COVID-19 vaccine hesitancy in Spain and associated factors.

Introduction: The present study explores the reasons of those who have not been vaccinated in the later stage of the vaccine rollout in Spain and its associated determinants. Methods: Cluster and logistic regression analyses were used to assess differences in claimed reasons for vaccine hesitancy in Spain using two samples of unvaccinated people (18-40 years old) gathered by an online cross-sectional survey from social networks (n = 910) and from a representative panel (n = 963) in October-November 2021. Results: The main reasons for not being vaccinated were believing that the COVID-19 vaccines had been developed too fast, they were experimental, and they were not safe, endorsed by 68.7% participants in the social network sample and 55.4% in the panel sample. The cluster analysis classified the participants into two groups. Logistic regression showed that Cluster 2 (individuals who reported structural constraints and health-related reasons such as pregnancy or medical recommendation) presented a lower trust in information from health professionals, had a lower willingness to get vaccinated in the future, and avoided less social/family events than those in Cluster 1 (reasons centered in distrust on COVID-19 vaccines, conspiracy thoughts and complacency). Conclusions: It is important to promote information campaigns that provide reliable information and fight fake news and myths. Future vaccination intention differs in both clusters, so these results are important for developing strategies target to increase vaccination uptake for those who do not reject the COVID-19 vaccine completely.

How patients with COVID-19 managed the disease at home during the first wave in Spain: a cross-sectional study.

OBJECTIVE: Most patients with mild COVID-19 had to stay at home trying to implement an optimal quarantine. The aim of this study was to describe the COVID-19 cases during the first wave of the pandemic in Spain, how they managed the disease at home, focusing on differences by age, as well as differences in knowledge, attitudes and preventive practices, compared with the uninfected population. DESIGN: An online survey was used to conduct a cross-sectional study of individuals who were 14 years or older living in Spain during the COVID-19 lockdown. The main variable was a COVID-19 case. Logistic regression models for COVID-19 cases were obtained using a backward stepwise procedure to assess the association between social variables, disease knowledge, attitudes, prevention practices and emotional impact. RESULTS: 3398 people completed the survey. Participants' mean age was 49.6 (SD=14.3). COVID-19 was significantly more prevalent among married people (5.3%) and those currently doing an on-site work (8.7%). Most of the COVID-19 cases stayed at home (84.0%) during the episode. There were significant age-based differences with regard to self-isolation conditions at home during the disease. COVID-19 cases showed better attitudes, practices and knowledge about disease symptoms and transmission than the uninfected population. COVID-19 cases also felt more depressed (adjusted OR: 3.46, 95% CI 1.45 to 8.26) and had better preventive behaviour than the uninfected population, such as always wearing a mask outside the home (adjusted OR 1.58, 95% CI 1.06 to 2.30). CONCLUSION: COVID-19 cases found it difficult to comply with recommended home self-isolation conditions, with differences by age group. COVID-19 had an important impact on care dependency in non-hospitalised patients, who were mostly dependent on their families for care. It is necessary to reinforce social and health services and to be ready to meet the care needs of populations during the different waves or in future epidemics.

Robotic right colectomy with intracorporeal anastomosis: experience with 52 consecutive cases.

BACKGROUND: In laparoscopic right hemicolectomy (LRC), extracorporeal or intracorporeal (ICA) anastomosis can be performed. Several authors have suggested advantages to ICA. This study reports our transition to and our experience with robotic right colectomy (RRC) with ICA. MATERIALS AND METHODS: From June 2009 to September 2012 we performed 58 consecutive RRCs, of which 52 were with ICA. Data were prospectively stored and retrospectively reviewed. RESULTS: Twenty-eight female and 30 male patients with a mean age of 71.6 ± 8.3 years (range, 52-89 years) were studied. Indications for surgery included adenocarcinoma (n=30), adenoma (n=20), diverticulitis (n=1), and Crohn's disease (n=1). For RRC with ICA (n=52), mean operative time (OT) was 193.2 ± 42.2 minutes (range, 123-239 minutes). Mean estimated blood loss (EBL) was 47.8 ± 59.5 mL (range, 5-300 mL). Mean length of hospital stay (LOS) was 3.7 ± 3.2 days (range, 1-21 days). Mean extraction-site incision size was 4.61 ± 0.78 cm (range, 2.5-6.5 cm). Mean lymph node harvest was 20.7 ± 8.2 (range, 6-40). Mean specimen length was 18.9 ± 7.2 cm (range 10-37). No intraoperative complications, conversions, or 30-day mortality occurred. Nine postoperative complications (19.1%) occurred, with one anastomotic leak (1.7%). For LRC with ICA as reported in the literature, OT ranges from 136 to 190 minutes, EBL ranges from 0 to 500 mL, median LOS ranges from 3 to 5 days, complication rates range from 6% to 15%, with ileus <22%, and conversion rates are <5%. CONCLUSIONS: RRC with ICA is safe and feasible. OTs and outcomes compare favorably with those published in the literature for LRC with ICA. The robot may facilitate transition to ICA, and if future studies confirm advantages of ICA, the role of RRC may gain importance.

Real-time detection of apneas on a PDA.

Patients suspected of suffering sleep apnea and hypopnea syndrome (SAHS) have to undergo sleep studies such as expensive polysomnographies to be diagnosed. Healthcare professionals are constantly looking for ways to improve the ease of diagnosis and comfort for this kind of patients as well as reducing both the number of sleep studies they need to undergo and the waiting times. Relating to this scenario, some research proposals and commercial products are appearing, but all of them record the physiological data of patients to portable devices and, in the morning, these data are loaded into hospital computers where physicians analyze them by making use of specialized software. In this paper, we present an alternative proposal that promotes not only a transmission of physiological data but also a real-time analysis of these data locally at a mobile device. For that, we have built a classifier that provides an accuracy of 93% and a receiver operating characteristic-area under the curve (ROC-AUC) of 98.5% on SpO(2) signals available in the annotated Apnea-ECG Database. This local analysis allows the detection of anomalous situations as soon as they are generated. The classifier has been implemented taking into consideration the restricted resources of mobile devices.

Architecture, cost-model and customization of real-time monitoring systems based on mobile biological sensor data-streams.

Innovation in the fields of wireless data communications, mobile devices and biosensor technology enables the development of new types of monitoring systems that provide people with assistance anywhere and at any time. In this paper we present an architecture useful to build those kind of systems that monitor data streams generated by biological sensors attached to mobile users. We pay special attention to three aspects related to the system efficiency: selection of the optimal granularity, that is, the selection of the size of the input data stream package that has to be acquired in order to start a new processing cycle; the possible use of compression techniques to store and send the acquired input data stream and; finally, the performance of a local analysis versus a remote one. Moreover, we introduce two particular real systems to illustrate the suitability and applicability of our proposal: an anywhere and at any time monitoring system of heart arrhythmias and an apnea monitoring system.