The best marker for guiding the clinical management of patients with raised intracranial pressure: the RAP index or the mean pulse amplitude?

Raised intracranial pressure is a common problem in a variety of neurosurgical conditions including traumatic brain injury, hydrocephalus and intracranial haemorrhage. The clinical management of these patients is guided by a variety of haemodynamic, biochemical and clinical factors. However to date there is no single parameter that is used to guide clinical management of patients with raised intracranial pressure (ICP). However, the role of ICP indices, specifically the mean pulse amplitude (AMP) and RAP index [correlation coefficient (R) between AMP amplitude (A) and mean ICP pressure (P); index of compensatory reserve], as an indicator of true ICP has been investigated. Whilst the RAP index has been used both as a descriptor of neurological deterioration in TBI patients and as a way of characterising the compensatory reserve in hydrocephalus, more recent studies have highlighted the limitation of the RAP index due to the influence that baseline effect errors have on the mean ICP, which is used in the calculation of the RAP index. These studies have suggested that the ICP mean pulse amplitude may be a more accurate marker of true intracranial pressure due to the fact that it is uninfluenced by the mean ICP and, therefore, the AMP may be a more reliable marker than the RAP index for guiding the clinical management of patients with raised ICP. Although further investigation needs to be undertaken in order to fully assess the role of ICP indices in guiding the clinical management of patients with raised ICP, the studies undertaken to date provide an insight into the potential role of ICP indices to treat raised ICP proactively rather than reactively and therefore help prevent or minimise secondary brain injury

Role of a medical student neuro-society organized neurosurgical conference: the Glasgow neuro experience

Background: Entering neurosurgical training in the United Kingdom demands extensive prior commitment and achievement, despite little to no exposure to the specialty in medical school. Conferences run by student “neuro-societies” offer a means to bridge this gap. This paper describes one student-led neuro-society’s experience of curating a 1-day national neurosurgical conference supported by our neurosurgical department. Methods: A pre-and post-conference survey was distributed to attendees to ascertain baseline opinions and conference impact using a five-point Likert Scale, and free text questions explored medical students’ opinions of neurosurgery and neurosurgical training. The conference offered four lectures and three workshops; the latter provided practical skills and networking opportunities. There were also 11 posters displayed throughout the day. Results: 47 medical students participated in our study. Post-conference, participants were more likely to understand what a neurosurgical career involves and how to secure training. They also reported increased knowledge about neurosurgery research, electives, audits, and project opportunities. Respondents enjoyed the workshops provided and suggested the inclusion of more female speakers in future. Conclusion: Neurosurgical conferences organized by student neuro-societies successfully address the gap between a lack of neurosurgery exposure and a competitive training selection. These events give medical students an initial understanding of a neurosurgical career through lectures and practical workshops; attendees also gain insight into attaining relevant achievements and have an opportunity to present research. Student neuro-society-organized conferences have the potential to be adopted internationally and used as a tool to educate on a global level and greatly aid medical students who are aspiring neurosurgeons

Time series analysis and prediction of intracranial pressure using time-varying dynamic linear models

Intracranial pressure (ICP) monitoring is a key clinical tool in the assessment and treatment of patients in a neuro-intensive care unit (neuro-ICU). As such, a deeper understanding of how an individual patient's ICP can be influenced by therapeutic interventions could improve clinical decision-making. A pilot application of a time-varying dynamic linear model was conducted using the BrainIT dataset, a multi-centre European dataset containing temporaneous treatment and vital-sign recordings. The study included 106 patients with a minimum of 27 h of ICP monitoring. The model was trained on the first 24 h of each patient's ICU stay, and then the next 2 h of ICP was forecast. The algorithm enabled switching between three interventional states: analgesia, osmotic therapy and paralysis, with the inclusion of arterial blood pressure, age and gender as exogenous regressors. The overall median absolute error was 2.98 (2.41-5.24) mmHg calculated using all 106 2-h forecasts. This is a novel technique which shows some promise for forecasting ICP with an adequate accuracy of approximately 3 mmHg. Further optimisation is required for the algorithm to become a usable clinical tool

Evaluation of software for automated measurement of adherence to ICP-monitoring threshold guideline

Challenges inherent in clinical guideline development include a long time lag between the key results and incorporation into best practice and the qualitative nature of adherence measurement, meaning it will have no directly measurable impact. To address these issues, a framework has been developed to automatically measure adherence by clinicians in neurological intensive care units to the Brain Trauma Foundation's intracranial pressure (ICP)-monitoring guidelines for severe traumatic brain injury (TBI).The framework processes physiological and treatment data taken from the bedside, standardises the data as a set of process models, then compares these models against similar process models constructed from published guidelines. A similarity metric (i.e. adherence measure) between the two models is calculated, composed of duration and scale of non-adherence.In a pilot clinical validation test, the framework was applied to physiological/treatment data from three TBI patients exhibiting ICP secondary insults at a local neuro-centre where clinical experts coded key clinical interventions/decisions about patient management.The framework identified non-adherence with respect to drug administration in one patient, with a spike in non-adherence due to an inappropriately high dosage; a second patient showed a high severity of guideline non-adherence; and a third patient showed non-adherence due to a low number of associated events and treatment annotations

Collectives of diagnostic biomarkers identify high-risk subpopulations of hematuria patients: exploiting heterogeneity in large-scale biomarker data

<p>Abstract</p> <p>Background</p> <p>Ineffective risk stratification can delay diagnosis of serious disease in patients with hematuria. We applied a systems biology approach to analyze clinical, demographic and biomarker measurements (n = 29) collected from 157 hematuric patients: 80 urothelial cancer (UC) and 77 controls with confounding pathologies.</p> <p>Methods</p> <p>On the basis of biomarkers, we conducted agglomerative hierarchical clustering to identify patient and biomarker clusters. We then explored the relationship between the patient clusters and clinical characteristics using Chi-square analyses. We determined classification errors and areas under the receiver operating curve of Random Forest Classifiers (RFC) for patient subpopulations using the biomarker clusters to reduce the dimensionality of the data.</p> <p>Results</p> <p>Agglomerative clustering identified five patient clusters and seven biomarker clusters. Final diagnoses categories were non-randomly distributed across the five patient clusters. In addition, two of the patient clusters were enriched with patients with 'low cancer-risk' characteristics. The biomarkers which contributed to the diagnostic classifiers for these two patient clusters were similar. In contrast, three of the patient clusters were significantly enriched with patients harboring 'high cancer-risk" characteristics including proteinuria, aggressive pathological stage and grade, and malignant cytology. Patients in these three clusters included controls, that is, patients with other serious disease and patients with cancers other than UC. Biomarkers which contributed to the diagnostic classifiers for the largest 'high cancer- risk' cluster were different than those contributing to the classifiers for the 'low cancer-risk' clusters. Biomarkers which contributed to subpopulations that were split according to smoking status, gender and medication were different.</p> <p>Conclusions</p> <p>The systems biology approach applied in this study allowed the hematuric patients to cluster naturally on the basis of the heterogeneity within their biomarker data, into five distinct risk subpopulations. Our findings highlight an approach with the promise to unlock the potential of biomarkers. This will be especially valuable in the field of diagnostic bladder cancer where biomarkers are urgently required. Clinicians could interpret risk classification scores in the context of clinical parameters at the time of triage. This could reduce cystoscopies and enable priority diagnosis of aggressive diseases, leading to improved patient outcomes at reduced costs.</p

Use of direct intracranial pressure and brain tissue oxygen monitoring in perioperative management of patients with moyamoya disease

Intracranial pressure monitoring and brain tissue oxygen monitoring are commonly used in head injury for goal-directed therapies, but there may be more indications for its use. Moyamoya disease involves progressive stenosis of the arterial circulation and formation of collateral vessels that are at risk of hemorrhage. The risk of ischemic events during revascularization surgery and postoperatively is high. Impaired cerebral autoregulation may be one of the factors that are implicated. We present our experience with monitoring of cerebral oxygenation and autoregulation in the pathological hemisphere during the perioperative period in four patients with moyamoya disease

International e-Delphi survey to define best practice in the reporting of intracranial pressure monitoring recording data

Introduction: Intracranial pressure (ICP) monitoring is a very commonly performed neurosurgical procedure but there is a wide variation in how it is reported, hindering analysis of it. The current study sought to generate consensus on the reporting of ICP monitoring recording data. Research question: “What should be included in an ICP monitoring report?” Material and methods: The exercise was completed via a modified eDelphi survey. An expert panel discussion was held from which themes were identified and used to produce a code to annotate the transcript of the discussion. Statements were generated for a further two rounds of electronic questionnaires distributed via the REDcap platform. A Likert scale was used to grade agreement with each statement in the survey. A statement was accepted if more than 70% agreement was achieved between respondents. Data was collated using Microsoft Excel and analysed using R. Results: 149 relevant statements were identified from the transcript and categorised into recording parameters, waveform characteristics or reporting. A total of 22 statements were generated for the first round of the survey which was answered by 39 respondents. Following the electronic round of surveys consensus was achieved for all but one statement regarding the acceptability of automating ICP reporting. This was put forward to a second round after which 79% agreement was reached. Discussion and conclusion: The themes and statements from this eDelphi can be used as a framework to allow the standardisation of the reporting of intracranial pressure monitoring data

International e-Delphi survey to define best practice in the reporting of intracranial pressure monitoring recording data

Introduction: Intracranial pressure (ICP) monitoring is a very commonly performed neurosurgical procedure but there is a wide variation in how it is reported, hindering analysis of it. The current study sought to generate consensus on the reporting of ICP monitoring recording data. Research question: "What should be included in an ICP monitoring report?" Material and methods: The exercise was completed via a modified eDelphi survey. An expert panel discussion was held from which themes were identified and used to produce a code to annotate the transcript of the discussion. Statements were generated for a further two rounds of electronic questionnaires distributed via the REDcap platform. A Likert scale was used to grade agreement with each statement in the survey. A statement was accepted if more than 70% agreement was achieved between respondents. Data was collated using Microsoft Excel and analysed using R. Results: 149 relevant statements were identified from the transcript and categorised into recording parameters, waveform characteristics or reporting. A total of 22 statements were generated for the first round of the survey which was answered by 39 respondents. Following the electronic round of surveys consensus was achieved for all but one statement regarding the acceptability of automating ICP reporting. This was put forward to a second round after which 79% agreement was reached. Discussion and conclusion: The themes and statements from this eDelphi can be used as a framework to allow the standardisation of the reporting of intracranial pressure monitoring data

Telemetric intracranial pressure: a snapshot does not give the full story

Telemetric intracranial pressure (ICP) monitors are useful tools in the management of complex hydrocephalus and idiopathic intracranial hypertension (IIH). Clinicians may use them as a "snapshot" screening tool to assess shunt function or ICP. We compared "snapshot" telemetric ICP recordings with extended, in-patient periods of monitoring to determine whether this practice is safe and useful for clinical decision making