Abstract
Purpose In recent years, radiofrequency identification has been used for the continuous measurement
of intracranial pressure (ICP) in patients with a cerebrospinal fluid (CSF) shunt
for hydrocephalus . Unlike ICP monitoring in an inpatient setting, measurements in
mobile patients outside the hospital provide ICP data that take into account the everyday
activities of each individual patient. Common methods of ICP monitoring and analysis
cannot be used for those patients. In addition, ICP measurements in mobile patients
require considerably longer observation times than in-hospital monitoring. For this
reason, ICP measurements over a period of 7 to 10 days must be analyzed effectively
and efficiently.
Methods A possible approach is to analyze ICP data graphically. Pathologic changes can be
expected to be associated with specific patterns that can be detected graphically
(e.g., Lundberg A waves). Patients without pathologic ICP values and without intracranial
pathologies usually show an approximately normal distribution of ICP data. By contrast,
patients with pathologic ICP values are likely to show major deviations from a normal
distribution such as changes in minimum and maximum values and multimodal distributions.
Against this background, we present a new graphical method for detecting pathologic
conditions. This novel method is based on the distribution of ICP data that is assessed
using GNU R, a free software package for statistical computing and graphics.
Results A left-skewed distribution indicates CSF shunt overdrainage and a right-skewed distribution
suggests CSF shunt underdrainage. In addition, an additive analysis of the number
of physiologic ICP values can be helpful in detecting possible causes of CSF shunt
overdrainage or underdrainage. The approach presented here shows that patients with
hydrocephalus objectively benefited from ICP-guided adjustments of the opening pressure
of a shunt valve or the insertion of a valve. This objective improvement was confirmed
by the patients' subjective perception of well-being.
Conclusions Further investigations should be performed to examine the influence of multimodal
ICP distributions and to assess how data analysis is affected by a drift that can
occur when a sensor has been in place for an extended period of time.
Keywords
intracranial pressure measurement - ventriculoperitoneal shunt - gravity-assisted
valve - hydrocephalus - telemetry
