Volumetric analysis of day of injury computed tomography is associated with rehabilitation outcomes after traumatic brain injury

Evolution of Severe Closed Head Injury: Assessing Ventricular Volume and Behavioral Measures at 30 and 90 Days Post-Injury

Background: Assessing functional outcomes in Severe Closed Head Injury (SCHI) is complex due to brain parenchymal changes. This study examines the Ventricles to Intracranial Volume Ratio (VBR) as a metric for these changes and its correlation with behavioral scales. Methods: Thirty-one SCHI patients were included. VBR was derived from CT scans at 3, 30, and 90 days post-injury and compared with Levels of Cognitive Functioning (LCF), Disability Rating Scale (DRS), and Early Rehabilitation Barthel Index (ERBI) assessments at 30 and 90 days. Results: Ten patients were excluded post-decompressive craniectomy or ventriculoperitoneal shunt. Findings indicated a VBR decrease at 3 days, suggesting acute phase compression, followed by an increase from 30 to 90 days, indicative of post-acute brain atrophy. VBR correlated positively with the Marshall score in the initial 72 h, positioning it as an early indicator of subsequent brain atrophy. Nevertheless, in contrast to the Marshall score, VBR had stronger associations with DRS and ERBI at 90 days. Conclusions: VBR, alongside behavioral assessments, presents a robust framework for evaluating SCHI progression. It supports early functional outcome correlations informing therapeutic approaches. VBR's reliability underscores its utility in neurorehabilitation for ongoing SCHI assessment and aiding clinical decisions.

The role of cognitive reserve in traumatic brain injury: a systematic review of observational studies

OBJECTIVE

Evaluate the role of cognitive reserve (CR) on cognitive and physical sequelae in traumatic brain injury (TBI).

METHODS

A comprehensive search strategy was conducted in four databases in English and Spanish in the last 12 years (2011-2023). Inclusion criteria: original cross-sectional and longitudinal studies whose main or secondary objective was to evaluate the effect of CR in adult patients with TBI. PRISMA guidelines were used to report the search and selection method and STROBE checklist was used to evaluate the quality of studies.

RESULTS

Eighteen observational studies were included in this review. Multiple sources of variability were observed: number of patients, time of evolution, severity of the TBI, type of CR proxy, cognitive assessment instrument, etc. However, the most commonly used indicators of CR were premorbid IQ and educational attainment. A positive and consistent association between CR and performance on cognitive tests after injury was found.

CONCLUSIONS

CR has a consistent positive effect on cognition and on some other aspects of recovery in traumatic brain injury. In future studies, it will be necessary to promote the use of CR indices based on various indicators and explore the effects of CR on other aspects related to the recovery of brain trauma.

Evaluating the state of non-invasive imaging biomarkers for traumatic brain injury

Non-invasive imaging biomarkers are useful for prognostication in patients with traumatic brain injury (TBI) at high risk for morbidity with invasive procedures. The authors present findings from a scoping review discussing the pertinent biomarkers. Embase, Ovid-MEDLINE, and Scopus were queried for original research on imaging biomarkers for prognostication of TBI in adult patients. Two reviewers independently screened articles, extracted data, and evaluated risk of bias. Data was synthesized and confidence evaluated with the linked evidence according to the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) approach. Our search yielded 3104 unique citations, 44 of which were included in this review. Study populations varied in TBI severity, as defined by Glasgow Coma Scale (GCS), including: mild (n=9), mild and moderate (n=3), moderate and severe (n=7), severe (n=6), and all GCS scores (n=17). Diverse imaging modalities were used for prognostication, predominantly computed tomography (CT) only (n=11), magnetic resonance imaging (MRI) only (n=9), and diffusion tensor imaging (DTI) (N=9). The biomarkers included diffusion coefficient mapping, metabolic characteristics, optic nerve sheath diameter, T1-weighted signal changes, cortical cerebral blood flow, axial versus extra-axial lesions, T2-weighted gradient versus spin echo, translocator protein levels, and trauma imaging of brainstem areas. The majority (93%) of studies identified that the imaging biomarker of interest had a statistically significant prognostic value; however, these are based on a very low to low level of quality of evidence. No study directly compared the effects on specific TBI treatments on the temporal course of imaging biomarkers. The current literature is insufficient to make a strong recommendation about a preferred imaging biomarker for TBI, especially considering GRADE criteria revealing low quality of evidence. Rigorous prospective research of imaging biomarkers of TBI is warranted to improve the understanding of TBI severity.

Prediction performance of the machine learning model in predicting mortality risk in patients with traumatic brain injuries: a systematic review and meta-analysis

PURPOSE

With the in-depth application of machine learning(ML) in clinical practice, it has been used to predict the mortality risk in patients with traumatic brain injuries(TBI). However, there are disputes over its predictive accuracy. Therefore, we implemented this systematic review and meta-analysis, to explore the predictive value of ML for TBI.

METHODOLOGY

We systematically retrieved literature published in PubMed, Embase.com, Cochrane, and Web of Science as of November 27, 2022. The prediction model risk of bias(ROB) assessment tool (PROBAST) was used to assess the ROB of models and the applicability of reviewed questions. The random-effects model was adopted for the meta-analysis of the C-index and accuracy of ML models, and a bivariate mixed-effects model for the meta-analysis of the sensitivity and specificity.

RESULT

A total of 47 papers were eligible, including 156 model, with 122 newly developed ML models and 34 clinically recommended mature tools. There were 98 ML models predicting the in-hospital mortality in patients with TBI; the pooled C-index, sensitivity, and specificity were 0.86 (95% CI: 0.84, 0.87), 0.79 (95% CI: 0.75, 0.82), and 0.89 (95% CI: 0.86, 0.92), respectively. There were 24 ML models predicting the out-of-hospital mortality; the pooled C-index, sensitivity, and specificity were 0.83 (95% CI: 0.81, 0.85), 0.74 (95% CI: 0.67, 0.81), and 0.75 (95% CI: 0.66, 0.82), respectively. According to multivariate analysis, GCS score, age, CT classification, pupil size/light reflex, glucose, and systolic blood pressure (SBP) exerted the greatest impact on the model performance.

CONCLUSION

According to the systematic review and meta-analysis, ML models are relatively accurate in predicting the mortality of TBI. A single model often outperforms traditional scoring tools, but the pooled accuracy of models is close to that of traditional scoring tools. The key factors related to model performance include the accepted clinical variables of TBI and the use of CT imaging.

Third Ventricle Volume Predicts Functional Outcome in Chronic Subdural Hematoma

OBJECTIVES

There is a lack of evidence demonstrating the utility of computed tomography (CT) to predict chronic subdural hematoma (CSDH) clinical outcomes. We aim to analyze the role of tomographic volumetric analysis in patients with CSDH.

METHODS

We performed a retrospective study of patients undergoing burr-hole craniostomy (BHC) for CSDH over five years at a tertiary care center. Degree of midline shift, radiographic density, subdural hematoma volume, acute blood volume, and third ventricle (3VV) and fourth ventricle (4VV) volume were estimated using semiautomatic segmentation of preoperative CT. Postoperative functional outcome was measured by two endpoints: National Institute of Health Stroke Scale (NIHSS) at discharge and short-term modified Rankin Scale (mRS) at 6-week follow-up. Univariate and multivariate analyses were performed using nonparametric tests. Discriminative capacity and optimal thresholds of independent variables were calculated by means of receiving-operative curves (ROC).

RESULTS

A total of 79 patients were included for analysis with a median age of 78.5 years. Greater preoperative 3VV independently correlated with poor discharge NIHSS (p = .01) and short-term mRS (p = .03). A cutoff value of 0.545 mL demonstrated the highest sensitivity (77.1%) and specificity (88.8%) with an odds ratio for an mRS functional dependence of 9.29 (p = .001).

CONCLUSIONS

Greater preoperative tomographic 3VV independently prognosticates poor discharge NIHSS and 6-week mRS. A threshold 3VV of 0.545 mL can be used to identify patients at higher risk of being dependent at first protocolized follow-up.

Improved neuropathological identification of traumatic brain injury through quantitative neuroimaging and neural network analyses: Some practical approaches for the neurorehabilitation clinician

BACKGROUND

Quantitative neuroimaging analyses have the potential to provide additional information about the neuropathology of traumatic brain injury (TBI) that more thoroughly informs the neurorehabilitation clinician.

OBJECTIVE

Quantitative neuroimaging is typically not covered in the standard radiological report, but often can be extracted via post-processing of clinical neuroimaging studies, provided that the proper volume acquisition sequences were originally obtained.

METHODS

Research and commercially available quantitative neuroimaging methods provide region of interest (ROI) quantification metrics, lesion burden volumetrics and cortical thickness measures, degree of focal encephalomalacia, white matter (WM) abnormalities and residual hemorrhagic pathology. If present, diffusion tensor imaging (DTI) provides a variety of techniques that aid in evaluating WM integrity. Using quantitatively identified structural and ROI neuropathological changes are most informative when done from a neural network approach.

RESULTS

Viewing quantitatively identifiable damage from a neural network perspective provides the neurorehabilitation clinician with an additional tool for linking brain pathology to understand symptoms, problems and deficits as well as aid neuropsychological test interpretation. All of these analyses can be displayed in graphic form, including3-D image analysis. A case study approach is used to demonstrate the utility of quantitative neuroimaging and network analyses in TBI.

CONCLUSIONS

Quantitative neuroimaging may provide additional useful information for the neurorehabilitation clinician.

Acute Imaging Findings Predict Recovery of Cognitive and Motor Function after Inpatient Rehabilitation for Pediatric Traumatic Brain Injury: A Pediatric Brain Injury Consortium Study

Traumatic brain injury (TBI) is a major cause of morbidity and mortality in children; survivors experience long-term cognitive and motor deficits. To date, studies predicting outcome following pediatric TBI have primarily focused on acute behavioral responses and proxy measures of injury severity; unsurprisingly, these measures explain very little of the variance following heterogenous injury. In adults, certain acute imaging biomarkers help predict cognitive and motor recovery following moderate to severe TBI. This multi-center, retrospective study, characterizes the day-of-injury computed tomographic (CT) reports of pediatric, adolescent, and young adult patients (2 months to 21 years old) who received inpatient rehabilitation services for TBI (n = 247). The study also determines the prognostic utility of CT findings for cognitive and motor outcomes assessed by the Pediatric Functional Independence Measure, converted to age-appropriate developmental functional quotient (DFQ), at discharge from rehabilitation. Subdural hematomas (66%), contusions (63%), and subarachnoid hemorrhages (59%) were the most common lesions; the majority of subjects had less severe Rotterdam CT scores (88%, ≤ 3). After controlling for age, gender, mechanism of injury, length of acute hospital stay, and admission DFQ in multivariate regression analyses, the highest Rotterdam score (β = -25.2, p < 0.01) and complete cisternal effacement (β = -19.4, p < 0.05) were associated with lower motor DFQ, and intraventricular hemorrhage was associated with lower motor (β = -3.7, p < 0.05) and cognitive DFQ (β = -4.9, p < 0.05). These results suggest that direct detection of intracranial injury provides valuable information to aid in prediction of recovery after pediatric TBI, and needs to be accounted for in future studies of prognosis and intervention.

Cognitive Recovery During Inpatient Rehabilitation Following Pediatric Traumatic Brain Injury: A Pediatric Brain Injury Consortium Study

OBJECTIVES

To characterize the demographics, clinical course, and predictors of cognitive recovery among children and young adults receiving inpatient rehabilitation following pediatric traumatic brain injury (TBI).

DESIGN

Retrospective observational, multicenter study.

SETTING

Eight acute pediatric inpatient rehabilitation facilities in the United States with specialized programs for treating patients with TBI.

PARTICIPANTS

Children and young adults (0-21 years) with TBI (n = 234) receiving inpatient rehabilitation.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Admission and discharge status assessed by the WeeFIM Cognitive Developmental Functional Quotient (DFQ) and Cognitive and Linguistic Scale (CALS).

RESULTS

Patients admitted to pediatric inpatient rehabilitation are diverse in cognitive functioning. While the majority of patients make improvements, cognitive recovery is constrained for those admitted with the most severe cognitive impairments. Age, time since injury to rehabilitation admission, and admission WeeFIM Cognitive DFQ are significant predictors of cognitive functioning at discharge from inpatient rehabilitation.

CONCLUSIONS

This work establishes a multicenter Pediatric Brain Injury Consortium and characterized the demographics and clinical course of cognitive recovery during inpatient rehabilitation of pediatric patients with TBI to aid in prospective study design.

Day-of-Injury Computed Tomography and Longitudinal Rehabilitation Outcomes: A Comparison of the Marshall and Rotterdam Computed Tomography Scoring Methods

OBJECTIVE

The aim of the study was to compare the relative predictive value of Marshall Classification System and Rotterdam scores on long-term rehabilitation outcomes. This study hypothesized that Rotterdam would outperform Marshall Classification System.

DESIGN

The study used an observational cohort design with a consecutive sample of 88 participants (25 females, mean age = 42.0 [SD = 21.3]) with moderate to severe traumatic brain injury who were admitted to trauma service with subsequent transfer to the rehabilitation unit between February 2009 and July 2011 and who had clearly readable computed tomography scans. Twenty-three participants did not return for the 9-mo postdischarge follow-up. Day-of-injury computed tomography images were scored using both Marshall Classification System and Rotterdam criteria by two independent raters, blind to outcomes. Functional outcomes were measured by length of stay in rehabilitation and the cognitive and motor subscales of the Functional Independence Measure at rehabilitation discharge and 9-mo postdischarge follow-up.

RESULTS

Neither Marshall Classification System nor Rotterdam scales as a whole significantly predicted Functional Independence Measure motor or cognitive outcomes at discharge or 9-mo follow-up. Both scales, however, predicted length of stay in rehabilitation. Specific Marshall scores (3 and 6) and Rotterdam scores (5 and 6) significantly predicted subacute outcomes such as Functional Independence Measure cognitive at discharge from rehabilitation and length of stay.

CONCLUSIONS

Marshall Classification System and Rotterdam scales may have limited utility in predicting long-term functional outcome, but specific Marshall and Rotterdam scores, primarily linked to increased severity and intracranial pressure, may predict subacute outcomes.

What interventions are performed in daily practice to prevent surgical site infections in neurosurgical patients? Findings from an explorative survey

Aim

The primary aim of the study was to describe the perioperative care ensured on a daily basis to prevent surgical site infection in Italian neurosurgeries; the secondary aim was to explore surgical site infections 30 days after the surgical procedures.

Methods

Patients cared for in 16 neurosurgical units who (a) were ≥18 years of age, (b) underwent neurosurgical procedures, and (c) were willing to participate in the study were taken into account.

Results

A total of 383 patients were included. A preoperative shower was performed in 332 cases (86.7%), shaving in 318 (83%) cases, and antibiotic prophylaxis was administered in 293 (76.5%) cases. Surgical site disinfection was performed mainly with povidone–iodine (344; 89.8%). A surgical site dressing was applied in 376 (98.2%) cases and was changed on average after 37.8h for shaved and 39h for non-shaved patients. Postoperative shampooing was performed only in 74 (19.3%) cases. Surgical site infection at 30 days occurred in three (0.8%) patients. Discussion and conclusions: Perioperative care aimed at preventing surgical site infections is variable across Italian neurosurgical units. More studies aimed at developing evidence capable of supporting decision-making processes in neurosurgery care are strongly recommended.