Development of Traumatic Brain Injury Associated Intracranial Hypertension Prediction Algorithms: A Narrative Review

Abstract

Traumatic intracranial hypertension (tIH) is a common and potentially lethal complication of moderate to severe traumatic brain injury (m-sTBI). It often develops with little warning and is managed reactively with the tiered application of intracranial pressure (ICP)-lowering interventions administered in response to an ICP rising above a set threshold. For over 45 years, a variety of research groups have worked toward the development of technology to allow for the preemptive management of tIH in the hope of improving patient outcomes. In 2022, the first operationalizable tIH prediction system became a reality. With such a system, ICP lowering interventions could be administered prior to the rise in ICP, thus protecting the patient from potentially damaging tIH episodes and limiting the overall ICP burden experienced. In this review, we discuss related approaches to ICP forecasting and IH prediction algorithms, which collectively provide the foundation for the successful development of an operational tIH prediction system. We also discuss operationalization and the statistical assessment of tIH algorithms. This review will be of relevance to clinicians and researchers interested in development of this technology as well as those with a general interest in the bedside application of machine learning (ML) technology.

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

“…In the case of studies requiring an alternative consent model, these studies will be considered affiliate projects, requiring data sharing agreements in addition to independent ethical approval. Specific examples of affiliate Open access projects with data sharing agreements in principle are the PREDICT-TBI study 28 and the Artificial Intelligence-Enhanced Management of Severe TBI (AIMS-TBI) 29 studies. The PREDICT-TBI project aims to use advanced imaging techniques, blood-bourne biomarkers and artificial intelligence (AI) techniques to accurately predict neurological outcomes, while the AIMS-TBI study focuses on the development and operationalisation of clinical AI algorithms designed to aid in the management of patients with msTBI in real time.…”

Using Artificial Intelligence to Predict Intracranial Hypertension in Patients After Traumatic Brain Injury: A Systematic Review

“…Second, the use of imaging (especially CT-scan) features in the prediction of ICP/IH in patients with TBI holds promise in relation to AI. Only one study [10] used an imagingrelated feature; the presence of abnormal ventricle size on CT. Future studies should explore the use of imaging features to train a predicting method, since AI may especially be able to outperform human interpretation [22]. Third, although the required sample frequency was a value per minute for the best performing model by Carra et al [20], another recent large validation study by Schweingruber et al [23] that was excluded in this systematic review given that the minority (less than a third) of included patients with brain injury were actually TBI, found that hourly sampling and missing data could still result in a high AUC (0.94-0.98 with 1 h prediction window).…”

A Comprehensive Perspective on Intracranial Pressure Monitoring and Individualized Management in Neurocritical Care: Results of a Survey with Global Experts

“…This underscores the need for additional parameters for guidance. In this context, multimodality neuromonitoring and ICP waveform (ICPW) or pulse morphology emerge as promising options for better differentiation of patients at risk of developing IH crisis [21,22] (Fig. 1).…”