Does nasal surgery improve multilevel surgical outcome in obstructive sleep apnea:A multicenter study on 735 patients

Objective Does nasal surgery affect multilevel surgical success outcome. Methods Prospective eight country nonrandomized trial of 735 obstructive sleep apnea (OSA) patients, who had multilevel palate and/or tongue surgery, divided into two groups, with or without nose surgery. Results There were 575 patients in nose group, 160 patients in no nose group. The mean age for nose group 44.6 ± 11.4, no nose group 44.2 ± 11.8. Mean preoperative BMI for nose group 27.5 ± 3.6, no nose group 27.5 ± 4.1, mean postoperative BMI nose group 26.3 ± 3.7, no nose group 27.1 ± 3.8 (P = .006). Mean preoperative AHI nose group 32.7 ± 19.4, no nose group 34.3 ± 25.0 (P = .377); and mean postoperative AHI nose group 13.5 ± 10.2, no nose group 17.1 ± 16.0 (P = .001). Mean preoperative ESS nose group was 11.3 ± 4.7, no nose group was 10.4 ± 5.4 (P = .051); and mean postoperative ESS nose group was 5.3 ± 3.2, no nose group was 6.7 ± 2.8 (P = .001). The nose group had higher percentage change (adjusted for age, gender, BMI) in AHI (33.7%, 95% CI 14% to 53.5%) compared to the no nose group (P = .001); the nose group also had more percentage change in ESS (37%, 95% CI 23.6% to 50.3%) compared to the no nose group (P < .001). Change in BMI did not affect AHI nor ESS change (Cohen effect 0.03 and 0.14, respectively). AHI change in both groups were also statistically significant in the mild OSA (P = .008) and the severe OSA (P = .01). Success rate of surgery for the nose group 68.2%, while the no nose group 55.0% (P = .002). Conclusion Combining nose surgery in multilevel surgery improves surgical success. Level of evidence IIC

Does nasal surgery improve multilevel surgical outcome in obstructive sleep apnea:A multicenter study on 735 patients

Objective Does nasal surgery affect multilevel surgical success outcome. Methods Prospective eight country nonrandomized trial of 735 obstructive sleep apnea (OSA) patients, who had multilevel palate and/or tongue surgery, divided into two groups, with or without nose surgery. Results There were 575 patients in nose group, 160 patients in no nose group. The mean age for nose group 44.6 ± 11.4, no nose group 44.2 ± 11.8. Mean preoperative BMI for nose group 27.5 ± 3.6, no nose group 27.5 ± 4.1, mean postoperative BMI nose group 26.3 ± 3.7, no nose group 27.1 ± 3.8 (P = .006). Mean preoperative AHI nose group 32.7 ± 19.4, no nose group 34.3 ± 25.0 (P = .377); and mean postoperative AHI nose group 13.5 ± 10.2, no nose group 17.1 ± 16.0 (P = .001). Mean preoperative ESS nose group was 11.3 ± 4.7, no nose group was 10.4 ± 5.4 (P = .051); and mean postoperative ESS nose group was 5.3 ± 3.2, no nose group was 6.7 ± 2.8 (P = .001). The nose group had higher percentage change (adjusted for age, gender, BMI) in AHI (33.7%, 95% CI 14% to 53.5%) compared to the no nose group (P = .001); the nose group also had more percentage change in ESS (37%, 95% CI 23.6% to 50.3%) compared to the no nose group (P < .001). Change in BMI did not affect AHI nor ESS change (Cohen effect 0.03 and 0.14, respectively). AHI change in both groups were also statistically significant in the mild OSA (P = .008) and the severe OSA (P = .01). Success rate of surgery for the nose group 68.2%, while the no nose group 55.0% (P = .002). Conclusion Combining nose surgery in multilevel surgery improves surgical success. Level of evidence IIC

Framework for mapping key areas for marine megafauna to inform Marine Spatial Planning: the Falkland Islands case study

Marine Spatial Planning (MSP) is becoming a key management approach throughout the world. The process includes the mapping of how humans and wildlife use the marine environment to inform the development of management measures. An integrated multi-species approach to identifying key areas is important for MSP because it allows managers a global representation of an area, enabling them to see where management can have the most impact for biodiversity protection. However, multi-species analysis remains challenging. This paper presents a methodological framework for mapping key areas for marine megafauna (seabirds, pinnipeds, cetaceans) by incorporating different data types across multiple species. The framework includes analyses of tracking data and observation survey data, applying analytical steps according to the type of data available during each year quarter for each species. It produces core-use area layers at the species level, then combines these layers to create megafauna core-use area layers. The framework was applied in the Falkland Islands. The study gathered over 750,000 tracking and at-sea observation locations covering an equivalent of 5495 data days between 1998 and 2015 for 36 species. The framework provides a step-by-step implementation protocol, replicable across geographic scales and transferable to multiple taxa. R scripts are provided. Common repositories, such as the Birdlife International Tracking Database, are invaluable tools, providing a secure platform for storing and accessing spatial data to apply the methodological framework. This provides managers with data necessary to enhance MSP efforts and marine conservation worldwide

Important At-Sea Areas of Colonial Breeding Marine Predators on the Southern Patagonian Shelf

The Patagonian Shelf Large Marine Ecosystem supports high levels of biodiversity and endemism and is one of the most productive marine ecosystems in the world. Despite the important role marine predators play in structuring the ecosystems, areas of high diversity where multiple predators congregate remains poorly known on the Patagonian Shelf. Here, we used biotelemetry and biologging tags to track the movements of six seabird species and three pinniped species breeding at the Falkland Islands. Using Generalized Additive Models, we then modelled these animals’ use of space as functions of dynamic and static environmental indices that described their habitat. Based on these models, we mapped the predicted distribution of animals from both sampled and unsampled colonies and thereby identified areas where multiple species were likely to overlap at sea. Maximum foraging trip distance ranged from 79 to 1,325 km. However, most of the 1,891 foraging trips by 686 animals were restricted to the Patagonian Shelf and shelf slope, which highlighted a preference for these habitats. Of the seven candidate explanatory covariates used to predict distribution, distance from the colony was retained in models for all species and negatively affected the probability of occurrence. Predicted overlap among species was highest on the Patagonian Shelf around the Falkland Islands and the Burdwood Bank. The predicted area of overlap is consistent with areas that are also important habitat for marine predators migrating from distant breeding locations. Our findings provide comprehensive multi-species predictions for some of the largest marine predator populations on the Patagonian Shelf, which will contribute to future marine spatial planning initiatives. Crucially, our findings highlight that spatially explicit conservation measures are likely to benefit multiple species, while threats are likely to impact multiple species