Analysis of cerebrospinal fluid pressure estimation using formulae derived from clinical data

David Fleischman, Amanda K. Bicket, Sandra S. Stinnett, John P. Berdahl, Jost B. Jonas, Ning Li Wang, Michael P Fautsch, R. Rand Allingham

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

PURPOSE. To evaluate a frequently used regression model and a new, modified regression model to estimate cerebrospinal fluid pressure (CSFP). METHODS. Datasets from the Beijing iCOP study from Tongren Hospital, Beijing, China, and the Mayo Clinic, Rochester, Minnesota, were tested in this retrospective, case-control study. An often-used regression model derived from the Beijing iCOP dataset, but without radiographic data, was used to predict CSFP by using demographic and physiologic data. A regression model was created using the Mayo Clinic dataset and tested against a validation group. The Mayo Clinic-derived formula was also tested against the Beijing Eye Study population. Intraclass correlation was used to assess predicted versus actual CSFP. RESULTS. The Beijing-derived regression equation was reported to have an intraclass correlation coefficient (ICC) of 0.71, indicating strong correlation between predicted and actual CSFP in the study population. The Beijing iCOP regression model poorly predicted CSFP in the Mayo Clinic population with an ICC of 0.14. The Mayo Clinic-derived regression model similarly did not predict CSFP in its Mayo Clinic validation group (ICC 0.28 6 0.04) nor in the Beijing Eye Study population (ICC 0.06). CONCLUSIONS. Formulae used to predict CSFP derived from clinical data fared poorly against a large retrospective dataset. This may be related to differences in lumbar puncture technique, in the populations tested, or the timing of collection of physiologic variables in the Mayo Clinic dataset. Caution should be used when interpreting results based on formulaic derivation of CSFP.

Original languageEnglish (US)
Pages (from-to)5625-5630
Number of pages6
JournalInvestigative Ophthalmology and Visual Science
Volume57
Issue number13
DOIs
StatePublished - Oct 1 2016

Fingerprint

Cerebrospinal Fluid Pressure
Population
Spinal Puncture
Beijing
Case-Control Studies
China
Demography
Datasets

Keywords

  • Cerebrospinal fluid
  • Cerebrospinal fluid pressure
  • Estimation equation
  • Lamina cribrosa
  • Translaminar pressure

ASJC Scopus subject areas

  • Ophthalmology
  • Sensory Systems
  • Cellular and Molecular Neuroscience

Cite this

Fleischman, D., Bicket, A. K., Stinnett, S. S., Berdahl, J. P., Jonas, J. B., Wang, N. L., ... Rand Allingham, R. (2016). Analysis of cerebrospinal fluid pressure estimation using formulae derived from clinical data. Investigative Ophthalmology and Visual Science, 57(13), 5625-5630. https://doi.org/10.1167/iovs.16-20119

Analysis of cerebrospinal fluid pressure estimation using formulae derived from clinical data. / Fleischman, David; Bicket, Amanda K.; Stinnett, Sandra S.; Berdahl, John P.; Jonas, Jost B.; Wang, Ning Li; Fautsch, Michael P; Rand Allingham, R.

In: Investigative Ophthalmology and Visual Science, Vol. 57, No. 13, 01.10.2016, p. 5625-5630.

Research output: Contribution to journalArticle

Fleischman, D, Bicket, AK, Stinnett, SS, Berdahl, JP, Jonas, JB, Wang, NL, Fautsch, MP & Rand Allingham, R 2016, 'Analysis of cerebrospinal fluid pressure estimation using formulae derived from clinical data', Investigative Ophthalmology and Visual Science, vol. 57, no. 13, pp. 5625-5630. https://doi.org/10.1167/iovs.16-20119
Fleischman, David ; Bicket, Amanda K. ; Stinnett, Sandra S. ; Berdahl, John P. ; Jonas, Jost B. ; Wang, Ning Li ; Fautsch, Michael P ; Rand Allingham, R. / Analysis of cerebrospinal fluid pressure estimation using formulae derived from clinical data. In: Investigative Ophthalmology and Visual Science. 2016 ; Vol. 57, No. 13. pp. 5625-5630.
@article{97d798fee32e4a7a88916259ea5075b6,
title = "Analysis of cerebrospinal fluid pressure estimation using formulae derived from clinical data",
abstract = "PURPOSE. To evaluate a frequently used regression model and a new, modified regression model to estimate cerebrospinal fluid pressure (CSFP). METHODS. Datasets from the Beijing iCOP study from Tongren Hospital, Beijing, China, and the Mayo Clinic, Rochester, Minnesota, were tested in this retrospective, case-control study. An often-used regression model derived from the Beijing iCOP dataset, but without radiographic data, was used to predict CSFP by using demographic and physiologic data. A regression model was created using the Mayo Clinic dataset and tested against a validation group. The Mayo Clinic-derived formula was also tested against the Beijing Eye Study population. Intraclass correlation was used to assess predicted versus actual CSFP. RESULTS. The Beijing-derived regression equation was reported to have an intraclass correlation coefficient (ICC) of 0.71, indicating strong correlation between predicted and actual CSFP in the study population. The Beijing iCOP regression model poorly predicted CSFP in the Mayo Clinic population with an ICC of 0.14. The Mayo Clinic-derived regression model similarly did not predict CSFP in its Mayo Clinic validation group (ICC 0.28 6 0.04) nor in the Beijing Eye Study population (ICC 0.06). CONCLUSIONS. Formulae used to predict CSFP derived from clinical data fared poorly against a large retrospective dataset. This may be related to differences in lumbar puncture technique, in the populations tested, or the timing of collection of physiologic variables in the Mayo Clinic dataset. Caution should be used when interpreting results based on formulaic derivation of CSFP.",
keywords = "Cerebrospinal fluid, Cerebrospinal fluid pressure, Estimation equation, Lamina cribrosa, Translaminar pressure",
author = "David Fleischman and Bicket, {Amanda K.} and Stinnett, {Sandra S.} and Berdahl, {John P.} and Jonas, {Jost B.} and Wang, {Ning Li} and Fautsch, {Michael P} and {Rand Allingham}, R.",
year = "2016",
month = "10",
day = "1",
doi = "10.1167/iovs.16-20119",
language = "English (US)",
volume = "57",
pages = "5625--5630",
journal = "Investigative Ophthalmology and Visual Science",
issn = "0146-0404",
publisher = "Association for Research in Vision and Ophthalmology Inc.",
number = "13",

}

TY - JOUR

T1 - Analysis of cerebrospinal fluid pressure estimation using formulae derived from clinical data

AU - Fleischman, David

AU - Bicket, Amanda K.

AU - Stinnett, Sandra S.

AU - Berdahl, John P.

AU - Jonas, Jost B.

AU - Wang, Ning Li

AU - Fautsch, Michael P

AU - Rand Allingham, R.

PY - 2016/10/1

Y1 - 2016/10/1

N2 - PURPOSE. To evaluate a frequently used regression model and a new, modified regression model to estimate cerebrospinal fluid pressure (CSFP). METHODS. Datasets from the Beijing iCOP study from Tongren Hospital, Beijing, China, and the Mayo Clinic, Rochester, Minnesota, were tested in this retrospective, case-control study. An often-used regression model derived from the Beijing iCOP dataset, but without radiographic data, was used to predict CSFP by using demographic and physiologic data. A regression model was created using the Mayo Clinic dataset and tested against a validation group. The Mayo Clinic-derived formula was also tested against the Beijing Eye Study population. Intraclass correlation was used to assess predicted versus actual CSFP. RESULTS. The Beijing-derived regression equation was reported to have an intraclass correlation coefficient (ICC) of 0.71, indicating strong correlation between predicted and actual CSFP in the study population. The Beijing iCOP regression model poorly predicted CSFP in the Mayo Clinic population with an ICC of 0.14. The Mayo Clinic-derived regression model similarly did not predict CSFP in its Mayo Clinic validation group (ICC 0.28 6 0.04) nor in the Beijing Eye Study population (ICC 0.06). CONCLUSIONS. Formulae used to predict CSFP derived from clinical data fared poorly against a large retrospective dataset. This may be related to differences in lumbar puncture technique, in the populations tested, or the timing of collection of physiologic variables in the Mayo Clinic dataset. Caution should be used when interpreting results based on formulaic derivation of CSFP.

AB - PURPOSE. To evaluate a frequently used regression model and a new, modified regression model to estimate cerebrospinal fluid pressure (CSFP). METHODS. Datasets from the Beijing iCOP study from Tongren Hospital, Beijing, China, and the Mayo Clinic, Rochester, Minnesota, were tested in this retrospective, case-control study. An often-used regression model derived from the Beijing iCOP dataset, but without radiographic data, was used to predict CSFP by using demographic and physiologic data. A regression model was created using the Mayo Clinic dataset and tested against a validation group. The Mayo Clinic-derived formula was also tested against the Beijing Eye Study population. Intraclass correlation was used to assess predicted versus actual CSFP. RESULTS. The Beijing-derived regression equation was reported to have an intraclass correlation coefficient (ICC) of 0.71, indicating strong correlation between predicted and actual CSFP in the study population. The Beijing iCOP regression model poorly predicted CSFP in the Mayo Clinic population with an ICC of 0.14. The Mayo Clinic-derived regression model similarly did not predict CSFP in its Mayo Clinic validation group (ICC 0.28 6 0.04) nor in the Beijing Eye Study population (ICC 0.06). CONCLUSIONS. Formulae used to predict CSFP derived from clinical data fared poorly against a large retrospective dataset. This may be related to differences in lumbar puncture technique, in the populations tested, or the timing of collection of physiologic variables in the Mayo Clinic dataset. Caution should be used when interpreting results based on formulaic derivation of CSFP.

KW - Cerebrospinal fluid

KW - Cerebrospinal fluid pressure

KW - Estimation equation

KW - Lamina cribrosa

KW - Translaminar pressure

UR - http://www.scopus.com/inward/record.url?scp=84992028366&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84992028366&partnerID=8YFLogxK

U2 - 10.1167/iovs.16-20119

DO - 10.1167/iovs.16-20119

M3 - Article

VL - 57

SP - 5625

EP - 5630

JO - Investigative Ophthalmology and Visual Science

JF - Investigative Ophthalmology and Visual Science

SN - 0146-0404

IS - 13

ER -