Consenso en el cribado de la retinopatía diabética

Artículo de revisión sobre el consenso en el cribado de la retinopatía diabética

Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio

A New Deep Learning Algorithm with Activation Mapping for Diabetic Retinopathy: Backtesting after 10 Years of Tele-Ophthalmology

We report the development of a deep learning algorithm (AI) to detect signs of diabetic retinopathy (DR) from fundus images. For this, we use a ResNet-50 neural network with a double resolution, the addition of Squeeze–Excitation blocks, pre-trained in ImageNet, and trained for 50 epochs using the Adam optimizer. The AI-based algorithm not only classifies an image as pathological or not but also detects and highlights those signs that allow DR to be identified. For development, we have used a database of about half a million images classified in a real clinical environment by family doctors (FDs), ophthalmologists, or both. The AI was able to detect more than 95% of cases worse than mild DR and had 70% fewer misclassifications of healthy cases than FDs. In addition, the AI was able to detect DR signs in 1258 patients before they were detected by FDs, representing 7.9% of the total number of DR patients detected by the FDs. These results suggest that AI is at least comparable to the evaluation of FDs. We suggest that it may be useful to use signaling tools such as an aid to diagnosis rather than an AI as a stand-alone tool

Intravitreal dexamethasone implants for diabetic macular edema

AIM: To evaluate the safety and efficacy of a dexamethasone (DEX) intravitreal implant for diabetic macular edema (DME). METHODS: Totally 113 eyes of 84 patients were divided in three subgroups: naive patients (n=11), pseudophakic patients (n=72) and phakic patients (n=30). Inclusive criterion comprised adult diabetic patients with central fovea thickening and impaired visual acuity resulting from DME for whom previous standard treatments showed no improvement in both central macular thickness (CMT) and best corrected visual acuity (BCVA) after at least 3mo of treatment. Outcome data were obtained from patient visits at baseline and at months 1, 3, 5, 9 and 12 after the first DEX implant injection. At each of these visits, patients underwent measurement of BCVA, a complete eye examination and measurement of CMT and macular volume (MV) carried out with optical coherence tomography (OCT) images. RESULTS: Seventy-three eyes (64.5%) received a single implant, 30 (26.5%) received two implants and 10 (9%) received three implants. At baseline, average in BCVA, CMT and MV were 43.5±20.8, 462.8±145 and 12.6±2.5 respectively. These values improved significantly at 1mo (BCVA: 47.2±19.5, CMT: 339.6±120, MV: 11.11±1.4) and 3mo (BCVA: 53.2±18.1, CMT: 353.8±141, MV: 11.3±1.3) (P≤0.05). At 5mo (BCVA: 50.9±19.8, CMT: 425±150, MV: 12.27±2.3), 9mo (BCVA: 48.4±17.6, CMT: 445.5±170, MV: 12.5±2.3) and 12mo (BCVA: 47.7±18.8, CMT: 413.2±149, MV: 12.03±2.5), improvements in the three parameters were no longer statistically significant and decreased progressively but did not reach baseline values. There were no clinical differences between subgroups. Ocular complications were minimal. CONCLUSION: Patients with DEX implants show maximum efficacy at 3mo which then declined progressively, but is still better than baseline values at the end of follow-up

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

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. 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). The meta-analysis to determine heterogeneity and bias between studies was carried out with the MetaXL 4.0. Since 2001, we have observed an increase in the detection of patients with DM, and at the same time, screening programs for RD have been launched; thus, we can deduce that the increase in the detection of patients with DM, many of them in the initial phases, far exceeds the increased detection of patients with DR. The prevalence of DR was higher between 2001 and 2008 with values of 28.85%. These values decreased over the following period between 2009 and 2020 with a mean of 15.28%. Similarly the STDR prevalence decrease from 3.67% to 1.92% after 2008. The analysis of the longitudinal studies determined that the annual DR incidence was 3.83%, and the STDR annual incidence was 0.41%. In Spain, for T2DM, the current prevalence of DR is 15.28% and 1.92% forSTDR. The annual incidence of DR is 3.83% and is 0.41% for STDR

Consenso en el cribado de la retinopatía diabética

Artículo de revisión sobre el consenso en el cribado de la retinopatía diabética