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

The Predictors of Early Treatment Effectiveness of Intravitreal Bevacizumab Application in Patients with Diabetic Macular Edema

The aim of this study was to establish whether multiple blood parameters might predict an early treatment response to intravitreal bevacizumab injections in patients with diabetic macular edema (DME). Seventy-eight patients with non-proliferative diabetic retinopathy (NPDR) and DME were included. The treatment response was evaluated with central macular thickness decrease and best corrected visual acuity increase one month after the last bevacizumab injection. Parameters of interest were the neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), vitamin D, and apolipoprotein B to A-I ratio (ApoB/ApoA-I). The NLR (2.03 ± 0.70 vs. 2.80 ± 1.08; p < 0.001), MLR (0.23 ± 0.06 vs. 0.28 ± 0.10; p = 0.011), PLR (107.4 ± 37.3 vs. 135.8 ± 58.0; p = 0.013), and SII (445.3 ± 166.3 vs. 675.3 ± 334.0; p < 0.001) were significantly different between responder and non-responder groups. Receiver operator characteristics analysis showed the NLR (AUC 0.778; 95% CI 0.669-0.864), PLR (AUC 0.628; 95% CI 0.511-0.735), MLR (AUC 0.653; 95% CI 0.536-0.757), and SII (AUC 0.709; 95% CI 0.595-0.806) could be predictors of response to bevacizumab in patients with DME and NPDR. Patients with severe NPDR had a significantly higher ApoB/ApoA-I ratio (0.70 (0.57-0.87) vs. 0.61 (0.49-0.72), p = 0.049) and lower vitamin D (52.45 (43.10-70.60) ng/mL vs. 40.05 (25.95-55.30) ng/mL, p = 0.025). Alterations in the NLR, PLR, MLR, and SII seem to provide prognostic information regarding the response to bevacizumab in patients with DME, whilst vitamin D deficiency and the ApoB/ApoA-I ratio could contribute to better staging.

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

Background

The 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.

Aim

Since 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.

Methodology

A 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.

Results

Focusing 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.

Conclusion

This 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.

Evaluation of systemic immune-inflammatory index in patients with wet age-related macular degeneration

CLINICAL RELEVANCE

The systemic immune-inflammatory index is a relatively new parameter and has been shown to increase in inflammatory diseases.

BACKGROUND

The primary aim of this study was to investigate the systemic immune-inflammatory index in patients with wet-type age-related macular degeneration. The secondary aim was to determine the relationship between best-corrected visual acuity, central macular thickness, subfoveal choroidal thickness, systemic immune-inflammatory index, platelet-to-lymphocyte ratio, and neutrophil-to-lymphocyte ratio.

METHODS

This study retrospectively analysed patients with wet-type age-related macular degeneration between 2018 and 2022. Demographic data and peripheral complete blood count were obtained from the electronic medical record system. The most recent best-corrected visual acuity, central macular thickness, and subfoveal choroidal thickness values (within one month) for complete blood count were obtained from case sheets and the optical coherence tomography digital image database. The systemic immune-inflammatory index, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio were calculated. Age- and sex-matched controls were also generated.

RESULTS

Thirty-three patients (23 males, 10 females) with wet-type age-related macular degeneration and 43 controls (24 males, 19 females) were included. The groups were similar in terms of age and sex (78.0 ± 6.3 vs. 75.6 ± 6.6 years, p = 0.59; p = 0.38 for sex). The systemic immune-inflammatory index was higher in the wet-type age-related macular degeneration group (460.5 vs. 440.4); however, this difference was not statistically significant. When the correlations between the systemic immune-inflammatory index, platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio, best-corrected visual acuity (logMAR), central macular thickness, and subfoveal choroidal thickness were examined, there was only a moderate positive correlation between best-corrected visual acuity and platelet-to-lymphocyte ratio (r = 0.46, p = 0.007).

CONCLUSION

There were no differences in the systemic immune-inflammatory index, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio between the wet-type age-related macular degeneration and control groups. There was a positive correlation between the platelet-to-lymphocyte ratio and best-corrected visual acuity (logMAR). The systemic immune-inflammatory index was higher in patients with wet-type age-related macular degeneration than in the control group; however, this difference was not statistically significant.

Association between systemic immune-inflammation index and diabetes: a population-based study from the NHANES

Background

Systemic Immune-Inflammation Index (SII) has been reported to be associated with diabetes. We aimed to assess possible links between SII and diabetes.

Methods

Data were obtained from the 2017-2020 National Health and Nutrition Examination Survey (NHANES) database. After removing missing data for SII and diabetes, we examined patients older than 20 years. Simultaneously, the relationship between SII and diabetes was examined using weighted multivariate regression analysis, subgroup analysis, and smooth curve fitting.

Results

There were 7877 subjects in this study, the average SII was 524.91 ± 358.90, and the prevalence of diabetes was 16.07%. Weighted multivariate regression analysis found that SII was positively associated with diabetes, and in model 3, this positive association remained stable (OR = 1.04; 95% CI: 1.02-1.06; p = 0.0006), indicating that each additional unit of SII, the possibility of having diabetes increased by 4%. Gender, age, BMI, regular exercise, high blood pressure, and smoking did not significantly affect this positive link, according to the interaction test (p for trend>0.05).

Discussion

Additional prospective studies are required to examine the precise connection between higher SII levels and diabetes, which may be associated with higher SII levels.

The predictive value of perioperative circulating markers on surgical complications in patients undergoing robotic-assisted radical prostatectomy

BACKGROUND

The occurrence of postoperative complications was associated with poor outcomes for patients undergoing robotic-assisted radical prostatectomy. A prediction model with easily accessible indices could provide valuable information for surgeons. This study aims to identify novel predictive circulating biomarkers significantly associated with surgical complications.

METHODS

We consecutively assessed all multiport robotic-assisted radical prostatectomies performed between 2021 and 2022. The clinicopathological factors and perioperative levels of multiple circulating markers were retrospectively obtained from the included patients. The associations of these indices with Clavien-Dindo grade II or greater complications, and surgical site infection were assessed using univariable and multivariable logistic regression models. Further, the models were validated for the overall performance, discrimination, and calibration.

RESULTS

In total, 229 patients with prostate cancer were enrolled in this study. Prolonged operative time could independently predict surgical site infection (OR, 3.39; 95% CI, 1.09-10.54). Higher RBC (day 1-pre) implied lower risks of grade II or greater complications (OR, 0.24; 95% CI, 0.07-0.76) and surgical site infection (OR, 0.23; 95% CI, 0.07-0.78). Additionally, RBC (day 1-pre) independently predicted grade II or greater complications of obese patients (P value = 0.005) as well as those in higher NCCN risk groups (P value = 0.012). Regarding the inflammatory markers, NLR (day 1-pre) (OR, 3.56; 95% CI, 1.37-9.21) and CRP (day 1-pre) (OR, 4.16; 95% CI, 1.69-10.23) were significantly associated with the risk of grade II or greater complications, and both the indices were independent predictors in those with higher Gleason score, or in higher NCCN risk groups (P value < 0.05). The NLR (day 0-pre) could also predict the occurrence of surgical site infection (OR, 5.04; 95% CI, 1.07-23.74).

CONCLUSIONS

The study successfully identified novel circulating markers to assess the risk of surgical complications. Postoperative increase of NLR and CRP were independent predictors for grade II or greater complications, especially in those with higher Gleason score, or in higher NCCN risk groups. Additionally, a marked decrease of RBC after the surgery also indicated a higher possibility of surgical complications, especially for the relatively difficult procedures.

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

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).

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

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.

The Role of Inflammation and Therapeutic Concepts in Diabetic Retinopathy-A Short Review

Diabetic retinopathy (DR) as a microangiopathy is the most common complication in patients with diabetes mellitus (DM) and remains the leading cause of blindness among adult population. DM in its complicated pathomechanism relates to chronic hyperglycemia, hypoinsulinemia, dyslipidemia and hypertension-all these components in molecular pathways maintain oxidative stress, formation of advanced glycation end-products, microvascular changes, inflammation, and retinal neurodegeneration as one of the key players in diabetes-associated retinal perturbations. In this current review, we discuss the natural history of DR with special emphasis on ongoing inflammation and the key role of vascular endothelial growth factor (VEGF). Additionally, we provide an overview of the principles of diabetic retinopathy treatments, i.e., in laser therapy, anti-VEGF and steroid options.

Identification of spinal tuberculosis subphenotypes using routine clinical data: a study based on unsupervised machine learning

OBJECTIVE

The identification of spinal tuberculosis subphenotypes is an integral component of precision medicine. However, we lack proper study models to identify subphenotypes in patients with spinal tuberculosis. Here we identified possible subphenotypes of spinal tuberculosis and compared their clinical results.

METHODS

A total of 422 patients with spinal tuberculosis who received surgical treatment were enrolled. Clustering analysis was performed using the K-means clustering algorithm and the routinely available clinical data collected from patients within 24 h after admission. Finally, the differences in clinical characteristics, surgical efficacy, and postoperative complications among the subphenotypes were compared.

RESULTS

Two subphenotypes of spinal tuberculosis were identified. Laboratory examination results revealed that the levels of more than one inflammatory index in cluster 2 were higher than those in cluster 1. In terms of disease severity, Cluster 2 showed a higher Oswestry Disability Index (ODI), a higher visual analysis scale (VAS) score, and a lower Japanese Orthopedic Association (JOA) score. In addition, in terms of postoperative outcomes, cluster 2 patients were more prone to complications, especially wound infections, and had a longer hospital stay.

CONCLUSION

K-means clustering analysis based on conventional available clinical data can rapidly identify two subtypes of spinal tuberculosis with different clinical results. We believe this finding will help clinicians to rapidly and easily identify the subtypes of spinal tuberculosis at the bedside and become the cornerstone of individualized treatment strategies.