April 2010
Volume 51, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2010
24-Hour Habitual Rhythm of Intraocular Pressure, Mean Arterial Pressure and Mean Ocular Perfusion Pressure in Untreated Normal-Tension Glaucoma Patients
Author Affiliations & Notes
  • Y. Nam
    Ophthalmology, Asan Medical Center, Seoul, Republic of Korea
  • K. Sung
    Ophthalmology, Asan Medical Center, Seoul, Republic of Korea
  • B. Moon
    Ophthalmology, Asan Medical Center, Seoul, Republic of Korea
  • J. Cho
    Ophthalmology, Asan Medical Center, Seoul, Republic of Korea
  • S. Kang
    Ophthalmology, Asan Medical Center, Seoul, Republic of Korea
  • M. S. Kook
    Ophthalmology, Asan Medical Center, Seoul, Republic of Korea
  • Footnotes
    Commercial Relationships  Y. Nam, None; K. Sung, None; B. Moon, None; J. Cho, None; S. Kang, None; M.S. Kook, None.
  • Footnotes
    Support  None.
Investigative Ophthalmology & Visual Science April 2010, Vol.51, 576. doi:
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      Y. Nam, K. Sung, B. Moon, J. Cho, S. Kang, M. S. Kook; 24-Hour Habitual Rhythm of Intraocular Pressure, Mean Arterial Pressure and Mean Ocular Perfusion Pressure in Untreated Normal-Tension Glaucoma Patients. Invest. Ophthalmol. Vis. Sci. 2010;51(13):576.

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

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Abstract

Purpose: : To characterize the 24-hour rhythm of intraocular pressure (IOP), mean arterial pressure (MAP), and mean ocular perfusion pressure (MOPP) in patients with untreated normal-tension glaucoma (NTG) in the habitual position.

Methods: : One-hundred seventy-nine NTG eyes were prospectively recruited and underwent 24-hour measurement of IOP and systemic blood pressure (BP) in the habitual position. Mean 24-hour rhythms of IOP, MAP[diastolic BP+1/3x(systolic BP-diastolic BP)], and MOPP [2/3 x MAP-IOP] were analyzed using polynomial curve fit. This curve fitting scheme was realized by using "polyfit" function of Matlab software version 6.5 (MathWorks, Inc.). The best curve fit was automatically determined when the overall difference between measured IOP and estimated curve at a given time point was the smallest. The differences between the values predicted from the mathematical models and the mean values of each parameters (IOP, MAP, and MOPP) at measured clock hour were obtained. The multiple linear regression analysis was used to derive explanatory variables (diurnal mean, peak, trough IOPs, MAPs, MOPPs, age, CCT, visual field mean deviation) having a statistically significant contribution to NTG risk factors - level of 24 hour IOP peak and MOPP troughs by the model.

Results: : The rhythmic nature of the 24-hour IOP of newly diagnosed NTG eyes was the third-order polynomial model [Y(mmHg)=-0.002t3+0.066t2-0.535t+17.024] with nocturnal acrophase (time of the highest value). Conversely, Both 24-hour MAP and MOPP exhibited nocturnal nadir (time of the lowest value) with third-order polynomial models[Y(mmHg)=0.005t3-0.13t2+0.605t+90.969, Y(mmHg)=0.005t3-0.152t2+0.936t+43.623, respectively]. The differences between the predicted values from the mathematical models and the measured mean IOP, MAP, and MOPP values were minimal at all measured clock hours (IOP difference range: 0.3 to 2.4 mm Hg). Multiple regression analysis showed that the level of 24-hour peak IOP was best predicted with diurnal peak IOP (R2 = 0.33, p=0.003) while that of 24-hour MOPP trough with diurnal peak MOPP (R2 = 0.36, P<0.001).

Conclusions: : Mean 24-hour habitual rhythm of IOP, MAP, and MOPP can be estimated in untreated NTG patients and values at different clock hours can be predicted with nonlinear mathematical models.

Keywords: intraocular pressure 
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