Intracranial Pressure Monitoring for Acute Brain Injured Patients: When, How, What Should We Monitor

Optic Nerve Sheath Diameter Estimation to Detect Increased Intracranial Pressure in Traumatic Brain Injury patients at a Level I Trauma Center in Eastern India

Objective

To evaluate the diagnostic accuracy of optic nerve sheath diameter (ONSD) measured by ultrasound as a non-invasive marker for detecting elevated intracranial pressure (ICP) in patients with traumatic brain injury (TBI), based on clinical and radiological findings.

Methods

This diagnostic accuracy study included 180 adult patients with isolated TBI admitted to a Level I Trauma Centre in Eastern India. ONSD was measured bilaterally using a 7.5 MHz linear ultrasound probe, 3 mm posterior to the globe. Clinical and radiological parameters were recorded, and increased ICP was determined based on a predefined clinical signs and computed tomography findings. Statistical analysis included logistic regression and receiver operating characteristic (ROC) curve analysis using Jamovi software.

Results

The mean ONSD was significantly higher in patients with increased ICP (5.36±0.56 mm) compared to those without (4.13±0.34 mm, p<0.001). ROC analysis showed excellent diagnostic performance (area under the curve: 0.942), with sensitivity and specificity of 93.2% and 81.8%, respectively, at a cut-off value of 5.0 mm. The positive predictive value was 74.0%, and the negative predictive value was 99.0%. Increased ONSD was associated with TBI severity and poor Glasgow Outcome Scale scores at 3 months.

Conclusion

Ultrasound-measured ONSD is a sensitive, non-invasive bedside tool for detecting increased ICP in TBI patients, particularly useful in resource-limited settings.

Pressure Gradient as a Predictor of Time Needed to Drain Cerebrospinal Fluid Via an External Ventricular Drain

BACKGROUND

Consensus is lacking on best practices regarding treatment of elevated intracranial pressure. One method is placement of an external ventricular drain to divert cerebrospinal fluid via continuous or intermittent drainage.

OBJECTIVE

To explore the time required for fluid to finish draining at various pressure gradients under high- and low-compliance conditions.

METHODS

An ex vivo model filled with 6200 mL saline and minimal air (low compliance) or 6050 mL saline and 150 mL air (high compliance) was attached to an external ventricular drain and transducer and then calibrated. The initial pressure in the chamber was set by adding or removing saline, and the buretrol was positioned to the set threshold. The external ventricular drain was then opened. Using different pressure gradients, 84 observations (42 low compliance, 42 high compliance) were obtained to identify the time to the second-to-last drop and the last drop (end of drainage).

RESULTS

The overall mean (SD) time from stopcock opening to last drop was 100.80 (65.84) seconds. The mean low-compliance time was 40.57 (15.83) seconds, and the mean high-compliance time was 161.00 (33.14) seconds (P < .001). Pressure gradient was a predictor of drainage time in both high-compliance (P < .001) and low-compliance (P < .001) conditions. In all 84 trials, fluid diversion was complete within 4.5 minutes (second-to-last drop, 2 minutes 48 seconds).

CONCLUSIONS

The results of this study highlight the need to standardize intracranial pressure monitoring practice and further scientific knowledge about the best drainage techniques for patients with acquired brain injury.

Developing practical machine learning survival models to identify high-risk patients for in-hospital mortality following traumatic brain injury

Machine learning (ML) offers precise predictions and could improve patient care, potentially replacing traditional scoring systems. A retrospective study at Emtiaz Hospital analyzed 3,180 traumatic brain injury (TBI) patients. Nineteen variables were assessed using ML algorithms to predict outcomes. Data preparation addressed missing values and balancing methods corrected imbalances. Model building involved training-test splits, survival analysis, and ML algorithms like Random Survival Forest (RSF) and Gradient Boosting. Feature importance was examined, with patient risk stratification guiding survival analysis. The best-performing model, RSF with ROS resampling, achieved the highest mean AUC of 0.80, the lowest IBS of 0.11, and IPCW c-index of 0.79, maintaining strong predictive ability over time. Top predictors for in-hospital mortality included age, GCS, pupil condition, PTT, IPH, and Rotterdam score, with high variations in predictive abilities over time. A risk stratification cut-off value of 63.34 separated patients into low and high-risk categories, with Kaplan-Meier curves showing significant survival differences. Our high-performing predictive model, built on first-day features, enables time-dependent risk assessment for tailored interventions and monitoring. Our study highlights the feasibility of AI tools in clinical settings, offering superior predictive accuracy and enhancing patient care for TBI cases.

Neurological manifestations of encephalitic alphaviruses, traumatic brain injuries, and organophosphorus nerve agent exposure

Encephalitic alphaviruses (EEVs), Traumatic Brain Injuries (TBI), and organophosphorus nerve agents (NAs) are three diverse biological, physical, and chemical injuries that can lead to long-term neurological deficits in humans. EEVs include Venezuelan, eastern, and western equine encephalitis viruses. This review describes the current understanding of neurological pathology during these three conditions, provides a comparative review of case studies vs. animal models, and summarizes current therapeutics. While epidemiological data on clinical and pathological manifestations of these conditions are known in humans, much of our current mechanistic understanding relies upon animal models. Here we review the animal models findings for EEVs, TBIs, and NAs and compare these with what is known from human case studies. Additionally, research on NAs and EEVs is limited due to their classification as high-risk pathogens (BSL-3) and/or select agents; therefore, we leverage commonalities with TBI to develop a further understanding of the mechanisms of neurological damage. Furthermore, we discuss overlapping neurological damage mechanisms between TBI, NAs, and EEVs that highlight novel medical countermeasure opportunities. We describe current treatment methods for reducing neurological damage induced by individual conditions and general neuroprotective treatment options. Finally, we discuss perspectives on the future of neuroprotective drug development against long-term neurological sequelae of EEVs, TBIs, and NAs.

"NeuroVanguard": a contemporary strategy in neuromonitoring for severe adult brain injury patients

Severe acute brain injuries, stemming from trauma, ischemia or hemorrhage, remain a significant global healthcare concern due to their association with high morbidity and mortality rates. Accurate assessment of secondary brain injuries severity is pivotal for tailor adequate therapies in such patients. Together with neurological examination and brain imaging, monitoring of systemic secondary brain injuries is relatively straightforward and should be implemented in all patients, according to local resources. Cerebral secondary injuries involve factors like brain compliance loss, tissue hypoxia, seizures, metabolic disturbances and neuroinflammation. In this viewpoint, we have considered the combination of specific noninvasive and invasive monitoring tools to better understand the mechanisms behind the occurrence of these events and enhance treatment customization, such as intracranial pressure monitoring, brain oxygenation assessment and metabolic monitoring. These tools enable precise intervention, contributing to improved care quality for severe brain injury patients. The future entails more sophisticated technologies, necessitating knowledge, interdisciplinary collaboration and resource allocation, with a focus on patient-centered care and rigorous validation through clinical trials.

Rheoencephalography: A non-invasive method for neuromonitoring

In neurocritical care, the gold standard method is intracranial pressure (ICP) monitoring for the patient's lifesaving. Since it is an invasive method, it is desirable to use an alternative, noninvasive technique. The computerized real-time invasive cerebral blood flow (CBF) autoregulation (AR) monitoring calculates the status of CBF AR, called the pressure reactivity index (PRx). Studies documented that the electrical impedance of the head (Rheoencephalography - REG) can detect the status of CBF AR (REGx) and ICP noninvasively. We aimed to test REG to reflect ICP and CBF AR. For nineteen healthy subjects we recorded bipolar bifrontal and bitemporal REG derivations and arm bioimpedance pulses with a 200 Hz sampling rate. The challenges were a 30-second breath-holding and head-down-tilt (HDT - Trendelenburg) position. Data were stored and processed offline. REG pulse wave morphology and REGx were calculated. The most relevant finding was the significant morphological change of the REG pulse waveform (2nd peak increase) during the HDT position. Breath-holding caused REG amplitude increase, but it was not significant. REGx in male and female group averages have similar trends during HDT by indicating the active status of CBF AR. The morphological change of REG pulse wave during HDT position was identical to ICP waveform change during increased ICP, reflecting decreased intracranial compliance. A correlation study between ICP and REG was initiated in neurocritical care patients. The noninvasive REG monitoring would also be useful in space research as well as in military medicine during the transport of wounded service members as well as for fighter pilots to indicate the loss of CBF and consciousness.