55 research outputs found
Clinical-decision criteria to identify recurrent diabetic macular edema patients suitable for fluocinolone acetonide implant therapy (Iluvien®) and follow-up considerations/ recommendations
Current management of diabetic macular edema (DME) predominantly involves treatment with short-acting intravitreal injections of anti-vascular endothelial growth factors (anti-VEGFs) and/or corticosteroids; however, short-acting therapies (lasting between 1 and 6 months) require frequent injections to maintain efficacy, meaning a considerable treatment burden for diabetic patients with multiple comorbidities. Continuous injections needed in some cases are an economic burden for patients/healthcare system, so real-life clinical practice tends to adopt a reactive approach, ie, watch and wait for worsening symptoms, which consequently increases the risk of undertreatment and edema recurrence. On March 7th 2019, a group of experts in retinal medicine and surgery held a roundtable meeting in Madrid, Spain to discuss how to (1) optimize clinical outcomes through earlier use of fluocinolone acetonide (FAc) implant (ILUVIEN®) in patients with persistent or recurrent DME despite therapy; and, (2) to provide guidance to assist physicians in deciding which patients should be treated with ILUVIEN. In this regard, a 36-month follow-up consensus protocol is presented. In conclusion, patients that achieve a complete or partial anatomical, and preferably functional, response following one or two intravitreal dexametha-sone implants, but with recurrence of edema after 3–4 months, are deemed by the authors most likely to benefit from ILUVIEN, and the switch to FAc implant should not be delayed more than 12 months after the initiation of at least the first dexamethasone implant
Haematophagic behavior in laboratory of Lutzomyia cruzi (Mangabeira) (Diptera: Psychodidae) in relation to three mammalian blood sources in Manaus, Brazil
Phenological synchrony and seasonality of understory Rubiaceae in the Atlantic Forest, Bahia, Brazil
Research trends in combinatorial optimization
Acknowledgments This work has been partially funded by the Spanish Ministry of Science, Innovation, and Universities through the project COGDRIVE (DPI2017-86915-C3-3-R). In this context, we would also like to thank the Karlsruhe Institute of Technology. Open access funding enabled and organized by Projekt DEAL.Peer reviewedPublisher PD
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