Clinical profile and associated risk factors of diabetic retinopathy at a tertiary eye center in Brunei Darussalam

Abstract

PURPOSE:

The purpose of the study was to determine the proportion of diabetic retinopathy (DR) among individuals with type II diabetes mellitus (T2D) and its associated risk factors.

MATERIALS AND METHODS:

This was a retrospective analysis of 988 DR outpatients attending a tertiary eye center, Brunei Darussalam, between January 1, 2021, and December 31, 2021.

RESULTS:

Eight hundred and fifty one patients (56.8 ± 10.9 years) with a total of 1702 eyes were included. The relative proportion of nonproliferative DR (NPDR) (n = 985, 59.1%) was higher than proliferative DR (PDR) (n = 681, 40.9%), especially in females (32.8%) and Malays (53.4%). The largest DR age groups were NPDR 60–69 years (22.7%) and 50–59 years, with PDR (13.6%). The mean average risk factors between NPDR and PDR only showed marginal differences. The PDR group received more laser treatment (37.2%) than the NPDR group (15.0%). Using a multivariate logistic regression model, visual acuity (VA), measured by logMAR, was significantly associated with differentiating PDR from NPDR. For each single unit increase in logMAR, the risk of PDR increased by 3.58 times (95% confidence interval: 3.04–4.22).

CONCLUSION:

The relative prevalence of NPDR was higher than PDR; however, variables such as hypertension, hyperlipidemia, duration of diabetes, weight, gender, and ethnicity were not strong determinants to differentiate between the two types. VA was associated with progression to PDR. This study highlights the need for early detection, regular screening, and patient education as preventive measures toward the progression of DR.

Introduction

Diabetes mellitus (DM) with an estimated prevalence of 9.7% in 2016,[1] accounted for 10.1% of the total deaths in Brunei Darussalam in 2017,[2] making it a major public health concern in the country. Diabetic retinopathy (DR), one of its most common microvascular complications, is a major cause of irreversible blindness and visual loss. Globally, the prevalence of DR in adults was estimated to affect 103 million individuals in 2020 and is projected to increase to 161 million individuals by 2045.[3] It was a leading global cause of the 0.86 million cases of blindness reported in persons over 50 years in 2020.[4] A meta-analysis of publications from 2015 to 2018 by the International Diabetes Federation[5] found that the global prevalence for any DR was 27.0%, 25.2% for nonproliferative DR (NPDR), 1.4% for proliferative DR (PDR), and 4.6% for diabetic macular edema, with an estimated prevalence of 12.5% DR for Southeast Asia. A 2017 cross-sectional study in Indonesia reported a prevalence of 9.4%–11.1% for NPDR, 12.1% PDR, but 26.3% for sight-threatening DR,[6] indicating a higher risk of blindness with the severity and progression of retinopathy. Mitigating DR before it progresses to the sight-threatening irreversible PDR stage is crucial for preserving sight. Current treatments for PDR include panretinal photocoagulation (PRP), antivascular endothelial growth factor (VEGF) intravitreal injections, and surgery. Early PRP laser treatment can preserve vision up to 50% in severe DR or high-risk PDR patients with uncontrolled diabetes, defaulters, or advanced retinopathy in the other eye,[7] whereas anti-VEGF intravitreal injections for 2 years retard retinal neovascularization.[8]

Commonly identified risks for vision loss include the duration of DM, obesity, hypertension, renal disease, uncontrolled DM, and hyperlipidemia.[9,10] Optimal control of DM and its associated systemic conditions can reduce sight-threatening retinopathy and improve the prognosis after treatment.[11] Good glycemic control and blood pressure can slow DR progression.[12] Longer duration of DM and poorly controlled DM are associated with a greater risk of developing DR[13] to occur between five and seven years of type II DM (T2D). Although there have been studies exploring the attributable factors to DM in Brunei Darussalam, to the best of our knowledge, there are no studies identifying the demographics of the stages of DR or factors that are linked to its progression at a tertiary eye care facility. Despite a lower prevalence of DM in 2017 compared to neighboring countries (13.7% in Singapore[14]) and a declining trend (17.39%[15] to 14.39% in 2022 in Malaysia[16]), Brunei has the highest reported obesity prevalence among Southeast Asian countries, at 28.2% (2015–2016).[17] That emphasizes the importance of exploring further mitigating factors that would help to take preventive measures to reduce the continuous burden of DM, which is the third leading non-communicable cause of death in the Sultanate.[18] A Singaporean-Malays study indicated that 10% of T2D had sight-threatening retinopathy,[19] which is particularly concerning as most of the Bruneian population are Malays, estimated at around 67.3%.[20]

Aims

This study aims to determine the proportion of types and severity of all DR eyes, using data from the main tertiary hospital, RIPAS. It also investigates the relationship between demographics (age, gender, and ethnicity), clinical profiles (HbA1c level, weight, blood pressure measurements, and duration of DM), and systematic comorbidities (hypertension, dyslipidemia, and renal disease) in DR. The outcome of this study may assist in identifying the impact of DR on vision, as well as the financial implications of delayed treatment. This understanding would allow targeted intervention, such as increasing public awareness in controlling risk factors to limit the progression of DR. Potentially, this allows the introduction of new policies and guidelines to reduce the number of cases of sight-threatening retinopathy and underpin follow-up prospective studies.

Materials and Methods

This was a retrospective cross-sectional study of DR in T2D outpatients at a tertiary eye center, seen between January 2021 and December 2021. The tertiary eye center is situated in one of the four most densely populated districts, comprising 322,400 persons (72% of Brunei population).[20] Patient information was extracted from the digital management system (Bru-HIMS), categorized under the International Classification of Diseases (ICD-10) code H36.0 denoting DR, but this was checked against other data. The data extracted were the demographic (age, gender, and ethnicity), systemic history (duration of diabetes in years, weight in kilogram, HbA1c levels, and systolic and diastolic blood pressure measurements), presence of hypertension, hyperlipidemia, and renal disease, and the best-corrected visual acuity (BCVA). These measurements included those taken within six months of the patient’s last visit. DR was categorized by severity into mild NPDR (presence of microaneurysm [MA]), moderate (one hemorrhage or MA, and/or retinal hemorrhages, hard exudates, cotton wool spots, and venous beading), and severe NPDR (≥(4-2-1 rule), >20 intraretinal hemorrhages in four quadrants, venous beading ≥2 quadrants, IRMA ≥1 quadrant, and PRP laser), and PDR (any neovascularization of disc or elsewhere, pre-retinal/vitreous hemorrhage). This is an adaptation of the International Classification of DR[21,22] severity scale, a parsimonious version of the Early Treatment DR Study scale.[23] Diagnosis of the type of NPDR and PDR was based on ophthalmological findings recorded by the attending ophthalmologists at the time of patients’ visits. Ethical approval was obtained from the Institute of Health Sciences Research Ethics Committee and the Medical and Health Research Ethics Committee (UBD/PAPRSBIHSRECC/2022/133), with a waiver of consent due to the retrospective nature of the study.

Operational definitions

The data from each eye were categorized as coming for the worst or best eye, and these were analyzed separately. The worst eye was defined as the eye with the worst BCVA. If the eyes had the same BCVA, we selected the right eye as the worst eye. Visual impairment (VI) is defined in accordance with the World Health Organization: BCVA in the better-seeing eye,[24] mild VI is defined as a VA worse than 0.3 logMAR (6/12), moderate VI as worse than 0.5 logMAR (6/18), severe VA as worse than 1.0 logMAR (6/60), and blindness as worse than 1.3 logMAR (3/60). In other words, the larger the logMAR value, the worse the vision, 0 being normal (6/6).

Sample

The initial inclusion factor was all cases of DR, ICD-10, code H36.0 “diabetic retinopathy” for persons living with T2D who attended the tertiary eye center at RIPAS Hospital for the year 2021. Exclusions were patients with retinopathy associated with other pathologies such as carotid occlusive disease, glaucoma with optic nerve atrophy, retinal degenerations, previous trauma, past ocular surgery, missing data, and other ocular conditions such as opaque cataracts, corneal opacities, and phthisic eyes that had limited fundal view.

For the expected prevalence of 22.6% acquired from another district eye clinic,[25] the required sample size was 831 for the margin error or absolute precision of ±3% in estimating the prevalence with 95% confidence and considering the potential loss of missing data of 10%. With this sample size, the anticipated 95% confidence interval was (19.6%, 25.6%). This sample size was calculated using the Scalex SP calculator.[26]

Data analysis

Univariate analysis used R (version 4.3.1, R Foundation for Statistical Computing, Vienna, Austria) to identify demographic characteristics and clinical factors associated with NPDR and PDR, including diabetes duration, HbA1c levels, weight, blood pressure, dyslipidemia, and chronic kidney diseases (CKDs). Age was subdivided into groups: <40, 40–49, 50–59, 60–69, and ≥70 years, while other variables such as ethnicity, gender, total number of laser treatments and anti-VEGF intravitreal injections, and presence of systemic factors were reported as real numbers or percentages. Data from each patient’s latest visit were analyzed, with the diagnosis reported separately for each eye.

Multivariate linear and logistic regression models were formed using the MATLAB (Nantucket MA) functions fitlm and fitglm, respectively. The linear models examined the variables associated with VA outcomes. The logistic models examined the associations with the discrimination NPDR versus PDR and reported the odds (relative risk) of the fitted independent associations. In both types of models, the explanatory variables were duration of DM, obesity, HbA1c level, systemic risk factors, hypertension renal disease, and hyperlipidemia. Multivariate models were done for better eyes, and the worst eyes separately to compare the outcomes. These are additive models. That means there is a constant, or intercept, term and the fitted values for the putative explanatory variables are the differences from the constant term allowing the additive causal factors to have a P value. The continuous variables such as age, weight, and duration of DM had their mean values removed, so that they did not affect the constant term. This did not affect the fitted slopes. P < 0.05 was considered statistically significant.

Results

After the exclusion of repeated encounters, a total of 988 registered patients diagnosed with DR attending a tertiary eye center at RIPAS Hospital were included. A further 137 patients were excluded; ten were due to type I DM, five had gestational DM, and 40 because fundi could not be viewed or assessed due to cataracts, corneal opacities, and physical eyes. The remaining 82 patients were excluded due to incomplete data. Therefore, 851 subjects were included for subsequent analysis. Each eye was considered separately and analyzed; thus, there were 1702 eyes. The average age for the overall DR patients seen in 2021 was 56.8 ± 10.9 years (range: 26.0–89.0 years), with the highest age groups being 60–69 years (32.5%), followed by 50–59 years (31.0%). There were more females (55.8%) than males, and the majority were Malays (89.8%) [Figure 1].

Figure 1.

Probabilities of encountering nonproliferative diabetic retinopathy (NPDR) versus proliferative diabetic retinopathy and best-corrected visual acuity in the study population. (a) Relative prevalence by age of NPDR and proliferative diabetic retinopathy (PDR) for this study group. (b) logMAR acuity for best and worst eyes of the 851 subjects (0 is normal (6/6) and larger is poorer acuity, blind being >1.3 (3/60), see Methods). (c) logMAR acuity for eyes with NPDR (n = 991) and PDR (n = 711)

Of the 1702 eyes, 28 had no NPDR or PDR with the available clinical data leaving 1674 eyes. All of these had a fellow eye that was NPDR. Figure 1a gives the relative proportion for this sample population of NPDR and PDR by age group. The largest age DR groups were the 60-to 69-year-old range with NPDR (22.7%) and 50- to 59-year-olds with PDR (13.6%). Figure 1b and c shows poorer acuity in the worst eyes and PDR subjects. We also wanted to provide data on therapeutic laser use. That could not be clearly determined from the clinical data leaving 1666 eyes. Table 1 shows the resulting numbers of eyes affected by NPDR and PDR (n = 1666) for various demographic factors. There was a higher relative prevalence of NPDR (n = 985, 59.1%) compared to PDR (n = 681, 40.9%), especially in females (32.8%) and Malays (53.4%). 37.2% of the PDR group laser received treatment.

Table 1.

Distribution of all eyes (n=1666) affected by diabetic retinopathy including the type of treatments received and demographic factors

Variables	n (%)	NPDR, n (%)	PDR, n (%)
Age (years)
<40	126 (7.6)	27 (1.6)	99 (5.9)
40–49	301 (18.1)	165 (9.9)	136 (8.2)
50–59	517 (31.0)	290 (17.4)	227 (13.6)
60–69	546 (32.8)	378 (22.7)	168 (10.1)
≥70	176 (10.6)	125 (7.5)	51 (3.1)
Gender
Male	730 (43.8)	439 (26.4)	291 (17.5)
Female	936 (56.1)	546 (32.8)	390 (23.4)
Ethnicity
Malay	1495 (89.7)	889 (53.4)	606 (36.4)
Chinese	115 (6.9)	64 (3.8)	51 (3.06)
Others	56 (3.4)	32 (1.9)	24 (1.44)
Treatment
No laser	796 (47.8)	735 (44.1)	61 (3.7)
Laser	870 (52.2)	250 (15.0)	620 (37.2)
No anti-VEGF injection	1524 (91.5)	905 (54.3)	619 (37.15)
Anti-VEGF injection	142 (8.5)	80 (4.8)	62 (3.7)

PDR=Proliferative diabetic retinopathy, NPDR=Non-PDR, VEGF=Vascular Endothelial Growth Factor

Clinical profile and systemic risk factors

Most of the DR patients in this study have systemic comorbidities such as hypertension (n = 786, 94.1%), dyslipidemia (n = 728, 87.2%), and renal disease (n = 257, 30.8%). The NPDR group had a higher proportion of hypertension (n = 448, 53.7%) and hyperlipidemia (n = 417, 50.0%), whereas the PDR group had higher renal disease (n = 130, 15.6%). About 30.8% of DR patients had CKD. The mean serum HbA1c level was 9.40 ± 8.58 (mean ± standard deviation) in NPDR. PDR and NPDR had similar durations of diabetes that were not significant. The only variables that were significant in differentiating NPDR from PDR in univariate analyses were HbA1c and diastolic BP [Table 2].

Table 2.

Clinical characteristics for diabetic retinopathy for worst eye (n=851 patients)

Variables	NPDR	PDR	P
Systolic BP (mmHg)	143.02±18.62	145.10±20.34	0.062
Diastolic BP (mmHg)	76.78±11.10	78.24±11.10	0.030
Duration (years)	13.11±7.78	13.33±9.02	0.356
HbA1c	9.40±8.58	8.60±2.36	0.043

The values denote mean±SD. NPDR=Non-PDR, PDR=Proliferative diabetic retinopathy, BP=Blood pressure

Multivariate logistic regression was performed to determine which variables were independently associated with NPDR versus PDR. A small number of eyes that could not be classified (n = 36) as either NPDR or PDR were excluded. Table 3 shows the results for the worst eyes. As mentioned in the methods, all the explanatory variables examined in the model are listed in the Supplementary Table 1. The outcome was parsimonious: only logMAR acuity and age were significant independent determinants of PDR as compared to NPDR. Every single unit step of logMAR increases the risk of PDR by 3.58 times (SE ranging from 3.04× to 4.22×). The effect of age was interesting, stating that age greater than the mean age reduced risk by 0.94× for every year older than the mean. The same model was used for the best eyes [Supplementary Table 2] and yielded similar results for BCVA and age: 3.76× and 0.94× respectively. Kidney disease increased PDR risk by 1.57× (P = 0.041).

Table 3.

Multivariate logistic regression model to determine factors that are associated with nonproliferative diabetic retinopathy versus proliferative diabetic retinopathy for the worst eye for the 848 subjects with complete datasets

	Estimate	SE	t-statistic	P	Odds	Low-SE	High-SE
Intercept	−2.766	0.632	−4.38	0.0000	0.06	0.03	0.12
HbA1c	−0.042	0.036	−1.14	0.2542	0.96	0.92	0.99
LogMAR	1.276	0.163	7.82	<0.001	3.58	3.04	4.22
Age (years)	−0.060	0.011	−5.67	<0.001	0.94	0.93	0.95
Weight (kg)	0.006	0.007	0.94	0.3451	1.01	1.00	1.01
Duration of DM (years)	0.003	0.012	0.28	0.7781	1.00	0.99	1.02
Male	−0.341	0.216	−1.58	0.1137	0.71	0.57	0.88
Chinese	0.711	0.395	1.80	0.0721	2.04	1.37	3.02
Other ethnicity	0.679	0.592	1.15	0.2513	1.97	1.09	3.56
Hypertension, yes	0.225	0.448	0.50	0.6147	1.25	0.80	1.96
Hyperlipidemia, yes	−0.274	0.318	−0.86	0.3884	0.76	0.55	1.04
Renal disease, yes	0.250	0.217	1.15	0.2506	1.28	1.03	1.59

SE=Standard error, DM=Diabetes mellitus, HbA1c=Glycated hemoglobin

Supplementary Table 1.

Linear model of the determinants of LogMAR acuity in the best eyes

	Estimate	SE	t-statistic	P
Intercept	0.255	0.092	2.78	0.0055
HbA1c	−0.001	0.002	−0.71	0.4756
Age (years)	0.005	0.001	4.00	0.0001
Weight (kg)	−0.001	0.001	−1.69	0.0906
DM duration (years)	−0.004	0.001	−2.55	0.0110
Male	−0.034	0.025	−1.34	0.1793
Chinese	−0.061	0.045	−1.35	0.1763
Other ethnicity	0.130	0.064	2.04	0.0413
Hypertension - yes	0.073	0.050	1.46	0.1451
Hyperlipidemia - yes	0.016	0.035	0.47	0.6377
Renal disease - yes	0.053	0.025	2.11	0.0355
Mild NPDR	−0.038	0.081	−0.47	0.6406
Moderate NPDR	−0.006	0.077	−0.08	0.9332
Severe NPDR	0.023	0.085	0.27	0.7841
PDR	0.146	0.077	1.89	0.0592

NPDR=Non-PDR, PDR=Proliferative diabetic retinopathy, DM=Diabetes mellitus, HbA1c=Glycated hemoglobin, SE=Standard error

Supplementary Table 2.

Logistic regression model of determinants of nonproliferative diabetic retinopathy versus proliferative diabetic retinopathy for the best fellow eyes

	Estimate	SE	t-statistic	P	Odds	Low-SE	High-SE
Intercept	−2.193	0.630	−3.48	0.0005	0.11	0.06	0.21
HbA1c	−0.064	0.043	−1.49	0.1371	0.94	0.90	0.98
LogMAR	1.326	0.328	4.04	0.0001	3.76	2.71	5.23
Age (years)	−0.066	0.011	−6.03	0.0000	0.94	0.93	0.95
Weight (kg)	−0.005	0.007	−0.78	0.4364	0.99	0.99	1.00
Duration of DM (years)	0.007	0.012	0.56	0.5771	1.01	0.99	1.02
Male	−0.128	0.220	−0.58	0.5610	0.88	0.71	1.10
Chinese	0.352	0.399	0.88	0.3773	1.42	0.95	2.12
Other ethnicity	0.067	0.614	0.11	0.9136	1.07	0.58	1.97
Hypertension, yes	−0.220	0.445	−0.49	0.6211	0.80	0.51	1.25
Hyperlipidemia, yes	−0.269	0.313	−0.86	0.3896	0.76	0.56	1.04
Renal disease, yes	0.450	0.221	2.04	0.0414	1.57	1.26	1.96

DM=Diabetes mellitus, HbA1c=Glycated hemoglobin, SE=Standard error

In the model of Table 2, the largest determinant of having PDR was BCVA. We, therefore, examined linear models examining which factors were associated with poorer vision (greater logMAR values). These were fitted for the worst eyes and the fellow best eyes. Table 4 shows the results for the worst eyes. Again, all the explored explanatory variables are listed in [Table 1]. A difference compared to Table 3 is that we now include a 4-level factor for the grades of DR from mild, moderate, and severe NPDR and PDR [the bottom 4 rows of Table 4]. Like the NPDR versus PDR model of Table 3, increasing age worsens logMAR by 0.006 per year (P = 0.0092). Unlike Table 3, weight, hyperlipidemia, and renal disease were significant. The weight factor was relative to the mean, so it appeared to decrease VA in younger patients by 0.004 steps per kilogram (P = 0.0139). Hyperlipidemia appeared to improve vision by -0.183 logMAR steps (P = 0.0094) [Table 3]. Renal disease was significant, worsening acuity by 0.216 logMAR units (P < 0.0001). Given the outcome of Table 4, it is not surprising that the PDR is a significant determinant of logMAR acuity, with PDR eyes having 0.358 steps higher logMAR values. NPDR is less likely to involve the fovea and so appeared not to determine VA. The intercept of Table 3 includes eyes that could not be classified into these four steps, as well as persons of the mean age and weight, Malays, females, and those without, hyperlipidemia, renal disease, or hypertension.

Table 4.

Worst eye multivariate model of the determinants of logMAR acuity for the same 848 subjects with complete datasets as in Table 3

	Estimate	SE	t-statistic	P
Intercept	0.771	0.195	3.95	0.0001
HbA1c	−0.004	0.003	−1.15	0.2519
Age (years)	0.006	0.002	2.61	0.0092
Weight (kg)	−0.004	0.002	−2.47	0.0139
DM duration (years)	−0.004	0.003	−1.51	0.1324
Male	0.018	0.050	0.35	0.7243
Chinese	−0.071	0.091	−0.78	0.4351
Other ethnicity	0.029	0.128	0.23	0.8211
Hypertension - yes	0.055	0.100	0.55	0.5859
Hyperlipidemia - yes	−0.183	0.070	−2.60	0.0094
Renal disease - yes	0.216	0.051	4.26	<0.0001
Mild NPDR	−0.169	0.180	−0.94	0.3479
Moderate NPDR	−0.123	0.170	−0.72	0.4709
Severe NPDR	−0.051	0.187	−0.27	0.7870
PDR	0.358	0.171	2.09	0.0365

Variables that were significant in determining DR severity. SE=Standard error, NPDR=Non-PDR, PDR=Proliferative diabetic retinopathy, DM=Diabetes mellitus, HbA1c=Glycated hemoglobin, DR=Diabetic retinopathy

The best-eye model is provided in Supplementary Table 1 and is summarized here: the significantly associated variables were like those for the worst eye and were age duration of DM (P = 0.011), and renal disease (P = 0.035). Longer duration of diabetes showed improvement in logMAR, probably due to better diabetic control in older people. Renal disease worsened the logMAR by 0.053 units (P = 0.0355), which is less severe than in the worst-eye model [Table 4].

Table 5 shows the distribution for mild, moderate, and severe acuity and blindness using the criteria provided in the Methods. Of the PDR subjects, 16.3% had a moderate acuity (0.5 logMAR, 6/18) and blindness. The figure for moderate NPDR was 9.2%.

Table 5.

Severity of visual impairment with diabetic retinopathy

VI severity	Mild NPDR	Moderate NPDR	Severe NPDR	PDR	Not classified
Normal	143 (8.4)	406 (23.9)	75 (4.4)	294 (17.3)	26 (1.5)
Mild	25 (1.5)	104 (6.1)	14 (0.8)	109 (6.4)	0 (0.0)
Moderate	17 (1.0)	119 (7.0)	28 (1.6)	135 (7.9)	6 (0.4)
Severe	3 (0.2)	13 (0.8)	4 (0.2)	38 (2.2)	0 (0.0)
Blindness	6 (0.4)	23 (1.4)	5 (0.3)	105 (6.2)	4 (0.2)

Values above denote n (%); VI=Visual impairment, NPDR=Non-PDR, PDR=Proliferative diabetic retinopathy

Discussion

In this study, we have collected valuable data on different severities of DR. This improves on early studies on DR done in Brunei[25] that had made making comparative data and references limited. Hopefully, this study will form the basis for future studies examining the effectiveness of any changes arising. We studied the sociodemographics of NPDR and PDR patients. Both genders had a similar proportion of any DR; however, females appeared to have a higher rate of both NPDR (30.8%) and PDR (24.6%). The mean age of patients with diabetes was 56.8: slightly younger in PDR at 54.1 and 58.7 for NPDR. However, categorically, the age group of 60–69 years had the highest number of both PDR and NPDR. Age was a significant determinant of a diagnosis of PDR versus NPDR [Table 3 and Supplementary Table 2].

The study Malay population in Brunei Darussalam was 89.7% (1495/1666), followed by Chinese and others. This is in line with the majority of Brunei Darussalam’s population being predominantly Malays, 65.4% in the latest national statistics for 2021.[27] This could have accounted for the higher proportion of Malays affected with NPDR (53.4%) and PDR (36.4%).

Comparative regional studies on the severity of DR among Malays are sparse. In Southeast Asia, the predominantly Malay population are mainly found in Malaysia and Indonesia, whereas in other countries, Malays represent a minority group. This limits direct regional comparison. Given that Malaysia, like Brunei, has a predominantly Malay population, our study showed a higher proportion of NPDR and PDR compared to the prevalence study in Indonesia (28.0% NPDR and 12.1% PDR).[6]

While studies on DR progression among Malays are sparse, data on DR among T2D offer valuable comparisons. A study in Indonesia reported a DR prevalence of 43.1%,[6] whereas Malaysia reported a slightly lower of 39.3%.[28] In Singapore, where Malays form a minority group in a predominantly Chinese population, DR prevalence was higher with 1 in 10 Malay adults with diabetes (35.0%).[19] Although there is a lack of nationwide study in Brunei, a study from one of the smaller district reported an overall DR prevalence of 22.6%. The higher proportion of NPDR and PDR in this study does not align with regional DR prevalence studies, possibly because, the Indonesian and Malaysian studies reflect DR prevalence among T2D, whereas our study included only patients with a definitive DR diagnosis. Nevertheless, the regional studies are particularly relevant within Brunei’s predominantly Malay population, where cultural and lifestyle factors may influence a higher prevalence of DM, potentially increasing the risk of DR. The observed regional similarities may be influenced by similar dietary patterns, genetic predispositions, and healthcare systems. Conversely, differences might be due to variations in healthcare accessibility, screening programs, or public health policies. This study provides one of the first insights at a tertiary center, into NPDR and PDR proportion within Brunei’s predominantly Malay population, adding to the limited data available in Southeast Asia. By drawing comparisons with neighboring countries, our findings contribute to understanding regional epidemiological patterns and may inform future healthcare strategies.

It was one of the objectives of this study to find the number of patients getting treatment. 52.2% (870/1666) of DR patients had received laser treatment, and 8.5% had received anti-VEGF intravitreal injections. Both NPDR and PDR had a similar proportion of anti-VEGF treatment; this may be due to other conditions, such as macula edema, which was not investigated in this study. As expected, PDR has a larger number of laser procedures in comparison to NPDR.

The onset of DR has been reported to occur 5–7 years after a person is diagnosed with DM;[29] however, we found a longer duration of 12–13 years. This could be due to an efficient referral system from our general practitioners, who refer diabetics to us quite promptly. If patients are lost or default, they are referred to other specialties to minimize missed DM eye screening appointments. Glycemic control averages about 8% in these patients. These risk factors were not determinants of PDR except HbA1c and BP measurement. The measurements were taken within 6 months of the last visit. These may not be the true representative of the whole control of systemic risk factors in patients. We noted that those with hyperlipidemia have better vision but that could be a treatment effect.

Visual acuity was found to be strongly associated with DR severity. Hence, we wanted to ascertain if other variables were associated with determining NPDR from PDR. As logMAR is significant in determining PDR, we have used logMAR as a continuous measure for DR severity. From this analysis, age, weight, and renal disease were determinants of PDR. These findings are similar to other studies.[10,12]

Our findings have important implications for public health policies on diabetes and its complications, particularly in resource-limited settings. With the growing burden of DR, integrating effective screening and early intervention is crucial. This study highlights key risk factors and patterns that can inform targeted screening, patient education, and resource allocation. In recent years, the implementation of artificial intelligence (AI)-assisted DR screening in all eye care facilities has enhanced accessibility and efficiency in detecting DR among diabetic patients. Future research could explore how AI-driven screening impacts patient outcomes, referral patterns, and long-term impact of AI-driven screening on disease severity distribution and healthcare resource allocation.

Strength and limitation

A key strength of this study is that the data were collected from the only tertiary eye center in the country, which serves as the main referral center for the most populous district. This makes our findings representative of the national population requiring specialized ophthalmic care. While including multiple centers across different districts could enhance external validity, the centralized nature of eye care in Brunei supports the applicability of our results.

However, the study’s retrospective design introduced certain limitations, including the unavailability of some clinical parameters. Systemic inflammatory and vascular biomarkers, which could offer deeper insights into DR progression, were not routinely collected, limiting their inclusion in our analysis. In addition, comorbidity data were gathered during the COVID-19 period, when healthcare disruptions may have affected routine assessments and follow-ups. As a result, patients had fewer clinic visits, and their disease control may not accurately reflect their usual disease state.

Furthermore, our study population consisted primarily of patients attending a tertiary eye center, which mainly manages diagnosed DR cases, including NPDR and PDR. Individuals with mild or undiagnosed DR often seek care at community eye clinics and may not have been captured in our cohort. This selection bias may limit the generalizability of our findings, particularly for early-stage DR. Nevertheless, the study population was from what could be considered, the largest in the country, from the most populous of the four districts in Brunei.

Future prospective studies incorporating a broader range of systemic inflammatory or vascular biomarkers including the use of fluorescein angiography for the classification of all cases, with longitudinal follow-up, would help identify the complex interplay of risk factors in DR progression. In addition, expanding data collection to include primary and secondary care centers would provide a more comprehensive understanding of DR across all severity levels and improve the generalizability of findings.

Conclusion

Almost all the variables, such as hypertension, hyperlipidemia, duration of diabetes, weight, gender, and ethnicity, were not strong determinants to identify NDPR versus PDR. The disease state is symmetrical between the eyes, with marginal differences. Therefore, it is of the utmost importance to intervene as early as possible as a preventive measure to avoid developing retinopathy. Patient education about DR and the importance of systemic risk factor controls is needed. Annual screening of diabetic patients is still very important, and it is essential to reach and access as much of the population as possible, especially in rural areas.

Data availability statement

The datasets generated and analyzed during the current study are not publicly available due to ownership restrictions and ethical considerations but are available from the corresponding author upon reasonable request.

Conflicts of interest

The authors declare that there are no conflicts of interests of this paper.

Funding Statement

Nil.