provide initial treatment for TBI, but only limited data describe the long-term course and outcomes of this care. We sought to characterize changes in neurologic status among adults with TBI patients enrolled in the Resuscitation Outcomes Consortium Hypertonic Saline (ROC-HS) trial.

Methods

We used data from the TBI cohort of the ROC-HS trial. The trial included adults with TBI, with Glasgow Coma Scale (GCS) ≤8, and excluded those with shock (systolic blood pressure [SBP] ≤70 or SBP 71-90 with a heart rate [HR] ≥108). The primary outcome was Glasgow Outcome Scale-Extended (GOS-E; 1 = dead, 8 = no disability) determined at (a) hospital discharge and (b) 6-month follow-up. We assessed changes in GOS-E between hospital discharge and 6-month follow-up using descriptive statistics and Sankey graphs.

Results

Among 1279 TBI included in the analysis, GOS-E categories at hospital discharge were as follows: favorable (GOS-E 5-8) 220 (17.2%), unfavorable (GOS-E 2-4) 664 (51.9%), dead (GOS-E 1) 321 (25.1%), and missing 74 (5.8%). GOS-E categories at 6-month follow-up were as follows: favorable 459 (35.9%), unfavorable 279 (21.8%), dead 346 (27.1%), and missing 195 (15.2%). Among initial TBI survivors with complete GOS-E, >96% followed one of three neurologic recovery patterns: (1) favorable to favorable (20.0%), (2) unfavorable to favorable (40.3%), and (3) unfavorable to unfavorable (36.0%). Few patients deteriorated from favorable to unfavorable neurologic status, and there were few additional deaths.

Conclusions

Among TBI receiving initial prehospital care in the ROC-HS trial, changes in 6-month neurologic status followed distinct patterns. Among TBI with unfavorable neurologic status at hospital discharge, almost half improved to favorable neurologic status at 6 months. Among those with favorable neurologic status at discharge, very few worsened or died at 6 months. These findings have important implications for TBI clinical care, research, and trial design.

Relationship between the shape of intracranial pressure pulse waveform and computed tomography characteristics in patients after traumatic brain injury

BACKGROUND

Midline shift and mass lesions may occur with traumatic brain injury (TBI) and are associated with higher mortality and morbidity. The shape of intracranial pressure (ICP) pulse waveform reflects the state of cerebrospinal pressure-volume compensation which may be disturbed by brain injury. We aimed to investigate the link between ICP pulse shape and pathological computed tomography (CT) features.

METHODS

ICP recordings and CT scans from 130 TBI patients from the CENTER-TBI high-resolution sub-study were analyzed retrospectively. Midline shift, lesion volume, Marshall and Rotterdam scores were assessed in the first CT scan after admission and compared with indices derived from the first 24 h of ICP recording: mean ICP, pulse amplitude of ICP (AmpICP) and pulse shape index (PSI). A neural network model was applied to automatically group ICP pulses into four classes ranging from 1 (normal) to 4 (pathological), with PSI calculated as the weighted sum of class numbers. The relationship between each metric and CT measures was assessed using Mann-Whitney U test (groups with midline shift > 5 mm or lesions > 25 cm3 present/absent) and the Spearman correlation coefficient. Performance of ICP-derived metrics in identifying patients with pathological CT findings was assessed using the area under the receiver operating characteristic curve (AUC).

RESULTS

PSI was significantly higher in patients with mass lesions (with lesions: 2.4 [1.9-3.1] vs. 1.8 [1.1-2.3] in those without; p << 0.001) and those with midline shift (2.5 [1.9-3.4] vs. 1.8 [1.2-2.4]; p < 0.001), whereas mean ICP and AmpICP were comparable. PSI was significantly correlated with the extent of midline shift, total lesion volume and the Marshall and Rotterdam scores. PSI showed AUCs > 0.7 in classification of patients as presenting pathological CT features compared to AUCs ≤ 0.6 for mean ICP and AmpICP.

CONCLUSIONS

ICP pulse shape reflects the reduction in cerebrospinal compensatory reserve related to space-occupying lesions despite comparable mean ICP and AmpICP levels. Future validation of PSI is necessary to explore its association with volume imbalance in the intracranial space and a potential complementary role to the existing monitoring strategies.

Integrating, Harmonizing, and Curating Studies With High-Frequency and Hourly Physiological Data: Proof of Concept from Seven Traumatic Brain Injury Data Sets

Research in severe traumatic brain injury (TBI) has historically been limited by studies with relatively small sample sizes that result in low power to detect small, yet clinically meaningful outcomes. Data sharing and integration from existing sources hold promise to yield larger more robust sample sizes that improve the potential signal and generalizability of important research questions. However, curation and harmonization of data of different types and of disparate provenance is challenging. We report our approach and experience integrating multiple TBI data sets containing collected physiological data, including both expected and unexpected challenges encountered in the integration process. Our harmonized data set included data on 1536 patients from the Citicoline Brain Injury Treatment Trial (COBRIT), Effect of erythropoietin and transfusion threshold on neurological recovery after traumatic brain injury: a randomized clinical trial (EPO Severe TBI), BEST-TRIP, Progesterone for the Treatment of Traumatic Brain Injury III Clinical Trial (ProTECT III), Transforming Research and Clinical Knowledge in Traumatic brain Injury (TRACK-TBI), Brain Oxygen Optimization in Severe Traumatic Brain Injury Phase-II (BOOST-2), and Ben Taub General Hospital (BTGH) Research Database studies. We conclude with process recommendations for data acquisition for future prospective studies to aid integration of these data with existing studies. These recommendations include using common data elements whenever possible, a standardized recording system for labeling and timing of high-frequency physiological data, and secondary use of studies in systems such as Federal Interagency Traumatic Brain Injury Research Informatics System (FITBIR), to engage investigators who collected the original data.

Analysis of intracranial pressure pulse waveform in traumatic brain injury patients: a CENTER-TBI study

OBJECTIVE

Intracranial pressure (ICP) pulse waveform analysis may provide valuable information about cerebrospinal pressure-volume compensation in patients with traumatic brain injury (TBI). The authors applied spectral methods to analyze ICP waveforms in terms of the pulse amplitude of ICP (AMP), high frequency centroid (HFC), and higher harmonics centroid (HHC) and also used a morphological classification approach to assess changes in the shape of ICP pulse waveforms using the pulse shape index (PSI).

METHODS

The authors included 184 patients from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) High-Resolution Sub-Study in the analysis. HFC was calculated as the average power-weighted frequency within the 4- to 15-Hz frequency range of the ICP power density spectrum. HHC was defined as the center of mass of the ICP pulse waveform harmonics from the 2nd to the 10th. PSI was defined as the weighted sum of artificial intelligence-based ICP pulse class numbers from 1 (normal pulse waveform) to 4 (pathological waveform).

RESULTS

AMP and PSI increased linearly with mean ICP. HFC increased proportionally to ICP until the upper breakpoint (average ICP of 31 mm Hg), whereas HHC slightly increased with ICP and then decreased significantly when ICP exceeded 25 mm Hg. AMP (p < 0.001), HFC (p = 0.003), and PSI (p < 0.001) were significantly greater in patients who died than in patients who survived. Among those patients with low ICP (< 15 mm Hg), AMP, PSI, and HFC were greater in those with poor outcome than in those with good outcome (all p < 0.001).

CONCLUSIONS

Whereas HFC, AMP, and PSI could be used as predictors of mortality, HHC may potentially serve as an early warning sign of intracranial hypertension. Elevated HFC, AMP, and PSI were associated with poor outcome in TBI patients with low ICP.

Traumatic Brain Injury (TBI) Detection: Past, Present, and Future

Traumatic brain injury (TBI) can produce temporary biochemical imbalance due to leaks through cell membranes or disruption of the axoplasmic flow due to the misalignment of intracellular neurofilaments. If untreated, TBI can lead to Alzheimer's, Parkinson's, or total disability. Mild TBI (mTBI) accounts for about about 90 percent of all TBI cases. The detection of TBI as soon as it happens is crucial for successful treatment management. Neuroimaging-based tests provide only a structural and functional mapping of the brain with poor temporal resolution. Such tests may not detect mTBI. On the other hand, the electroencephalogram (EEG) provides good spatial resolution and excellent temporal resolution of the brain activities beside its portability and low cost. The objective of this paper is to provide clinicians and scientists with a one-stop source of information to quickly learn about the different technologies used for TBI detection, their advantages and limitations. Our research led us to conclude that even though EEG-based TBI detection is potentially a powerful technology, it is currently not able to detect the presence of a mTBI with high confidence. The focus of the paper is to review existing approaches and provide the reason for the unsuccessful state of EEG-based detection of mTBI.

Neurological Pupil Index for the Early Prediction of Outcome in Severe Acute Brain Injury Patients

In this study, we examined the early value of automated quantitative pupillary examination, using the Neurological Pupil index (NPi), to predict the long-term outcome of acute brain injured (ABI) patients. We performed a single-centre retrospective study (October 2016−March 2019) in ABI patients who underwent NPi measurement during the first 3 days following brain insult. We examined the performance of NPi—alone or in combination with other baseline demographic (age) and radiologic (CT midline shift) predictors—to prognosticate unfavourable 6-month outcome (Glasgow Outcome Scale 1−3). A total of 145 severely brain-injured subjects (65 traumatic brain injury, TBI; 80 non-TBI) were studied. At each time point tested, NPi <3 was highly predictive of unfavourable outcome, with highest specificity (100% (90−100)) at day 3 (sensitivity 24% (15−35), negative predictive value 36% (34−39)). The addition of NPi, from day 1 following ABI to age and cerebral CT scan, provided the best prognostic performance (AUROC curve 0.85 vs. 0.78 without NPi, p = 0.008; DeLong test) for 6-month neurological outcome prediction. NPi, assessed at the early post-injury phase, has a superior ability to predict unfavourable long-term neurological outcomes in severely brain-injured patients. The added prognostic value of NPi was most significant when complemented with baseline demographic and radiologic information.

Outcome Prediction in Patients with Severe Traumatic Brain Injury Using Deep Learning from Head CT Scans

Background After severe traumatic brain injury (sTBI), physicians use long-term prognostication to guide acute clinical care yet struggle to predict outcomes in comatose patients. Purpose To develop and evaluate a prognostic model combining deep learning of head CT scans and clinical information to predict long-term outcomes after sTBI. Materials and Methods This was a retrospective analysis of two prospectively collected databases. The model-building set included 537 patients (mean age, 40 years ± 17 [SD]; 422 men) from one institution from November 2002 to December 2018. Transfer learning and curriculum learning were applied to a convolutional neural network using admission head CT to predict mortality and unfavorable outcomes (Glasgow Outcomes Scale scores 1-3) at 6 months. This was combined with clinical input for a holistic fusion model. The models were evaluated using an independent internal test set and an external cohort of 220 patients with sTBI (mean age, 39 years ± 17; 166 men) from 18 institutions in the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study from February 2014 to April 2018. The models were compared with the International Mission on Prognosis and Analysis of Clinical Trials in TBI (IMPACT) model and the predictions of three neurosurgeons. Area under the receiver operating characteristic curve (AUC) was used as the main model performance metric. Results The fusion model had higher AUCs than did the IMPACT model in the prediction of mortality (AUC, 0.92 [95% CI: 0.86, 0.97] vs 0.80 [95% CI: 0.71, 0.88]; P < .001) and unfavorable outcomes (AUC, 0.88 [95% CI: 0.82, 0.94] vs 0.82 [95% CI: 0.75, 0.90]; P = .04) on the internal data set. For external TRACK-TBI testing, there was no evidence of a significant difference in the performance of any models compared with the IMPACT model (AUC, 0.83; 95% CI: 0.77, 0.90) in the prediction of mortality. The Imaging model (AUC, 0.73; 95% CI: 0.66-0.81; P = .02) and the fusion model (AUC, 0.68; 95% CI: 0.60, 0.76; P = .02) underperformed as compared with the IMPACT model (AUC, 0.83; 95% CI: 0.77, 0.89) in the prediction of unfavorable outcomes. The fusion model outperformed the predictions of the neurosurgeons. Conclusion A deep learning model of head CT and clinical information can be used to predict 6-month outcomes after severe traumatic brain injury. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Haller in this issue.

A Robust, Fully Automatic Detection Method and Calculation Technique of Midline Shift in Intracranial Hemorrhage and Its Clinical Application

A midline shift (MLS) is an important clinical indicator for intracranial hemorrhage. In this study, we proposed a robust, fully automatic neural network-based model for the detection of MLS and compared it with MLSs drawn by clinicians; we also evaluated the clinical applications of the fully automatic model. We recruited 300 consecutive non-contrast CT scans consisting of 7269 slices in this study. Six different types of hemorrhage were included. The automatic detection of MLS was based on modified Keypoint R-CNN with keypoint detection followed by training on the ResNet-FPN-50 backbone. The results were further compared with manually drawn outcomes and manually defined keypoint calculations. Clinical parameters, including Glasgow coma scale (GCS), Glasgow outcome scale (GOS), and 30-day mortality, were also analyzed. The mean absolute error for the automatic detection of an MLS was 0.936 mm compared with the ground truth. The interclass correlation was 0.9899 between the automatic method and MLS drawn by different clinicians. There was high sensitivity and specificity in the detection of MLS at 2 mm (91.7%, 80%) and 5 mm (87.5%, 96.7%) and MLSs greater than 10 mm (85.7%, 97.7%). MLS showed a significant association with initial poor GCS and GCS on day 7 and was inversely correlated with poor 30-day GOS (p < 0.001). In conclusion, automatic detection and calculation of MLS can provide an accurate, robust method for MLS measurement that is clinically comparable to the manually drawn method.

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.

Hyperattenuations on flat-panel computed tomography after successful recanalization of mechanical thrombectomy for anterior circulation occlusion

Background

To evaluate intraparenchymal hyperattenuation (IPH) on flat-panel computed tomography (FPCT) findings and their clinical usefulness for predicting prognosis after successful mechanical thrombectomy (MT) for acute occlusion of anterior circulation.

Methods

A retrospective review was conducted for 158 consecutive patients undergoing mechanical thrombectomy during the last six years. After excluding those with posterior circulation occlusion or incomplete recanalization and those without FPCT, 82 patients were finally included. Immediate post-procedural IPH on FPCT was categorized into four patterns (none, striatal, cortical, or combined pattern). Follow-up magnetic resonance images or CT scans after 48 hours from MT were analyzed according to FPCT findings. The existence of hemorrhagic transformation, intracerebral hemorrhage, and brain swelling was evaluated. Functional clinical outcomes were accessed with post-procedural 3-month modified Rankin scales (mRS).

Results

Of 82 patients, 34 patients were found to have IPH (16 with a striatal pattern, 8 with a cortical pattern, and 10 with a combined pattern). Hemorrhagic complication (P<0.001), brain swelling (P<0.001), and poor mRS scores (P=0.042) showed significant differences according to IPH patterns. Multivariate logistic regression analysis revealed that the presence of a striatal pattern (OR: 13.26, P<0.001), cortical pattern (OR: 11.61, P=0.009), and combined pattern (OR: 45.34, P<0.001) independently predicted hemorrhagic complications. The location of the occlusion (OR: 4.13, P=0.034), cortical pattern (OR: 5.94, P=0.039), and combined pattern (OR: 39.85, P=0.001) predicted brain swelling. Age (OR: 1.07, P=0.006) and the presence of a combined pattern (OR: 10.58, P=0.046) predicted poor clinical outcomes.

Conclusions

FPCT is a rapid and effective tool for a prompt follow-up just after MT to predict prognosis. Those with striatal patterns showed relatively good clinical outcomes despite significant hemorrhage. Cortical IPH patterns independently predicted a high rate of post-procedural hemorrhage or brain swelling. Combined pattern is a strong predictor for both radiologic and poor clinical outcomes.

Preoperative brain shift is a prognostic factor for survival in certain neurosurgical diseases other than severe head injury: a case series and literature review

Preoperative brain shift after severe brain injury is a prognostic factor for survival. The aim of this study was to determine whether preoperative brain shift in conditions other than severe head injury has significant prognostic value. We analyzed a radiological database of 800 consecutive patients, who underwent neurosurgical treatment. Brain shift was measured at two anatomical landmarks: Monro’s foramina (MF) and the corpus callosum (CC). Four hundred seventy-three patients were included. The disease exerting the highest mean brain shift was acute subdural hematoma (MF 11.6 mm, CC 12.4 mm), followed by intraparenchymal hematoma (MF 10.2 mm, CC 10.3 mm) and malignant ischemia (MF 10.4 mm, CC 10.5 mm). On univariate analysis, brain shift was a significant negative factor for survival in all diseases (p < 0.001). Analyzed individually by group, brain shift at both anatomical landmarks had a statistically significant effect on survival in malignant ischemia and at one anatomical landmark in chronic subdural and intraparenchymal hematomas. Multivariate analysis demonstrated that the only independent factor negatively impacting survival was brain shift at MF (OR = 0.89; 95% CI: 0.84–0.95) and CC (OR = 0.90; 95% CI: 0.85–0.96). Brain shift is a prognostic factor for survival in patients with expansive intracranial lesions in certain neurosurgical diseases. MF and CC are reliable anatomical landmarks and should be quoted routinely in radiological reports as well as in neurosurgical practice.

Radiographic predictors of clinical outcome in traumatic brain injury after decompressive craniectomy

BACKGROUND

Primary decompressive craniectomy (DC) is considered for traumatic brain injury (TBI) patients with clinical deterioration, presenting large amounts of high-density lesions on computed tomography (CT). Postoperative CT findings may be suitable for prognostic evaluation. This study evaluated the radiographic predictors of clinical outcome and survival using pre- and postoperative CT scans of such patients.

METHODS

We enrolled 150 patients with moderate to severe TBI who underwent primary DC. They were divided into two groups based on the 6-month postoperative Glasgow Outcome Scale Extended scores (1-4, unfavorable; 5-8, favorable). Radiographic parameters, including hemorrhage type, location, presence of skull fracture, midline shifting, hemispheric diameter, effacement of cisterns, parenchymal hypodensity, and craniectomy size, were reviewed. Stepwise logistic regression analysis was used to identify the prognostic factors of clinical outcome and 6-month mortality.

RESULTS

Multivariable logistic regression analysis revealed that age (odds ratio [OR] = 1.09; 95% confidence interval [CI] 1.032-1.151; p = 0.002), postoperative low density (OR = 12.58; 95% CI 1.247-126.829; p = 0.032), and postoperative effacement of the ambient cistern (OR = 14.52; 95% CI 2.234-94.351; p = 0.005) and the crural cistern (OR = 4.90; 95% CI 1.359-17.678; p = 0.015) were associated with unfavorable outcomes. Postoperative effacement of the crural cistern was the strongest predictor of 6-month mortality (OR = 8.93; 95% CI 2.747-29.054; p = 0.000).

CONCLUSIONS

Hemispheric hypodensity and effacement of the crural and ambient cisterns on postoperative CT after primary DC seems to associate with poor outcome in patients with TBI.

Identification of predictive MRI and functional biomarkers in a pediatric piglet traumatic brain injury model

Traumatic brain injury (TBI) at a young age can lead to the development of long-term functional impairments. Severity of injury is well demonstrated to have a strong influence on the extent of functional impairments; however, identification of specific magnetic resonance imaging (MRI) biomarkers that are most reflective of injury severity and functional prognosis remain elusive. Therefore, the objective of this study was to utilize advanced statistical approaches to identify clinically relevant MRI biomarkers and predict functional outcomes using MRI metrics in a translational large animal piglet TBI model. TBI was induced via controlled cortical impact and multiparametric MRI was performed at 24 hours and 12 weeks post-TBI using T1-weighted, T2-weighted, T2-weighted fluid attenuated inversion recovery, diffusion-weighted imaging, and diffusion tensor imaging. Changes in spatiotemporal gait parameters were also assessed using an automated gait mat at 24 hours and 12 weeks post-TBI. Principal component analysis was performed to determine the MRI metrics and spatiotemporal gait parameters that explain the largest sources of variation within the datasets. We found that linear combinations of lesion size and midline shift acquired using T2-weighted imaging explained most of the variability of the data at both 24 hours and 12 weeks post-TBI. In addition, linear combinations of velocity, cadence, and stride length were found to explain most of the gait data variability at 24 hours and 12 weeks post-TBI. Linear regression analysis was performed to determine if MRI metrics are predictive of changes in gait. We found that both lesion size and midline shift are significantly correlated with decreases in stride and step length. These results from this study provide an important first step at identifying relevant MRI and functional biomarkers that are predictive of functional outcomes in a clinically relevant piglet TBI model. This study was approved by the University of Georgia Institutional Animal Care and Use Committee (AUP: A2015 11-001) on December 22, 2015.

Factors Associated with Early versus Delayed Expansion of Acute Subdural Hematomas Initially Managed Conservatively

Acute subdural hematomas (ASDHs) are highly morbid and increasingly common. Hematoma expansion is a potentially fatal complication, and few studies have examined whether factors associated with hematoma expansion vary over time. To answer this, we performed a case-control study in a cohort of initially conservatively managed patients with ASDH. Two time periods were considered, early (<72 h from injury) and delayed (>72 h from injury). Cases were defined as patients who developed ASDH expansion in the appropriate period; controls were patients who had stable imaging. Associated factors were determined with logistic regression. We identified 68 cases and 237 controls in the early follow-up cohort. Early ASDH expansion was associated with coagulopathy (adjusted odds ratio [aOR] 2.3, 95 % CI: 1.2-4.5; p = 0.02), thicker ASDHs (aOR 1.1, 95% CI: 1.03-1.2; p = 0.006), additional intracranial lesions (aOR 3, 95% CI: 1.6-6.2; p = 0.002), no/minimal trauma history (aOR 0.4, 95% CI: 0.2-0.9; p = 0.03), and duration between injury and initial scan (aOR 0.9, 95% CI: 0.8-0.97; p = 0.04). In the delayed follow-up cohort, there were 41 cases and 126 controls. Delayed ASDH expansion was associated with older age (aOR 1.3 per 10 years, 95% CI: 1.1-1.6; p = 0.01), systolic blood pressure (SBP) >160 on hospital presentation (aOR 4.5, 95% CI: 1.8-11.3; p = 0.001), midline shift (aOR 1.5 per 1 mm, 95% CI: 1.3-1.9; p < 0.001), and convexity location (aOR 14.1, 95% CI: 2.6-265; p = 0.013). We conclude that early and delayed ASDH expansion are different processes with different associated factors, and that elevated SBP may be a modifiable risk factor of delayed expansion.

Morbidity and mortality in elderly patients undergoing evacuation of acute traumatic subdural hematoma

OBJECTIVE

Acute traumatic subdural hematoma (atSDH) can be a life-threatening neurosurgical emergency that necessitates immediate evacuation. The elderly population can be particularly vulnerable to tearing bridging veins. The aim of this study was to evaluate inpatient morbidity and mortality, as well as predictors of inpatient mortality, in a national trauma database.

METHODS

The authors queried the 2016–2017 National Trauma Data Bank registry for patients aged 65 years and older who had undergone evacuation of atSDH. Patients were categorized into three age groups: 65–74, 75–84, and 85+ years. A multivariable logistic regression model was fitted for inpatient mortality adjusting for age group, sex, race, presenting Glasgow Coma Scale (GCS) category (3–8, 9–12, and 13–15), Injury Severity Score, presence of coagulopathy, presence of additional hemorrhages (epidural hematoma [EDH], intraparenchymal hematoma [IPH], and subarachnoid hemorrhage [SAH]), presence of midline shift > 5 mm, and pupillary reactivity (both, one, or none).

RESULTS

A total of 2508 patients (35% females) were analyzed. Age distribution was as follows: 990 patients at 65–74 years, 1096 at 75–84, and 422 at 85+. Midline shift > 5 mm was present in 72% of cases. With regard to additional hemorrhages, SAH was present in 21%, IPH in 10%, and EDH in 2%. Bilaterally reactive pupils were noted in 90% of patients. A major complication was observed in 14.4% of patients, and the overall mortality rate was 18.3%. In the multivariable analysis, the presenting GCS category was found to be the strongest predictor of postoperative inpatient mortality (3–8 vs 13–15: OR 3.63, 95% CI 2.68–4.92, p < 0.001; 9–12 vs 13–15: OR 2.64, 95% CI 1.79–3.90, p < 0.001; 30% of overall variation), followed by the presence of SAH (OR 2.86, 95% CI 2.21–3.70, p < 0.001; 25% of overall variation) and the presence of midline shift > 5 mm (OR 2.40, 95% CI 1.74–3.32, p < 0.001; 11% of overall variation). Model discrimination was excellent (c-index 0.81). Broken down by age decile group, mortality increased from 8.0% to 15.4% for GCS 13–15 to around 36% for GCS 9–12 to almost as high as 60% for GCS 3–8, particularly in those aged 85 years and older.

CONCLUSIONS

The present results from a national trauma database will, the authors hope, assist surgeons in preoperative discussions with patients and their families with regard to expected postoperative outcomes following surgical evacuation of an atSDH.