Real-World Analysis of the Aging Effects on Visual Field Reliability Indices in Central 10-2 Tests
Abstract
:1. Introduction
2. Materials and Methods
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Kang, J.M.; Tanna, A.P. Glaucoma. Med. Clin. North Am. 2021, 105, 493–510. [Google Scholar] [CrossRef] [PubMed]
- Caprioli, J. The importance of rates in glaucoma. Am. J. Ophthalmol. 2008, 145, 191–192. [Google Scholar] [CrossRef] [PubMed]
- Artes, P.H.; Iwase, A.; Ohno, Y.; Kitazawa, Y.; Chauhan, B.C. Properties of perimetric threshold estimates from Full Threshold, SITA Standard, and SITA Fast strategies. Investig. Ophthalmol. Vis. Sci. 2002, 43, 2654–2659. [Google Scholar]
- Russell, R.A.; Crabb, D.P.; Malik, R.; Garway-Heath, D.F. The relationship between variability and sensitivity in large-scale longitudinal visual field data. Investig. Ophthalmol. Vis. Sci. 2012, 53, 5985–5990. [Google Scholar] [CrossRef]
- Gardiner, S.K. Differences in the Relation Between Perimetric Sensitivity and Variability Between Locations Across the Visual Field. Investig. Ophthalmol. Vis. Sci. 2018, 59, 3667–3674. [Google Scholar] [CrossRef]
- Heijl, A.; Lindgren, A.; Lindgren, G. Test-retest variability in glaucomatous visual fields. Am. J. Ophthalmol. 1989, 108, 130–135. [Google Scholar] [CrossRef]
- Henson, D.B.; Chaudry, S.; Artes, P.H.; Faragher, E.B.; Ansons, A. Response variability in the visual field: Comparison of optic neuritis, glaucoma, ocular hypertension, and normal eyes. Investig. Ophthalmol. Vis. Sci. 2000, 41, 417–421. [Google Scholar]
- Spry, P.G.; Johnson, C.A. Identification of progressive glaucomatous visual field loss. Surv. Ophthalmol. 2002, 47, 158–173. [Google Scholar] [CrossRef]
- Demirel, S.; Vingrys, A.J. Eye Movements During Perimetry and the Effect that Fixational Instability Has on Perimetric Outcomes. J. Glaucoma. 1994, 3, 28–35. [Google Scholar] [CrossRef]
- Hirasawa, K.; Kobayashi, K.; Shibamoto, A.; Tobari, H.; Fukuda, Y.; Shoji, N. Variability in monocular and binocular fixation during standard automated perimetry. PLoS ONE. 2018, 13, e0207517. [Google Scholar] [CrossRef]
- Matsuura, M.; Hirasawa, K.; Murata, H.; Asaoka, R. The Relationship Between Visual Acuity and the Reproducibility of Visual Field Measurements in Glaucoma Patients. Investig. Ophthalmol. Vis. Sci. 2015, 56, 5630–5635. [Google Scholar] [CrossRef] [PubMed]
- Gracitelli, C.P.B.; Zangwill, L.M.; Diniz-Filho, A.; Abe, R.Y.; Girkin, C.A.; Weinreb, R.N.; Liebmann, J.M.; Medeiros, F.A. Detection of Glaucoma Progression in Individuals of African Descent Compared With Those of European Descent. JAMA Ophthalmol. 2018, 136, 329–335. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Diniz-Filho, A.; Delano-Wood, L.; Daga, F.B.; Cronemberger, S.; Medeiros, F.A. Association Between Neurocognitive Decline and Visual Field Variability in Glaucoma. JAMA Ophthalmol. 2017, 135, 734–739. [Google Scholar] [CrossRef] [PubMed]
- Jaffe, G.J.; Alvarado, J.A.; Juster, R.P. Age-related changes of the normal visual field. Arch. Ophthalmol. 1986, 104, 1021–1025. [Google Scholar] [CrossRef]
- Drance, S.M.; Berry, V.; Hughes, A. Studies on the effects of age on the central and peripheral isopters of the visual field in normal subjects. Am. J. Ophthalmol. 1967, 63, 1667–1672. [Google Scholar] [CrossRef]
- Newkirk, M.R.; Gardiner, S.K.; Demirel, S.; Johnson, C.A. Assessment of false positives with the Humphrey Field Analyzer II perimeter with the SITA Algorithm. Investig. Ophthalmol. Vis. Sci. 2006, 47, 4632–4637. [Google Scholar] [CrossRef]
- Junoy Montolio, F.G.; Wesselink, C.; Gordijn, M.; Jansonius, N.M. Factors that influence standard automated perimetry test results in glaucoma: Test reliability, technician experience, time of day, and season. Investig. Ophthalmol. Vis. Sci. 2012, 53, 7010–7017. [Google Scholar] [CrossRef]
- Bengtsson, B. Reliability of computerized perimetric threshold tests as assessed by reliability indices and threshold reproducibility in patients with suspect and manifest glaucoma. Acta Ophthalmol. Scand. 2000, 78, 519–522. [Google Scholar] [CrossRef]
- Bengtsson, B.; Heijl, A. False-negative responses in glaucoma perimetry: Indicators of patient performance or test reliability? Investig. Ophthalmol. Vis. Sci. 2000, 41, 2201–2204. [Google Scholar] [CrossRef]
- Shirakami, T.; Omura, T.; Fukuda, H.; Asaoka, R.; Tanito, M. Real-World Analysis of the Aging Effects on Visual Field Reliability Indices in Humans. J Clin Med. 2021, 10, 5775. [Google Scholar] [CrossRef]
- Asaoka, R.; Fujino, Y.; Aoki, S.; Matsuura, M.; Murata, H. Estimating the Reliability of Glaucomatous Visual Field for the Accurate Assessment of Progression Using the Gaze-Tracking and Reliability Indices. Ophthalmol. Glaucoma. 2019, 2, 111–119. [Google Scholar] [CrossRef] [PubMed]
- Heijl, A.; Patella, V.M.; Chong, L.X.; Iwase, A.; Leung, C.K.; Tuulonen, A.; Lee, G.C.; Callan, T.; Bengtsson, B. A New SITA Perimetric Threshold Testing Algorithm: Construction and a Multicenter Clinical Study. Am. J. Ophthalmol. 2019, 198, 154–165. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Heijl, A.; Lindgren, G.; Olsson, J. Normal variability of static perimetric threshold values across the central visual field. Arch. Ophthalmol. 1987, 105, 1544–1549. [Google Scholar] [CrossRef] [PubMed]
- Curcio, C.A.; Millican, C.L.; Allen, K.A.; Kalina, R.E. Aging of the human photoreceptor mosaic: Evidence for selective vulnerability of rods in central retina. Investig. Ophthalmol. Vis. Sci. 1993, 34, 3278–3296. [Google Scholar]
- Gao, H.; Hollyfield, J.G. Aging of the human retina. Differential loss of neurons and retinal pigment epithelial cells. Investig. Ophthalmol. Vis. Sci. 1992, 33, 1–17. [Google Scholar]
- Nag, T.C.; Gorla, S.; Kumari, C.; Roy, T.S. Aging of the human choriocapillaris: Evidence that early pericyte damage can trigger endothelial changes. Exp. Eye Res. 2021, 212, 108771. [Google Scholar] [CrossRef]
- Jackson, G.R.; Owsley, C.; Cordle, E.P.; Finley, C.D. Aging and scotopic sensitivity. Vis. Res. 1998, 38, 3655–3662. [Google Scholar] [CrossRef]
- Adams, C.W.; Bullimore, M.A.; Wall, M.; Fingeret, M.; Johnson, C.A. Normal aging effects for frequency doubling technology perimetry. Optom. Vis. Sci. 1999, 76, 582–587. [Google Scholar] [CrossRef]
- Beck, R.W.; Bergstrom, T.J.; Lichter, P.R. A clinical comparison of visual field testing with a new automated perimeter, the Humphrey Field Analyzer, and the Goldmann perimeter. Ophthalmology 1985, 92, 77–82. [Google Scholar] [CrossRef]
- Hudson, C.; Wild, J.M.; O’Neill, E.C. Fatigue effects during a single session of automated static threshold perimetry. Investig. Ophthalmol. Vis. Sci. 1994, 35, 268–280. [Google Scholar]
- Searle, A.E.; Wild, J.M.; Shaw, D.E.; O’Neill, E.C. Time-related variation in normal automated static perimetry. Ophthalmology 1991, 98, 701–707. [Google Scholar] [CrossRef]
- Kelly, S.R.; Bryan, S.R.; Crabb, D.P. Does eye examination order for standard automated perimetry matter? Acta Ophthalmol. 2019, 97, e833–e838. [Google Scholar] [CrossRef] [PubMed]
Parameter | Mean ± SD | Range |
---|---|---|
Age (years) | 66.6 ± 14.2 | 10.0–95.0 |
MD (dB) | −15.9 ± 10.0 | −36.3–2.8 |
PSD (dB) | 9.0 ± 4.6 | 0.8–17.4 |
FL (%) | 5.0 ± 8.8 | 0.0–95.2 |
FN (%) | 5.9 ± 9.0 | 0.0–81.0 |
FP (%) | 1.4 ± 3.1 | 0.0–62.0 |
ρ * p * | Age (Years) | MD (dB) | PSD (dB) | FL (%) | FN (%) | FP (%) |
---|---|---|---|---|---|---|
Age (years) | −0.18 | 0.07 | −0.01 | 0.21 | −0.02 | |
MD (dB) | <0.0001 * | −0.32 | 0.09 | −0.26 | 0.12 | |
PSD (dB) | <0.0001 * | <0.0001 * | −0.08 | 0.09 | −0.02 | |
FL (%) | 0.6158 | <0.0001 * | <0.0001 * | 0.10 | 0.30 | |
FN (%) | <0.0001 * | <0.0001 * | <0.0001 * | <0.0001 * | 0.10 | |
FP (%) | 0.1065 | <0.0001 * | 0.1803 | <0.0001 * | <0.0001 * |
Age Group (Years) | n | Mean (%) | SD | Lower 95%CI | Upper 95%CI | p-Value | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
vs. 20–29 | vs. 30–39 | vs. 40–49 | vs. 50–59 | vs. 60–69 | vs. 70–79 | vs. 80–89 | vs. 90–99 | ||||||
10–19 | 67 | 13.21 | 1.08 | 11.10 | 15.32 | <0.0001 * | <0.0001 * | <0.0001 * | <0.0001 * | <0.0001 * | <0.0001 * | <0.0001 * | <0.0001 * |
20–29 | 88 | 6.14 | 0.94 | 4.30 | 7.98 | - | 0.9782 | 0.4866 | 0.8989 | 0.9968 | 0.9813 | 0.6565 | 0.9886 |
30–39 | 217 | 4.95 | 0.60 | 3.78 | 6.12 | - | - | 0.9315 | 1.0000 | 0.9992 | 1.0000 | 0.9919 | 1.0000 |
40–49 | 383 | 3.98 | 0.45 | 3.09 | 4.86 | - | - | - | 0.8678 | 0.1131 | 0.2906 | 0.9989 | 0.9992 |
50–59 | 904 | 4.77 | 0.29 | 4.19 | 5.34 | - | - | - | - | 0.7632 | 0.9781 | 0.9807 | 1.0000 |
60–69 | 1766 | 5.37 | 0.21 | 4.96 | 5.78 | - | - | - | - | - | 0.9965 | 0.0782 | 0.9998 |
70–79 | 2185 | 5.14 | 0.19 | 4.77 | 5.51 | - | - | - | - | - | - | 0.2985 | 1.0000 |
80–89 | 998 | 4.34 | 0.28 | 3.80 | 4.89 | - | - | - | - | - | - | - | 1.0000 |
90–99 | 66 | 4.75 | 1.08 | 2.63 | 6.88 | - | - | - | - | - | - | - | - |
Age Group (Years) | n | Mean (%) | SD | Lower 95%CI | Upper 95%CI | p-Value | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
vs. 20–29 | vs. 30–39 | vs. 40–49 | vs. 50–59 | vs. 60–69 | vs. 70–79 | vs. 80–89 | vs. 90–99 | ||||||
10–19 | 63 | 5.30 | 8.54 | 3.15 | 7.45 | 1.0000 | 0.9990 | 0.9954 | 0.9763 | 0.9980 | 0.9918 | 0.0014 * | 0.0066 * |
20–29 | 86 | 5.74 | 12.45 | 3.07 | 8.41 | - | 0.9974 | 0.9889 | 0.9488 | 0.9942 | 0.9895 | 0.0004 * | 0.0040 * |
30–39 | 213 | 4.30 | 7.99 | 3.22 | 5.38 | - | - | 1.0000 | 0.9998 | 1.0000 | 0.0770 | <0.0001 * | <0.0001 * |
40–49 | 385 | 4.97 | 9.49 | 4.02 | 5.92 | - | - | - | 1.0000 | 1.0000 | 0.0013 * | <0.0001 * | <0.0001 * |
50–59 | 820 | 4.12 | 7.15 | 3.63 | 4.61 | - | - | - | - | 0.9796 | <0.0001 * | <0.0001 * | <0.0001 * |
60–69 | 1695 | 4.53 | 7.85 | 4.16 | 4.90 | - | - | - | - | - | <0.0001 * | <0.0001 * | <0.0001 * |
70–79 | 2051 | 6.58 | 9.88 | 6.15 | 7.01 | - | - | - | - | - | - | <0.0001 * | 0.0010 * |
80–89 | 900 | 10.00 | 11.47 | 9.25 | 10.75 | - | - | - | - | - | - | - | 0.9815 |
90–99 | 58 | 11.24 | 13.23 | 7.76 | 14.72 | - | - | - | - | - | - | - | - |
Age Group (Years) | n | Mean (%) | SD | Lower 95%CI | Upper 95%CI | p-Value | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
vs. 20–29 | vs. 30–39 | vs. 40–49 | vs. 50–59 | vs. 60–69 | vs. 70–79 | vs. 80–89 | vs. 90–99 | ||||||
10–19 | 67 | 6.45 | 11.97 | 3.53 | 9.37 | <0.0001 * | <0.0001 * | <0.0001 * | <0.0001 * | <0.0001 * | <0.0001 * | <0.0001 * | <0.0001 * |
20–29 | 98 | 2.57 | 7.08 | 1.15 | 3.99 | - | 1.0000 | 0.0548 | 0.0090 * | 0.0385 * | 0.0220 * | 0.0026 * | 0.0465 * |
30–39 | 225 | 2.24 | 3.97 | 1.71 | 2.76 | - | - | 0.0057 * | <0.0001 * | 0.0008 * | 0.0002 * | <0.0001 * | 0.0269 * |
40–49 | 399 | 1.59 | 4.11 | 1.19 | 1.99 | - | - | - | 0.9990 | 1.0000 | 1.0000 | 0.9449 | 0.9749 |
50–59 | 912 | 1.22 | 2.59 | 1.06 | 1.39 | - | - | - | - | 0.9072 | 0.9876 | 0.9983 | 0.9963 |
60–69 | 1805 | 1.40 | 3.03 | 1.26 | 1.54 | - | - | - | - | - | 0.9998 | 0.3584 | 0.9363 |
70–79 | 2217 | 1.33 | 2.62 | 1.22 | 1.44 | - | - | - | - | - | - | 0.6134 | 0.9666 |
80–89 | 1003 | 1.15 | 2.42 | 1.00 | 1.30 | - | - | - | - | - | - | - | 0.9998 |
90–99 | 66 | 0.91 | 1.97 | 0.43 | 1.39 | - | - | - | - | - | - | - | - |
Parameters | FLs (%) | FNs (%) | FPs (%) | ||||||
---|---|---|---|---|---|---|---|---|---|
R | 95% CI | p-Value | R | 95% CI | p-Value | R | 95% CI | p-Value | |
Age (/years) | 0.00 | −0.03–0.04 | 0.9014 | 0.13 | 0.09–0.16 | <0.0001 ** | 0.00 | −0.01–0.01 | 0.9267 |
MD (/dB) | −0.03 | −0.06–0.00 | 0.0503 | −0.32 | −0.36–−0.28 | <0.0001 ** | 0.03 | 0.02–0.04 | <0.0001 ** |
PSD (/dB) | −0.18 | −0.24–−0.12 | <0.0001 ** | −0.14 | −0.21–−0.06 | 0.0004 ** | 0.02 | 0.00–0.03 | 0.0401 * |
Parameters | Mean ± SD (95% CI Range) | p-Value | |
---|---|---|---|
10-2 (n = 6302) | 30-2 (n = 32503) | ||
Age (years) | 68.8 ± 10.9 (68.5–69.1) | 68.4 ± 11.2 (68.3–68.6) | 0.0234 * |
MD (dB) | −16.1 ± 9.8 (−16.4–−15.9) | −7.3 ± 8.3 (−7.3–−7.2) | <0.0001 ** |
PSD (dB) | 9.1 ± 4.6 (9.0–9.2) | 6.6 ± 4.7 (6.6–6.7) | <0.0001 ** |
FL (%) | 5.0 ± 8.6 (4.7–5.2) | 8.1 ± 10.8 (8.0–8.2) | <0.0001 ** |
FN (%) | 6.0 ± 9.0 (5.7–6.2) | 4.9 ± 7.1 (4.8–5.0) | 0.9364 |
FP (%) | 1.3 ± 2.7 (1.2–1.4) | 2.4 ± 4.0 (2.4–2.5) | <0.0001 ** |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Shirakami, T.; Omura, T.; Fukuda, H.; Asaoka, R.; Tanito, M. Real-World Analysis of the Aging Effects on Visual Field Reliability Indices in Central 10-2 Tests. J. Pers. Med. 2022, 12, 1600. https://doi.org/10.3390/jpm12101600
Shirakami T, Omura T, Fukuda H, Asaoka R, Tanito M. Real-World Analysis of the Aging Effects on Visual Field Reliability Indices in Central 10-2 Tests. Journal of Personalized Medicine. 2022; 12(10):1600. https://doi.org/10.3390/jpm12101600
Chicago/Turabian StyleShirakami, Tomoki, Tetsuro Omura, Hiroki Fukuda, Ryo Asaoka, and Masaki Tanito. 2022. "Real-World Analysis of the Aging Effects on Visual Field Reliability Indices in Central 10-2 Tests" Journal of Personalized Medicine 12, no. 10: 1600. https://doi.org/10.3390/jpm12101600
APA StyleShirakami, T., Omura, T., Fukuda, H., Asaoka, R., & Tanito, M. (2022). Real-World Analysis of the Aging Effects on Visual Field Reliability Indices in Central 10-2 Tests. Journal of Personalized Medicine, 12(10), 1600. https://doi.org/10.3390/jpm12101600