When should screening for diabetic retinopathy begin for children with type 1 diabetes?

Ensemble machine learning reveals key features for diabetes duration from electronic health records

Diabetes is a metabolic disorder that affects more than 420 million of people worldwide, and it is caused by the presence of a high level of sugar in blood for a long period. Diabetes can have serious long-term health consequences, such as cardiovascular diseases, strokes, chronic kidney diseases, foot ulcers, retinopathy, and others. Even if common, this disease is uneasy to spot, because it often comes with no symptoms. Especially for diabetes type 2, that happens mainly in the adults, knowing how long the diabetes has been present for a patient can have a strong impact on the treatment they can receive. This information, although pivotal, might be absent: for some patients, in fact, the year when they received the diabetes diagnosis might be well-known, but the year of the disease unset might be unknown. In this context, machine learning applied to electronic health records can be an effective tool to predict the past duration of diabetes for a patient. In this study, we applied a regression analysis based on several computational intelligence methods to a dataset of electronic health records of 73 patients with diabetes type 1 with 20 variables and another dataset of records of 400 patients of diabetes type 2 with 49 variables. Among the algorithms applied, Random Forests was able to outperform the other ones and to efficiently predict diabetes duration for both the cohorts, with the regression performances measured through the coefficient of determination R2. Afterwards, we applied the same method for feature ranking, and we detected the most relevant factors of the clinical records correlated with past diabetes duration: age, insulin intake, and body-mass index. Our study discoveries can have profound impact on clinical practice: when the information about the duration of diabetes of patient is missing, medical doctors can use our tool and focus on age, insulin intake, and body-mass index to infer this important aspect. Regarding limitations, unfortunately we were unable to find additional dataset of EHRs of patients with diabetes having the same variables of the two analyzed here, so we could not verify our findings on a validation cohort.

Clinical and Demographic Factors Associated With Diabetic Retinopathy Among Young Patients With Diabetes

IMPORTANCE

Diabetic retinopathy (DR) is a leading cause of vision loss worldwide. As the incidence of both type 1 and type 2 diabetes among youths continues to increase around the world, understanding the factors associated with the development of DR in this age group is important.

OBJECTIVE

To identify factors associated with DR among children, adolescents, and young adults with type 1 or type 2 diabetes in the US.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study pooled data from 2 large academic pediatric centers in the US (Baylor College of Medicine/Texas Children's Hospital [BCM/TCH] Diabetes and Endocrine Care Center and Johns Hopkins University [JHU] Pediatric Diabetes Center) to form a diverse population for analysis. Data were collected prospectively at the JHU center (via point-of-care screening using fundus photography) from December 3, 2018, to November 1, 2019, and retrospectively at the BCM/TCH center (via electronic health records of patients who received point-of-care screening using retinal cameras between June 1, 2016, and May 31, 2019). A total of 1640 individuals aged 5 to 21 years with type 1 or type 2 diabetes (308 participants from the JHU center and 1332 participants from the BCM/TCH center) completed DR screening and had gradable images.

MAIN OUTCOME AND MEASURES

Prevalence of DR, as identified on fundus photography, and factors associated with DR.

RESULTS

Among 1640 participants (mean [SD] age, 15.7 [3.6] years; 867 female individuals [52.9%]), 1216 (74.1%) had type 1 diabetes, and 416 (25.4%) had type 2 diabetes. A total of 506 participants (30.9%) were Hispanic, 384 (23.4%) were non-Hispanic Black or African American, 647 (39.5%) were non-Hispanic White, and 103 (6.3%) were of other races or ethnicities (1 was American Indian or Alaska Native, 50 were Asian, 1 was Native Hawaiian or Pacific Islander, and 51 did not specify race or ethnicity, specified other race or ethnicity, or had unavailable data on race or ethnicity). Overall, 558 of 1216 patients (45.9%) with type 1 diabetes used an insulin pump, and 5 of 416 patients (1.2%) with type 2 diabetes used an insulin pump. Diabetic retinopathy was found in 57 of 1640 patients (3.5%). Patients with DR vs without DR had a greater duration of diabetes (mean [SD], 9.4 [4.4] years vs 6.6 [4.4] years; P < .001) and higher hemoglobin A1c (HbA1c) levels (mean [SD], 10.3% [2.4%] vs 9.2% [2.1%]; P < .001). Among those with type 1 diabetes, insulin pump use was associated with a lower likelihood of DR after adjusting for race and ethnicity, insurance status, diabetes duration, and HbA1c level (odds ratio [OR], 0.43; 95% CI, 0.20-0.93; P = .03). The likelihood of having DR was 2.1 times higher among Black or African American participants compared with White participants (OR, 2.12; 95% CI, 1.12-4.01; P = .02); this difference was no longer significant after adjusting for duration of diabetes, insurance status, insulin pump use (among patients with type 1 diabetes only), and mean HbA1c level (type 1 diabetes: OR, 1.79; 95% CI, 0.83-3.89; P = .14; type 2 diabetes: OR, 1.08; 95% CI, 0.30-3.85; P = .91).

CONCLUSIONS AND RELEVANCE

This study found that although the duration of diabetes and suboptimal glycemic control have long been associated with DR, insulin pump use (among those with type 1 diabetes) was independently associated with a lower likelihood of DR, which is likely owing to decreased glycemic variability and increased time in range (ie, the percentage of time blood glucose levels remain within the 70-180 mg/dL range). Black or African American race was found to be associated with DR in the univariable analysis but not in the multivariable analysis, which may represent disparities in access to diabetes technologies and care.

Prevalence of diabetic retinopathy in children and young people living with diabetes: protocol for a systematic review

INTRODUCTION

The frequency of diabetes mellitus in childhood is increasing. Thus, more children and young people are at risk of developing diabetic retinopathy and diabetes related visual impairment. However, there is no consensus on optimal screening strategies for the paediatric population reflecting the lack of clarity about the current burden of disease in this group. We aim to estimate the prevalence of diabetic retinopathy in children and young people living with types 1 or 2 diabetes, and to investigate potential sources of heterogeneity in this figure so as to inform screening strategies for this population.

METHODS AND ANALYSIS

PubMed and EMBASE will be searched from 1995 to 2016 using the OvidSP platform with no language restriction. Additionally, manual review of the references lists of included articles will be conducted. Two investigators will independently screen titles and abstracts for potential eligibility. Studies which report prevalence of diabetic retinopathy among general populations of children and young people with types 1 or 2 diabetes will be included. Pooled prevalence estimates of diabetic retinopathy reported in studies with sample size greater than 200 participants will be calculated by the random effect model. Forest plots will be used to summarise individual and pooled estimates of the prevalence. Heterogeneity between studies will be assessed using the I² statistic and explored through meta-regressions and subgroup analyses if the necessary data are available.

ETHICS AND DISSEMINATION

Ethics approval is not required as this is a review of anonymised published data. We will report the findings of this systematic review in a peer-reviewed journal, and share it with the relevant professionals including health authorities through our Diabetic Eye disease in Childhood Study collaborative network.

CLINICAL TRAIL REGISTRATION

PROSPERO (CRD42017067178).

Ophthalmic manifestations of endocrine disorders-endocrinology and the eye

Disorders of the endocrine system usually manifest in a multi-organ fashion. More specifically, many endocrinopathies become apparent in the eye first through a variety of distinct pathophysiologic disturbances. The eye provides physicians with valuable clues for the recognition and management of numerous systemic diseases, including many disorders of the endocrine pathway. Recognizing ophthalmic manifestations of endocrine disorders is critical not only for rapid diagnosis and treatment, but also to prevent significant morbidity and mortality. In this review, we discuss relevant ophthalmic findings associated with key disorders of the pancreas, thyroid gland, and hypothalamic-pituitary axis, as well as with multiple hereditary endocrine syndromes. We have chosen to focus on diabetes mellitus (DM), Graves' ophthalmopathy, pituitary tumors, and some less common disorders that underscore the unique relationship between the eye and the endocrine system.