38 research outputs found
A case series analysing patients with dental anxiety: a patient-centred model based on psychological profiling
Anxiety and distress can jeopardize dental care experience of patients and may affect the clinical result. Although a wide range of sedation and analgesia techniques are currently available to relieve distress and pain during dental procedures, operative models to choose the most effective sedation-analgesic strategies are lacking. This case series proposes a patient-centred model to optimize patients' cooperation during dental care delivery. We describe how to achieve correct anaesthesia by using the least sedative procedure, accounting for the dental procedure needed and patient's psychological profile. Five patients were considered as paradigmatic to show the balance between patients' subjective experiences and the clinical procedures: a patient with low stress, good compliance (case 1); moderate stress and reduction in compliance (case 2); anxious patient (case 3); patient with acute anxiety and emotional distress (case 4); anguished patient (case 5). A multimodal treatment of emotional and behavioural condition and a patient-centred model approach contributed to achieve the best patient satisfaction in the five cases detailed here
Wearable proximity sensors for monitoring a mass casualty incident exercise: a feasibility study
Over the past several decades, naturally occurring and man-made mass casualty
incidents (MCI) have increased in frequency and number, worldwide. To test the
impact of such event on medical resources, simulations can provide a safe,
controlled setting while replicating the chaotic environment typical of an
actual disaster. A standardised method to collect and analyse data from mass
casualty exercises is needed, in order to assess preparedness and performance
of the healthcare staff involved. We report on the use of wearable proximity
sensors to measure proximity events during a MCI simulation. We investigated
the interactions between medical staff and patients, to evaluate the time
dedicated by the medical staff with respect to the severity of the injury of
the victims depending on the roles. We estimated the presence of the patients
in the different spaces of the field hospital, in order to study the patients'
flow. Data were obtained and collected through the deployment of wearable
proximity sensors during a mass casualty incident functional exercise. The
scenario included two areas: the accident site and the Advanced Medical Post
(AMP), and the exercise lasted 3 hours. A total of 238 participants simulating
medical staff and victims were involved. Each participant wore a proximity
sensor and 30 fixed devices were placed in the field hospital. The contact
networks show a heterogeneous distribution of the cumulative time spent in
proximity by participants. We obtained contact matrices based on cumulative
time spent in proximity between victims and the rescuers. Our results showed
that the time spent in proximity by the healthcare teams with the victims is
related to the severity of the patient's injury. The analysis of patients' flow
showed that the presence of patients in the rooms of the hospital is consistent
with triage code and diagnosis, and no obvious bottlenecks were found
Estimating household contact matrices structure from easily collectable metadata
Contact matrices are a commonly adopted data representation, used to develop
compartmental models for epidemic spreading, accounting for the contact
heterogeneities across age groups. Their estimation, however, is generally time
and effort consuming and model-driven strategies to quantify the contacts are
often needed. In this article we focus on household contact matrices,
describing the contacts among the members of a family and develop a parametric
model to describe them. This model combines demographic and easily quantifiable
survey-based data and is tested on high resolution proximity data collected in
two sites in South Africa. Given its simplicity and interpretability, we expect
our method to be easily applied to other contexts as well and we identify
relevant questions that need to be addressed during the data collection
procedure
Lack of SARS-CoV-2 RNA environmental contamination in a tertiary referral hospital for infectious diseases in Northern Italy
none140noNAnoneColaneri M.; Seminari E.; Piralla A.; Zuccaro V.; Di Filippo A.; Baldanti F.; Bruno R.; Mondelli M.U.; Brunetti E.; Di Matteo A.; Maiocchi L.; Pagnucco L.; Mariani B.; Ludovisi S.; Lissandrin R.; Parisi A.; Sacchi P.; Patruno S.F.A.; Michelone G.; Gulminetti R.; Zanaboni D.; Novati S.; Maserati R.; Orsolini P.; Vecchia M.; Sciarra M.; Asperges E.; Sambo M.; Biscarini S.; Lupi M.; Roda S.; Chiara Pieri T.; Gallazzi I.; Sachs M.; Valsecchi P.; Perlini S.; Alfano C.; Bonzano M.; Briganti F.; Crescenzi G.; Giulia Falchi A.; Guarnone R.; Guglielmana B.; Maggi E.; Martino I.; Pettenazza P.; Pioli di Marco S.; Quaglia F.; Sabena A.; Salinaro F.; Speciale F.; Zunino I.; De Lorenzo M.; Secco G.; Dimitry L.; Cappa G.; Maisak I.; Chiodi B.; Sciarrini M.; Barcella B.; Resta F.; Moroni L.; Vezzoni G.; Scattaglia L.; Boscolo E.; Zattera C.; Michele Fidel T.; Vincenzo C.; Vignaroli D.; Bazzini M.; Iotti G.; Mojoli F.; Belliato M.; Perotti L.; Mongodi S.; Tavazzi G.; Marseglia G.; Licari A.; Brambilla I.; Daniela B.; Antonella B.; Patrizia C.; Giulia C.; Giuditta C.; Marta C.; Rossana D.; Milena F.; Bianca M.; Roberta M.; Enza M.; Stefania P.; Maurizio P.; Elena P.; Antonio P.; Francesca R.; Antonella S.; Maurizio Z.; Guy A.; Laura B.; Ermanna C.; Giuliana C.; Luca D.; Gabriella F.; Gabriella G.; Alessia G.; Viviana L.; Claudia L.; Valentina M.; Simona P.; Marta P.; Alice B.; Giacomo C.; Irene C.; Alfonso C.; Di Martino R.; Di Napoli A.; Alessandro F.; Guglielmo F.; Loretta F.; Federica G.; Alessandra M.; Federica N.; Giacomo R.; Beatrice R.; Maria S.I.; Monica T.; Nepita Edoardo V.; Calvi M.; Tizzoni M.; Nicora C.; Triarico A.; Petronella V.; Marena C.; Muzzi A.; Lago P.; Comandatore F.; Bissignandi G.; Gaiarsa S.; Rettani M.; Bandi C.Colaneri, M.; Seminari, E.; Piralla, A.; Zuccaro, V.; Di Filippo, A.; Baldanti, F.; Bruno, R.; Mondelli, M. U.; Brunetti, E.; Di Matteo, A.; Maiocchi, L.; Pagnucco, L.; Mariani, B.; Ludovisi, S.; Lissandrin, R.; Parisi, A.; Sacchi, P.; Patruno, S. F. A.; Michelone, G.; Gulminetti, R.; Zanaboni, D.; Novati, S.; Maserati, R.; Orsolini, P.; Vecchia, M.; Sciarra, M.; Asperges, E.; Sambo, M.; Biscarini, S.; Lupi, M.; Roda, S.; Chiara Pieri, T.; Gallazzi, I.; Sachs, M.; Valsecchi, P.; Perlini, S.; Alfano, C.; Bonzano, M.; Briganti, F.; Crescenzi, G.; Giulia Falchi, A.; Guarnone, R.; Guglielmana, B.; Maggi, E.; Martino, I.; Pettenazza, P.; Pioli di Marco, S.; Quaglia, F.; Sabena, A.; Salinaro, F.; Speciale, F.; Zunino, I.; De Lorenzo, M.; Secco, G.; Dimitry, L.; Cappa, G.; Maisak, I.; Chiodi, B.; Sciarrini, M.; Barcella, B.; Resta, F.; Moroni, L.; Vezzoni, G.; Scattaglia, L.; Boscolo, E.; Zattera, C.; Michele Fidel, T.; Vincenzo, C.; Vignaroli, D.; Bazzini, M.; Iotti, G.; Mojoli, F.; Belliato, M.; Perotti, L.; Mongodi, S.; Tavazzi, G.; Marseglia, G.; Licari, A.; Brambilla, I.; Daniela, B.; Antonella, B.; Patrizia, C.; Giulia, C.; Giuditta, C.; Marta, C.; D'Alterio, Rossana; Milena, F.; Bianca, M.; Roberta, M.; Enza, M.; Stefania, P.; Maurizio, P.; Elena, P.; Antonio, P.; Francesca, R.; Antonella, S.; Maurizio, Z.; Guy, A.; Laura, B.; Ermanna, C.; Giuliana, C.; Luca, D.; Gabriella, F.; Gabriella, G.; Alessia, G.; Viviana, L.; Meisina, Claudia; Valentina, M.; Simona, P.; Marta, P.; Alice, B.; Giacomo, C.; Irene, C.; Alfonso, C.; Di Martino, R.; Di Napoli, A.; Alessandro, F.; Guglielmo, F.; Loretta, F.; Federica, G.; Albertini, Alessandra; Federica, N.; Giacomo, R.; Beatrice, R.; Maria, S. I.; Monica, T.; Nepita Edoardo, V.; Calvi, M.; Tizzoni, M.; Nicora, C.; Triarico, A.; Petronella, V.; Marena, C.; Muzzi, A.; Lago, P.; Comandatore, F.; Bissignandi, G.; Gaiarsa, S.; Rettani, M.; Bandi, C
Clinical characteristics of coronavirus disease (COVID-19) early findings from a teaching hospital in Pavia, North Italy, 21 to 28 February 2020
We describe clinical characteristics, treatments and outcomes of 44 Caucasian patients with coronavirus disease (COVID-19) at a single hospital in Pavia, Italy, from 21\u201328 February 2020, at the beginning of the outbreak in Europe. Seventeen patients developed severe disease, two died. After a median of 6 days, 14 patients were discharged from hospital. Predictors of lower odds of discharge were age>65 years, antiviral treatment and for severe disease, lactate dehydrogenase >300 mg/dL
Containing the accidental laboratory escape of potential pandemic influenza viruses
BACKGROUND: The recent work on the modified H5N1 has stirred an intense debate on the risk associated with the accidental release from biosafety laboratory of potential pandemic pathogens. Here, we assess the risk that the accidental escape of a novel transmissible influenza strain would not be contained in the local community. METHODS: We develop here a detailed agent-based model that specifically considers laboratory workers and their contacts in microsimulations of the epidemic onset. We consider the following non-pharmaceutical interventions: isolation of the laboratory, laboratory workersâ household quarantine, contact tracing of cases and subsequent household quarantine of identified secondary cases, and school and workplace closure both preventive and reactive. RESULTS: Model simulations suggest that there is a non-negligible probability (5% to 15%), strongly dependent on reproduction number and probability of developing clinical symptoms, that the escape event is not detected at all. We find that the containment depends on the timely implementation of non-pharmaceutical interventions and contact tracing and it may be effective (>90% probability per event) only for pathogens with moderate transmissibility (reproductive number no larger than R(0)â=â1.5). Containment depends on population density and structure as well, with a probability of giving rise to a global event that is three to five times lower in rural areas. CONCLUSIONS: Results suggest that controllability of escape events is not guaranteed and, given the rapid increase of biosafety laboratories worldwide, this poses a serious threat to human health. Our findings may be relevant to policy makers when designing adequate preparedness plans and may have important implications for determining the location of new biosafety laboratories worldwide
Effect of titanium carbide coating by ion plating plasma assisted deposition on osteoblast response:A chemical,morphological and gene expression investigation.
Titanium is among the most used materials for the production of medical and dental prostheses because of its specific weight, mechanical performances, cost and biocompatibility. Unfortunately the implant may release titanium particles, thus reducing, in the long term, the integrative properties of a titanium prosthesis, producing inflammation, osteolysis and mobilization. To overcome this problem, several coating procedures of titanium implants have been proposed. To improve osteoblast proliferation and implant integration, we have optimized a protocol to treat any kind of implant, based on the Ion Plated Plasma Assisted (IPPA) deposition of a well-controlled TiOxâTiCyâC nanostructured layer. Our approach consisted in a two-level analysis: the surface structure and chemistry of the substrates have been characterized by AFM, SEM and XPS at every step of the preparation, and the effects of the coating on the osteoblast morphology and genetic response (PCR) have been evaluated. These analyses show that osteoblasts grown on the treated titanium samples have a higher proliferation rate, formation of more filopodia and have positively improved mRNA synthesis of proteins involved in bone formation, when compared to those grown on uncoated ones. In conclusion, the combined effects of the composition and morphology of the nanostructured layer deposited with the IPPA technique, is a definite increase of osteoblast growth rate and differentiation, and indicate a better and stronger anchorage of the cells to the coated substrate, when compared to the untreated samples. Due to its relative low costs and adaptability to industrial production, this technique represents a very promising tool to improve the quality of any kind of prosthesis
Survival prediction of stage I lung adenocarcinomas by expression of 10 genes
Adenocarcinoma is the predominant histological subtype of lung cancer, the leading cause of cancer deaths in the world. At stage I, the tumor is cured by surgery alone in about 60% of cases. Markers are needed to stratify patients by prognostic outcomes and may help in devising more effective therapies for poor prognosis patients. To achieve this goal, we used an integrated strategy combining meta-analysis of published lung cancer microarray data with expression profiling from an experimental model. The resulting 80-gene model was tested on an independent cohort of patients using RT-PCR, resulting in a 10-gene predictive model that exhibited a prognostic accuracy of approximately 75% in stage I lung adenocarcinoma when tested on 2 additional independent cohorts. Thus, we have identified a predictive signature of limited size that can be analyzed by RT-PCR, a technology that is easy to implement in clinical laboratories
Estimating household contact matrices structure from easily collectable metadata
International audienceContact matrices are a commonly adopted data representation, used to develop compartmental models for epidemic spreading, accounting for the contact heterogeneities across age groups. Their estimation, however, is generally time and effort consuming and model-driven strategies to quantify the contacts are often needed. In this article we focus on household contact matrices, describing the contacts among the members of a family and develop a parametric model to describe them. This model combines demographic and easily quantifiable survey-based data and is tested on high resolution proximity data collected in two sites in South Africa. Given its simplicity and interpretability, we expect our method to be easily applied to other contexts as well and we identify relevant questions that need to be addressed during the data collection procedure