Diurnal variation in intraocular pressure of normal-tension glaucoma eyes

Ophthalmology. 1993 May;100(5):643-50. doi: 10.1016/s0161-6420(93)31594-0.

Abstract

Background: The nature of intraocular pressure (IOP) in normal-tension glaucoma (NTG) has not been studied in detail, although the information on the IOP is indispensable for diagnosis and treatment of NTG.

Methods: After at least six IOP measurements at daytime clinic, diurnal IOP was measured at 10:00 AM, 12:00 noon, 2:00, 4:00, 6:00, 8:00, 10:00 PM, 12:00 midnight, and at 3:00, 6:00, 8:00, and 10:00 AM by 1-day hospitalization in 118 NTG suspects. Four subjects with peak IOPs exceeding 21 mmHg were diagnosed as primary open-angle glaucoma (POAG) whose eyes all had mean clinic IOPs above 16 mmHg. The remaining 114 patients were diagnosed as having NTG, and their right eye data were used for analysis.

Results: The rhythmic nature of the diurnal IOP of NTG was analyzed by fitting the data to a cosine curve. In 54.4% of the eyes, the correlation between the measured IOP and the values predicted from the cosine curve was significant (r > 0.60, P < 0.05), and the equation, diurnal IOP = 13.9 + 1.7 cos 2 pi (t/24-0.40) mmHg, which was similar to that reported in normals, was obtained. Multiple regression analysis showed that the mean diurnal IOP was best predicted with the mean of the six clinic IOPs and systolic blood pressure (R2 = 0.67), and the peak diurnal IOP with the mean of six clinic IOPs (R2 = 0.50). The estimate fell within +/- 1 and +/- 2 mmHg of the actual value in 83% and 96% of the left eyes for the former and in 69% and 93% for the latter, respectively. No eyes with peak diurnal IOP exceeding 21 mmHg were overlooked with the cutoff IOP of 16 mmHg.

Conclusion: The mean and peak diurnal IOP could be predicted with the mean of clinic IOPs.

MeSH terms

  • Blood Pressure
  • Circadian Rhythm / physiology*
  • Female
  • Glaucoma, Open-Angle / diagnosis
  • Glaucoma, Open-Angle / physiopathology*
  • Humans
  • Intraocular Pressure / physiology*
  • Male
  • Middle Aged
  • Regression Analysis
  • Time Factors