BASIC INVESTIGATION
Influence of Age and Gender on Corneal Biomechanical Properties in a Healthy Italian Population Ernesto Strobbe, MD, Mauro Cellini, MD, Umberto Barbaresi, MD, and Emilio C. Campos, MD
Purpose: The aim of this study was to assess corneal hysteresis (CH) and corneal resistance factor (CRF) in healthy subjects, to evaluate the relationship with age, and to investigate possible associations with other ocular factors.
Methods: Four hundred Italian subjects (male-to-female ratio, 168:232; mean age, 58.8 6 17.2 years) were included and divided into 5 subgroups based on age. CH, CRF, and central corneal thickness (CCT) were measured by using the Ocular Response Analyzer and the integrated handheld pachymeter, and their relationship with gender, age, and ocular factors was evaluated. Results: The mean CH, CRF, and CCT values were 10 6 1.6 mm Hg,
10.5 6 1.7 mm Hg, and 532.2 mm, respectively. Women had a lower mean CH (9.9 vs. 10.2 mm Hg; P = 0.04) and CRF (10.3 vs. 10.8 mm Hg; P = 0.03) than did men. The youngest subjects had the highest CH (11.2 6 1.5 mm Hg), whereas the oldest patients had the lowest CH values (9 6 1.1 mm Hg). No significant differences in CRF were observed between age groups. CH and CRF showed a positive correlation (r = 0.58; P , 0.001), and both had a positive association with CCT (r = 0.27; P , 0.001 and r = 0.57; P , 0.001, respectively). The strongest correlations were observed between Goldmann-correlated intraocular pressure (IOP) and corneal-compensated IOP (r = 0.68; P , 0.001) and between Goldmann-correlated IOP and Goldmann applanation tonometry (r = 0.88; P , 0.001).
Conclusions: Gender and advancing age may influence corneal biomechanical properties. In our population, CH decreased with aging, and men demonstrated a higher CH and CRF than women did. Further, CH, CRF, and CCT were significantly related. Key Words: corneal hysteresis, corneal resistance factor, ocular response analyzer, corneal biomechanics (Cornea 2014;33:968–972)
Received for publication March 24, 2014; revision received May 13, 2014; accepted May 15, 2014. Published online ahead of print July 9, 2014. From the Ophthalmology Unit, Department of Experimental, Diagnostic, and Specialty Medicine, Alma Mater Studiorum, University of Bologna, Bologna, Italy. E. Strobbe is responsible for the conception, design, analysis, and interpretation of data, drafting the article, and final approval of the manuscript. M. Cellini, U. Barbaresi, E. C. Campos are responsible for the conception, acquisition of data, review, and final approval of the paper. The authors have no funding or conflicts of interest to disclose. Reprints: Ernesto Strobbe, MD, Department of Experimental, Diagnostic, and Specialty Medicine, University of Bologna, Via Massarenti 9, 40138 Bologna, Italy (e-mail: [email protected]). Copyright © 2014 by Lippincott Williams & Wilkins
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T
he biomechanical properties of the cornea may provide important biological information that is useful in various fields of ophthalmology, including in intraocular pressure (IOP) measurement,1 contact lens wear,2 wound healing,3 corneal pathologies,4 and refractive surgery procedures,5 and may aid in the diagnosis and management of ocular diseases. Corneal properties have traditionally been studied by in vitro techniques that have experimentally evaluated factors such as viscoelasticity and hydration. Recently, corneal hysteresis (CH) and corneal resistance factor (CRF) have become subjects of increasing interest because they provide more comprehensive information about corneal biomechanics, may have diagnostic value, and may be easily and rapidly measured in vivo in a clinical setting by using the Ocular Response Analyzer [(ORA); Reichert, Inc, Depew, NY]. CH involves the measurement of viscous properties; indeed, it is thought to primarily reflect the viscous damping in the cornea, which is the ability of this tissue to absorb and dissipate energy, whereas CRF is an empirically derived parameter that is representative of corneal elastic properties, which is thought to reflect the overall resistance of this tissue.6 These parameters are strongly influenced by the corneal collagen composition and by the structure and properties of corneal layers, and by the thickness, curvature, and hydration of the corneal tissue. Increasing age may alter and modify some of these parameters and thus may indirectly influence corneal biomechanics.7 Researchers have identified collagen fibrils to be the main load-carrying components of the stroma, and found a clear link between the content and distribution of these fibrils and the biomechanical behavior of the cornea.8 Given the promising nature of the possibility of measuring corneal biomechanics in vivo, many studies covering a wide range of topics, such as glaucoma,9 keratoconus,4 and refractive surgery,5 have been performed and published using the ORA. However, to the best of our knowledge, there are few reports in the literature that evaluate the effect of aging on corneal biomechanical properties in a healthy population, and these data are drawn from Japanese, Chinese, and Brazilian subjects.7,10,11 The purpose of this study is to assess the biomechanical properties of the cornea in healthy Italian patients by using the ORA and to evaluate the relationship with age to aid in understanding the behavior of CH and CRF in vivo and to investigate the possible associations with other ocular factors.
METHODS This was a cross-sectional noninterventional study in which subjects presenting for a complete eye examination at Cornea Volume 33, Number 9, September 2014
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the Ophthalmology Unit of the S’Orsola-Malpighi Hospital between October 2011 and July 2013 were invited to participate. After a comprehensive explanation of the purpose of the study and of the noninvasive procedures was given, patients signed informed consent forms before inclusion according to the tenets of the Declaration of Helsinki. Approval was obtained from the Institutional Review Board and Ethical Committee of University of Bologna. A total of 400 healthy white Italian volunteers [168 males and 232 females; mean age 58.8 6 17.2 years (range: 21–88 years)] were consecutively recruited and were divided into 5 subgroups based on age: younger than 46 years (group A); between 46 and 55 years (group B); between 56 and 65 years (group C); between 66 and 75 years (group D); and older than 76 years (group E). All participants were above 18 years of age, were phakic, had no history of ocular injury or surgery or disease, were not contact lens wearers, and were able to cooperate so as to obtain reliable ORA readings. They were not using any topical ocular medication, and had no history of systemic disease affecting the eye. Subjects with a refractive error .6 diopters (D) for myopia, .4 D for hyperopia, or .1.5 D for astigmatism were excluded from the study. Each participant underwent an ophthalmologic examination, including visual acuity, Goldmann applanation tonometry (GAT), biomicroscopy of the anterior and posterior segment, assessment of central corneal thickness (CCT), and measurements of the biomechanical properties of the cornea, by using the ORA (Reichert, Inc). Details of the ORA properties and functions have been described elsewhere.6 Repeated measurements were taken to ensure that those with artifacts or of poor quality were eliminated, until 4 reliable measurements for each eye of every patient were obtained, and the average was used for statistical evaluation. A reliable ORA measurement was defined as (1) clean, approximately symmetrical applanation signal peaks; (2) fairly smooth signal at the descending curve, trough, and ascending curve; (3) flat baseline signal; and (4) waveform score .7. ORA measurements were performed before pachymetry to eliminate any possible effect of applanation on the properties of the cornea. Four parameters obtained by the measurements, including CH, CRF, Goldmann-correlated IOP (IOPg), and corneal-compensated IOP (IOPcc), were recorded. Ultrasound pachymetry (20 MHz) was performed with the ORA-integrated handheld pachymeter, after the application of
topical anesthesia with 0.4% oxybuprocaine hydrochloride. In all subjects, only 1 eye was randomly selected for statistical analysis. The ophthalmological examinations were carried out during hospital consulting hours, between 11 AM and 2 PM to eliminate possible confounders that could affect the results of the CCT, ORA, and IOP measurements, as demonstrated by Laiquzzaman et al.12
STATISTICAL ANALYSIS
All data are presented as mean 6 SD. Statistical analysis was performed using the Mann–Whitney U test and the Kruskall–Wallis test to compare the values of ocular variables between males and females and among the 5 study groups, respectively. To analyze the strength of the correlation between variables, the Spearman correlation test was calculated. Further, linear regression analysis, adjusting for age and gender, was used to assess the effect of each variable on CH and CRF. A P value ,0.05 was considered to be statistically significant.
RESULTS The 5 age groups comprised 400 eyes of 400 patients; 42% were men and 58% were women, and genders were not equally distributed within the 5 groups. The means of age, spherical equivalent, CCT, IOP, visual acuity, and corneal biomechanical parameters of the study patients globally and divided by age groups are summarized in Table 1. Visual acuity decreased from the first 3 groups to the last 2 groups because there was a higher proportion of cataract. In all eyes, the mean CH value was 10 6 1.6 mm Hg, the mean CRF was 10.5 6 1.7 mm Hg, and the mean CCT was 532.2 6 35.1 mm, whereas the mean GAT, IOPg, and IOPcc were 15.9 6 2.8 mm Hg, 16.2 6 2.9 mm Hg, and 17.1 6 3.5 mm Hg, respectively. Notably, we found that the youngest subjects had the highest CH (11.2 6 1.5 mm Hg), whereas the lowest CH values were found within the oldest patients (9 6 1.1 mm Hg); in detail, the differences were statistically significant between groups A and C (P , 0.01), groups A and D (P , 0.001), and groups A and E (P , 0.001), and between groups B and E (P , 0.001) (Table 2). However, CRF values did not show any significant differences among the age groups (P . 0.05).
TABLE 1. Demographic and Ocular Features and Corneal Biomechanical Properties in the Study Patients All Age, yrs Males/females Visual acuity (decimals) Refractive error (spherical equivalent) GAT, mm Hg CCT, mm CH, mm Hg CRF, mm Hg IOPg, mm Hg IOPcc, mm Hg
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,46 yrs (A)
46–55 yrs (B)
56–65 yrs (C)
66–75 yrs (D)
.75 yrs (E)
n = 400
n = 80
n = 80
n = 80
n = 80
n = 80
58.8 6 17.2 168/232 0.9 6 0.1 20.4 6 1.9 15.9 6 2.8 532.2 6 35.1 10 6 1.6 10.5 6 1.7 16.2 6 2.9 17.1 6 3.5
32.9 6 9.1 28/52 1.0 6 0.0 22.0 6 2.2 14.4 6 2.4 522.8 6 38.8 11.2 6 1.5 10.4 6 1.8 14.7 6 2.4 14.6 6 2.4
50.4 6 2.8 36/44 1.0 6 0.0 21.2 6 1.6 16 6 2.4 523.5 6 30.4 10.6 6 1.6 10.8 6 1.9 16 6 2.3 16.8 6 3.1
59.4 6 2.9 16/64 1.0 6 0.0 21.1 6 1.3 16.8 6 3.3 550.3 6 26.6 9.9 6 1.1 10.5 6 1.2 17.1 6 3.4 18.3 6 3.9
71.3 6 2.7 48/32 0.9 6 0.1 20.3 6 0.9 16.3 6 2.7 520.6 6 26.3 9.6 6 1.6 10.3 6 2 16.8 6 2.9 18.1 6 3.7
80.1 6 4.2 40/40 0.7 6 0.1 20.6 6 0.8 15.7 6 2.6 543.8 6 41 9 6 1.1 10.4 6 1.6 16.2 6 2.8 17.8 6 3.1
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TABLE 2. Comparison of Ocular Parameters Among the 5 Age Groups of the Study Population CH CCT
,46 yrs (A)
56–65 yrs (C) P
66–75 yrs (D) P
.75 yrs (E) P
* *
,0.01 ,0.01 * ,0.01
,0.001 * * * * ,0.01
,0.001 * ,0.001 * * * * *
46–55 yrs (B) P
56–65 yrs (C) P
66–75 yrs (D) P
.75 yrs (E) P
* * ,0.05
,0.01 ,0.05 ,0.001 * * *
,0.05 ,0.05 ,0.001 * * * * * *
* * ,0.001 * * * * * * * * *
46–55 yrs (B)
,46 yrs (A) 46–55 yrs (B) 56–65 yrs (C) 66–75 yrs (D)
GAT IOPg ,46 yrs (A)
IOPcc ,46 yrs (A)
46–55 yrs (B)
56–65 yrs (C)
66–75 yrs (D)
*Not statistically significant (P . 0.05).
Regarding GAT and IOPg values, the differences were statistically significant between groups A and C (P , 0.01 and P , 0.05, respectively), and between groups A and D (P , 0.05 for both the variables), whereas IOPcc values were significantly different between group A and the other 4 groups (A vs. B, P , 0.05, whereas in the remaining comparisons, P , 0.001) (Table 2). In a subgroup analysis, men demonstrated both a higher mean CH and mean CRF compared with women (10.2 vs. 9.9 mm Hg; P = 0.04 and 10.8 vs. 10.3 mm Hg; P = 0.03, respectively), whereas the mean CCT values were similar (Table 3). A negative correlation was noted between age and CH (r = 20.45; P , 0.001) and between CH and IOPcc
TABLE 3. Demographic and Ocular Features in Males and Females No Age, yrs Refractive error (spherical equivalent) GAT, mm Hg CCT, mm CH, mm Hg CRF, mm Hg IOPg, mm Hg IOPcc, mm Hg
970
Males
Females
P
168 60.4 6 18 20.1 6 1.4
232 57.7 6 16.7 20.6 6 2.2
0.29 0.18
6 6 6 6 6 6
0.50 0.74 0.04 0.03 0.51 0.08
15.7 532.3 10.2 10.8 16 16.8
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2.7 32.9 1.6 1.9 2.9 3.9
16 532.2 9.9 10.3 16.3 17.4
2.9 36.8 1.6 1.6 2.9 3.2
(r = 20.40; P , 0.001), whereas a positive association was found between CH and CRF (r = 0.58; P , 0.001), CRF and GAT (r = 0.51; P , 0.001), and CRF and IOPg (r = 0.43; P , 0.001); moreover, CCT was positively related with all biochemical parameters, GAT, age, and refractive error, and showed the strongest linear relationship with CRF (r = 0.57; P , 0.001). Among all the variables, the strongest correlations were observed between IOPg and IOPcc (r = 0.68; P , 0.001), and between IOPg and GAT (r = 0.88; P , 0.001) (Table 4). Finally, the relationships between corneal biomechanical properties with ocular variables were assessed through age- and gender-adjusted linear regression analyses (Table 5). The association between CH and GAT was not significant (P = 0.877), whereas CRF increased by 0.31 mm Hg for every millimeter of mercury increase in GAT (P , 0.001). Regarding the relationships between CH, CRF, and CCT, we found that CH and CRF increased by 0.01 and 0.03 mm Hg, respectively, for every 1-mm increase in CCT (P , 0.001 for both the variables). Further, for every unit increase in refractive error (spherical equivalent), CRF increased by 0.2 mm Hg (P = 0.002) (Table 5).
DISCUSSION In this study, we have demonstrated that both increasing age and gender have an important role on corneal biomechanical properties in a healthy Italian population. Ó 2014 Lippincott Williams & Wilkins
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TABLE 4. Spearman Correlation Among the Ocular Parameters and Between the Ocular Parameters and Age in the Study Population CRF CH
r = 0.58 P , 0.001
CRF
CCT r= P, r= P,
0.27 0.001 0.57 0.001
CCT
GAT
IOPg
IOPcc
Age
Refractive Error
r = 20.03 P = 0.69 r = 0.51 P , 0.001 r = 0.27 P , 0.001
r = 20.14 P = 0.046 r = 0.43 P , 0.001 r = 0.22 P , 0.01 r = 0.88 P , 0.001
r = 20.40 P , 0.001 r = 0.19 P , 0.01 r = 0.24 P , 0.001 r = 0.57 P , 0.001 r = 0.68 P , 0.001
r = 20.45 P , 0.001 r = 20.006 P = 0.93 r = 0.17 P , 0.05 r = 0.18 P , 0.01 r = 0.21 P , 0.01 r = 0.32 P , 0.001
r = 20.06 P = 0.38 r = 0.17 P , 0.05 r = 0.15 P , 0.05 r = 0.09 P , 0.22 r = 0.58 P = 0.09 r = 0.58 P , 0.05
GAT IOPg IOPcc
Both mean CH and CRF values in our study sample were very similar to those reported in studies involving healthy Chinese,10 Japanese,13 and Brazilian subjects.11 However, a recent study provided evidence that black people have lower CH and CRF values than white subjects had.14 We also observed that, in females, both CH and CRF values were significantly lower than those of males; in detail, females showed a 3% (P = 0.04) and 4.6% (P = 0.03) decrease, respectively, compared with men, but this finding is not in agreement with previous reports.10,11 Therefore, these contrasting data may be because corneal biomechanics may have different behavior between males and females in various ethnic groups. Currently, however, there are no concurring opinions about the existence of a strong relationship between corneal biomechanical parameters and gender.15 Further studies and investigations are still required to better understand the role of gender on corneal biomechanics and the influence of race on both CH and CRF values in males and females. Notably, CH had a decreasing trend with age. Indeed, in our population, aged between 21 and 88 years, CH showed the highest mean values in the youngest group (11.2 mm Hg) and the lowest mean values in the oldest group (9 mm Hg); in detail, subjects of the 46- to 55-year-old group did not show a statistically significant reduction compared with subjects of the youngest group, whereas patients of the 3 remaining age groups showed a decrease of 11.6% (P , 0.01), 14.3% (P , 0.001), and 19.6% (P , 0.001), respectively. Finally, a linear
regression analyses on CH provided evidence that CH decreased by 0.04 mm Hg for every year of age. CRF however did not have any relationship with age. Our results are confirmed by Ortiz et al,16 who observed a statistically significant difference in CH between the youngest group (#14 years old) and the oldest group (.60 years old), whereas no relationship between CRF and age was reported. Narayanaswamy et al,10 however, found that CH and CRF decreased with increasing age; in particular, CH showed the same decreasing trend for every year of age as shown in our study. Previous experimental studies17,18 have demonstrated age-related structural and biochemical changes in the human cornea, with an increase in collagen-fibril diameter and interfibrillar crosslinking in the stroma, probably leading to increased tissue rigidity. Further, the increase in the Young modulus of elasticity, which was proposed by Elsheikh et al,18 is in agreement with the decrease of CH with increasing age. Regarding the relationship between CH and CRF, our data revealed a positive significant correlation (r = 0.58; P , 0.001), as also stated by Shah et al,19 confirming the association between the 2 corneal biomechanical properties, although it has been reported that they are not the same measured parameters and that they are not always proportionally related. In 2000, Doughty et al15 determined the normal CCT values in human corneas and found a mean CCT of 535 mm, based on a meta-analysis approach of 600 eyes and concluded that there is no substantial change in CCT with age, and that
TABLE 5. Linear Regression Analyses on CH and CRF CH, mm Hg b (95% CI) Gender (female) Age, yrs Refractive error (spherical equivalent) GAT, mm Hg CCT, mm
20.340 20.041 20.066 20.006 0.012
(20.784 to 0.104) (20.053 to 20.030) (20.181 to 0.049) (20.085 to 0.073) (0.006 to 0.018)
CRF, mm Hg P 0.135 ,0.001 0.259 0.877 ,0.001
b (95% CI) 20.555 0.001 0.196 0.313 0.028
(21.038 to 20.071) (20.013 to 0.014) (0.073 to 0.320) (0.238 to 0.388) (0.022 to 0.033)
P 0.026 0.921 0.002 ,0.001 ,0.001
Adjusted for age and gender. CI, confidence interval.
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the association of race and CCT has not been investigated adequately in the literature and any gender-related determinant of CCT remains poorly defined. This finding seems to be true for whites, although some gender-dependent differences in CCT in nonwhite men and women have been reported.20 In our study sample, we observed a similar mean CCT, no differences between males and females, and a weak but significant positive correlation between increasing age and CCT. This may be explained by the possible age-dependent corneal hydration-control changes.21 According to our data, CCT was positively related to CH (r = 0.27; P , 0.001) and CRF (r = 0.57; P , 0.001), as already reported by previous studies.10,11 In detail, CH and CRF increased by 0.01 and 0.03 mm Hg, respectively, for every 1-mm increase in the CCT. This is because CH is a measure of viscous damping of the cornea, whereas CRF is a better indicator of the overall resistance of the corneal tissue. The strongest correlations were found between IOPg and GAT (r = 0.88; P , 0.001) as also demonstrated by Ayala and Chen,22 and between IOPg and IOPcc (r = 0.68; P , 0.001). Interestingly, IOPcc values were, on average, higher than GAT values and were strongly related to GAT (r = 0.57; P , 0.001), as previously established by Ehrlich et al23 in a study performed on normal and glaucomatous eyes. Based on our findings, IOPg, IOPcc, and GAT showed a statistically significant positive relationship with the age of the participants, as already reported in the Blue Mountains Eye Study performed on a white Australian urban population, which demonstrated an age-related increase of IOP values.24 According to the authors, this trend was probably dependent on systemic factors such as blood pressure and body mass index. Our study, despite patients with high blood pressure and diabetes being excluded, confirmed the existence of a relationship between age and IOP. In our population, CH did not show a significant relationship with GAT and IOPg, although it was negatively related to IOPcc (r = 20.40; P , 0.001), whereas a positive correlation between CRF and GAT (r = 0.51; P , 0.001), CRF and IOPg (r = 0.43; P , 0.001), and CRF and IOPcc (r = 0.19; P , 0.01) was reported. These data suggest that, although CH and CRF are strictly associated parameters, they may be differently influenced by normal range IOP values and are in agreement with previous studies.9,10 This study has some limitations. By including only 400 healthy Italian subjects, we were not able to assess whether these results might be applied to other groups with the same ethnic origin or to evaluate potential differences among patients with various diseases. Another limitation is the cross-sectional design of the study. Third, we had a small proportion of males compared with females and an unequal distribution among the 5 age groups, which probably precludes a detailed comparative analysis. In conclusion, our study provides additional data regarding the influence of aging and gender on corneal biomechanical properties in healthy Italian subjects. CH values demonstrated a decreasing trend with age, and females showed lower CH and CRF than males did. Finally, CH, CRF, and CCT were strongly associated.
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Future longitudinal studies are clearly required to confirm these results and to better clarify the role of increasing age on corneal tissue and the relationship between age- and ORAderived parameters. REFERENCES 1. Liu J, Roberts CJ. Influence of corneal biomechanical properties on intraocular pressure measurement: quantitative analysis. J Cataract Refract Surg. 2005;31:146–155. 2. Swarbrick HA. Orthokeratology review and update. Clin Exp Optom. 2006;89:124–143. 3. Dupps WJ Jr, Wilson SE. Biomechanics and wound healing in the cornea. Exp Eye Res. 2006;83:709–720. 4. Ventura BV, Machado AP, Ambrósio R Jr, et al. Analysis of waveformderived ORA parameters in early forms of keratoconus and normal corneas. J Refract Surg. 2013;29:637–643. 5. Shah S, Laiquzzaman M, Yeung I, et al. The use of the ocular response analyser to determine corneal hysteresis in eyes before and after excimer laser refractive surgery. Cont Lens Anterior Eye. 2009;32:123–128. 6. Luce DA. Determining in vivo biomechanical properties of the cornea with an ocular response analyzer. J Cataract Refract Surg. 2005;31:156–162. 7. Kamiya K, Shimizu K, Ohmoto F. Effect of aging on corneal biomechanical parameters using the ocular response analyzer. J Refract Surg. 2009;25:888–893. 8. Boote C, Dennis S, Huang Y, et al. Lamellar orientation in human cornea in relation to mechanical properties. J Struct Biol. 2005;149:1–6. 9. Medeiros FA, Meira-Freitas D, Lisboa R, et al. Corneal hysteresis as a risk factor for glaucoma progression: a prospective longitudinal study. Ophthalmology. 2013;120:1533–1540. 10. Narayanaswamy A, Chung RS, Wu RY, et al. Determinants of corneal biomechanical properties in an adult Chinese population. Ophthalmology. 2011;118:1253–1259. 11. Fontes BM, Ambrósio R Jr, Alonso RS, et al. Corneal biomechanical metrics in eyes with refraction of 219.00 to +9.00 D in healthy Brazilian patients. J Refract Surg. 2008;24:941–945. 12. Laiquzzaman M, Bhojwani R, Cunliffe I, et al. Diurnal variation of ocular hysteresis in normal subjects: relevance in clinical context. Clin Experiment Ophthalmol. 2006;34:114–118. 13. Kamiya K, Hagishima M, Fujimura F, et al. Factors affecting corneal hysteresis in normal eyes. Graefes Arch Clin Exp Ophthalmol. 2008;246: 1491–1494. 14. Leite MT, Alencar LM, Gore C, et al. Comparison of corneal biomechanical properties between healthy blacks and whites using the ocular response analyzer. Am J Ophthalmol. 2010;150:163–168. 15. Doughty MJ, Zaman ML. Human corneal thickness and its impact on intraocular pressure measures: a review and meta-analysis approach. Surv Ophthalmol. 2000;44:367–408. 16. Ortiz D, Piñero D, Shabayek MH, et al. Corneal biomechanical properties in normal, post-laser in situ keratomileusis, and keratoconic eyes. J Cataract Refract Surg. 2007;33:1371–1375. 17. Daxer A, Misof K, Grabner B, et al. Collagen fibrils in the human corneal stroma: structure and aging. Invest Ophthalmol Vis Sci. 1998;39:644–648. 18. Elsheikh A, Wang D, Rama P, et al. Experimental assessment of human corneal hysteresis. Curr Eye Res. 2008;33:205–213. 19. Shah S, Laiquzzaman M, Cunliffe I, et al. The use of the Reichert ocular response analyser to establish the relationship between ocular hysteresis, corneal resistance factor and central corneal thickness in normal eyes. Cont Lens Anterior Eye. 2006;29:257–262. 20. Alsbirk PH. Corneal thickness. I. Age variation, sex difference and oculometric correlations. Acta Ophthalmol (Copenh). 1978;56:95–104. 21. Polse KA, Brand R, Mandell R, et al. Age differences in corneal hydration control. Invest Ophthalmol Vis Sci. 1989;30:392–399. 22. Ayala M, Chen E. Measuring corneal hysteresis: threshold estimation of the waveform score from the ocular response analyzer. Graefes Arch Clin Exp Ophthalmol. 2012;250:1803–1806. 23. Ehrlich JR, Radcliffe NM, Shimmyo M. Goldmann applanation tonometry compared with corneal-compensated intraocular pressure in the evaluation of primary open-angle glaucoma. BMC Ophthalmol. 2012;12:52. 24. Rochtchina E, Mitchell P, Wang JJ. Relationship between age and intraocular pressure: the Blue Mountains Eye Study. Clin Experiment Ophthalmol. 2002;30:173–175.
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Influence of Age and Gender on Corneal Biomechanical Properties in a Healthy Italian Population Ernesto Strobbe, MD, Mauro Cellini, MD, Umberto Barbaresi, MD, and Emilio C. Campos, MD
Purpose: The aim of this study was to assess corneal hysteresis (CH) and corneal resistance factor (CRF) in healthy subjects, to evaluate the relationship with age, and to investigate possible associations with other ocular factors.
Methods: Four hundred Italian subjects (male-to-female ratio, 168:232; mean age, 58.8 6 17.2 years) were included and divided into 5 subgroups based on age. CH, CRF, and central corneal thickness (CCT) were measured by using the Ocular Response Analyzer and the integrated handheld pachymeter, and their relationship with gender, age, and ocular factors was evaluated. Results: The mean CH, CRF, and CCT values were 10 6 1.6 mm Hg,
10.5 6 1.7 mm Hg, and 532.2 mm, respectively. Women had a lower mean CH (9.9 vs. 10.2 mm Hg; P = 0.04) and CRF (10.3 vs. 10.8 mm Hg; P = 0.03) than did men. The youngest subjects had the highest CH (11.2 6 1.5 mm Hg), whereas the oldest patients had the lowest CH values (9 6 1.1 mm Hg). No significant differences in CRF were observed between age groups. CH and CRF showed a positive correlation (r = 0.58; P , 0.001), and both had a positive association with CCT (r = 0.27; P , 0.001 and r = 0.57; P , 0.001, respectively). The strongest correlations were observed between Goldmann-correlated intraocular pressure (IOP) and corneal-compensated IOP (r = 0.68; P , 0.001) and between Goldmann-correlated IOP and Goldmann applanation tonometry (r = 0.88; P , 0.001).
Conclusions: Gender and advancing age may influence corneal biomechanical properties. In our population, CH decreased with aging, and men demonstrated a higher CH and CRF than women did. Further, CH, CRF, and CCT were significantly related. Key Words: corneal hysteresis, corneal resistance factor, ocular response analyzer, corneal biomechanics (Cornea 2014;33:968–972)
Received for publication March 24, 2014; revision received May 13, 2014; accepted May 15, 2014. Published online ahead of print July 9, 2014. From the Ophthalmology Unit, Department of Experimental, Diagnostic, and Specialty Medicine, Alma Mater Studiorum, University of Bologna, Bologna, Italy. E. Strobbe is responsible for the conception, design, analysis, and interpretation of data, drafting the article, and final approval of the manuscript. M. Cellini, U. Barbaresi, E. C. Campos are responsible for the conception, acquisition of data, review, and final approval of the paper. The authors have no funding or conflicts of interest to disclose. Reprints: Ernesto Strobbe, MD, Department of Experimental, Diagnostic, and Specialty Medicine, University of Bologna, Via Massarenti 9, 40138 Bologna, Italy (e-mail: [email protected]). Copyright © 2014 by Lippincott Williams & Wilkins
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he biomechanical properties of the cornea may provide important biological information that is useful in various fields of ophthalmology, including in intraocular pressure (IOP) measurement,1 contact lens wear,2 wound healing,3 corneal pathologies,4 and refractive surgery procedures,5 and may aid in the diagnosis and management of ocular diseases. Corneal properties have traditionally been studied by in vitro techniques that have experimentally evaluated factors such as viscoelasticity and hydration. Recently, corneal hysteresis (CH) and corneal resistance factor (CRF) have become subjects of increasing interest because they provide more comprehensive information about corneal biomechanics, may have diagnostic value, and may be easily and rapidly measured in vivo in a clinical setting by using the Ocular Response Analyzer [(ORA); Reichert, Inc, Depew, NY]. CH involves the measurement of viscous properties; indeed, it is thought to primarily reflect the viscous damping in the cornea, which is the ability of this tissue to absorb and dissipate energy, whereas CRF is an empirically derived parameter that is representative of corneal elastic properties, which is thought to reflect the overall resistance of this tissue.6 These parameters are strongly influenced by the corneal collagen composition and by the structure and properties of corneal layers, and by the thickness, curvature, and hydration of the corneal tissue. Increasing age may alter and modify some of these parameters and thus may indirectly influence corneal biomechanics.7 Researchers have identified collagen fibrils to be the main load-carrying components of the stroma, and found a clear link between the content and distribution of these fibrils and the biomechanical behavior of the cornea.8 Given the promising nature of the possibility of measuring corneal biomechanics in vivo, many studies covering a wide range of topics, such as glaucoma,9 keratoconus,4 and refractive surgery,5 have been performed and published using the ORA. However, to the best of our knowledge, there are few reports in the literature that evaluate the effect of aging on corneal biomechanical properties in a healthy population, and these data are drawn from Japanese, Chinese, and Brazilian subjects.7,10,11 The purpose of this study is to assess the biomechanical properties of the cornea in healthy Italian patients by using the ORA and to evaluate the relationship with age to aid in understanding the behavior of CH and CRF in vivo and to investigate the possible associations with other ocular factors.
METHODS This was a cross-sectional noninterventional study in which subjects presenting for a complete eye examination at Cornea Volume 33, Number 9, September 2014
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the Ophthalmology Unit of the S’Orsola-Malpighi Hospital between October 2011 and July 2013 were invited to participate. After a comprehensive explanation of the purpose of the study and of the noninvasive procedures was given, patients signed informed consent forms before inclusion according to the tenets of the Declaration of Helsinki. Approval was obtained from the Institutional Review Board and Ethical Committee of University of Bologna. A total of 400 healthy white Italian volunteers [168 males and 232 females; mean age 58.8 6 17.2 years (range: 21–88 years)] were consecutively recruited and were divided into 5 subgroups based on age: younger than 46 years (group A); between 46 and 55 years (group B); between 56 and 65 years (group C); between 66 and 75 years (group D); and older than 76 years (group E). All participants were above 18 years of age, were phakic, had no history of ocular injury or surgery or disease, were not contact lens wearers, and were able to cooperate so as to obtain reliable ORA readings. They were not using any topical ocular medication, and had no history of systemic disease affecting the eye. Subjects with a refractive error .6 diopters (D) for myopia, .4 D for hyperopia, or .1.5 D for astigmatism were excluded from the study. Each participant underwent an ophthalmologic examination, including visual acuity, Goldmann applanation tonometry (GAT), biomicroscopy of the anterior and posterior segment, assessment of central corneal thickness (CCT), and measurements of the biomechanical properties of the cornea, by using the ORA (Reichert, Inc). Details of the ORA properties and functions have been described elsewhere.6 Repeated measurements were taken to ensure that those with artifacts or of poor quality were eliminated, until 4 reliable measurements for each eye of every patient were obtained, and the average was used for statistical evaluation. A reliable ORA measurement was defined as (1) clean, approximately symmetrical applanation signal peaks; (2) fairly smooth signal at the descending curve, trough, and ascending curve; (3) flat baseline signal; and (4) waveform score .7. ORA measurements were performed before pachymetry to eliminate any possible effect of applanation on the properties of the cornea. Four parameters obtained by the measurements, including CH, CRF, Goldmann-correlated IOP (IOPg), and corneal-compensated IOP (IOPcc), were recorded. Ultrasound pachymetry (20 MHz) was performed with the ORA-integrated handheld pachymeter, after the application of
topical anesthesia with 0.4% oxybuprocaine hydrochloride. In all subjects, only 1 eye was randomly selected for statistical analysis. The ophthalmological examinations were carried out during hospital consulting hours, between 11 AM and 2 PM to eliminate possible confounders that could affect the results of the CCT, ORA, and IOP measurements, as demonstrated by Laiquzzaman et al.12
STATISTICAL ANALYSIS
All data are presented as mean 6 SD. Statistical analysis was performed using the Mann–Whitney U test and the Kruskall–Wallis test to compare the values of ocular variables between males and females and among the 5 study groups, respectively. To analyze the strength of the correlation between variables, the Spearman correlation test was calculated. Further, linear regression analysis, adjusting for age and gender, was used to assess the effect of each variable on CH and CRF. A P value ,0.05 was considered to be statistically significant.
RESULTS The 5 age groups comprised 400 eyes of 400 patients; 42% were men and 58% were women, and genders were not equally distributed within the 5 groups. The means of age, spherical equivalent, CCT, IOP, visual acuity, and corneal biomechanical parameters of the study patients globally and divided by age groups are summarized in Table 1. Visual acuity decreased from the first 3 groups to the last 2 groups because there was a higher proportion of cataract. In all eyes, the mean CH value was 10 6 1.6 mm Hg, the mean CRF was 10.5 6 1.7 mm Hg, and the mean CCT was 532.2 6 35.1 mm, whereas the mean GAT, IOPg, and IOPcc were 15.9 6 2.8 mm Hg, 16.2 6 2.9 mm Hg, and 17.1 6 3.5 mm Hg, respectively. Notably, we found that the youngest subjects had the highest CH (11.2 6 1.5 mm Hg), whereas the lowest CH values were found within the oldest patients (9 6 1.1 mm Hg); in detail, the differences were statistically significant between groups A and C (P , 0.01), groups A and D (P , 0.001), and groups A and E (P , 0.001), and between groups B and E (P , 0.001) (Table 2). However, CRF values did not show any significant differences among the age groups (P . 0.05).
TABLE 1. Demographic and Ocular Features and Corneal Biomechanical Properties in the Study Patients All Age, yrs Males/females Visual acuity (decimals) Refractive error (spherical equivalent) GAT, mm Hg CCT, mm CH, mm Hg CRF, mm Hg IOPg, mm Hg IOPcc, mm Hg
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,46 yrs (A)
46–55 yrs (B)
56–65 yrs (C)
66–75 yrs (D)
.75 yrs (E)
n = 400
n = 80
n = 80
n = 80
n = 80
n = 80
58.8 6 17.2 168/232 0.9 6 0.1 20.4 6 1.9 15.9 6 2.8 532.2 6 35.1 10 6 1.6 10.5 6 1.7 16.2 6 2.9 17.1 6 3.5
32.9 6 9.1 28/52 1.0 6 0.0 22.0 6 2.2 14.4 6 2.4 522.8 6 38.8 11.2 6 1.5 10.4 6 1.8 14.7 6 2.4 14.6 6 2.4
50.4 6 2.8 36/44 1.0 6 0.0 21.2 6 1.6 16 6 2.4 523.5 6 30.4 10.6 6 1.6 10.8 6 1.9 16 6 2.3 16.8 6 3.1
59.4 6 2.9 16/64 1.0 6 0.0 21.1 6 1.3 16.8 6 3.3 550.3 6 26.6 9.9 6 1.1 10.5 6 1.2 17.1 6 3.4 18.3 6 3.9
71.3 6 2.7 48/32 0.9 6 0.1 20.3 6 0.9 16.3 6 2.7 520.6 6 26.3 9.6 6 1.6 10.3 6 2 16.8 6 2.9 18.1 6 3.7
80.1 6 4.2 40/40 0.7 6 0.1 20.6 6 0.8 15.7 6 2.6 543.8 6 41 9 6 1.1 10.4 6 1.6 16.2 6 2.8 17.8 6 3.1
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TABLE 2. Comparison of Ocular Parameters Among the 5 Age Groups of the Study Population CH CCT
,46 yrs (A)
56–65 yrs (C) P
66–75 yrs (D) P
.75 yrs (E) P
* *
,0.01 ,0.01 * ,0.01
,0.001 * * * * ,0.01
,0.001 * ,0.001 * * * * *
46–55 yrs (B) P
56–65 yrs (C) P
66–75 yrs (D) P
.75 yrs (E) P
* * ,0.05
,0.01 ,0.05 ,0.001 * * *
,0.05 ,0.05 ,0.001 * * * * * *
* * ,0.001 * * * * * * * * *
46–55 yrs (B)
,46 yrs (A) 46–55 yrs (B) 56–65 yrs (C) 66–75 yrs (D)
GAT IOPg ,46 yrs (A)
IOPcc ,46 yrs (A)
46–55 yrs (B)
56–65 yrs (C)
66–75 yrs (D)
*Not statistically significant (P . 0.05).
Regarding GAT and IOPg values, the differences were statistically significant between groups A and C (P , 0.01 and P , 0.05, respectively), and between groups A and D (P , 0.05 for both the variables), whereas IOPcc values were significantly different between group A and the other 4 groups (A vs. B, P , 0.05, whereas in the remaining comparisons, P , 0.001) (Table 2). In a subgroup analysis, men demonstrated both a higher mean CH and mean CRF compared with women (10.2 vs. 9.9 mm Hg; P = 0.04 and 10.8 vs. 10.3 mm Hg; P = 0.03, respectively), whereas the mean CCT values were similar (Table 3). A negative correlation was noted between age and CH (r = 20.45; P , 0.001) and between CH and IOPcc
TABLE 3. Demographic and Ocular Features in Males and Females No Age, yrs Refractive error (spherical equivalent) GAT, mm Hg CCT, mm CH, mm Hg CRF, mm Hg IOPg, mm Hg IOPcc, mm Hg
970
Males
Females
P
168 60.4 6 18 20.1 6 1.4
232 57.7 6 16.7 20.6 6 2.2
0.29 0.18
6 6 6 6 6 6
0.50 0.74 0.04 0.03 0.51 0.08
15.7 532.3 10.2 10.8 16 16.8
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6 6 6 6 6 6
2.7 32.9 1.6 1.9 2.9 3.9
16 532.2 9.9 10.3 16.3 17.4
2.9 36.8 1.6 1.6 2.9 3.2
(r = 20.40; P , 0.001), whereas a positive association was found between CH and CRF (r = 0.58; P , 0.001), CRF and GAT (r = 0.51; P , 0.001), and CRF and IOPg (r = 0.43; P , 0.001); moreover, CCT was positively related with all biochemical parameters, GAT, age, and refractive error, and showed the strongest linear relationship with CRF (r = 0.57; P , 0.001). Among all the variables, the strongest correlations were observed between IOPg and IOPcc (r = 0.68; P , 0.001), and between IOPg and GAT (r = 0.88; P , 0.001) (Table 4). Finally, the relationships between corneal biomechanical properties with ocular variables were assessed through age- and gender-adjusted linear regression analyses (Table 5). The association between CH and GAT was not significant (P = 0.877), whereas CRF increased by 0.31 mm Hg for every millimeter of mercury increase in GAT (P , 0.001). Regarding the relationships between CH, CRF, and CCT, we found that CH and CRF increased by 0.01 and 0.03 mm Hg, respectively, for every 1-mm increase in CCT (P , 0.001 for both the variables). Further, for every unit increase in refractive error (spherical equivalent), CRF increased by 0.2 mm Hg (P = 0.002) (Table 5).
DISCUSSION In this study, we have demonstrated that both increasing age and gender have an important role on corneal biomechanical properties in a healthy Italian population. Ó 2014 Lippincott Williams & Wilkins
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TABLE 4. Spearman Correlation Among the Ocular Parameters and Between the Ocular Parameters and Age in the Study Population CRF CH
r = 0.58 P , 0.001
CRF
CCT r= P, r= P,
0.27 0.001 0.57 0.001
CCT
GAT
IOPg
IOPcc
Age
Refractive Error
r = 20.03 P = 0.69 r = 0.51 P , 0.001 r = 0.27 P , 0.001
r = 20.14 P = 0.046 r = 0.43 P , 0.001 r = 0.22 P , 0.01 r = 0.88 P , 0.001
r = 20.40 P , 0.001 r = 0.19 P , 0.01 r = 0.24 P , 0.001 r = 0.57 P , 0.001 r = 0.68 P , 0.001
r = 20.45 P , 0.001 r = 20.006 P = 0.93 r = 0.17 P , 0.05 r = 0.18 P , 0.01 r = 0.21 P , 0.01 r = 0.32 P , 0.001
r = 20.06 P = 0.38 r = 0.17 P , 0.05 r = 0.15 P , 0.05 r = 0.09 P , 0.22 r = 0.58 P = 0.09 r = 0.58 P , 0.05
GAT IOPg IOPcc
Both mean CH and CRF values in our study sample were very similar to those reported in studies involving healthy Chinese,10 Japanese,13 and Brazilian subjects.11 However, a recent study provided evidence that black people have lower CH and CRF values than white subjects had.14 We also observed that, in females, both CH and CRF values were significantly lower than those of males; in detail, females showed a 3% (P = 0.04) and 4.6% (P = 0.03) decrease, respectively, compared with men, but this finding is not in agreement with previous reports.10,11 Therefore, these contrasting data may be because corneal biomechanics may have different behavior between males and females in various ethnic groups. Currently, however, there are no concurring opinions about the existence of a strong relationship between corneal biomechanical parameters and gender.15 Further studies and investigations are still required to better understand the role of gender on corneal biomechanics and the influence of race on both CH and CRF values in males and females. Notably, CH had a decreasing trend with age. Indeed, in our population, aged between 21 and 88 years, CH showed the highest mean values in the youngest group (11.2 mm Hg) and the lowest mean values in the oldest group (9 mm Hg); in detail, subjects of the 46- to 55-year-old group did not show a statistically significant reduction compared with subjects of the youngest group, whereas patients of the 3 remaining age groups showed a decrease of 11.6% (P , 0.01), 14.3% (P , 0.001), and 19.6% (P , 0.001), respectively. Finally, a linear
regression analyses on CH provided evidence that CH decreased by 0.04 mm Hg for every year of age. CRF however did not have any relationship with age. Our results are confirmed by Ortiz et al,16 who observed a statistically significant difference in CH between the youngest group (#14 years old) and the oldest group (.60 years old), whereas no relationship between CRF and age was reported. Narayanaswamy et al,10 however, found that CH and CRF decreased with increasing age; in particular, CH showed the same decreasing trend for every year of age as shown in our study. Previous experimental studies17,18 have demonstrated age-related structural and biochemical changes in the human cornea, with an increase in collagen-fibril diameter and interfibrillar crosslinking in the stroma, probably leading to increased tissue rigidity. Further, the increase in the Young modulus of elasticity, which was proposed by Elsheikh et al,18 is in agreement with the decrease of CH with increasing age. Regarding the relationship between CH and CRF, our data revealed a positive significant correlation (r = 0.58; P , 0.001), as also stated by Shah et al,19 confirming the association between the 2 corneal biomechanical properties, although it has been reported that they are not the same measured parameters and that they are not always proportionally related. In 2000, Doughty et al15 determined the normal CCT values in human corneas and found a mean CCT of 535 mm, based on a meta-analysis approach of 600 eyes and concluded that there is no substantial change in CCT with age, and that
TABLE 5. Linear Regression Analyses on CH and CRF CH, mm Hg b (95% CI) Gender (female) Age, yrs Refractive error (spherical equivalent) GAT, mm Hg CCT, mm
20.340 20.041 20.066 20.006 0.012
(20.784 to 0.104) (20.053 to 20.030) (20.181 to 0.049) (20.085 to 0.073) (0.006 to 0.018)
CRF, mm Hg P 0.135 ,0.001 0.259 0.877 ,0.001
b (95% CI) 20.555 0.001 0.196 0.313 0.028
(21.038 to 20.071) (20.013 to 0.014) (0.073 to 0.320) (0.238 to 0.388) (0.022 to 0.033)
P 0.026 0.921 0.002 ,0.001 ,0.001
Adjusted for age and gender. CI, confidence interval.
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the association of race and CCT has not been investigated adequately in the literature and any gender-related determinant of CCT remains poorly defined. This finding seems to be true for whites, although some gender-dependent differences in CCT in nonwhite men and women have been reported.20 In our study sample, we observed a similar mean CCT, no differences between males and females, and a weak but significant positive correlation between increasing age and CCT. This may be explained by the possible age-dependent corneal hydration-control changes.21 According to our data, CCT was positively related to CH (r = 0.27; P , 0.001) and CRF (r = 0.57; P , 0.001), as already reported by previous studies.10,11 In detail, CH and CRF increased by 0.01 and 0.03 mm Hg, respectively, for every 1-mm increase in the CCT. This is because CH is a measure of viscous damping of the cornea, whereas CRF is a better indicator of the overall resistance of the corneal tissue. The strongest correlations were found between IOPg and GAT (r = 0.88; P , 0.001) as also demonstrated by Ayala and Chen,22 and between IOPg and IOPcc (r = 0.68; P , 0.001). Interestingly, IOPcc values were, on average, higher than GAT values and were strongly related to GAT (r = 0.57; P , 0.001), as previously established by Ehrlich et al23 in a study performed on normal and glaucomatous eyes. Based on our findings, IOPg, IOPcc, and GAT showed a statistically significant positive relationship with the age of the participants, as already reported in the Blue Mountains Eye Study performed on a white Australian urban population, which demonstrated an age-related increase of IOP values.24 According to the authors, this trend was probably dependent on systemic factors such as blood pressure and body mass index. Our study, despite patients with high blood pressure and diabetes being excluded, confirmed the existence of a relationship between age and IOP. In our population, CH did not show a significant relationship with GAT and IOPg, although it was negatively related to IOPcc (r = 20.40; P , 0.001), whereas a positive correlation between CRF and GAT (r = 0.51; P , 0.001), CRF and IOPg (r = 0.43; P , 0.001), and CRF and IOPcc (r = 0.19; P , 0.01) was reported. These data suggest that, although CH and CRF are strictly associated parameters, they may be differently influenced by normal range IOP values and are in agreement with previous studies.9,10 This study has some limitations. By including only 400 healthy Italian subjects, we were not able to assess whether these results might be applied to other groups with the same ethnic origin or to evaluate potential differences among patients with various diseases. Another limitation is the cross-sectional design of the study. Third, we had a small proportion of males compared with females and an unequal distribution among the 5 age groups, which probably precludes a detailed comparative analysis. In conclusion, our study provides additional data regarding the influence of aging and gender on corneal biomechanical properties in healthy Italian subjects. CH values demonstrated a decreasing trend with age, and females showed lower CH and CRF than males did. Finally, CH, CRF, and CCT were strongly associated.
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Future longitudinal studies are clearly required to confirm these results and to better clarify the role of increasing age on corneal tissue and the relationship between age- and ORAderived parameters. REFERENCES 1. Liu J, Roberts CJ. Influence of corneal biomechanical properties on intraocular pressure measurement: quantitative analysis. J Cataract Refract Surg. 2005;31:146–155. 2. Swarbrick HA. Orthokeratology review and update. Clin Exp Optom. 2006;89:124–143. 3. Dupps WJ Jr, Wilson SE. Biomechanics and wound healing in the cornea. Exp Eye Res. 2006;83:709–720. 4. Ventura BV, Machado AP, Ambrósio R Jr, et al. Analysis of waveformderived ORA parameters in early forms of keratoconus and normal corneas. J Refract Surg. 2013;29:637–643. 5. Shah S, Laiquzzaman M, Yeung I, et al. The use of the ocular response analyser to determine corneal hysteresis in eyes before and after excimer laser refractive surgery. Cont Lens Anterior Eye. 2009;32:123–128. 6. Luce DA. Determining in vivo biomechanical properties of the cornea with an ocular response analyzer. J Cataract Refract Surg. 2005;31:156–162. 7. Kamiya K, Shimizu K, Ohmoto F. Effect of aging on corneal biomechanical parameters using the ocular response analyzer. J Refract Surg. 2009;25:888–893. 8. Boote C, Dennis S, Huang Y, et al. Lamellar orientation in human cornea in relation to mechanical properties. J Struct Biol. 2005;149:1–6. 9. Medeiros FA, Meira-Freitas D, Lisboa R, et al. Corneal hysteresis as a risk factor for glaucoma progression: a prospective longitudinal study. Ophthalmology. 2013;120:1533–1540. 10. Narayanaswamy A, Chung RS, Wu RY, et al. Determinants of corneal biomechanical properties in an adult Chinese population. Ophthalmology. 2011;118:1253–1259. 11. Fontes BM, Ambrósio R Jr, Alonso RS, et al. Corneal biomechanical metrics in eyes with refraction of 219.00 to +9.00 D in healthy Brazilian patients. J Refract Surg. 2008;24:941–945. 12. Laiquzzaman M, Bhojwani R, Cunliffe I, et al. Diurnal variation of ocular hysteresis in normal subjects: relevance in clinical context. Clin Experiment Ophthalmol. 2006;34:114–118. 13. Kamiya K, Hagishima M, Fujimura F, et al. Factors affecting corneal hysteresis in normal eyes. Graefes Arch Clin Exp Ophthalmol. 2008;246: 1491–1494. 14. Leite MT, Alencar LM, Gore C, et al. Comparison of corneal biomechanical properties between healthy blacks and whites using the ocular response analyzer. Am J Ophthalmol. 2010;150:163–168. 15. Doughty MJ, Zaman ML. Human corneal thickness and its impact on intraocular pressure measures: a review and meta-analysis approach. Surv Ophthalmol. 2000;44:367–408. 16. Ortiz D, Piñero D, Shabayek MH, et al. Corneal biomechanical properties in normal, post-laser in situ keratomileusis, and keratoconic eyes. J Cataract Refract Surg. 2007;33:1371–1375. 17. Daxer A, Misof K, Grabner B, et al. Collagen fibrils in the human corneal stroma: structure and aging. Invest Ophthalmol Vis Sci. 1998;39:644–648. 18. Elsheikh A, Wang D, Rama P, et al. Experimental assessment of human corneal hysteresis. Curr Eye Res. 2008;33:205–213. 19. Shah S, Laiquzzaman M, Cunliffe I, et al. The use of the Reichert ocular response analyser to establish the relationship between ocular hysteresis, corneal resistance factor and central corneal thickness in normal eyes. Cont Lens Anterior Eye. 2006;29:257–262. 20. Alsbirk PH. Corneal thickness. I. Age variation, sex difference and oculometric correlations. Acta Ophthalmol (Copenh). 1978;56:95–104. 21. Polse KA, Brand R, Mandell R, et al. Age differences in corneal hydration control. Invest Ophthalmol Vis Sci. 1989;30:392–399. 22. Ayala M, Chen E. Measuring corneal hysteresis: threshold estimation of the waveform score from the ocular response analyzer. Graefes Arch Clin Exp Ophthalmol. 2012;250:1803–1806. 23. Ehrlich JR, Radcliffe NM, Shimmyo M. Goldmann applanation tonometry compared with corneal-compensated intraocular pressure in the evaluation of primary open-angle glaucoma. BMC Ophthalmol. 2012;12:52. 24. Rochtchina E, Mitchell P, Wang JJ. Relationship between age and intraocular pressure: the Blue Mountains Eye Study. Clin Experiment Ophthalmol. 2002;30:173–175.
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