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. The algorithm developed uses nine risk factors: current age, sex, body mass index (BMI), duration and treatment of diabetes mellitus (DM), arterial hypertension, Glicated hemoglobine (HbA1c), urine-albumin ratio and glomerular filtration. Results: The mean current age of 67.03±10.91, and 272 were male (53.2%), and DM duration was 10.12±6.4 years, 222 had DR (35.8%). The CDSS was employed for 1 year. The prediction algorithm that the CDSS uses included nine risk factors: current age, sex, BMI, DM duration and treatment, arterial hypertension, HbA1c, urine-albumin ratio and glomerular filtration. The area under the curve (AUC) for predicting the presence of any DR achieved a value of 0.9884, the sensitivity of 98.21%, specificity of 99.21%, positive predictive value of 98.65%, negative predictive value of 98.95%, α error of 0.0079 and ß error of 0.0179. Conclusion: Our CDSS for predicting DR was successful when applied to a real population.

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. A fuzzy decision tree is a hierarchical data structure that classifies a patient into several classes to some level, depending on the values that the patient presents in the attributes related to the DR risk factors. Each node of the tree is an attribute, and each branch of the node is related to a possible value of the attribute. The leaves of the tree link the patient to a particular class (DR, no DR). RESULTS: A CDSS was built with 200 trees in the forest and three variables at each node. Accuracy of the CDSS was 80.76%, sensitivity was 80.67%, and specificity was 85.96%. Applied variables were current age, gender, DM duration and treatment, arterial hypertension, body mass index, HbA1c, estimated glomerular filtration rate, and microalbuminuria. DISCUSSION: Some studies concluded that screening every 3 years was cost effective, but did not personalize risk factors. In this study, the random forest test using fuzzy rules permit us to build a personalized CDSS. CONCLUSIONS: We have developed a CDSS that can help in screening diabetic retinopathy programs, despite our results more testing is essential.

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. RESULTS: Annual incidence of any-DR was 8.21 ± 0.60% (7.06%-8.92%), sight-threatening diabetic retinopathy (STDR) was 2.65 ± 0.14% (2.48%-2.88%), and diabetic macular edema (DME) was 2.21 ± 0.18% (2%-2.49%). Renal study results were as follows: UACR > 30 mg/g had an annual incidence of 7.02 ± 0.05% (6.97%-7.09%), eGFR < 60 ml/min/1.73 m2 incidence was 5.89 ± 0.12% (5.70%-6.13%). Cox's proportional regression analysis of DR incidence shows that renal function studied by eGFR < 60 ml/min/1.73 m2 was less significant (p = 0.04, HR 1.223, 1.098-1.201) than UACR ≥ 300 mg/g (p < 0.001, HR 1.485, 1.103-1.548). The study of STDR shows that eGFR < 60 ml/min/1.73 m2 was significant (p = 0.02, HR 1.890, 1.267-2.820), UACR ≥ 300 mg/g (p < 0.001, HR 2.448, 1.595-3.757), and DME shows that eGFR < 60 ml/min/1.73 m2 was significant (p = 0.02, HR 1.920, 1.287-2.864) and UACR ≥ 300 mg/g (p < 0.001, HR 2.432, 1.584-3.732). CONCLUSIONS: The UACR has a better association with diabetic retinopathy than the eGFR, although both are important risk factors for diabetic retinopathy.

Differences in incidence of diabetic retinopathy between type 1 and 2 diabetes mellitus: a nine-year follow-up study.

BACKGROUND/AIMS: To determine the incidence of any diabetic retinopathy (any-DR), sight-threatening diabetic retinopathy (STDR) and diabetic macular oedema (DMO) and their risk factors in type 1 diabetes mellitus (T1DM) over a screening programme. METHODS: Nine-year follow-up, prospective population-based study of 366 patients with T1DM and 15 030 with T2DM. Epidemiological risk factors were as follows: current age, age at DM diagnosis, sex, type of DM, duration of DM, arterial hypertension, levels of glycosylated haemoglobin (HbA1c), triglycerides, cholesterol fractions, serum creatinine, estimated glomerular filtration rate (eGFR) and urine albumin to creatinine ratio (UACR). RESULTS: Sum incidence of any-DR was 47.26% with annual incidence 15.16±2.19% in T1DM, and 26.49% with annual incidence 8.13% in T2DM. Sum incidence of STDR was 18.03% with annual incidence 5.77±1.21% in T1DM, and 7.59% with annual incidence 2.64±0.15% in T2DM. Sum incidence of DMO was 8.46% with annual incidence 2.68±038% in patients with T1DM and 6.36% with annual incidence 2.19±0.18% in T2DM. Cox's survival analysis showed that current age and age at diagnosis were risk factors at p<0.001, as high HbA1c levels at p<0.001, LDL cholesterol was significant at p<0.001, eGFR was significant at p<0.001 and UACR at p=0.017. CONCLUSIONS: The incidence of any-DR and STDR was higher in patients with T1DM than those with T2DM. Also, the 47.26% sum incidence of any-DR in patients with T1DM was higher than in a previous study (35.9%), which can be linked to poor metabolic control of DM. Our results suggest that physicians should be encouraged to pay greater attention to treatment protocols for T1DM in patients.

Cost of diabetic retinopathy and macular oedema in a population, an eight year follow up.

BACKGROUND: Prospective, population-based study of an 8-year follow up. To determine the direct cost of diabetic retinopathy [DR], evaluating our screening programme and the cost of treating DR, focusing on diabetic macular oedema [DMO] after anti-vascular endothelial growth factor [anti-VEGF] treatment. METHODS: A total of 15,396 diabetes mellitus [DM] patients were studied. We determined the cost-effectiveness of our screening programme against an annual programme by applying the Markov simulation model. We also compared the cost-effectiveness of anti-VEGF treatment to laser treatment for screened patients with DMO. RESULTS: The cost of our 2.5-year screening programme was as follows: per patient with any-DR, €482.85 ± 35.14; per sight-threatening diabetic retinopathy [STDR] patient, €1528.26 ± 114.94; and €1826.98 ± 108.26 per DMO patient. Comparatively, an annual screening programme would result in increases as follows: 0.77 in QALY per patient with any-DR and 0.6 and 0.44 per patient with STDR or DMO, respectively, with an incremental cost-effective ratio [ICER] of €1096.88 for any-DR, €4571.2 for STDR and €7443.28 per DMO patient. Regarding diagnosis and treatment, the mean annual total cost per patient with DMO was €777.09 ± 49.45 for the laser treated group and €7153.62 ± 212.15 for the anti-VEGF group, with a QALY gain of 0.21, the yearly mean cost was €7153.62 ± 212.15 per patient, and the ICER was €30,361. CONCLUSIONS: Screening for diabetic retinopathy every 2.5 years is cost-effective, but should be adjusted to a patient's personal risk factors. Treatment with anti-VEGF for DMO has increased costs, but the cost-utility increases to 0.21 QALY per patient.

Changes observed in diabetic retinopathy: eight-year follow-up of a Spanish population.

BACKGROUND/AIMS: To determine the changes in the incidence of diabetic retinopathy (DR), diabetic macular oedema (DMO) and their risk factors in a population-based study of patients with diabetes mellitus (DM) referred to our 16 Primary Health Care Areas (HCAs). METHODS: Prospective population-based study of a total of 15 396 Caucasian patients with DM, who represent 86.53% of the total patients with DM in our HCAs, were studied over an 8-year follow-up period. All patients were screened with a mean follow-up of 3.18±1.11 times for each patient over the 8 years. RESULTS: The yearly mean value of any DR was 8.37±2.19% (8.09%-8.99%); of advanced DR yearly mean value of 0.46±0.22% (0.03-0.78); and of DMO a yearly mean value of 2.19±0.18% (2%-2.49%). A clear increase was observed in the last 3 years, any DR increased from 8.09% in 2007 to 8.99% in 2014, and DMO from 2% in 2007 to 2.49% in 2014. These increases were more evident in some age groups. For patients with any DR aged 41-50 and 51-60 and for patients with advanced DR aged 41-50, 51-60 and 61-70, the increase was more marked, related to an increase in HbA1c values or to patients treated with insulin. CONCLUSIONS: An increase in the incidence of DR and DMO was observed, especially in the younger patients aged between 31 and 70 years. This is linked to bad metabolic control of DM. Our results suggest a greater number of ocular complications in the near future, such as neovascular glaucoma, if these current findings are not addressed.

Importance of telemedicine in diabetes care: Relationships between family physicians and ophthalmologists.

Diabetic retinopathy (DR) is the worldwide leading cause of legal blindness. In 2010, 1.9% of diabetes mellitus (DM) patients were legally blind and 10.2% had visual impairment. The control of DM parameters (glycemia, arterial tension and lipids) is the gold standard for preventing DR complications, although, unfortunately, DR still appeared in a 25% to 35% of patients. The stages of severe vision threading DR, include proliferative DR (6.96%) and diabetic macular edema (6.81%). This review aims to update our knowledge on DR screening using telemedicine, the different techniques, the problems, and the inclusion of different professionals such as family physicians in care programs.

Resultados de la implantación de la cámara no midriática sobre la población diabética / Results of non-mydriatic fundus camera screening in a diabetic population

Objetivo: Determinar el impacto de la implantación de sistemas de cribado de retinopatía diabética (RD) mediante cámara no midriática (CNM) en una población con diabetes mellitus (DBT). Métodos: Estudio prospectivo de 6 años de duración, sobre el cribado oportunístico de una población de 12 801 pacientes con DBT. Resultados: Se revisaron 10 047 pacientes con DBT, un 78.48% de los individuos con DBT censados. En 86 (0.86%) pacientes no se pudo interpretar la imagen y debieron ser referidos a las consultas de oftalmología. Un total de 1 908 pacientes (19%) requirió dilatación pupilar. A los 6 años se detectó RD en 1 410 pacientes, con una incidencia anual del 6.15%; la forma leve fue la más frecuente, con un 77.94% de casos. La incidencia de edema macular diabético fue del 4.84% anual. Se verificó la presencia de otras enfermedades en 995 pacientes (9.91%). Conclusiones: Podemos extraer que el cribado mediante CNM es altamente útil para poder acceder a una gran parte de la población diabética, en especial aquella que acude con escasa frecuencia al oftalmólogo, lo que nos permite diagnosticar un número importante de individuos susceptibles de tratamiento láser para evitar que presenten ceguera.

Resultados de la implantación de la cámara no midriática sobre la población diabética / Results of non-mydriatic fundus camera screening in a diabetic population

Objetivo: Determinar el impacto de la implantación de sistemas de cribado de retinopatía diabética (RD) mediante cámara no midriática (CNM) en una población con diabetes mellitus (DBT). Métodos: Estudio prospectivo de 6 años de duración, sobre el cribado oportunístico de una población de 12 801 pacientes con DBT. Resultados: Se revisaron 10 047 pacientes con DBT, un 78.48% de los individuos con DBT censados. En 86 (0.86%) pacientes no se pudo interpretar la imagen y debieron ser referidos a las consultas de oftalmología. Un total de 1 908 pacientes (19%) requirió dilatación pupilar. A los 6 años se detectó RD en 1 410 pacientes, con una incidencia anual del 6.15%; la forma leve fue la más frecuente, con un 77.94% de casos. La incidencia de edema macular diabético fue del 4.84% anual. Se verificó la presencia de otras enfermedades en 995 pacientes (9.91%). Conclusiones: Podemos extraer que el cribado mediante CNM es altamente útil para poder acceder a una gran parte de la población diabética, en especial aquella que acude con escasa frecuencia al oftalmólogo, lo que nos permite diagnosticar un número importante de individuos susceptibles de tratamiento láser para evitar que presenten ceguera. (AU)

Effectiveness of a structured motivational intervention including smoking cessation advice and spirometry information in the primary care setting: the ESPITAP study.

BACKGROUND: There is current controversy about the efficacy of smoking cessation interventions that are based on information obtained by spirometry. The objective of this study is to evaluate the effectiveness in the primary care setting of structured motivational intervention to achieve smoking cessation, compared with usual clinical practice. DESIGN: Multicentre randomized clinical trial with an intervention and a control group. SETTING: 12 primary care centres in the province of Tarragona (Spain). SUBJECTS OF STUDY: 600 current smokers aged between 35 and 70 years with a cumulative habit of more than 10 packs of cigarettes per year, attended in primary care for any reason and who did not meet any of the exclusion criteria for the study, randomly assigned to structured intervention or standard clinical attention. INTERVENTION: Usual advice to quit smoking by a general practitioner as well as a 20-minute personalized visit to provide detailed information about spirometry results, during which FEV1, FVC, FEF 25-75% and PEF measurements were discussed and interpreted in terms of theoretical values. Additional information included the lung age index (defined as the average age of a non-smoker with the same FEV1 as the study participant), comparing this with the chronological age to illustrate the pulmonary deterioration that results from smoking. MEASUREMENTS: Spirometry during the initial visit. Structured interview questionnaire administered at the primary care centre at the initial visit and at 12-month follow-up. Telephone follow-up interview at 6 months. At 12-month follow-up, expired CO was measured in patients who claimed to have quit smoking. MAIN VARIABLES: Smoking cessation at 12 months. ANALYSIS: Data will be analyzed on the basis of "intention to treat" and the unit of analysis will be the individual smoker. EXPECTED RESULTS: Among active smokers treated in primary care we anticipate significantly higher smoking cessation in the intervention group than in the control group. DISCUSSION: Application of a motivational intervention based on structured information about spirometry results, improved abstinence rates among smokers seen in actual clinical practice conditions in primary care. TRIAL REGISTRATION: ClinicalTrial.gov, number NCT01194596.

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 (63.80% versus 17.63%). Greater patient adherence was observed in Group 1 than in Group 2 when patients came to retinography (98.25% versus 87.52%). There were no significant differences in other technique variables. The prevalence of diabetic retinopathy was similar in both groups (8.98% in Group 1 and 9.16% in Group 2), but the prevalence of severe proliferative diabetic retinopathy was higher in Group 2 (1.69% [severe] and 0.45% [proliferative]) than in Group 1 (1.01% and 0.11%, respectively). Diabetic macular edema was more prevalent in Group 2 (2.03%). CONCLUSIONS: The inclusion of general practitioners in the screening method seems to be important. A great number of patients with diabetes mellitus were screened, and a higher percentage of patients with diabetic retinopathy or macular edema were detected.