|Year : 2016 | Volume
| Issue : 3 | Page : 193-198
Study of factors influencing central corneal thickness among patients attending ophthalmology outpatient department at a tertiary care center in North Kerala
Vivek Oommen Varghese, Latha N Vadakkemadam, Shamin Jacob, KK Praveena, Ratheesh Raj, Jipina Kizhakkepatt
Department of Ophthalmology, Academy of Medical Sciences, Pariyaram, Kannur, Kerala, India
|Date of Web Publication||2-May-2017|
Dr. Latha N Vadakkemadam
Department of Ophthalmology, Academy of Medical Sciences, Pariyaram, Kannur - 670 503, Kerala
Source of Support: None, Conflict of Interest: None
Context: Central corneal thickness (CCT) was assumed to be a constant when Goldmann designed his applanation tonometer. Knowledge of the CCT is of importance in the assessment of intraocular pressures (IOPs).
Aim: The aim of the study was to examine the association of CCT with ocular, demographic, and metabolic factors such as age, race, gender, smoking, alcoholism, diabetes mellitus, hypertension, obesity, metabolic syndrome, corneal curvature, and axial length.
Settings and Design: A cross-sectional study was conducted in 166 patients aged between 30 and 70 years who had presented for routine eye checkup from January 1, 2014, to July 1, 2015, in our Ophthalmology Department.
Subjects and Methods: Patient parameters were recorded using an interview schedule, and complete ocular examination, including visual acuity and IOPs, were recorded. CCT was measured using PacScan Plus A-Scan/Pachymeter.
Statistical Analysis Used: Mean CCT across different variables were compared using ANOVA and t-test. Further analysis was done using univariate and multivariate analysis.
Results: On univariate analysis, it was found that age, presence, and duration of diabetes, elevated fasting blood sugar levels, alcohol consumption, corneal curvature (in diopters), and IOP were associated with CCT. Multivariate analysis showed significant association of CCT with age, duration of diabetes, corneal curvature, and IOP (P < 0.05).
Conclusions: From our study, we concluded that CCT was significantly associated with age, duration of diabetes, corneal curvature, and IOP. Duration of diabetes and IOP showed a positive correlation with CCT whereas age and corneal curvature showed a negative correlation.
Keywords: Central corneal thickness, corneal curvature, diabetes mellitus, intraocular pressure
|How to cite this article:|
Varghese VO, Vadakkemadam LN, Jacob S, Praveena K K, Raj R, Kizhakkepatt J. Study of factors influencing central corneal thickness among patients attending ophthalmology outpatient department at a tertiary care center in North Kerala. Kerala J Ophthalmol 2016;28:193-8
|How to cite this URL:|
Varghese VO, Vadakkemadam LN, Jacob S, Praveena K K, Raj R, Kizhakkepatt J. Study of factors influencing central corneal thickness among patients attending ophthalmology outpatient department at a tertiary care center in North Kerala. Kerala J Ophthalmol [serial online] 2016 [cited 2019 Jan 16];28:193-8. Available from: http://www.kjophthal.com/text.asp?2016/28/3/193/205435
| Introduction|| |
The thickness of the cornea is directly related to the dehydrating function of the endothelium, and it can be measured indirectly by pachymetry. The normal central corneal thickness (CCT) is around 510–520 microns. It is measured using optical or ultrasound methods.
Thicker corneas are associated with higher intraocular pressures (IOPs),, due to increase in resistance to indentation and vice versa in thin corneas. It also has a great role in refractive surgeries.,
CCT was assumed to be a constant but subsequently found that it varies. So giving importance to this, we analyze the association of CCT with ocular, demographic, and metabolic risk factors.
| Subjects and Methods|| |
Our study was a hospital-based cross-sectional study of 166 patients who had attended the Outpatient Department of Ophthalmology. The sampling frame consisted of patients aged 30–70 years presenting for routine eye checkup under the executive checkup scheme. The study period was 18 months: January 1, 2014, to July 1, 2015. Patients who have a history of previous intraocular surgery, ocular trauma, intraocular inflammation, glaucoma, laser photocoagulation, laser in situ keratomileusis, photorefractive keratectomy, systemic disease other than diabetes and hypertension, contact lens use (past or present), and patients not giving consent were excluded from the study.
Approval for the study protocol was granted by the Hospital's Institutional Review Board comprising of Ethical and Research Committee. Written informed consent was obtained from all participants before enrollment.
All participants underwent a standardized interview and clinical examination at the Outpatient Department of Ophthalmology. Complete ocular examination including visual acuity and IOP recording was done before the measurements of CCT.
CCT was measured using the PacScan Plus A-Scan/Pachymeter. Five readings were taken from each eye at one point along the corneal surface by a single ophthalmologist using MAP1-MULTI mode, and its average value was recorded [Figure 1] and [Figure 2]. The readings were taken between 10 am and 1 pm.
Axial length of the eye was measured using PacScan Plus A-Scan. IOP was measured using Goldmann Applanation Tonometer. Corneal curvature including keratometric values was recorded using automated refractor. Refractive error was recorded using the technique of retinoscopy.
The participant's height was measured in meters with a wall-mounted tape and the weight measured using a weighing scale to determine the body mass index (BMI). BMI is calculated as weight (kg) divided by the square of height (m)
Participants were classified as underweight if BMI is <18.5 and normal if BMI is ≥18.5 but <25. If their BMI is ≥25 but <30, they were considered overweight. Obesity is defined as BMI ≥30, systolic and diastolic blood pressures were taken with a sphygmomanometer. Hypertension was defined as blood pressure values >140/90 mm Hg and was classified according to JNC 7. Fasting and postprandial blood samples were drawn from all participants to determine serum lipids and serum glucose. Diabetes was defined as nonfasting glucose levels ≥200 mg/dl (11.1 mmol/l) or physician diagnosis of diabetes and use of diabetic medication. Metabolic syndrome was diagnosed when participants met 3 or more of the following criteria: (1) BMI ≥ 25, (2) hypertriglyceridemia (≥1.7 mmol/l or ≥151 mg/dl), (3) low level of high-density lipoprotein cholesterol levels (HDL) (≤1.0 mmol/l or ≤40 mg/dl in male participants, ≤1.3 mmol/l or ≤50 mg/dl in female subjects), (4) hypertension, and (5) diabetes mellitus. Self-reported smoking status was assessed. Participants were classified based on smoking habit information collected using a standardized questionnaire. Smoking was classified as never smokers (smoked <100 cigarettes in their lifetime and not currently smoking), former smokers (smoked ≥100 cigarettes in their lifetime and currently a nonsmoker), and current smokers (smoked ≥100 cigarettes in their lifetime and currently a smoker). Based on information on years since quitting smoking, former smokers were classified as ≤1 year and >1 year.
On analysis, the Pearson's coefficient for the right and left eye is 0.984. Hence, we used the CCT of the right eye for further analysis to find the factors associated with CCT.
Mean CCT across different variables were compared using ANOVA and t-test. Post hoc (Tukey) was done for those in which ANOVA yielded a significant P value. Using linear regression, the mean difference in CCT per change in parameters were calculated. Those with P< 0.2 were included in multivariate analysis and results were obtained.
| Results|| |
A total of 166 patients were enrolled in our study. The mean age was 47.8 years with a standard deviation of 10.1. Out of the 166 participants, 71.7% were male, and 28.3% were female. The CCT was normally distributed with a mean of 536.71 μm. There was no statistical difference in mean CCT between males (537.18 μm) and females (535.85 μm) (P = 0.8). CCT was found to decrease with age (P = 0.002).
Mean CCT across different variables were compared using ANOVA and t-test. Post hoc (Tukey) was done for those in which ANOVA yielded a significant P value.
The correlation between CCT in the right eye and different parameters were identified [Table 1].
| Discussion|| |
In our study, the mean CCT of the right eye showed significant association with age, duration of diabetes, corneal curvature (in diopters), and IOP. The associations of diabetes, fasting blood sugars, total cholesterol levels, current smoking, and alcoholism with CCT were significant only at the univariate level [Table 2] and [Table 7]. There were no significant associations between gender, glycosylated hemoglobin (HbA1c) levels, BMI, hypertension, obesity, metabolic syndrome, HDL, LDL, blood urea, serum creatinine levels, and CCT [Table 3].
The mean CCT of the right eye among the study group was (536.81 ± 2.58 μm). The mean CCT of the right eye among the different age groups were studied [Table 9].
Age showed significant negative correlation with CCT (P = −0.002). Several published studies have identified a significant decrease in CCT with age similar to our study. The studies by Kamiya, Nishiyama et al., studies among Mongolian individuals, and Nepalese population  have reported decrease in CCT with age which was significant. Thinner CCT may be a risk factor for the development and progression of glaucoma. Thinner CCT may lead to an underestimation of IOP in persons with normal tension glaucoma).
The mean CCT among diabetics was (548.59 ± 5.31 μm) which was higher compared to nondiabetics who had a mean CCT of (533.77 ± 2.90 μm). However, it was not statistically significant on performing multivariate analysis. This finding is consistent with the findings of investigators, including Chooetal and Sudhiretal who found no significant difference in CCT between diabetic and nondiabetics. However, studies conducted by Lee et al., Ozdamar et al., and Busted et al. found that CCT was significantly higher among diabetic population.,
The CCT was found to be significantly increased in patients with duration of diabetes of 10 or more years (574.13 ± 8.07 μm) as compared to those with duration <10 years (540.73 ± 5.70 μm) (P = −0.016). This is supported by the findings of Lee et al. which showed a significant correlation of CCT with diabetic duration after controlling for age. Several studies have documented abnormalities of corneal endothelial morphology and increased CCT in persons with diabetes. Abnormal glucose metabolism may cause corneal endothelial dysfunction which results in stromal hydration and swelling of the cornea. Thus, the increase in CCT may be attributed to the endothelial damage brought about by the longstanding diabetes mellitus.
The present study did not find any significant correlation between CCT and HbA1c levels which is considered as an indicator of long-term control of diabetes. The mean CCT among those with HbA1c <6.5 g% was (533.57 ± 2.81 μm), with HbA1c values (6.5–7.9 g%) was (543.83 ± 9.14 μm), and with HbA1c &XS#62;8 g% was (548.10 ± 8.16 μm) [Table 4]. This is similar to the study by Ozdamar which did not show a significant correlation of CCT with respect to the level of glycosylated hemoglobin.
In the present study, the mean CCT among current smokers was (548.36 ± 5.35 μm) which was higher than that among nonsmokers (535.98 ± 3.15 μm), but it was not statistically significant. The Funagata study reported that current smoking was associated with increased CCT. Even though few other studies have reported that corneal hysteresis is more elevated in chronic smokers than in nonsmokers, we could not find any other studies which reported increased CCT among current smokers.
The mean CCT among current alcoholics was (545.94 ± 4.58 μm) which was higher than that among nonalcoholics (532.64 ± 3.06 μm). Although this difference was significant on univariate analysis (P = 0.016), it lost its significance on multivariate analysis (P = 0.244). Hence, current alcoholism was not found to be associated with CCT.
In the present study, we have found a negative correlation between CCT of the right eye and keratometry value of the right eye (Pearson coefficient = −0.21, P = 0.01). This finding was similar to the Singapore Malay Eye Study, which found that CCT increased with greater radius of corneal curvature and the study by Giridhar Eye Institute, which also showed a negative correlation between CCT and corneal curvature (in diopters) [Table 5]. Similar results were reported by Atsuo Tomidokoro et al. in the Tajimi study from Japan, and the studies among Singaporean children which showed that the radius of corneal curvature correlated with CCT significantly.
The correlation between CCT and IOP is well known-eyes with greater mean CCT tend to have higher IOP, and our results confirm this. The IOP in the right eye showed significant correlation with the CCT of the right eye (P = 0.001) [Table 6]. This result was similar to the Funagata study, The Singapore Malay Eye study, The Central India Eye and Medical study, and the study of CCT in Nepalese population, all of which showed a significant positive correlation of CCT with IOP.
The factors such as age, duration of diabetes, and corneal curvature which are associated with CCT may cause variations in the measurement of IOP by applanation tonometry [Table 8]. This might be of significance in glaucoma where IOP appears to be the only known risk factor which is amenable to medical treatment. The IOP measurements by applanation might be wrong when the CCT values lie outside normal limits thus leading to misclassification of disease in the setting of glaucoma. Hence, it is necessary to include CCT measurements along with IOP in patients with the above-mentioned factors and find the true IOP before classifying and treating them. The studies also show that the use of prostaglandin analogs such as latanoprost and travoprost significantly decreases the CCT in patients with open-angle glaucoma.
|Table 8: Associations of central corneal thickness in multivariate-adjusted model|
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| Conclusions|| |
Our study shows that CCT was significantly associated with age, duration of diabetes mellitus, corneal curvature (in diopters), and IOP. While age and corneal curvature showed a negative correlation, IOP, and duration of diabetes showed a positive correlation with CCT.
Diabetes, fasting blood sugars, total cholesterol levels, current smoking, and alcoholism were associated with CCT at the univariate level. Gender, HbA1c levels, BMI, hypertension, obesity, metabolic syndrome, HDL, LDL, blood urea, serum creatinine levels, axial length, and refraction showed no significant association with CCT.
Dr Aslesh O. P., Assistant Professor, Department of Community Medicine, Academy of Medical Sciences, Pariyaram.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Hedbys BO, Mishima S. The thickness-hydration relationship of the cornea. Exp Eye Res 1966;5:221-8.
Kremer FB, Walton P, Gensheimer G. Determination of corneal thickness using ultrasonic pachometry. Ann Ophthalmol 1985;17:506-7.
Mishima S. Corneal thickness. Surv Ophthalmol 1968;13:57-96.
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.
Brandt JD. Corneal thickness in glaucoma screening, diagnosis, and management. Curr Opin Ophthalmol 2004;15:85-9.
Shah S, Chatterjee A, Mathai M, Kelly SP, Kwartz J, Henson D, et al.
Relationship between corneal thickness and measured intraocular pressure in a general ophthalmology clinic. Ophthalmology 1999;106:2154-60.
Pallikaris IG, Kymionis GD, Astyrakakis NI. Corneal ectasia induced by laser in situ
keratomileusis. J Cataract Refract Surg 2001;27:1796-802.
Binder PS. Ectasia after laser in situ
keratomileusis. J Cataract Refract Surg 2003;29:2419-29.
Shimmyo M, Ross AJ, Moy A, Mostafavi R. Intraocular pressure, Goldmann applanation tension, corneal thickness, and corneal curvature in Caucasians, Asians, Hispanics, and African Americans. Am J Ophthalmol 2003;136:603-13.
Whitacre MM, Stein RA, Hassanein K. The effect of corneal thickness on applanation tonometry. Am J Ophthalmol 1993;115:592-6.
WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004;363:157-63.
American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care 2007;30:S42-7.
Grundy SM, Brewer HB Jr., Cleeman JI, Smith SC Jr., Lenfant C; American Heart Association; National Heart, Lung, et al.
Definition of metabolic syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation 2004;109:433-8.
Kamiya C. Studies on corneal thickness (Part 1). J Jpn Contact Lens Soc 1973;24:1-7.
Nishiyama K, Urakawa Y, Okubo H. Aging changes in central corneal thickness. Nippon Ganka Gakkai Zasshi 1987;91:415-9.
Foster PJ, Baasanhu J, Alsbirk PH, Munkhbayar D, Uranchimeg D, Johnson GJ. Central corneal thickness and intraocular pressure in a Mongolian population. Ophthalmology 1998;105:969-73.
Godar ST, Kaini KR, Khattri JB. Factors affecting the central corneal thickness in nepalese population. Nepal J Med Sci 2012;1:7-10.
Herndon LW, Choudhri SA, Cox T, Damji KF, Shields MB, Allingham RR. Central corneal thickness in normal, glaucomatous, and ocular hypertensive eyes. Arch Ophthalmol 1997;115:1137-41.
Sudhir RR, Raman R, Sharma T. Changes in the corneal endothelial cell density and morphology in patients with type 2 diabetes mellitus: A population-based study, Sankara Nethralaya Diabetic Retinopathy and Molecular Genetics Study (SN-DREAMS, Report 23). Cornea 2012;31:1119-22.
Ozdamar Y, Cankaya B, Ozalp S, Acaroglu G, Karakaya J, Ozkan SS. Is there a correlation between diabetes mellitus and central corneal thickness? J Glaucoma 2010;19:613-6.
Busted N, Olsen T, Schmitz O. Clinical observations on the corneal thickness and the corneal endothelium in diabetes mellitus. Br J Ophthalmol 1981;65:687-90.
Lee JS, Oum BS, Choi HY, Lee JE, Cho BM. Differences in corneal thickness and corneal endothelium related to duration in diabetes. Eye (Lond) 2006;20:315-8.
Nishitsuka K, Kawasaki R, Kanno M, Tanabe Y, Saito K, Honma K, et al.
Determinants and risk factors for central corneal thickness in Japanese persons: The Funagata Study. Ophthalmic Epidemiol 2011;18:244-9.
Su DH, Wong TY, Foster PJ, Tay WT, Saw SM, Aung T. Central corneal thickness and its associations with ocular and systemic factors: The Singapore Malay Eye Study. Am J Ophthalmol 2009;147:709-16.e1.
Elias A, Giridhar A, Mahesh G. Central corneal thickness and relating factors – A prospective observational study: Kerala J Ophthal 2009;21:149-53.
Nangia V, Jonas JB, Sinha A, Matin A, Kulkarni M. Central corneal thickness and its association with ocular and general parameters in Indians: The Central India Eye and Medical Study. Ophthalmology 2010;117:705-10.
Kass MA, Heuer DK, Higginbotham EJ, Johnson CA, Keltner JL, Miller JP, et al.
The Ocular Hypertension Treatment Study: A randomized trial determines that topical ocular hypotensive medication delays or prevents the onset of primary open-angle glaucoma. Arch Ophthalmol 2002;120:701-13.
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8], [Table 9]