Pressure ulcers management: an economic evaluation

Introduction. Pressure ulcer management represents a growing problem for medical and social health care systems all over the world, particularly in European Union countries where the incidence of pressure ulcers in older persons (> 60 years of age) is predicted to rise. Objectives. The aim of this study was to provide evidence for the lower impact on economic resources of using advanced dressings for the treatment of pressure ulcers with respect to conventional simple dressings. Methods. Two different models of analysis, derived from Activity Based Costing and Health Technology Assessment, were used to measure, over a 30-day period, the direct costs incurred by pressure ulcer treatment for community-residing patients receiving integrated home care. Results. Although the mean cost per home care visit was higher in the advanced dressings patient group than in the simple dressings patient one (? 22.31 versus ? 16.03), analysis of the data revealed that the cost of using advanced dressings was lower due to fewer home care visits (22 versus 11). Conclusion. The results underline the fact that decision-makers need to improve their understanding of the advantages of taking a long-term view with regards to the purchase and use of materials. This could produce considerable savings of resources in addition to improving treatment efficacy for the benefit of patients and the health care system

Analisi multitemporale dell’uso del suolo della dorsale appenninica marchigiana nel XIX e XX secolo

Questo studio ha permesso di ricostruire, per la prima volta nell’Appennino Umbro-Marchigiano, l’evoluzione temporale dell’uso del suolo lungo un arco di tempo di 150 anni e su una superficie di vasta estensione (circa 8000 ettari). Il dato principale che emerge è la sostanziale discontinuità ecologica di tutti gli ecosistemi naturali e seminaturali, fatte salve alcune importanti patches pascolive e, in misura molto minore, boschive. In totale neanche il 20% del territorio dell’area considerata è rimasto stabile nel corso degli ultimi 150 anni; queste aree rappresentano, dal punto di vista floristico, dei potenziali siti di rifugio per le specie erbacee di prateria e per quelle sciafile di bosco. Si tratta quindi di siti estremamente importanti per la conservazione della biodiversità e serbatoi genetici da cui può ripartire la colonizzazione degli ambienti antropizzati e non più utilizzati come le aree agricole abbandonate. È interessante annotare, ad esempio, come proprio in corrispondenza della più ampia patch forestale stabile (Monte Fiegni) sia presente una delle più importanti stazioni dell’Appennino Umbro-Marchigiano di tasso (Taxus baccata) ed agrifoglio (Ilex aquifolium), all’interno di una faggeta basso-montana. Si evidenzia, inoltre, una tendenza alla semplificazione del mosaico ambientale di queste aree montane. Tale semplificazione risulta bene evidente per gli ecosistemi di prateria (stabili e neoformati) che tendono a conservarsi prioritariamente all’interno delle classi di pendenza minore. Questo fenomeno riassume in se il senso dei mutati input che l’economia contemporanea offre alle attività zootecniche; nel corso dei secoli, infatti, si è passati da forme di economia basate sulla transumanza ovina ad un’attività zootecnica di tipo stanziale e dedita soprattutto all’allevamento bovino. Questa differente tipologia zootecnica richiede habitat diversi e, in particolare per quanto concerne i bovini, sono assolutamente indispensabili praterie di elevata produttività e moderata stasi estiva, condizioni che nell’Appennino si verificano solo in corrispondenza delle aree caratterizzate da morfologie a bassa energia di rilievo e in cui si sono anche conservati suoli profondi. Permanendo queste tendenze socio-economiche, dunque, in futuro tenderanno sostanzialmente a scomparire gli ecosistemi di prateria aperta sostituiti da boschi. Questo, se da un lato rappresenta un aspetto che va nel senso della naturale dinamica degli ecosistemi, dall’altro potrebbe comportare dei problemi per la conservazione della biodiversità floristica e faunistica

Revealing the Hidden Details of Nanostructure in a Pharmaceutical Cream

Creams are multi-component semi-solid emulsions that find widespread utility across a wide range of pharmaceutical, cosmetic, and personal care products, and they also feature prominently in veterinary preparations and processed foodstuffs. The internal architectures of these systems, however, have to date been inferred largely through macroscopic and/or indirect experimental observations and so they are not well-characterized at the molecular level. Moreover, while their long-term stability and shelf-life, and their aesthetics and functional utility are critically dependent upon their molecular structure, there is no real understanding yet of the structural mechanisms that underlie the potential destabilizing effects of additives like drugs, anti-oxidants or preservatives, and no structure-based rationale to guide product formulation. In the research reported here we sought to address these deficiencies, making particular use of small-angle neutron scattering and exploiting the device of H/D contrast variation, with complementary studies also performed using bright-field and polarised light microscopy, small-angle and wide-angle X-ray scattering, and steady-state shear rheology measurements. Through the convolved findings from these studies we have secured a finely detailed picture of the molecular structure of creams based on Aqueous Cream BP, and our findings reveal that the structure is quite different from the generic picture of cream structure that is widely accepted and reproduced in textbooks

MSR32 COVID-19 Beds’ Occupancy and Hospital Complaints: A Predictive Model

Objectives COVID-19 pandemic limited the number of patients that could be promptly and adequately taken in charge. The proposed research aims at predicting the number of patients requiring any type of hospitalizations, considering not only patients affected by COVID-19, but also other severe viral diseases, including untreated chronic and frail patients, and also oncological ones, to estimate potential hospital lawsuits and complaints. Methods An unsupervised learning approach of artificial neural network’s called Self-Organizing Maps (SOM), grounding on the prediction of the existence of specific clusters and useful to predict hospital behavioral changes, has been designed to forecast the hospital beds’ occupancy, using pre and post COVID-19 time-series, and supporting the prompt prediction of litigations and potential lawsuits, so that hospital managers and public institutions could perform an impacts’ analysis to decide whether to invest resources to increase or allocate differentially hospital beds and humans capacity. Data came from the UK National Health Service (NHS) statistic and digital portals, concerning a 4-year time horizon, related to 2 pre and 2 post COVID-19 years. Results Clusters revealed two principal behaviors in selecting the resources allocation. In case of increase of non-COVID hospitalized patients, a reduction in the number of complaints (-55%) emerged. A higher number of complaints was registered (+17%) against a considerable reduction in the number of beds occupied (-26%). Based on the above, the management of hospital beds is a crucial factor which can influence the complaints trend. Conclusions The model could significantly support in the management of hospital capacity, helping decision-makers in taking rational decisions under conditions of uncertainty. In addition, this model is highly replicable also in the estimation of current hospital beds, healthcare professionals, equipment, and other resources, extremely scarce during emergency or pandemic crises, being able to be adapted for different local and national settings

ALART: A novel lidar system for vegetation height retrieval from space

We propose a multi-kHz Single-Photon Counting (SPC) space LIDAR, exploiting low energy pulses with high repetition frequency (PRF). The high PRF allows one to overcome the low signal limitations, as many return shots can be collected from nearly the same scattering area. The ALART space instrument exhibits a multi-beam design, providing height retrieval over a wide area and terrain slope measurements. This novel technique, working with low SNRs, allows multiple beam generation with a single laser, limiting mass and power consumption. As the receiver has a certain probability to detect multiple photons from different levels of canopy, a histogram is constructed and used to retrieve the properties of the target tree, by means of a modal decomposition of the reconstructed waveform. A field demonstrator of the ALART space instrument is currently being developed by a European consortium led by cosine | measurement systems and funded by ESA under the TRP program. The demonstrator requirements have been derived to be representative of the target instrument and it will be tested in an equipped tower in woodland areas in the Netherlands. The employed detectors are state-of-the-art CMOS Single-Photon Avalanche Diode (SPAD) matrices with 1024 pixels. Each pixel is independently equipped with an integrated Time-to-Digital Converter (TDC), achieving a timing accuracy that is much lower than the SPAD dead time, resulting in a distance resolution in the centimeter range. The instrument emits nanosecond laser pulses with energy on the order of several J, at a PRF of ~ 10 kHz, and projects on ground a three-beams pattern. An extensive field measurement campaign will validate the employed technologies and algorithms for vegetation height retrieval

Consistency and trends of technological innovations: a network approach to the international patent classification data

Classifying patents by the technology areas they pertain is important to enable information search and facilitate policy analysis and socio-economic studies. Based on the OECD Triadic Patent Family database, this study constructs a cohort network based on the grouping of IPC subclasses in the same patent families, and a citation network based on citations between subclasses of patent families citing each other. This paper presents a systematic analysis approach which obtains naturally formed network clusters identified using a Lumped Markov Chain method, extracts community keys traceable over time, and investigates two important community characteristics: consistency and changing trends. The results are verified against several other methods, including a recent research measuring patent text similarity. The proposed method contributes to the literature a network-based approach to study the endogenous community properties of an exogenously devised classification system. The application of this method may improve accuracy and efficiency of the IPC search platform and help detect the emergence of new technologies