OCT-Based Biomarkers are Associated with Systemic Inflammation in Patients with Treatment-Naïve Diabetic Macular Edema

Zhou, Jingxin; Song, Siyuan; Zhang, Yi; Jin, Kai; Ye, Juan

doi:10.1007/s40123-022-00576-x

Cited by 14 publications

(12 citation statements)

References 66 publications

(84 reference statements)

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“…A growing number of studies today have attempted to use spectral domain optical coherence tomography based (SD-OCT based) imaging biomarkers for diagnosis, monitoring and treatment-prediction of DME. The biomarkers include retinal hyper-reflective foci [14][15][16][17][18][19], presence of disorganization of the inner retinal layers [20] [21,22], disruption of ellipsoid zone [12,[23][24][25], disruption of external limiting membrane [13,23,26,27], vitreo-macular status [28], and intra-retinal cyst [29]. Response to anti-VEGF injections has also been reported to be influenced by different morphological subtypes of DME, with the sub-type diffuse retinal thickening showing the least improvement and serous retinal detachment showing the most improvement [30].…”

Section: Introductionmentioning

confidence: 99%

Predictive factors for treatment outcomes with intravitreal anti-vascular endothelial growth factor injections in diabetic macular edema in clinical practice

et al. 2023

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Background Intravitreal anti-vascular endothelial growth factor (anti-VEGF) injections are the standard of care for diabetic macular edema (DME), a common complication of diabetes. This study aimed to identify factors influencing DME intravitreal anti-VEGF treatment outcomes in real-world practice. Methods This was a multi-center retrospective observational study using medical chart review of participants receiving anti-VEGF injections for DME (N = 248). Demographic and clinical variables were assessed for association with best corrected visual acuity (BCVA) and central macular thickness (CMT) outcomes using regression models. Results There was a significant improvement in BCVA (p < 0.001) and CMT (p < 0.001) after 12 months of treatment, although 21% of participants had decreased BCVA, and 41% had a < 10% CMT reduction at 12 months. Higher baseline BCVA (p = 0.022, OR=-0.024, 95% CI=-0.046,-0.004) and longer duration of diabetic retinopathy (p = 0.048, OR=-0.064, 95% CI=-0.129,-0.001) were negative predictors for BCVA response, whereas Aflibercept treatment (p = 0.017, OR = 1.107, 95% CI = 0.220,2.051) compared with other drugs and a positive “early functional response” (p < 0.001, OR=-1.393, 95% CI=-1.946,-0.857) were positive predictors. A higher baseline CMT (p < 0.001, OR = 0.019, 95% CI = 0.012,0.0261) and an “early anatomical response”, (p < 0.001, OR=-1.677, 95% CI=-2.456, -0.943) were predictors for greater reduction in CMT. Overall, the variables could predict only 23% of BCVA and 52% of CMT response. Conclusions The study shows a significant proportion of DME patients do not respond to anti-VEGF therapy and identifies several clinical predictors for treatment outcomes. Trial registration The study was approved through the Human Research Ethics Committee, University of Tasmania (approval number H0012902), and the Southern Adelaide Clinical Human Research Ethics Committee (approval number 86 − 067).

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Section: Introductionmentioning

confidence: 99%

Predictive factors for treatment outcomes with intravitreal anti-vascular endothelial growth factor injections in diabetic macular edema in clinical practice

et al. 2023

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“…Because both PLR and NLR have previously been used as markers for inflammation 36,37 . Also, PLR, NLR, and SII are standard tests that are inexpensive and predictive indicators for diabetic patients 38–41 . As well as in diabetes, PLR, NLR, and SII levels are considered predictive and prognostic markers for metabolic diseases such as diabetes with complications 40–43 .…”

Section: Discussionmentioning

confidence: 99%

Assessment of the systemic immune‐inflammation index in type 2 diabetic patients with and without dry eye disease: A case‐control study

Alhalwani,

Jambi,

Borai

et al. 2024

Health Science Reports

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BackgroundThe inflammation plays a role in the pathophysiology of type‐2 diabetes progression, and the mechanism remains unclear. The systemic immune‐inflammation index (SII) is a novel inflammatory marker for type 2 diabetes patients and integrates multiple indicators in complete blood counts and routine blood tests.AimSince there is no international diagnostic standard for dry eye disease (DED), this study uses low‐cost inflammatory blood biomarkers to investigate the correlation between SII and DM2–DED and determine the diagnosis indices of other biomarkers in DM2–DED.MethodologyA case‐control retrospective analysis of totel patients n = 293 randomly selected and categorized into four groups: DED, DM2, DM2‐DED, and healthy subjects. Demographic and blood biomarker variables were classified as categorical and continuous variables. The platelet‐to‐lymphocyte ratio (PLR), lymphocytes‐to‐lymphocyte ratio, neutrophil‐to‐lymphocyte ratio (NLR), and SII were calculated platelet count multiply by NLR and analyzed for their correlation for all groups.ResultsFocusing on DM2‐DED patients was more common in females, 59.6%, than in males, 40.2%. The mean ages were 60.7 ± 11.85 years, a statistically significant difference with all groups. In the study group DM2‐DED, there was an increase in all blood markers compared to all remaining groups except PLR. Only neutrophil, hemoglobin A1c (HbA1c), and fasting blood sugar levels were statistically significant differences in DM2‐DED patients (p > 0.001, p < 0.001, and p < 0.001, respectively) compared to all groups. There was a positive correlation between HbA1c and PLR, HbA1c and NLR, and HbA1c and SII (r = 0.037, p = 0.705; r = 0.031, p = 0.754; and r = 0.066, p < 0.501, respectively) in the DM2‐DED group.ConclusionThis study demonstrated that elevated SII values were linked to elevated HbA1c in DM2‐DED patients. The potential of SII and HbA1c as early diagnostic indicators for ocular problems associated with diabetes mellitus is highlighted by their favorable connection in diagnosing DM2‐DED.

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“…OCT imaging has become the gold standard for the diagnosis and grading of DME. Current evidence shows that different OCT biomarkers (IRF, SRF, ELM/EZ integrity, and HRF) are particularly related to DME outcomes, even more than the central retinal thickness [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 25 , 26 , 32 , 33 ]. Although these OCT biomarkers have been correlated with both pre-treatment and post-treatment anatomic and functional outcomes (e.g., retinal thickness and visual acuity), they have different pathogenetic characteristics and, therefore, represent different aspects (phenotypes) of DME.…”

Section: Discussionmentioning

confidence: 99%

“…Among major OCT features, the presence and amount of intraretinal (IRF) and subretinal fluid (SRF), the integrity of the external limiting membrane (ELM) and ellipsoid zone (EZ), and the number of hyperreflective foci (HRF) have been identified as the most currently reliable OCT biomarkers for DME diagnosis and prognosis [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

Validation of an Automated Artificial Intelligence Algorithm for the Quantification of Major OCT Parameters in Diabetic Macular Edema

Midena

Toto

Frizziero

et al. 2023

JCM

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Artificial intelligence (AI) and deep learning (DL)-based systems have gained wide interest in macular disorders, including diabetic macular edema (DME). This paper aims to validate an AI algorithm for identifying and quantifying different major optical coherence tomography (OCT) biomarkers in DME eyes by comparing the algorithm to human expert manual examination. Intraretinal (IRF) and subretinal fluid (SRF) detection and volumes, external limiting-membrane (ELM) and ellipsoid zone (EZ) integrity, and hyperreflective retina foci (HRF) quantification were analyzed. Three-hundred three DME eyes were included. The mean central subfield thickness was 386.5 ± 130.2 µm. IRF was present in all eyes and confirmed by AI software. The agreement (kappa value) (95% confidence interval) for SRF presence and ELM and EZ interruption were 0.831 (0.738–0.924), 0.934 (0.886–0.982), and 0.936 (0.894–0.977), respectively. The accuracy of the automatic quantification of IRF, SRF, ELM, and EZ ranged between 94.7% and 95.7%, while accuracy of quality parameters ranged between 99.0% (OCT layer segmentation) and 100.0% (fovea centering). The Intraclass Correlation Coefficient between clinical and automated HRF count was excellent (0.97). This AI algorithm provides a reliable and reproducible assessment of the most relevant OCT biomarkers in DME. It may allow clinicians to routinely identify and quantify these parameters, offering an objective way of diagnosing and following DME eyes.

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OCT-Based Biomarkers are Associated with Systemic Inflammation in Patients with Treatment-Naïve Diabetic Macular Edema

Cited by 14 publications

References 66 publications

Predictive factors for treatment outcomes with intravitreal anti-vascular endothelial growth factor injections in diabetic macular edema in clinical practice

Predictive factors for treatment outcomes with intravitreal anti-vascular endothelial growth factor injections in diabetic macular edema in clinical practice

Assessment of the systemic immune‐inflammation index in type 2 diabetic patients with and without dry eye disease: A case‐control study

Validation of an Automated Artificial Intelligence Algorithm for the Quantification of Major OCT Parameters in Diabetic Macular Edema

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