Artificial Intelligence-Based Screening System for Diabetic Retinopathy in Primary Care.

Background: This study aimed to test an artificial intelligence-based reading system (AIRS) capable of reading retinographies of type 2 diabetic (T2DM) patients and a predictive algorithm (DRPA) that predicts the risk of each patient with T2DM of developing diabetic retinopathy (DR).

Methods: We tested the ability of the AIRS to read and classify 15,297 retinal photographs from our database of diabetics and 1200 retinal images taken with Messidor-2 into the different DR categories. We tested the DRPA in a sample of 40,129 T2DM patients.

Evaluation of Postoperative Pain When Adding a Tibial Nerve Block to the Femoral Nerve Block for Total Knee Arthroplasty.

: The aim of this study was to compare the postoperative analgesic efficacy when a tibial nerve block was added to the femoral nerve block for total knee arthroplasty (TKA). : A total of 60 patients were randomly assigned to the experimental group (EG) or the control group (CG) in a 1:1 ratio. The thirty patients who formed the CG underwent an ultrasound-guided femoral nerve block together with neuraxial anaesthesia and the administration of opioids and NSAIDs through an intravenous elastomeric pump for the management of the postoperative pain; the other thirty, who formed the EG, underwent neuraxial anaesthesia together with femoral and tibial nerve blocks.

Distribution of Microaneurysms and Hemorrhages in Accordance with the Grading of Diabetic Retinopathy in Type Diabetes Patients.

(1) Underlying Diabetic Retinopathy (DR) is the primary cause of poor vision in young adults. There are automatic image reading systems that can aid screening for DR. (2) Methods: Using our automatic reading system we have counted the number of microaneurysms and hemorrhages in the four quadrants of the ETDRS grid and evaluated the differences between them according to the type of DR.

Referable Diabetic Retinopathy Prediction Algorithm Applied to a Population of 120,389 Type 2 Diabetics over 11 Years Follow-Up.

(1) Background: Although DR screening is effective, one of its most significant problems is a lack of attendance. The aim of the present study was to demonstrate the effectiveness of our algorithm in predicting the development of any type of DR and referable DR. (2) Methods: A retrospective study with an 11-year follow-up of a population of 120,389 T2DM patients was undertaken.

Effect of Lipids on Diabetic Retinopathy in a Large Cohort of Diabetic Patients after 10 Years of Follow-Up.

(1) Background: Diabetic retinopathy (DR) remains the leading cause of low vision and blindness in young adults of working age. Although the most important risk factors-such as the duration of diabetes mellitus (DM) and glycemic control measured by HbA1c-are known, the effects of lipids are not as clear. The aim of the present study is to analyze the effects of lipids on the development of DR.

Risk Factors for Recurrent Vitreous Hemorrhage in Type 2 Diabetes Mellitus Patients after Posterior Vitrectomy.

(Background) The aim of this study was to determine the factors related to recurrent vitreous hemorrhage (RVH) in a sample of proliferative diabetic retinopathy (PDR) patients. (Methods) This was a retrospective, review-based study. We studied 183 eyes from 121 type 2 diabetes patients with PDR.

Impact of the COVID-19 Pandemic on the Metabolic Control of Diabetic Patients in Diabetic Retinopathy and Its Screening.

(1) Background: Diabetic retinopathy (DR) is a complication of diabetes mellitus (DM), screening programs of which have been affected by the COVID-19 pandemic. The aim of the present study was to determine the impact of the COVID-19 pandemic on the screening of diabetes patients in our healthcare area (HCA). (2) Methods: We carried out a retrospective study of patients with DM who had attended the DR screening program between January 2015 and June 2022.

Differences in Multifocal Electroretinogram Study in Two Populations of Type 1 and Type 2 Diabetes Mellitus Patients without Diabetic Retinopathy.

(1) Background: Diabetic retinopathy (DR) is a diabetes mellitus (DM) complication where neurodegeneration plays a significant role. The aim of our study was to determine the differences between type 1 DM (T1DM) and 2 DM (T2DM) in the multifocal electroretinogram (mERG).; (2) Methods: A mERG study was performed in two groups, a T1DM group with 72 eyes of 36 patients compared with 72 eyes of 36 patients with T2DM, randomly selected from our DM databases, without DR.

Changes in the Epidemiology of Diabetic Retinopathy in Spain: A Systematic Review and Meta-Analysis.

Background: The aim of the present study was to determine the prevalence and incidence of diabetic retinopathy (DR) and its changes in the last 20 years in type 2 diabetes mellitus (T2DM) patients in Spain.

Methods: A systematic review with a meta-analysis was carried out on the studies published between 2001-2020 on the prevalence and incidence of DR and sight-threatening diabetic retinopathy (STDR) in Spain. The articles included were selected from four databases and publications of the Spanish Ministry of Health and Regional Health Care System (RHCS).

Real-world outcomes of a clinical decision support system for diabetic retinopathy in Spain.

Objective: The aim of present study was to evaluate our clinical decision support system (CDSS) for predicting risk of diabetic retinopathy (DR). We selected randomly a real population of patients with type 2 diabetes (T2DM) who were attending our screening programme.

Methods And Analysis: The sample size was 602 patients with T2DM randomly selected from those who attended the DR screening programme.

Validation of an Algorithm for the Prediction of Diabetic Retinopathy in Type 1 Diabetic Patients in a Spanish Population.

Aim: The aim of the present study was to build a clinical decision support system (CDSS) that can predict the presence of diabetic retinopathy (DR) in type 1 diabetes (T1DM) patients.

Material And Method: We built two versions of our CDSS to predict the presence of any-type DR and sight-threatening DR (STDR) in T1DM patients. The first version was trained using 324 T1DM and 826 T2DM patients.

Testing a Deep Learning Algorithm for Detection of Diabetic Retinopathy in a Spanish Diabetic Population and with MESSIDOR Database.

Background: The aim of the present study was to test our deep learning algorithm (DLA) by reading the retinographies.

Methods: We tested our DLA built on convolutional neural networks in 14,186 retinographies from our population and 1200 images extracted from MESSIDOR. The retinal images were graded both by the DLA and independently by four retina specialists.

The Effect of HbA Variability as a Risk Measure for Microangiopathy in Type 1 Diabetes Mellitus.

Background: To measure the relationship between variability in HbA and microalbuminuria (MA) and diabetic retinopathy (DR) in the long term.

Methods: A prospective case-series study, was conducted on 366 Type 1 Diabetes Mellitus patients with normoalbuminuria and without diabetic retinopathy at inclusion. The cohort was followed for a period of 12 years.

Validation of a Deep Learning Algorithm for Diabetic Retinopathy.

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Glomerular Filtration Rate and/or Ratio of Urine Albumin to Creatinine as Markers for Diabetic Retinopathy: A Ten-Year Follow-Up Study.

Aims: To determine the relationship between diabetic nephropathy and diabetic retinopathy on a population of type 2 diabetes mellitus patients.

Methods: A prospective ten-year follow-up population-based study. We determined differences between estimated glomerular filtration rate (eGFR) using the chronic kidney disease epidemiology collaboration equation and urine albumin to creatinine ratio.

A Clinical Decision Support System for Diabetic Retinopathy Screening: Creating a Clinical Support Application.

Background: The aim of this study was to build a clinical decision support system (CDSS) in diabetic retinopathy (DR), based on type 2 diabetes mellitus (DM) patients.

Method: We built a CDSS from a sample of 2,323 patients, divided into a training set of 1,212 patients, and a testing set of 1,111 patients. The CDSS is based on a fuzzy random forest, which is a set of fuzzy decision trees.

Multifocal electroretinography changes at the 1-year follow-up in a cohort of diabetic macular edema patients treated with ranibizumab.

Purpose: To determine the changes in the multifocal electroretinogram (mfERG) at 1 year in a clinical series of diabetic macular edema (DME) patients treated with ranibizumab (RNBZ) using a pro re nata protocol.

Methods: We analyzed a clinical series of 35 eyes of 35 patients with DME at baseline and after treating them with RNBZ over 1 year, in order to determine the change in the macular function, which was assessed by means of the response density and the implicit time of the first-order kernel (FOK) P1 wave of the mfERG at the foveola (R1), fovea (R2) and parafovea (R3). These electrophysiological parameters were studied taking into account different independent variables, such as DME type, degree of diabetic retinopathy (DR), level of preservation of both the ellipsoid zone (IS/OS) and the external limiting membrane (ELM) and changes in central retinal thickness (CRT) and total macular volume (TMV).

Diabetic Macular Edema Pathophysiology: Vasogenic versus Inflammatory.

Diabetic macular edema (DME) can cause blindness in diabetic patients suffering from diabetic retinopathy (DR). DM parameters controls (glycemia, arterial tension, and lipids) are the gold standard for preventing DR and DME. Although the vascular endothelial growth factor (VEGF) is known to play a role in the development of DME, the pathological processes leading to the onset of this disease are highly complex and the exact sequence in which they occur is still not completely understood.

Laser treatment for diabetic macular edema in the 21st century.

Diabetic macular edema (DME) is the leading cause of blindness in the diabetic population. The diabetes Control and Complications Trial reported that 27% of patients affected by type 1 diabetes develop DME within 9 years of onset. Other studies have shown that in patients with type 2 diabetes, the prevalence increased from 3% to 28% within 5 years of diagnosis to twenty years after the onset.

Relationship between diabetic retinopathy, microalbuminuria and overt nephropathy, and twenty-year incidence follow-up of a sample of type 1 diabetic patients.

Purpose: To determine the incidence and relationship of diabetic retinopathy (DR), microalbuminuria and overt nephropathy (ON).

Method: A 20-year prospective study, in a cohort of 110 consecutive type 1 diabetes mellitus (DM) patients, without diabetic retinopathy or microalbuminuria at enrolment in 1990.

Results: The 20-year incidence of any DR was 70.

Ten-year incidence of diabetic retinopathy and macular edema. Risk factors in a sample of people with type 1 diabetes.

Aims: To determine the 10-year incidence of diabetic retinopathy (DR) and macular edema (DME), and its relationship with its risk factors in a sample of type 1 diabetes mellitus.

Methods: A total of 334 patients without diabetic retinopathy at baseline underwent a 10-year prospective study, the risk factors included: age, gender, diabetes duration, HbA1c, LDL-C, HDl-C, TC/HDL-C ratio, ApoA1, ApoB, ApoB/ApoA1 ratio, and triglycerides were recorded. Risk factors for diabetic macular edema (DME) were also recorded.

Prospective comparison of two methods of screening for diabetic retinopathy by nonmydriatic fundus camera.

Purpose: To compare the results obtained by two screening techniques for diabetic retinopathy.

Methods: Patients were assessed in two groups, according to whether the retinal images were analyzed by the general practitioner (Group 1) or by the ophthalmologist (Group 2) in a two-year prospective study using telemedicine.

Results: The number of patients referred to the nonmydriatic fundus camera unit was higher in Group 1 than in Group 2 (63.

Prevalence and relationship between diabetic retinopathy and nephropathy, and its risk factors in the North-East of Spain, a population-based study.

Purpose: To determine the prevalence of microangiopathy, and its risk factors in a population-based study of diabetes mellitus patients in the north-eastern area of Spain.

Methods: A population-based transversal study of 8,187 type 2 (83.37% of the diagnosed patients) and 488 type 1 (85.