Diabetic retinopathy is one of the leading causes of blindness today ...

Copyright 2011 by The Association for Research in Vision and Ophthalmology, Inc.
Association of Mean Ocular Perfusion Pressure and Diabetic Retinopathy in Type 2 Diabetes Mellitus. Sankara Nethralaya
Diabetic Retinopathy Epidemiology And Molecular Genetic Study (SN-DREAMS, report 28)
Running title: Ocular perfusion pressure and diabetic retinopathy
Authors:
Rajiv Raman (MS, DNB) 1
Aditi Gupta (MS) 1
Vaitheeswaran Kulothungan (MSc, Mphil) 2
Tarun Sharma (MD, FRCSEd, MBA) 1
Institutional Affiliation: 1 Shri Bhagwan Mahavir Vitreoretinal Services, 18, College Road, Sankara Nethralaya, Chennai-
600 006, Tamil Nadu, India
2 Department of Preventive Ophthalmology, 18, College Road, Sankara Nethralaya, Chennai-600 006, Tamil Nadu, India
Address for correspondence:
Dr. Tarun Sharma, MD, FRCSEd, MBA
Director, Shri Bhagwan Mahavir Vitreoretinal Services, Sankara Nethralaya, College Road, Chennai - 600 006, Tamil
Nadu, India.
E- mail: drtaruns@gmail.com
Word Count: 3325
1
IOVS Papers in Press. Published on May 5, 2011 as Manuscript iovs.10-6903

Abstract
Purpose
To elucidate the distribution of Mean Ocular Perfusion Pressure (MOPP) and to study the relationship between MOPP
and Diabetic Retinopathy (DR) in a south Indian sub-population with diabetes.
Methods
This was a population-based, cross-sectional study comprising 1368 subjects, aged ≥ 40, with Type 2 diabetes. DR was
diagnosed on the basis of modified Klein classification. Systolic and diastolic blood pressure (SBP and DBP) were
recorded using the mercury sphygmomanometer. Intraocular pressure (IOP) was assessed by applanation tonometry.
MOPP was derived using . SPSS (version 9.0) was used for statistical
analysis.
Results
The mean ± SD, for MOPP was 52.6 ± 9.0 mm Hg, higher in women than men (p=0.046). In comparison to subjects
without DR, MOPP was higher in men with sight threatening diabetic retinopathy (STDR) (p=0.030) and higher in women
with any DR (p=0.008) and non-STDR (p=0.006). However, on multivariate analysis after adjusting for all factors, MOPP
2

was found to be not associated with DR (OR=1.02 95% CI=0.99-1.03, p=0.149), non-STDR (OR=1.02 95% CI=0.99-1.03,
p=0.312) and STDR (OR=1.02 95% CI=0.98-1.05; p=0.358).
Conclusions
Univariate analysis revealed very small differences in the association of MOPP and DR among both the genders which
are probably of no clinical significance. Multivariate analysis showed no association between MOPP and DR. There
seems to be very little evidence for a link between MOPP and DR. It might be more informative to evaluate the
association in longitudinal studies.
3

Introduction
Diabetic Retinopathy (DR) is one of the leading causes of blindness today. However, the causes of vascular pathology in
this disease are not fully understood. 1-3 Though, chronic hyperglycemia initiates the processes, 4 the factors that link
elevated glucose levels to vascular cell dysfunction, capillary dropout and tissue hypoxia, and to abnormal angiogenesis,
remain poorly described. 2,5,6 Dysfunctional retinal perfusion can explain few aspects of the pathophysiology of DR. 1
Subjects with diabetes suffer from dysfunctional retinal perfusion. 1,2 While these deficiencies may, in part, reflect
responses to a primary event occurring in the retinal microvasculature, they may independently contribute to the
development and progression of this disease. 1 The blood flow in any tissue is generated by the perfusion pressure. The
circumferential stress in a vessel is directly proportional to the perfusion pressure. 7 A higher perfusion pressure can
increase the circumferential stress damage to the vessel wall, leading to a continuing propensity to dilatation with
subsequent hyperperfusion. 8 At the same time, high perfusion pressure can also reduce the retinal perfusion by causing
autoregulation of the retinal vasculature, 8 though the diabetic vascular system is known for its abnormal autoregulatory
capacity. 9 In any case, both increased and decreased retinal blood flow will be detrimental for the development of DR. 2
Moreover, higher perfusion pressure and the resultant stress changes can also increase the net pressure gradient from
vessels to tissue, leading to more fluid leaving the retinal capillaries (Starling’s forces) 10 and an increased risk for rupture
(Laplace’s law). 10 Since there is no lymphatic circulation to drain away this excess interstitial fluid, increased leakage will
4

esult in retinal edema and diabetic maculopathy and vessel rupture will cause hemorrhages and capillary dropout,
manifesting as clinical DR. 11
The Mean Ocular Perfusion Pressure (MOPP) is expressed as two third of the difference between the Mean Arterial
Pressure (MAP) and the Intraocular Pressure (IOP). Since MOPP is a potentially modifiable factor, knowing its
relationship to diabetic retinopathy and maculopathy can prove useful in preventing such diabetes complications.
MOPP has previously been implicated in the development of diabetic retinopathy. 8,12-15 However, the relationship between
MOPP and DR as studied in previous reports remains unclear. Some studies showed that high ocular perfusion pressure
is associated with progression of DR. 8,12-13 and others suggested that MOPP decreased as DR worsened. 14 Another study
also reported a higher MOPP with macular edema. 15
This study aims to elucidate the distribution of MOPP, systemic factors associated with MOPP and its relationship with
DR in a population-based sample of subjects with Type 2 diabetes in south India.
Methods
The details of the study design and methodology are described elsewhere. 16 The study was approved by the Institutional
Review Board, and a written informed consent was obtained from the subjects as per the Helsinki Declaration. 17 The
study population was selected by multistage systematic random sampling. The sampling was stratified based on the
socio-economic criteria. In the first stage of the study, divisions were selected using computer generated random
5

numbers. Study subjects were then selected randomly from each selected division. The sample size was calculated
based on the assumption that the prevalence of DR in the general population above 40 years of age was 1.3%, as
estimated in the Andhra Pradesh Eye Disease Study; 18 with a relative precision of 25%, a dropout rate of 20% and a
design effect of 2. The estimated sample size was 5830. To meet the target, 600 individuals were enumerated from each
of the 10 selected divisions. Of the 5999 subjects enumerated, 5784 (96.42%) responded for first fasting blood sugar
estimation. Of 5784, 1816 were subjects with Type 2 diabetes and were invited to visit the base hospital for
comprehensive evaluation, including second blood sugar estimation. Of these 1816 subjects,1563 (85.60%) responded,
including 1175 having previously diagnosed diabetes; and 388 provisionally diagnosed as having diabetes. Again,138
subjects were excluded because in 2 subjects, the age criterion was not met, and in 136, second fasting blood sugar was
less than 110 mg/dl. An additional 11 individuals were excluded because their digital fundus photographs were of poor
quality, making them ungradable for further analysis. Thus, a total of 1414 subjects with Type 2 diabetes were available
for the study.
Thus, in present study, 1680 subjects out of 5784 (28.2%) had Type 2 diabetes. We have previously reported a temporal
trend of increase in prevalence of diabetes in the general population between NUDS (National urban diabetes study) and
our study; from 23.8% in 2000 to 28.2% in 2006. 19 Subjects with Type 2 diabetes were identified based on the American
Diabetes Association criteria and they underwent a detailed examination at the base hospital. 20
6

After eight hours of overnight fasting, the fasting blood sample was taken to estimate the plasma glucose. For those with
provisional diabetes, the presence of diabetes was confirmed by re-estimating the fasting blood glucose by enzymatic
assay; glucose was oxidized by glucose oxidase to produce gluconate and hydrogen peroxide, which was then detected
photometrically. Glycosylated hemoglobin fractions were estimated by using Merck Micro Lab 120 semi-automated
analyzer (Bio-Rad DiaSTAT HbA1c Reagent Kit). 20 The total serum cholesterol (CHOD-POD method), serum triglycerides
(CHOD-POD) and HDL (after protein precipitation CHOD-POD method), were estimated. Hypercholesterolemia was
defined as serum total cholesterol levels ≥200 mg/dL, hypertriglyceridemia as serum triglycerides level ≥150 mg/dL and
serum HDL was designated as low if

Pune, India), according to a protocol similar to that used in the Multi-ethnic Study of Atherosclerosis. 23 Two readings were
taken, five minutes apart. A third measurement was made if the Systolic Blood Pressure (SBP) differed by more than 10
mm Hg or the Diastolic Blood Pressure (DBP) differed by more than 5 mm Hg. 24 The mean between the two closest
readings was taken as the blood pressure. Hypertension was defined as SBP ≥140 mm Hg or DBP ≥90 mm Hg.
The IOP in both the eyes were measured using the Goldmann applanation tonometer (Zeiss AT 030 Applanation
Tonometer, Carl Zeiss, Jena, Germany), using 0.05% proparacaine eye drops as topical anesthesia and 2% fluorescein to
stain the tear film. In many recent reports, MOPP has been identified as an independent risk factor for open angle
glaucoma 25 and glaucoma is documented to have protective influence on DR. 26 Hence, we further excluded 46 subjects
with glaucoma (IOP>21 mm Hg) from the analysis so that the direct association between MOPP and DR can be assessed
which is independent of the relationship of either to glaucoma. Thus 1368 subjects were analyzed in this study.
MAP is calculated as:
where the difference between the systolic and diastolic blood pressures is identified as the pulse pressure. The MOPP is
calculated from two third of the difference between MAP and IOP and two third is added to the formula to estimate the
ophthalmic artery pressure. Hence, MOPP is derived using the following relation 27 :
8

Diabetic Retinopathy
All patients had their fundi photographed using the 45 0 four-field stereoscopic digital photography (Carl Zeiss Fundus
Camera, Visucamlite, and Jena, Germany) after pupillary dilatation. DR was diagnosed based on the modified Klein
classification (Modified Early Treatment Diabetic Retinopathy Study scales). 28 For those who showed symptoms of any
DR, additional 30º seven-field stereo digital pairs were taken. The prevalence of DR in the general population above 40
year of age in our study was found to be 3.5%. 19 DR was divided into mild, moderate and severe Non-Proliferative
Diabetic Retinopathy (NPDR) and Proliferative Diabetic Retinopathy (PDR); Clinically Significant Macular Edema (CSME)
and non-CSME was graded as absent or present. 29 Mild and moderate NPDR was defined as non-sight threatening
diabetic retinopathy (non-STDR) and severe NPDR, PDR and CSME were defined as Sight Threatening Diabetic
Retinopathy (STDR). 30 This grading was done by two independent observers in a masked fashion; the grading agreement
was high (k=0.83). 16
Statistical analysis:
A computerized database was created for all the records. Statistical software (SPSS for Windows, ver.13.0 SPSS
Science, Chicago, IL) was used for statistical analysis. All the data were expressed as mean ± S.D or as percentage, if
categorical. The statistical significance was assumed at p values ≤0.05. Univariate and multivariate logistic regression
analyses were performed to elucidate the risk factors for microangiopathies. The Odds Ratio (OR), with 95% confidence
9

intervals, was calculated for the studied variables. The factors that were used for multivariate analysis included the factors
associated with mean arterial pressure (age, gender, duration of diabetes, age of onset of diabetes, glycosylated
hemoglobin, body mass index, waist circumference, micro- and macroalbuminuria, serum total cholesterol, serum
triglycerides, serum high density lipoproteins, and anemia) as well as the factors associated with intraocular pressure
(height and weight of the subject and central corneal thickness).
Results
Table 1 describes the baseline characteristics of the study population. Of the 1368 subjects, 875 (64%) had systemic
hypertension. The mean ± SD for SBP, DBP, MOPP and IOP, in the overall study population, were 139.0 ± 20.8 mm Hg
(median, 140), 82.0 ± 11.4 mm Hg (median, 80), 52.6 ± 9.0 mm Hg (median, 51.4), and 14.80 ± 2.9 mm Hg (median, 14)
respectively. Women had higher SBP (p

p=0.546 overall, p=0.663 in men, p=0.228 in women for IOP). SBP increased (p

STDR when compared with the no-DR group. Similarly, MOPP when adjusted for all factors, was found to be not
associated with DR (OR=1.02 95% CI=0.99-1.03, p=0.149), non-STDR (OR=1.02 95% CI=0.99-1.03, p=0.312) and STDR
(OR=1.02 95% CI=0.98-1.05; p=0.358). When compared to subjects with no maculopathy, MOPP adjusted with all
variables, had no association with non-CSME and CSME (results not shown in the table).
Discussion
We report the MOPP among subjects with Type 2 diabetes and elucidate the systemic factors associated with MOPP and
its association with DR. In the present study, women had higher MOPP than men. Also, SBP was found to be higher
among women than men. Recently, Zheng at al 25 reported higher MOPP, higher DBP, but lower SBP in men than in
women. Higher SBP in women in the present study can probably be explained by the higher BMI in women 22 and poor
health-seeking behaviour of women in Indian sub-continent. 31
There was no significant trend of MOPP with age, as seen in Figure 1. We found a very small association of MOPP with
the age of onset of diabetes and weight of the subject, which may not be clinically significant. We also found that MOPP is
associated with presence of nephropathy and serum lipids (triglycerides). There was no association with glycemic control
and duration of diabetes. This lack of association is interesting as poor glycemic control and longer duration of diabetes
are the most important risk factors for DR. Kohner observed that retinal hyperperfusion was worse in those with poor
12

diabetic control. 32 Konno et al observed a transition from decreasing retinal blood flow to increasing retinal blood flow in
patients with longer duration of Type 1 diabetes and suggested that there was a net decrease in the resistance to flow
with longer duration of diabetes. 33 Thus, longer duration of diabetes and poor glycemic control might be associated with
increased retinal perfusion and a decrease in the resistance to flow. However, MOPP is calculated from IOP and
measured brachial blood pressure and it is unlikely that retinal changes can explain any change or lack of change in
MOPP. Moreover, blood flow changes are related to the complex pathologic alterations that occur in the diabetic retina
and are not yet understood fully. 33
On evaluating the relationship between MOPP and DR among both genders, we found that in men, a higher MOPP was
associated with STDR and CSME; whereas in women, it was associated with any DR and non-STDR. However, the size
of the differences found (in mm of Hg) was very small and most had only borderline statistical significance which
disappeared on multivariate analysis. Moss et al reported that a higher MOPP predicted higher incidence and progression
of DR in younger-onset patients. 12 Patel et al reported a higher MOPP in the DR group when compared with the non-
diabetic control subjects and a higher MOPP in the PDR group than in the no DR group. 8 Another report also showed that
low MOPP appeared to protect against DR. 13 Langham et al suggested that ophthalmic arterial blood pressure and MOPP
decreased with worsening retinopathy. 14 However, they did not report calculations of MOPP in their series of 33 patients
and their suggestion was based on the indirect evidence of decrease in the choroidal blood flow with severity of
retinopathy in diabetes. Roy et al observed that after adjusting for the duration of diabetes, patients with a higher MOPP
13

were, on an average, twice as likely to have macular edema and severe hard exudates compared with those with lower
MOPP. 15
Thus, there is contradictory evidence in literature regarding the relationship of MOPP with DR. However, none of these
reports studied the gender-wise association, which might explain these differences. A recent study evaluated the
distribution of MOPP and its association with open angle glaucoma and found that the association was stronger in women
than in men. 25 This was attributed to the more frequent occurrence of vascular dysregulations among women in white
populations. In the present study, as depicted in table 1, women subjects had higher BMI as compared to men subjects.
Earlier, we reported an increased prevalence of obesity, defined by BMI, in women compared to men. 22 Increasing
evidence for the role played by adipocytokines like adiponectin, 34 leptin 35-36 , hepatocyte growth factor 37 and Zinc- 2-
Glycoprotein 38 in pathogenesis of DR and the reports of inverse association between sex-hormone-binding globulin and
insulin levels in men and women 39-40 prompted us to evaluate the gender differences between MOPP and DR. However,
we did not find any significant association of MOPP with DR, non-STDR and STDR on multivariate analysis.
Though, direct relationship of MOPP and DR has not been studied in many reports, there are many studies which have
evaluated the association of retinal blood flow with DR. An overview of retinal perfusion abnormalities in the different
stages of DR shows contradictory findings . 2 One of the first hints of altered retinal blood flow in patients with diabetes
mellitus came from Kohner et al, 41-42 who reported an increased retinal blood flow in patients with absent or mild, but not
with moderate or severe DR. The lack of increased blood flow in those with severe DR was explained on the
14

asis that the blood vessels were so diseased that it could not respond even to a strong autoregulatory stimulus.
Increased retinal blood flow in the early stages of DR and decreased retinal blood flow in PDR was also observed in
subsequent reports. 43-44 By contrast, Blair et al did not observe an alteration of mean retinal circulation time in the early
retinal damage but reported prolongation in PDR. 45 Yoshida et al reported increasing blood flow with the progression of
background DR. 46 In Type 1 diabetic patients, Bursell et al reported an increased mean circulation time indicative of
reduced retinal blood flow in subjects with no apparent DR 47 and a sequential decrease in mean circulation time with
advancing NPDR. 48 Another report observed a shift from decreased to increased retinal blood flow with progression of the
disease in Type 1 diabetes. 49 Patel et al reported an increase in the total retinal blood flow with progression of DR,
showing highest values in patients with PDR. 8 However, evidence from a variety of other studies showed that retinal
vasodilatation occurred before the clinical onset of DR in patients with diabetes, 50,2 and increased ocular blood flow was
observed in patients having background DR. 51,2
Thus, despite the contradictory results, there is evidence that both increased and decreased retinal blood flow is
detrimental for the development of DR. 2 However, it should be considered that alterations in MOPP cannot be directly
correlated to alterations in retinal blood flow. In the late stages of DR, the nature of ocular perfusion abnormalities appears
to strongly depend on glycemic control as well as on the specific pathologic features. 2
15

The limitations of our study included its cross-sectional design and its focus on patients with Type 2 diabetes only.
Whether our results can be extrapolated to patients with Type 1 diabetes is unclear. Another limitation is the unavailability
of data on how many were treated for high IOP or high blood pressure. Since this information is not available, the
treatment is a possible confounder in this study. Also, we did not study the retinal blood flow in our study population. It will
be interesting to study the retinal blood flow and MOPP among both genders.
On univariate analysis, we found very small gender differences in MOPP (of 1 mm of Hg, which is about 2% of the mean),
which are probably of no clinical significance. On multivariate logistic regression analysis of MOPP with DR with
sequential adjustment of risk factors, we did not find any statistical association between MOPP and DR. However, the
present study evaluated the MOPP association at a single point of time rather than prospectively. Hence, future
prospective studies may provide more information about the association between the MOPP and DR, if any, though the
clinical significance of such an association seems little only.
Conclusion
We report no association of MOPP with DR, non-STDR and STDR. There seems to be very little evidence for a link
between MOPP and DR, at least for a link that matters. Since DR is a multifactorial disease and perfusion pressure and
vascular factors are likely to be involved in its pathophysiology, it might be more informative to evaluate these
associations in prospective studies.
16

Acknowledgements:
We acknowledge the support of RD Tata Trust, Mumbai, for this project.
17

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24

Figure Legends
Fig 1: Genderwise distribution of blood pressure, mean ocular perfusion pressure and intraocular pressure in the study
population with Type 2 diabetes
25

Table 1: Baseline characteristics of the study population
Overall
Mean ± SD
Men Women p
n 1368 723 645
SBP (mm of Hg) 139.00 ± 20.8 137.05 ± 20.1 141.30 ± 21.8

Table 2: Systemic factors associated with mean ocular perfusion pressure in the study population
MOPP range (mm Hg)
26.2-46.4 46.5-51.4 51.5-57.5 57.6-90.2 p*
n 357 328 343 340
Age (years) 1.00 (Reference) 1.00 (0.99-1.02) 1.01 (0.99-1.03) 1.03 (1.01-1.05) 0.035
Gender (female) 1.00 (Reference) 1.34 (0.85-2.09) 1.37 (0.86-2.18) 0.87 (0.54-1.40) 0.054
Duration of diabetes (years) 1.00 (Reference) 0.99 (0.96-1.02) 1.01 (0.98-1.04) 0.97 (0.94-1.00) 0.389
Age of onset of diabetes
(years)
1.00 (Reference) 1.00 (0.99-1.02) 1.00 (0.98-1.02) 1.03 (1.01-1.05) 0.028
HbA1c>7 1.00 (Reference) 1.47 (1.05-2.06) 1.29 (0.92-1.80) 1.05 (0.74-1.50) 0.588
Generalized obesity
defined by BMI
1.00 (Reference) 0.85 (0.40-1.81) 0.49 (0.21-1.18) 0.90 (0.40-2.02)

Table 3: Association of mean ocular perfusion pressure with diabetic retinopathy and diabetic maculopathy
Overall
MOPP (mm of Hg)
Men Women
n Mean±SD p* n Mean±SD p* n Mean±SD p*
Retinopathy
No DR 1124 52.3±8.9 ref 571 51.9±8.6 ref 553 52.7±9.1 ref
Any DR 244 53.6±9.6 0.042 152 52.6±9.1 0.379 92 55.2±10.4 0.008
Non-STDR 200 53.4±9.6 0.112 123 51.9±8.6 1.00 77 55.8±10.7 0.006
STDR
Maculopathy
No
44 54.4±9.7 0.126 29 55.5±10.5 0.03 15 52.3±7.9 0.866
maculopathy 164 53.7±9.4 ref 103 52.2±8.2 ref 61 55.2±10.8 ref
Non-CSME 64 53.5±10.5 0.889 40 52.6±11.1 0.814 24 55.0±9.5 0.937
CSME 16 53.4±8.8 0.903 9 58.0±8.2 0.044 7 47.6±5.7 0.073
MOPP= Mean ocular perfusion pressure, DR= Diabetic retinopathy, STDR= Sight threatening diabetic
retinopathy, CSME= Clinically significant macular edema
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Table 4: Multivariate logistic regression analysis of MOPP with DR with sequential adjustment of risk factors
Association of MOPP with DR, non-STDR No DR vs
No DR vs
No DR vs
and STDR
any DR
non-STDR
STDR
OR (95% of CI) p OR (95% of CI) p OR (95% of CI) p
MOPP (Unadjusted) 1.01 (0.99-1.03) 0.134 1.01 (0.99-1.02) 0.403 1.02 (0.99-1.06) 0.111
Adjusted for gender 1.01 (0.99-1.03) 0.094 1.01 (0.99-1.02) 0.333 1.03 (0.99-1.06) 0.088
Adjusted for age, gender 1.01 (0.99-1.03) 0.102 1.01 (0.99-1.02) 0.343 1.03 (0.99-1.06) 0.093
Adjusted for age, gender, duration of DM 1.02 (1.01-1.03) 0.032 1.01 (0.99-1.03) 0.185 1.03 (1.00-1.07) 0.051
Adjusted for age, gender, duration, BMI 1.03 (1.01-1.04) 0.003 1.02 (1.00-1.03) 0.047 1.04 (1.01-1.07) 0.018
Adjusted for age, gender, duration, BMI,
HbA1c
1.03 (1.01-1.04) 0.003 1.02 (1.00-1.03) 0.05 1.04 (1.01-1.07) 0.020
Adjusted for age, gender, duration, BMI,
HbA1c, cholesterol
1.03 (1.01-1.04) 0.003 1.02 (1.00-1.04) 0.047 1.04 (1.01-1.07) 0.021
Adjusted for age, gender, duration, BMI,
HbA1c, cholesterol, HDL
1.03 (1.01-1.04) 0.003 1.02 (1.00-1.03) 0.047 1.04 (1.00-1.07) 0.028
Adjusted for age, gender, duration, BMI,
HbA1c, cholesterol, HDL, TG
1.03 (1.01-1.04) 0.003 1.02 (1.00-1.04) 0.045 1.04 (1.00-1.07) 0.028
Adjusted for age, gender, duration, BMI,
HbA1c, cholesterol, HDL, TG, albuminuria
1.02 (1.00-1.03) 0.048 1.02 (0.99-1.03) 0.101 1.02 (0.98-1.05) 0.368
Adjusted for age, gender, duration, BMI,
HbA1c, cholesterol, HDL, TG,
albuminuria, WC
1.02 (1.00-1.03) 0.048 1.02 (0.99-1.03) 0.101 1.02 (0.98-1.05) 0.38
Adjusted for age, gender, duration, BMI,
HbA1c, cholesterol, HDL, TG,
albuminuria, WC, onset of DM
1.02 (0.99-1.03) 0.149 1.02 (0.99-1.03) 0.312 1.02 (0.98-1.05) 0.358
MOPP= Mean ocular perfusion pressure, DR= Diabetic retinopathy, STDR= Sight threatening diabetic retinopathy,DM=Diabetes mellitus, BMI=
Body mass index, HbA1c= Glycosylated hemoglobin, HDL=High density lipoproteins, TG= Triglycerides, WC= Waist circumference
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