Time Series Analysis and Prediction of Intracranial Pressure Using Time-Varying Dynamic Linear Models.
Acta Neurochir Suppl
; 131: 225-229, 2021.
Article
en En
| MEDLINE
| ID: mdl-33839849
ABSTRACT
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.
Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Presión Intracraneal
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Acta Neurochir Suppl
Año:
2021
Tipo del documento:
Article
País de afiliación:
Reino Unido