June 2021
Volume 62, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2021
Physiology-enhanced data analytics to evaluate the effect of altitude on intraocular pressure
Author Affiliations & Notes
  • Giovanna Guidoboni
    Electrical Engineering Computer Science, Mathematics, University of Missouri, Columbia, Missouri, United States
  • Marcela Szopos
    MAP5 UMR CNRS 8145, Universite de Paris, Paris, France
  • Alice Chandra Verticchio Vercellin
    Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York, United States
    Department of Surgical and Clinical, Diagnostic and Pediatric Sciences, Section of Ophthalmology, Universita degli Studi di Pavia, Pavia, Lombardia, Italy
  • Carlo Bruttini
    Department of Surgical and Clinical, Diagnostic and Pediatric Sciences, Section of Ophthalmology, Universita degli Studi di Pavia, Pavia, Lombardia, Italy
    IRCCS Fondazione Policlinico San Matteo, Pavia, Italy
  • Ivano Riva
    Department of Surgical and Clinical, Diagnostic and Pediatric Sciences, Section of Ophthalmology, Universita degli Studi di Pavia, Pavia, Lombardia, Italy
    IRCCS Fondazione Policlinico San Matteo, Pavia, Italy
  • Brent A Siesky
    Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Alon Harris
    Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Luciano Quaranta
    Department of Surgical and Clinical, Diagnostic and Pediatric Sciences, Section of Ophthalmology, Universita degli Studi di Pavia, Pavia, Lombardia, Italy
    IRCCS Fondazione Policlinico San Matteo, Pavia, Italy
  • Footnotes
    Commercial Relationships   Giovanna Guidoboni, Foresite Healthcare LLC (C), Gspace LLC (I); Marcela Szopos, None; Alice Chandra Verticchio Vercellin, None; Carlo Bruttini, None; Ivano Riva, None; Brent Siesky, None; Alon Harris, AdOM (C), AdOM (S), AdOM (I), Luseed (C), Luseed (I), Oxymap (I), Phileas Pharma (S), Phileas Pharma (I), Qlaris (C), Qlaris (S), Qlaris (I), QuLent (I); Luciano Quaranta, Allergan (R), Allergan (F), Bausch&Lomb (R), Bausch&Lomb (F), Fidia-Sooft (C), Novartis (R), Novartis (F), Omikron (F), Santen (R), Santen (F), SIFI (F), Thea (R), Visufarma (R), Visufarma (C)
  • Footnotes
    Support  NSF-DMS 1853222/2021192
Investigative Ophthalmology & Visual Science June 2021, Vol.62, 559. doi:
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      Giovanna Guidoboni, Marcela Szopos, Alice Chandra Verticchio Vercellin, Carlo Bruttini, Ivano Riva, Brent A Siesky, Alon Harris, Luciano Quaranta; Physiology-enhanced data analytics to evaluate the effect of altitude on intraocular pressure. Invest. Ophthalmol. Vis. Sci. 2021;62(8):559.

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

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Abstract

Purpose : While it is known that altitude affects intraocular pressure (IOP), the underlying mechanisms remain unclear. Mean arterial pressure (MAP) and osmotic pressure difference (OPD) are considered important factors governing the IOP change with altitude. Herein we use a novel physiology-enhanced approach to analyze data from the Mont Blanc Study (MBS) (Bruttini et al. 2020), with the goal of assessing the relative roles of MAP and OPD on IOP.

Methods : In MBS, IOP and MAP were measured in 33 healthy volunteers at 77 m above sea level (a.s.l.) (Pavia, PV, Italy), at 1,300 m a.s.l. (Courmayeur, CM, Italy) and 3,466 m a.s.l. (Pointe Helbronner, PH, Mont Blanc Mountain, Italy), in addition to other systemic factors. A validated mathematical model for aqueous humor (AH) circulation (Szopos et al 2016) was used to analyze the MBS data. In the model, IOP is predicted as the result of the balance between AH production and drainage, with MAP and OPD included as parameters regulating AH production.

Results : A first analysis is conducted using measured MAP as an individualized model input to predict the corresponding IOP and compare it with IOP measured at different altitudes (PV, CM, PH). Fig.1 shows that changes in MAP are not sufficient to explain the measured IOP differences, since the measured IOP decreases with altitude while the model-predicted IOP increases. A second analysis is conducted by using the measured MAP and IOP as an individualized model inputs and estimates the OPD that would be necessary to have AH flow balance at different altitudes (PV, CM, PH). Fig. 2 shows that changes in OPD, in conjunction with MAP, capture the decreasing trend of IOP with altitude as observed in MBS.

Conclusions : Physiology-enhanced data analytics based on mathematical modeling suggests OPD plays an important role in regulating IOP with changes in altitude. Modeling factors that are conjectured to be relevant such as OPD may provide insights into parameters that cannot be measured directly. Future model analytics will include the effect of temperature and central corneal thickness for enhanced specificity.

This is a 2021 ARVO Annual Meeting abstract.

 

Comparison between measured and model-predicted IOP based on individualized MAP.

Comparison between measured and model-predicted IOP based on individualized MAP.

 

Model-predicted OPD based on individualized MAP and IOP inputs.

Model-predicted OPD based on individualized MAP and IOP inputs.

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