A Higher Serum Calcium Level is an Independent Risk Factor for Vision-Threatening Diabetic Retinopathy in Patients with Type 2 Diabetes: Cross-Sectional and Longitudinal Analyses

Predicting vision-threatening diabetic retinopathy in patients with type 2 diabetes mellitus: Systematic review, meta-analysis, and prospective validation study

Background

Delayed diagnosis and treatment of vision-threatening diabetic retinopathy (VTDR) is a common cause of visual impairment in individuals with type 2 diabetes mellitus (T2DM). Identification of VTDR predictors is the key to early prevention and intervention, but the predictors from previous studies are inconsistent. This study aims to conduct a systematic review and meta-analysis of the existing evidence for VTDR predictors, then to develop a risk prediction model after quantitatively summarising the predictors across studies, and finally to validate the model with two Chinese cohorts.

Methods

We systematically retrieved cohort studies that reported predictors of VTDR in T2DM patients from PubMed, Ovid, Embase, Scopus, Cochrane Library, Web of Science, and ProQuest from their inception to December 2023. We extracted predictors reported in two or more studies and combined their corresponding relative risk (RRs) using meta-analysis to obtain pooled RRs. We only selected predictors with statistically significant pooled RRs to develop the prediction model. We also prospectively collected two Chinese cohorts of T2DM patients as the validation set and assessed the discrimination and calibration performance of the prediction model by the time-dependent ROC curve and calibration curve.

Results

Twenty-one cohort studies involving 622 490 patients with T2DM and 57 107 patients with VTDR were included in the meta-analysis. Age of diabetes onset, duration of diabetes, glycosylated haemoglobin (HbA1c), estimated glomerular filtration rate (eGFR), hypertension, high albuminuria and diabetic treatment were used to construct the prediction model. We validated the model externally in a prospective multicentre cohort of 555 patients with a median follow-up of 52 months (interquartile range = 39-77). The area under the curve (AUC) of the prediction model was all above 0.8 for 3- to 10-year follow-up periods and different cut-off value of each year provided the optimal balance between sensitivity and specificity. The data points of the calibration curves for each year closely surround the corresponding dashed line.

Conclusions

The risk prediction model of VTDR has high discrimination and calibration performance based on validation cohorts. Given its demonstrated effectiveness, there is significant potential to expand the utilisation of this model within clinical settings to enhance the detection and management of individuals at high risk of VTDR.

Association of serum calcium levels with diabetic kidney disease in normocalcemic type 2 diabetes patients: a cross-sectional study

To explore the association between serum calcium levels within normal ranges and Diabetic Kidney Disease (DKD) in type 2 diabetes patients. In this cross-sectional study, we analyzed clinical data from type 2 diabetes patients admitted to the Endocrinology Department of the Affiliated Hospital of Qingdao University from January 1, 2021, to December 1, 2022. We measured serum calcium levels, corrected for albumin, and screened for diabetes-related complications, including DKD. The association between corrected serum calcium levels and DKD was evaluated using logistic regression, with adjustments made for potential confounders and a generalized additive model (GAM) to explore non-linear relationships, supplemented by subgroup analyses. Among the 3016 patients (52.55% male, 47.45% female), the mean corrected serum calcium was 2.29 ± 0.08 mmol/L. DKD was present in 38.73% of patients. A 0.1 mmol/L increase in corrected serum calcium was associated with a 44% increased risk of DKD (OR = 1.44, 95% CI 1.28-1.61, p < 0.0001). The GAM indicated a linear relationship between corrected serum calcium and DKD risk, consistent across subgroups. Corrected serum calcium levels were linearly associated with DKD risk in type 2 diabetes patients, underlining its potential role in risk assessment. These findings emphasize the clinical importance of monitoring serum calcium levels. However, the need for further prospective studies to confirm these findings is underscored by the study's cross-sectional design.

Bias or biology? Importance of model interpretation in machine learning studies from electronic health records

Objective

The rate of diabetic complication progression varies across individuals and understanding factors that alter the rate of complication progression may uncover new clinical interventions for personalized diabetes management.

Materials and Methods

We explore how various machine learning (ML) models and types of electronic health records (EHRs) can predict fast versus slow onset of neuropathy, nephropathy, ocular disease, or cardiovascular disease using only patient data collected prior to diabetes diagnosis.

Results

We find that optimized random forest models performed best to accurately predict the diagnosis of a diabetic complication, with the most effective model distinguishing between fast versus slow nephropathy (AUROC = 0.75). Using all data sets combined allowed for the highest model predictive performance, and social history or laboratory alone were most predictive. SHapley Additive exPlanations (SHAP) model interpretation allowed for exploration of predictors of fast and slow complication diagnosis, including underlying biases present in the EHR. Patients in the fast group had more medical visits, incurring a potential informed decision bias.

Discussion

Our study is unique in the realm of ML studies as it leverages SHAP as a starting point to explore patient markers not routinely used in diabetes monitoring. A mix of both bias and biological processes is likely present in influencing a model's ability to distinguish between groups.

Conclusion

Overall, model interpretation is a critical step in evaluating validity of a user-intended endpoint for a model when using EHR data, and predictors affected by bias and those driven by biologic processes should be equally recognized.

Association between Dietary Calcium and Potassium and Diabetic Retinopathy: A Cross-Sectional Retrospective Study

Background: Micronutrients are considered to have an important role in metabolic process. The relationships between micronutrients and diabetic complication, such as retinopathy, are rarely discussed. The main purpose of the current study was to investigate the relationship between dietary micronutrients and diabetic retinopathy in an adult population. Methods: 5321 participants from National Health and Nutritional Examination Survey (NHANES) 2005–2008 were included in this cross-sectional study. Diabetic retinopathy was diagnosed by the severity scale of the Early Treatment Diabetic Retinopathy Study (ETDRS) using nonmydriatic fundus photography. Micronutrients were assessed by 24-h dietary recall. The relationship between dietary micronutrients and the occurrence of diabetic retinopathy was analyzed by a logistic regression model. Results: Dietary calcium and potassium were inversely associated with diabetic retinopathy (OR: 0.729, 95%CI: 0.562–0.945; OR: 0.875, 95%CI: 0.787–0.973). Higher quartile of dietary calcium and potassium was associated with lower occurrence of diabetic retinopathy (OR: 0.664, 95%CI: 0.472–0.933; OR: 0.700, 95%CI: 0.495–0.989). Furthermore, increased amounts of dietary calcium and potassium were significantly associated with reduced occurrence of diabetic retinopathy (OR: 0.701, 95%CI: 0.546–0.900; OR: 0.761, 95%CI: 0.596–0.972). Conclusions: Higher levels of dietary calcium and potassium are suggested to reduce the risk of diabetic retinopathy with dose–response effect. The evaluation of dietary micronutrients might be a part of treatment for patients with diabetic complications.

Reduced serum calcium is associated with a higher risk of retinopathy in non-diabetic individuals: The Chinese Multi-provincial Cohort Study

AIMS

As a common micro-vascular disease, retinopathy can also present in non-diabetic individuals and increase the risk of clinical cardiovascular disease. Understanding the relationship between serum calcium and retinopathy would contribute to etiological study and disease prevention.

METHODS

A total of 1836 participants (aged 55-84 years and diabetes-free) from the Chinese Multi-Provincial Cohort Study-Beijing Project in 2012 were included for analyzing the relation between serum calcium level and retinopathy prevalence. Of these, 1407 non-diabetic participants with data on serum calcium in both the 2007 and 2012 surveys were included for analyzing the association of five-year changes in serum calcium with retinopathy risk. The retinopathy was determined from retinal images by ophthalmologists and a computer-aided system using convolutional neural network (CNN). The association between serum calcium and retinopathy risk was assessed by multivariate logistic regression.

RESULTS

Among the 1836 participants (male, 42.5%), 330 (18.0%) had retinopathy determined by CNN. After multivariate adjustment, the odds ratio (OR) comparing the lowest quartiles (serum calcium < 2.38 mmol/L) to the highest quartiles (serum calcium ≥ 2.50 mmol/L) for the prevalence of retinopathy determined by CNN was 1.58 (95% confidence interval [CI]: 1.10 - 2.27). The findings were consistent with the result discerned by ophthalmologists, and either by CNN or ophthalmologists. These relationships are preserved even in those without metabolic risk factors, including hypertension, high hemoglobin A1c, high fasting blood glucose, or high low-density lipoprotein cholesterol. Over 5 years, participants with the sustainably low levels of serum calcium (OR: 1.58; 95%CI: 1.05 - 2.39) and those who experienced a decrease in serum calcium (OR: 1.56; 95%CI: 1.04 - 2.35) had an increased risk of retinopathy than those with the sustainably high level of serum calcium.

CONCLUSIONS

Reduced serum calcium was independently associated with an increased risk of retinopathy in non-diabetic individuals. Moreover, reduction of serum calcium could further increase the risk of retinopathy even in the absence of hypertension, high glucose, or high cholesterol. This study suggested that maintaining a high level of serum calcium may be recommended for reducing the growing burden of retinopathy. Further large prospective studies will allow more detailed information.