Objective: Patient satisfaction with glaucoma therapy is one of the aspects that affects adequate adherence to treatment; therefore, it would be interesting to measure the satisfaction properly. We present the development process and psychometric properties of a new instrument for measuring patient satisfaction with glaucoma treatment. Material and methods: After collection and discussion of contents, a 38-item questionnaire was proposed and arranged into seven theoretical domains. The questionnaire was applied to a sample of 194 patients and its length was reduced using an exploratory factor analysis. Psychometric properties were assessed under classic theory. Results: The final questionnaire is formed by 22 items grouped into seven dimensions: expectations and beliefs about treatment, ease of use, efficacy, undesired effects, impact on health-related quality of life, medical care, and general satisfaction with treatment. Some dimensions correlated slightly. The reliability of the dimensions ranged from 0.77 to 0.93. Confirmatory factor analysis revealed an additional support of the proposed structure (χ² (188) = 217, P = 0.073). Glausat scores were proven to correlate with patients’ self rating on medication tolerability, and with clinicians’ assessment of tolerability, effectiveness and compliance. Conclusions: The Glausat questionnaire has proven to be reliable and structurally valid. This instrument may be used to assess patients’ satisfaction with glaucoma treatment.

To analyze compounded recombinant human epidermal growth factor (rhEGF) effectiveness on skin lesions through a case series. Multicentric series of skin lesions treated with topical rhEGF. Site: Patients from 56 different health professionals, three different countries, and two recruitment years. Seventy-seven patients with skin lesions, mean age of 63.15 years (min = 18, max = 95); 53.2% of patients were men and 46.8% were women; 47 of the lesions were ulcers (venous, arterial, and diabetic foot), others were surgical and traumatic wounds, burns, and scars. Most common pathologies were type 2 diabetes mellitus and chronic venous insufficiency. Mean previous evolution time before inclusion was 29.59 months. Cures using compounded topical rhEGF most commonly used rhEGF concentration: 30 μg/g; most used excipient: gel; average time between cures: 36 h (24-48); and mean follow-up: 6.6 weeks (max = 20). Lesions appearance, margins and bed, lesional size evolution, treatment subjective effectiveness, tolerability and comfort through professional oppinion. Qualitative assessment: effectiveness 8.65, tolerability 9.53, and comfort 8.86 (max = 10). Perilesional skin showed improvement in 93.5% of the cases, lesions margins and wound bed appearance improved in 92.2% of the cases, respectively. Wound area decreased a mean average of 66.7%. About 43.3% of included venous ulcers had a greater than 40% cure rate in 4 weeks. Heterogeneity of the included pathologies, limited time follow-up in some cases. Topical rhEGF in individualized formulation (compounding) seems to exhibit effectiveness, comfort, and tolerability. Further larger-size studies with experimental design will allow to establish more precise concentrations, indications, and clinical guidelines.

Introduction: Sleep surfaces must adapt to individual somatotypic features to maintain a comfortable, convenient and healthy sleep, preventing diseases and injuries. Individually determining the most adequate rest surface can often be a complex and subjective question. Objectives: To design and validate an automatic multimodal somatotype determination model to automatically recommend an individually designed mattress-topper-pillow combination. Methods: Design and validation of an automated prescription model for an individualised sleep system is performed through a single-image 2 D–3 D analysis and body pressure distribution, to objectively determine optimal individual sleep surfaces combining five different mattress densities, three different toppers and three cervical pillows. Results: A final study (n = 151) and re-analysis (n = 117) defined and validated the model, showing high correlations between calculated and real data (>85% in height and body circumferences, 89.9% in weight, 80.4% in body mass index and more than 70% in morphotype categorisation). Conclusions: Somatotype determination model can accurately prescribe an individualised sleep solution. This can be useful for healthy people and for health centres that need to adapt sleep surfaces to people with special needs. Next steps will increase model’s accuracy and analise, if this prescribed individualised sleep solution can improve sleep quantity and quality; additionally, future studies will adapt the model to mattresses with technological improvements, tailor-made production and will define interfaces for people with special needs.