Abstract
Purpose
To evaluate the association of sickle-cell disease (SCD) and sickle-cell trait (SCT) disease with diabetic retinopathy (DR) in patients with diabetes mellitus (DM).
Design
Population-based, retrospective cohort study utilizing data from the TriNetX Research Network, including 119 million patients across 80 health care organizations worldwide.
Participants
Diabetes mellitus patients (type 1 [T1DM] or 2 [T2DM]), with or without SCD and SCT, were included. Three cohorts were analyzed, including (1) DM patients without SCD, SCT, or sickle-cell/hemoglobin-C; (2) DM with SCD; and (3) DM with SCT.
Methods
All patients with DM were categorized into 3 cohorts based on the presence of SCD and SCT. Each cohort underwent 1:1 propensity score matching for demographics, blood glucose levels, hemoglobin A1C, and other relevant comorbidities.
Main Outcome Measures
Risk of DR in DM patients with and without SCD or SCT.
Results
There was no significant difference in the risk of any T1DR between those with and without SCD. However, for those with SCT, there was a notable twofold increased risk for T1-proliferative DR (PDR) (relative risk [RR]: 2.03; 95% confidence interval [CI]: 1.33–3.01). In contrast, there was an elevated risk for any T2DR in patients with SCD (RR: 1.50; 95% CI: 1.19–1.88), particularly due to higher PDR risks in T2DM patients (RR: 1.83; 95% CI: 1.29–2.60). The risk of mild to moderate T2DM non-PDR was also found to be higher in patients with SCT.
Conclusions
The risk of any DR was increased in T2DM patients with SCD or SCT, with increased risks for PDR in patients with SCT and T1DM. This indicates there may be a potential role of sickle-cell disorders in diabetic eye disease progression.
Financial Disclosure(s)
Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
Keywords: Diabetes mellitus, Diabetic retinopathy, Sickle cell disease, Sickle cell trait, Propensity score matching
Diabetes mellitus (DM), including both type 1 (T1DM) and type 2 (T2DM), represents an escalating global health challenge. It is characterized by chronic hyperglycemia due to defects in insulin secretion, insulin action, or both.1 Diabetes mellitus has been implicated in a host of severe long-term complications, including cardiovascular disease, kidney failure, nerve damage, and microvascular complications such as diabetic retinopathy (DR) and cataract.2, 3, 4, 5 Diabetic retinopathy, in particular, is a major concern due to its substantial contribution to disease burden, frequently leading to significant visual impairment and even blindness in adults.6, 7, 8, 9
Sickle-cell disease (SCD) and sickle-cell trait (SCT) disease are genetic hemoglobin (Hb) disorders characterized by the presence of sickle Hb.10,11 Full SCD (Hb), the more severe form, is associated with repeated vaso-occlusive crises, chronic hemolytic anemia, and systemic inflammation.12,13 On the other hand, SCT, usually milder, is characterized by the presence of both normal and HbS, with individuals generally asymptomatic under normal conditions.14 Sickle-cell trait is widely found in regions affected by malaria, such as sub-Saharan Africa, India, the Middle East, and in specific populations in Europe and the Americas.15 With rates of T2DM increasing, it has been suggested that a growing number of people will have both conditions concomitantly.16 Sickle-cell disease and SCT have been associated with an increased risk of microvascular17,18 and ocular complications,19 but their effects on the development and progression of DR in DM patients remain understudied.20
The investigation into the relationship between SCD, SCT, and the development of DR in DM patients is important for several reasons. It may shed light on whether these sickle cell disorders exacerbate the progression of diabetic ocular complications, providing crucial information for the risk assessment and management of these complications. Additionally, it could help identify therapeutic targets and preventive strategies, potentially improving patients’ outcomes. In this study, we sought to explore the association of SCD and SCT, and DR in a large, diverse cohort of patients with DM.
Methods
This is a population-based, retrospective cohort study. We utilized data from the TriNetX Research Network, a large database network of 119 million patients across 80 health care organizations worldwide. TriNetX is an international health research network that facilitates access to electronic health records—including diagnoses, procedures, medications, lab results, and genomic data—from numerous large-scale health care organizations. The data in this study were obtained from a subset of these health care organizations collectively known as the “Research” network and was performed in December 2023. This work used deidentified previously collected data. The study was determined to be exempt from the institutional review board approval at the University of Arkansas for Medical Sciences. The study complied with the tents of the Declaration of Helsinki.
We screened all patients’ data in the TriNetX research network for the presence of DM using International Classification of Diseases (ICD)-10 codes (ICD codes: E08-E13). We included all patients who had a diagnosis of T1DM or T2DM, dividing them into 3 cohorts. The first cohort included patients with DM with no history of sickle-cell disorders (ICD: D57.xx). The second cohort was those with DM and a diagnosis of SCD (ICD: D57 or D57.1), excluding those with SCT or sickle-cell/Hb-C disease. The third cohort comprised patients with DM and a diagnosis of SCT (ICD: D57.3), excluding those with SCD or sickle-cell/Hb-C disease. We excluded, from all cohorts, patients with any history of retinal disorders in diseases classified elsewhere (H36.xx), which includes proliferative and nonproliferative sickle-cell retinopathy.
The index date for each patient within a cohort was the day on which the patient first met the selected criteria for the cohort. The index event encapsulated events that transpired within the last 20 years only. We excluded patients who experienced their index event > 20 years back. We conducted 1:1 propensity score matching across cohorts based on demographic variables (age, sex, ethnicity, and race), blood glucose levels, HbS A1C, and the following confounding comorbidities with a 10-year lookback period: hypertension, chronic kidney disease, and hyperlipidemia. By employing propensity score matching, we achieved a balanced distribution of confounding factors between the groups, thereby enhancing their comparability.21 In each cohort, we tracked patients to evaluate the likelihood of developing DR as the main outcome measure. As a secondary outcome, we also analyzed the grade of retinopathy: mild nonproliferative DR (NPDR) (ICD: E11.32 and E10.32), moderate NPDR (ICD: E11.33 and E10.33), severe NPDR (ICD: E11.34 and E10.34), and proliferative DR (PDR) (ICD: E11.35 and E10:35). We also examined the comparative risk of having to undergo panretinal photocoagulation (PRP) (Current Procedural Terminology: 67228), vitrectomy (Current Procedural Terminology: 67040, 67041, 67042, and 67113), and intravitreal injections (Current Procedural Terminology: 67028) between cohorts.
We presented the baseline characteristics by averages and standard deviations for continuous variables and counts and proportions for binary variables. In addition, for all comparison points, we supplied the outcomes from the propensity score matching, encompassing standardized mean differences for each covariate before and after the matching process and the relative risk (RR). The threshold for statistical significance for this study was P < 0.05 with 2-sided tests.
Results
SCD vs. No Sickle-Cell Disorders Among T1 and T2 Diabetics
Our first cohort comparison was those with DM, with and without SCD. There were 7 352 765 patients with DM with no history of sickle-cell disorders and 4285 patients with DM and a diagnosis of SCD. We found the overall risk in patients with SCD was 2.85% for any T1DR (1.81% PDR) and 4.28% for any T2DR (2.01% PDR) across the study period. For comparison, the risk in patients without SCD or SCT was found to be 3.42% for any T1DR (1.78% PDR) and 3.54% for any T2DR (0.36% PDR). After matching, there were 4208 patients in each group. Table 1 shows the results of the propensity score matching. Overall, we found the risk of T1DR or T2DR in patients with SCD was only slightly higher in those without SCD (RR: 1.39; 95% confidence interval [CI]: 1.12–1.72, P = 0.002). We found that the risk of any T1DR (NPDR and PDR) was comparable between groups (RR: 1.26; 95% CI: 0.69 to −2.30, P = 0.445). The risk of mild (RR: 0.78; 95% CI: 0.34–1.75), moderate (RR: 1.00; 95% CI: 0.42–2.40), and severe (RR: 1.00; 95% CI: 0.42–2.40) T1-NPDR was comparable between patients with and without SCD. The risk of T1-PDR was also comparable between groups (RR: 1.50; 95% CI: 0.68–3.33, P = 0.317).
Table 1.
Propensity Score Matching Results Between Patients With DM Plus SCD and DM Minus Sickle-Cell Disorders
| Characteristics | Before Matching |
After Matching |
||||
|---|---|---|---|---|---|---|
| DM w/out SCD (n = 7 352 765) | DM with SCD (n = 4285) | Std. Diff. | DM w/out SCD (n = 4208) | DM with SCD (n = 4208) | Std. Diff. | |
| Age, mean (SD) | 59.3 (16.2) | 53 (18) | 0.368 | 52.3 (17.8) | 53 (18) | 0.039 |
| Sex, No. (%) | ||||||
| Male | 3 464 981 (48.98) | 1732 (41.16) | 0.158 | 1739 (41.33) | 1732 (41.16) | 0.003 |
| Female | 3 449 571 (48.76) | 2424 (57.61) | 0.178 | 2417 (57.44) | 2424 (57.61) | 0.003 |
| Ethnicity, No. (%) | ||||||
| Non-Hispanic/LatinX | 4 083 243 (57.72) | 2756 (65.49) | 0.160 | 2758 (65.54) | 2756 (65.49) | 0.001 |
| Hispanic/LatinX | 676 721 (9.56) | 264 (6.27) | 0.122 | 264 (6.27) | 264 (6.27) | < 0.001 |
| Race, No. (%) | ||||||
| White | 4 126 545 (58.33) | 1111 (26.40) | 0.682 | 1092 (25.95) | 1111 (26.40) | 0.010 |
| Black or AA | 1 116 860 (15.79) | 2198 (52.23) | 0.833 | 2207 (52.45) | 2198 (52.23) | 0.004 |
| Asian | 289 460 (4.09) | 69 (1.64) | 0.147 | 70 (1.66) | 69 (1.64) | 0.002 |
| American Indian or Alaskan Native | 33 731 (0.48) | 14 (0.33) | 0.023 | 19 (0.45) | 14 (0.33) | 0.019 |
| Native Hawaiian or Pacific Islander | 44 089 (0.62) | 10 (0.24) | 0.059 | 31 (0.73) | 10 (0.24) | 0.072 |
| Laboratory values, mean (SD) | ||||||
| Blood glucose | 144 (71.4) | 136 (73.6) | 0.105 | 137 (72) | 136 (73.6) | 0.009 |
| HbA1C | 7.15 (1.92) | 6.79 (1.9) | 0.186 | 6.85 (1.9) | 6.79 (1.9) | 0.031 |
| Comorbidities, No. (%) | ||||||
| Chronic kidney disease | 263 492 (3.73) | 828 (19.68) | 0.512 | 838 (19.84) | 828 (19.68) | 0.004 |
| Hypertension | 1 398 089 (19.76) | 2307 (54.82) | 0.777 | 2244 (53.33) | 2307 (54.82) | 0.030 |
| Hyperlipidemia | 703 657 (9.95) | 1355 (32.20) | 0.567 | 1316 (31.27) | 1355 (32.20) | 0.019 |
AA = African American; DM = diabetes mellitus; No. = number/frequency; SCD = sickle-cell disease; SD = standard deviation; Std. Diff. = standardized difference.
Those with “unknown” sex, ethnicity, and race were removed from analysis.
Overall, the risk for any T2DR, encompassing both NPDR and PDR, was found to be higher in patients with SCD compared with those without a sickle-cell disorder (RR: 1.50; 95% CI: 1.19–1.88, P < 0.001). We found that this significant risk difference was primarily driven by patients with PDR pathology (RR: 1.83; 95% CI: 1.29–2.60, P < 0.001). The risk of mild T2-NPDR was slightly higher in the SCD group (RR: 1.35; 95% CI: 1.04–1.82, P = 0.04). For moderate and severe T2-NPDR, there was no observed elevated risk of between groups (RR: 1.36; 95% CI: 0.81–2.32 and RR: 1.45; 95% CI: 0.67–3.13, respectively) (Fig 1). We next examined the risk of undergoing several key procedures between cohorts. Among patients with T1DM we found no elevated risk of PRP (RR: 0.67; 95% CI: 0.30–1.48, P = 0.313), IV injections (RR: 0.54; 95% CI: 0.28–1.02, P = 0.056), or vitrectomy procedures (RR: 0.63; 95% CI: 0.29–1.37, P = 0.235) between those with and without SCD. In patients with T2DM, we also observed no significant difference among those receiving PRP (RR: 1.43; 95% CI: 0.72–2.83, P = 0.302), IV injections (RR: 0.89; 95% CI: 0.56–1.43, P = 0.626), or vitrectomy procedures (RR: 1.29; 95% CI: 0.64–2.58, P = 0.479).
Figure 1.
Comparisons of patients with diagnoses of diabetes mellitus (DM) plus sickle-cell disease vs. DM without sickle-cell disorders after propensity score matching. Significance is indicated by confidence interval lines that do not cross risk ratio of 1. DR = diabetic retinopathy; T1DM = type 1 diabetes mellitus; T2DM = type 2 diabetes mellitus.
SCT vs. No Sickle-Cell Disorders Among T1 and T2 Diabetics
We next determined the impact of an underlying diagnosis of SCT in DM patients across outcomes. The overall risk in patients with SCT was 4.19% for any T1DR (2.79% PDR) and 5.73% for any T2DR (2.41% PDR). Table 2 shows the results before and after propensity score matching and included 12 895 patients before matching. After matching, there were 12 748 in both groups. The risk of any T1DR was found to be higher in patients with SCT compared with those without any sickle-cell disorder (RR: 1.70; 95% CI: 1.23–2.38, P = 0.002). The risk of mild (RR: 1.38; 95% CI: 0.79–2.42), moderate (RR: 1.50; 95% CI: 0.67–3.33), and severe (RR: 1.00; 95% CI: 0.42–2.40) T1-NPDR was comparable between patients with and without SCT. We found that the risk of T1-PDR was significantly higher in the SCT group compared with patients without a history of sickle-cell disorders (RR: 2.03; 95% CI: 1.33–3.01, P = 0.0008).
Table 2.
Propensity Score Matching Results Between Patients With DM Plus SCT and DM Minus Sickle-Cell Disorders
| Characteristics | Before Matching |
After Matching |
||||
|---|---|---|---|---|---|---|
| DM w/out SCD (n = 7 352 765) | DM with SCT (n = 12 895) | Std. Diff. | DM w/out SCD (n = 12 748) | DM with SCT (n = 12 748) | Std. Diff. | |
| Age, mean (SD) | 59.3 (16.2) | 50.2 (16.9) | 0.551 | 50.2 (16.9) | 50.2 (16.9) | 0.005 |
| Sex, No. (%) | ||||||
| Male | 3 464 981 (48.98) | 3377 (26.49) | 0.477 | 3380 (26.51) | 3377 (26.49) | 0.0005 |
| Female | 3 449 571 (48.76) | 9182 (72.03) | 0.489 | 9179 (72.00) | 9182 (72.03) | 0.0005 |
| Ethnicity, No. (%) | ||||||
| Non-Hispanic/LatinX | 4 083 243 (57.72) | 8872 (69.59) | 0.249 | 8895 (69.78) | 8872 (69.59) | 0.004 |
| Hispanic/LatinX | 676 721 (9.56) | 372 (2.91) | 0.277 | 351 (2.75) | 372 (2.91) | 0.009 |
| Race, No. (%) | ||||||
| White | 4 126 545 (58.33) | 494 (3.88) | 1.45 | 469 (3.68) | 494 (3.87) | 0.010 |
| Black or AA | 1 116 860 (15.79) | 9860 (77.35) | 1.56 | 9855 (77.31) | 9860 (77.35) | 0.001 |
| Asian | 289 460 (4.09) | 69 (0.54) | 0.28 | 86 (0.68) | 69 (0.54) | 0.017 |
| American Indian or Alaskan Native | 33 731 (0.48) | 20 (0.16) | 0.07 | 73 (0.57) | 20 (0.16) | 0.069 |
| Native Hawaiian or Pacific Islander | 44 089 (0.62) | 10 (0.08) | 0.09 | 65 (0.51) | 10 (0.08) | 0.079 |
| Lab values, mean (SD) | ||||||
| Blood glucose | 144 (71.5) | 135 (72.9) | 0.132 | 136 (73.3) | 135 (72.9) | 0.018 |
| HbA1C | 7.15 (1.92) | 7.04 (2.00) | 0.057 | 6.92 (1.93) | 7.04 (2.00) | 0.059 |
| Comorbidities, No. (%) | ||||||
| Chronic kidney disease | 262 049 (3.70) | 2068 (16.22) | 0.427 | 2038 (15.99) | 2068 (16.22) | 0.006 |
| Hypertension | 1 372 198 (19.39) | 7154 (56.12) | 0.818 | 7162 (56.18) | 7154 (56.12) | 0.001 |
| Hyperlipidemia | 687 949 (9.72) | 3771 (29.58) | 0.516 | 3759 (29.48) | 3771 (29.58) | 0.002 |
AA = African American; DM = diabetes mellitus; No. = number/frequency; SCD = sickle-cell disease; SCT = sickle-cell trait; SD = standard deviation; Std. Diff. = standardized difference.
Those with “unknown” sex, ethnicity, and race were removed from analysis.
Overall, the risk for any T2DR was found to be higher in patients with SCT compared with those without any sickle-cell disorder (RR: 1.75; 95% CI: 1.55–1.97, P < 0.0001). We found an elevated risk of mild (RR: 1.56; 95% CI: 1.35–1.82) and moderate (RR: 1.82; 95% CI: 1.38–3.3) T2-NPDR, with no increased risk of severe (RR: 1.47; 95% CI: 0.97–2.25) T2-NPDR between patients with and without SCT. The risk of T2-PDR was significantly higher in patients with SCT compared with those with no sickle-cell disorder (RR: 1.97; 95% CI: 1.63–2.40, P < 0.0001) (Fig 2). Among patients with T1DM we found no increased risk of having PRP (RR: 0.86; 95% CI: 0.56–1.33, P = 0.498), IV injections (RR: 0.90; 95% CI: 0.65–1.25, P = 0.549), or vitrectomy procedures (RR: 1.05; 95% CI: 0.69–1.60, P = 0.825) in those with SCT compared with those with DM without any history of SCT. In focusing on patients with T2DM we found a significantly elevated risk of PRP (RR: 1.61; 95% CI: 1.11–2.32, P = 0.001), IV injections (RR: 2.00; 95% CI: 1.52–2.64, P < 0.0001), and vitrectomy procedures (RR: 2.16; 95% CI: 1.47–3.19, P < 0.0001).
Figure 2.
Comparisons of patients with diagnoses of diabetes mellitus (DM) plus sickle-cell trait vs. DM without sickle-cell disorders after propensity score matching. Significance is indicated by confidence interval (CI) lines that do not cross risk ratio of 1. DR = diabetic retinopathy; T1DM = type 1 diabetes mellitus; T2DM = type 2 diabetes mellitus.
Discussion
This large population-based study examined the association between sickle-cell disorders and the coexistence of DR. We found that in patients with SCD, there is an elevated risk of PDR in patients with T2DM. In patients with SCT, we found an increased risk of PDR in patients with T1DM and T2DM. These findings suggest the importance of accounting for sickle cell disorders in DM patients' screening and clinical management.22, 23, 24
While the role of SCD and SCT in microvascular complications has been previously reported, this study provides data on the association of these sickle-cell disorders with DR. Our findings align with the consensus that SCD and SCT may accelerate the development of microvascular complications in diabetes,25, 26, 27 but extend this understanding to show specific impacts on DR stages and differential impact of SCD versus SCT in the setting of T1DM and T2DM. Our study shows that the impact of sickle-cell disorders appears more pronounced in patients with T2DM, especially for those with SCT, and most importantly, modulate PDR risk. Our findings corroborate the work by Skinner et al28 (2018), who showed significantly increased risks of DR in patients with SCT and T2DM (n = 60) compared with T2DM alone (n = 52). A plausible explanation for this difference could lie in the chronic hyperglycemia that often characterizes T2DM, exacerbating the already compromised red blood cell function in these individuals leading to increased vascular damage. In the Skinner et al study, they also showed a heightened stiffness in arteries, elevated blood viscosity, increased thixotropic index, and higher concentrations of plasma advanced glycation end-products in patients with SCT and T2DM, which may provide a vascular link for these observed elevated risks. This heightened vascular damage, chronic inflammation, and oxidative stress, common in both DM and sickle cell disorders, may contribute to an accelerated onset and progression of DR.29, 30, 31 Another study by Diaw et al32 (2015) was the first to show the impact of T2DM in patients with SCT. They found increased blood viscosity and higher levels of oxidative stress in patients with T2DM and SCT. A recent study utilizing large data from the United Kingdom Biobank found that SCT was significantly associated with an elevated risk of DM-related complications.33 Additionally, Vangipuarm et al, Jackson et al, and Nagpal et al,22,24 reported cases where vascular disorders, predominantly DM and SCT, may have resulted in a synergetic effect on the development of retinopathy. However, there are contradictory findings in the literature among other populations; a single-center study of 446 West Indian diabetic patients found no association between SCT and DR presence or progression,20 and a study of 200 patients from Saudi Arabia suggested a protective effect of SCT against the development and progression of DR.34
Another finding from our study was the differential impact of SCD and SCT on various stages of DR. While both conditions increased the risk of PDR, the overall impact appears more pronounced in patients with SCT. Bowers et al35 uncovered that individuals with SCT require a higher optimal hematocrit to maximize oxygen delivery. This implies a greater concentration of red blood cells is needed for optimal physiological function, which, as a side effect, leads to increased blood viscosity. In the context of our study, where patients with SCT exhibited a heightened risk of PDR, particularly in T2DM, this higher blood viscosity could be a contributing factor. The elevated hematocrit and resultant increased viscosity in SCT could be exacerbating the vascular damage, chronic inflammation, and oxidative stress that are characteristic of diabetes, particularly under the conditions of chronic hyperglycemia seen in T2DM. A potential mechanism, suggested by the findings of Bowers et al, involves impaired blood flow dynamics due to increased viscosity. This impaired hemodynamics could lead to more pronounced microvascular insults in the retinal vasculature, contributing to the pathogenesis of DR.35 The altered blood flow and shear stress could also amplify endothelial dysfunction and promote a prothrombotic state, thereby providing a plausible explanation for the increased incidence and severity of DR observed in our cohort of SCT patients with diabetes.
Our study has several strengths that enhance its validity and reliability. Firstly, utilizing a large, population-based cohort provides a diverse and representative sample, enhancing the generalizability of our findings. Moreover, applying propensity score matching allowed us to effectively control for potential confounding factors, including demographics and relevant systemic comorbidities. However, it is important to acknowledge the inherent limitations of a retrospective analysis. Despite our efforts to account for confounding variables, residual confounding is still possible due to unmeasured factors not included in our analysis. Additionally, misclassification bias may have occurred, as some cases of proliferative sickle retinopathy could have been misdiagnosed as PDR and vice versa. However, given the distinct phenotypical presentations of sickle retinopathy versus DR, we believe that any potential misclassification is likely to be minimal and unlikely to significantly impact our results. Caution also needs to be exercised when interpreting our findings in relation to the specific DR grading. Because of the clinical diagnosis of retinopathy grading, which may be made by clinicians without the use of fundus photography, inaccuracies can occur.36 However, we expect this type of error to be nondifferential across all groups. Furthermore, although SCT and SCD status are now tested in United States through newborn screening, asymptomatic individuals with SCT may be unknown to the affected individuals and/or their health care team.33 This may influence the accuracy of our findings. Lastly, it is crucial to consider the potential limitations associated with the generalizability of our findings. Variations in health care access and quality across different health care systems may influence the outcomes observed in our study. Therefore, caution should be exercised when extrapolating our results to populations with different health care contexts.
In conclusion, our study provides evidence that SCD and SCT may be associated with an increased risk of DR in DM patients, specifically PDR in those with T2DM. These findings underscore the importance of considering sickle cell disorders in DR screening and clinical management of DM patients. Furthermore, our study calls for deeper exploration into the underlying mechanisms connecting sickle-cell disorders with DR progression in DM patients, aiming to enhance patient outcomes.
Manuscript no. XOPS-D-23-00252
Footnotes
Disclosure(s):
All authors have completed and submitted the ICMJE disclosures form.
The authors have no proprietary or commercial interest in any materials discussed in this article.
HUMAN SUBJECTS: No human subjects were included in this study.
No animal subjects were used in this study.
The study was determined to be exempt from the institutional review board approval at the University of Arkansas for Medical Sciences. The study complied with the tents of the Declaration of Helsinki.
Author Contributions:
Conception and design: Chauhan, Elhusseiny, Sallam
Data collection: Chauhan, Elhusseiny
Analysis and interpretation: Chauhan, Elhusseiny
Obtained funding: Sallam
Overall responsibility: Sallam
References
- 1.Kumar V., Abbas A.K., Aster J.C., Perkins J.A. 10 th ed. Elsevier; Philadelphia, PA: 2018. Robbins basic pathology. [Google Scholar]
- 2.Lu W.L., Shen P.C., Lee C.H., et al. High risk of early cataracts in young type 1 diabetes group: a nationwide cohort study. Int J Endocrinol. 2020;2020 doi: 10.1155/2020/8160256. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Spaide R.F. Measurable aspects of the retinal neurovascular unit in diabetes, glaucoma, and controls. Am J Ophthalmol. 2019;207:395–409. doi: 10.1016/j.ajo.2019.04.035. [DOI] [PubMed] [Google Scholar]
- 4.Chauhan M.Z., Rather P.A., Samarah S.M., et al. Current and novel therapeutic approaches for treatment of diabetic macular edema. Cells. 2022;11:1950. doi: 10.3390/cells11121950. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.ElSheikh R.H., Chauhan M.Z., Sallam A.B. Current and novel therapeutic approaches for treatment of neovascular age-related macular degeneration. Biomolecules. 2022;12:1629. doi: 10.3390/biom12111629. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Pradeepa R., Anitha B., Mohan V., et al. Risk factors for diabetic retinopathy in a South Indian type 2 diabetic population--the Chennai urban rural epidemiology study (CURES) eye study 4. Diabet Med. 2008;25:536–542. doi: 10.1111/j.1464-5491.2008.02423.x. [DOI] [PubMed] [Google Scholar]
- 7.Chew E.Y., Davis M.D., Danis R.P., et al. The effects of medical management on the progression of diabetic retinopathy in persons with type 2 diabetes: the action to Control Cardiovascular Risk in Diabetes (ACCORD) eye study. Ophthalmology. 2014;121:2443–2451. doi: 10.1016/j.ophtha.2014.07.019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Chatziralli I.P. The role of glycemic control and variability in diabetic retinopathy. Diabetes Ther. 2018;9:431–434. doi: 10.1007/s13300-017-0345-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Eleiwa K.T., Bayoumy A., Elhusseiny M.A., et al. Longitudinal analysis of subfoveal choroidal thickness after panretinal laser photocoagulation in diabetic retinopathy using swept-source optical coherence tomography. Rom J Ophthalmol. 2020;64:285–291. [PMC free article] [PubMed] [Google Scholar]
- 10.John N. A review of clinical profile in sickle cell traits. Oman Med J. 2010;25:3–8. doi: 10.5001/omj.2010.2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Rees D.C., Williams T.N., Gladwin M.T. Sickle-cell disease. Lancet. 2010;376:2018–2031. doi: 10.1016/S0140-6736(10)61029-X. [DOI] [PubMed] [Google Scholar]
- 12.Kavanagh P.L., Fasipe T.A., Wun T. Sickle cell disease: a review. JAMA. 2022;328:57–68. doi: 10.1001/jama.2022.10233. [DOI] [PubMed] [Google Scholar]
- 13.Conran N., Belcher J.D. Inflammation in sickle cell disease. Clin Hemorheol Microcirc. 2018;68:263–299. doi: 10.3233/CH-189012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Pecker L.H., Naik R.P. The current state of sickle cell trait: implications for reproductive and genetic counseling. Blood. 2018;132:2331–2338. doi: 10.1182/blood-2018-06-848705. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Piel F.B., Patil A.P., Howes R.E., et al. Global epidemiology of sickle haemoglobin in neonates: a contemporary geostatistical model-based map and population estimates. Lancet. 2013;381:142–151. doi: 10.1016/S0140-6736(12)61229-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Skinner S., Pialoux V., Fromy B., et al. Sickle-cell trait and diagnosis of type 2 diabetes. Lancet Diabetes Endocrinol. 2018;6:840–843. doi: 10.1016/S2213-8587(18)30033-0. [DOI] [PubMed] [Google Scholar]
- 17.Usmani A., Machado R.F. Vascular complications of sickle cell disease. Clin Hemorheol Microcirc. 2018;68:205–221. doi: 10.3233/CH-189008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Naik R.P., Haywood C., Jr. Sickle cell trait diagnosis: clinical and social implications. Hematology Am Soc Hematol Educ Program. 2015;2015(1):160–167. doi: 10.1182/asheducation-2015.1.160. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Osafo-Kwaako A., Kimani K., Ilako D., et al. Ocular manifestations of sickle cell disease at the Korle-bu Hospital, Accra, Ghana. Eur J Ophthalmol. 2011;21:484–489. doi: 10.5301/EJO.2010.5977. [DOI] [PubMed] [Google Scholar]
- 20.Page M.M., MacKay J.M., Paterson G. Sickle cell trait and diabetic retinopathy. Br J Ophthalmol. 1979;63:837–838. doi: 10.1136/bjo.63.12.837. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Baek S., Park S.H., Won E., et al. Propensity score matching: a conceptual review for radiology researchers. Korean J Radiol. 2015;16:286–296. doi: 10.3348/kjr.2015.16.2.286. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Nagpal K.C., Asdourian G.K., Patrianakos D., et al. Proliferative retinopathy in sickle cell trait. Report of seven cases. Arch Intern Med. 1977;137:325–328. [PubMed] [Google Scholar]
- 23.Jackson H., Bentley C.R., Hingorani M., et al. Sickle retinopathy in patients with sickle trait. Eye (Lond) 1995;9:589–593. doi: 10.1038/eye.1995.145. [DOI] [PubMed] [Google Scholar]
- 24.Vangipuarm G., Saraf S.S., Zhang Q., et al. Profound presentation of retinopathy in a patient with sickle cell trait and diabetes mellitus. J Ophthalmic Vis Res. 2020;15:116–117. doi: 10.18502/jovr.v15i1.5962. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Detterich J.A., Kato R., Bush A., et al. Sickle cell microvascular paradox-oxygen supply-demand mismatch. Am J Hematol. 2019;94:678–688. doi: 10.1002/ajh.25476. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Zhou J., Han J., Nutescu E.A., et al. Type 2 diabetes mellitus in patients with sickle cell disease: a population-based Longitudinal analysis of 3 cohorts. Blood. 2018;132:4817. [Google Scholar]
- 27.Sun R., Han J., Lash J.P., et al. Diabetes, diabetic control, and kidney dysfunction in adults with sickle cell disease. Blood. 2022;140:5442–5443. [Google Scholar]
- 28.Skinner S.C., Diaw M., Pialoux V., et al. Increased prevalence of type 2 diabetes-related complications in combined type 2 diabetes and sickle cell trait. Diabetes Care. 2018;41:2595–2602. doi: 10.2337/dc18-1289. [DOI] [PubMed] [Google Scholar]
- 29.Vona R., Sposi N.M., Mattia L., et al. Sickle cell disease: role of oxidative stress and antioxidant therapy. Antioxidants (Basel) 2021;10:296. doi: 10.3390/antiox10020296. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Kowluru R.A., Chan P.S. Oxidative stress and diabetic retinopathy. Exp Diabetes Res. 2007;2007 doi: 10.1155/2007/43603. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Vinson J.A. Oxidative stress in cataracts. Pathophysiology. 2006;13:151–162. doi: 10.1016/j.pathophys.2006.05.006. [DOI] [PubMed] [Google Scholar]
- 32.Diaw M., Pialoux V., Martin C., et al. Sickle cell trait worsens oxidative stress, abnormal blood rheology, and vascular dysfunction in type 2 diabetes. Diabetes Care. 2015;38:2120–2127. doi: 10.2337/dc15-0699. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Hulsizer J., Resurreccion W.K., Shi Z., et al. Sickle cell trait and risk for common diseases: evidence from the UK Biobank. Am J Med. 2022;135:e279–e287. doi: 10.1016/j.amjmed.2022.03.024. [DOI] [PubMed] [Google Scholar]
- 34.Al Harbi M., Khandekar R., Kozak I., Schatz P. Association between sickle cell trait and the prevalence and severity of diabetic retinopathy. PLoS One. 2016;11 doi: 10.1371/journal.pone.0159215. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Bowers A.S., Pepple D.J., Reid H.L. Optimal haematocrit in subjects with normal haemoglobin genotype (HbAA), sickle cell trait (HbAS), and homozygous sickle cell disease (HbSS) Clin Hemorheol Microcirc. 2011;47:253–260. doi: 10.3233/CH-2011-1387. [DOI] [PubMed] [Google Scholar]
- 36.Sallam A., Scanlon P.H., Stratton I.M., et al. Agreement and reasons for disagreement between photographic and hospital biomicroscopy grading of diabetic retinopathy. Diabet Med. 2011;28:741–746. doi: 10.1111/j.1464-5491.2011.03273.x. [DOI] [PubMed] [Google Scholar]