Patient-reported outcomes and visual acuity after 12 months of anti-VEGF-treatment for sight-threatening diabetic macular edema in a real world setting

Aims To examine objective visual acuity measured with ETDRS, retinal thickness (OCT), patient reported outcome and describe levels of glycated hemoglobin and its association with the effects on visual acuity in patients treated with anti-VEGF for visual impairment due to diabetic macular edema (DME) during 12 months in a real world setting. Methods In this cross-sectional study, 58 patients (29 females and 29 males; mean age, 68 years) with type 1 and type 2 diabetes diagnosed with DME were included. Medical data and two questionnaires were collected; an eye-specific (NEI VFQ-25) and a generic health-related quality of life questionnaire (SF-36) were used. Results The total patient group had significantly improved visual acuity and reduced retinal thickness at 4 months and remains at 12 months follow up. Thirty patients had significantly improved visual acuity, and 27 patients had no improved visual acuity at 12 months. The patients with improved visual acuity had significantly improved scores for NEI VFQ-25 subscales including general health, general vision, near activities, distance activities, and composite score, but no significant changes in scores were found in the group without improvements in visual acuity. Conclusions Our study revealed that anti-VEGF treatment improved visual acuity and central retinal thickness as well as patient-reported outcome in real world 12 months after treatment start.

How do different densities in a network affect the optimal location of service centers?

The p-median problem is often used to locate p service centers by minimizing their distances to a geographically distributed demand (n). The optimal locations are sensitive to geographical context such as road network and demand points especially when they are asymmetrically distributed in the plane. Most studies focus on evaluating performances of the p-median model when p and n vary. To our knowledge this is not a very well-studied problem when the road network is alternated especially when it is applied in a real world context. The aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the density in the road network is alternated. The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 service centers we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000. To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when nodes in the road network increase and p is low. When p is high the improvements are larger. The results also show that choice of the best network depends on p. The larger p the larger density of the network is needed. 

Does road network density matter in optimally locating facilities?

Optimal location on the transport infrastructure is the preferable requirement for many decision making processes. Most studies have focused on evaluating performances of optimally locate p facilities by minimizing their distances to a geographically distributed demand (n) when p and n vary. The optimal locations are also sensitive to geographical context such as road network, especially when they are asymmetrically distributed in the plane. The influence of alternating road network density is however not a very well-studied problem especially when it is applied in a real world context. This paper aims to investigate how the density level of the road network affects finding optimal location by solving the specific case of p-median location problem. A denser network is found needed when a higher number of facilities are to locate. The best solution will not always be obtained in the most detailed network but in a middle density level. The solutions do not further improve or improve insignificantly as the density exceeds 12,000 nodes, some solutions even deteriorate. The hierarchy of the different densities of network can be used according to location and transportation purposes and increase the efficiency of heuristic methods. The method in this study can be applied to other location-allocation problem in transportation analysis where the road network density can be differentiated.