July 2018
Volume 59, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2018
Validation of an equation model to predict intracranial pressure in clinical studies
Author Affiliations & Notes
  • Niro Kasahara
    Ophthalmology, Santa Casa de Sao Paulo Sch of Med Sci, S?o Paulo, S?o Paulo, Brazil
  • Mateus Matuoka
    Ophthalmology, Santa Casa de Sao Paulo Sch of Med Sci, S?o Paulo, S?o Paulo, Brazil
  • Katia Santos
    Ophthalmology, Santa Casa de Sao Paulo Sch of Med Sci, S?o Paulo, S?o Paulo, Brazil
  • Natasha Cruz
    Ophthalmology, Santa Casa de Sao Paulo Sch of Med Sci, S?o Paulo, S?o Paulo, Brazil
  • Alvaro R Martins
    Clinical Pathology Laboratory, Irmandade da Santa Casa de Misericordia de Sao Paulo, Sao Paulo, São Paulo, Brazil
  • Stanley Nigro
    Clinical Pathology Laboratory, Irmandade da Santa Casa de Misericordia de Sao Paulo, Sao Paulo, São Paulo, Brazil
  • Footnotes
    Commercial Relationships   Niro Kasahara, None; Mateus Matuoka, None; Katia Santos, None; Natasha Cruz, None; Alvaro Martins, None; Stanley Nigro, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 614. doi:
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      Niro Kasahara, Mateus Matuoka, Katia Santos, Natasha Cruz, Alvaro R Martins, Stanley Nigro; Validation of an equation model to predict intracranial pressure in clinical studies. Invest. Ophthalmol. Vis. Sci. 2018;59(9):614.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Recent studies have implicated the role of intracranial pressure (ICP) as a major contributor to glaucoma. The lack of alternative non-invasive methods to measure the ICP limits further research on this field. Using multivariate analysis, Jonas et al developed a formula to estimate the ICP for the Chinese population. Since then, the equation has not been tested or validated in different populations. The purpose of this cross-sectional, observational study was to compare the predicted with the measured ICP and to validate the equation for clinical studies in a small validation cohort of Brazilian patients.

Methods : The sample comprised patients with neurological disorders scheduled to have lumbar puncture. Height, weight, and blood pressure were measured for each patient. The ICP was measured by lumbar puncture using aseptic technique. After all data were collected, the predictive ICP was calculated according to the equation of Jonas et al:
ICP = (0.44 × BMI) + (0.16 × DBP) - (0.18 × age); where, ICP is intracranial pressure (mmHg), BMI is body mass index (kg/m2), DBP is diastolic blood pressure (mmHg), and age input is in years. The Bland-Altman analysis was done to compare predicted and measured ICP with 95% limits of agreement.

Results : A small cohort of 39 subjects enrolled the study. Mean age was 43.9 ± 18.4 years; 10 were male and 29 female. As to diagnosis, 5 had multiple sclerosis, 4 had infectious meningitis, 3 cerebral pseudotumor, and the other patients had different conditions. The figure below displays the Bland-Altman plot of the differences between the two techniques against their averages. Most data points were positioned between the two limits of agreement so the two methods are considered to be in agreement.

Conclusions : The results of this study favor the use of Jonas equation as a proxy method to predict ICP. We cannot propose the use of the equation on clinical grounds for diagnosis and monitoring of patients with neurological disorders; however, it may be a suitable surrogate method to predict ICP in large clinical studies.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

 

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