Preference of young adults for COVID-19 vaccination in the United Kingdom: a discrete choice experiment.

OBJECTIVES: To determine preferences for COVID-19 vaccinations in the young adult population in the United Kingdom (UK). METHOD: A discrete choice experiment survey was conducted in UK young adults. Participants were asked to choose between two hypothetical vaccines the one they preferred the most. Vaccines were defined by five attributes (effectiveness, risk of side effects, duration of protection, number of doses, confidence in available evidence), identified following a systematic literature review and qualitative interviews with 13 young adults. A random parameters logit model, a latent class model, and subgroup analyses were used to identify preferences. RESULTS: One hundred and forty-nine respondents were included (70% women, mean age 23 years). All five attributes significantly influenced respondents' vaccination decisions. Respondents valued higher effectiveness, lower risk of side effects, longer protection duration, and a smaller number of doses. Based on the range of levels of each attribute, vaccine effectiveness was the most important attribute (relative importance 34%), followed by risk of side effects (32%), and duration of vaccine protection (22%). CONCLUSIONS: The five investigated vaccine attributes appear to play an important role in young adults' decision-making process. Results of this study may help health authorities designing appropriate strategies in future vaccines campaigns in the younger UK population.

Beliefs regarding COVID-19 vaccinations of young adults in the United Kingdom: An interview study applying the Integrated Change Model.

INTRODUCTION: Young adults are considered one of the most hesitant groups towards getting vaccinated in the UK, which threatens the success of the vaccination program in ending the pandemic. Identifying and understanding the socio-cognitive beliefs is important to effectively design and implement health communication interventions. Therefore, the aim of this study was to identify the underlying beliefs regarding COVID-19 vaccinations among young adults in the UK. METHODS: The study consisted of online, one-on-one interviews with 18 individuals (6 males, 12 females) aged between 18 and 29 years, conducted in June 2021. The guiding theoretical framework was the I-Change Model. Interviews were recorded and transcribed verbatim. The transcripts were independently coded by two researchers by using the constructs of the I-Change Model. Belief statements were elicited from the codes and the frequency of belief statements was recorded and compared between intenders and non-intenders. RESULTS: Similar beliefs were observed in intenders and non-intenders for most constructs of the I-Change Model. However, non-intenders distinguished themselves from intenders by their higher perceived risks of side effects and higher perceived disadvantages of being vaccinated. Non-intenders expressed the belief that the risk of unknown or long-term side effects, such as blood clotting and impact on fertility, were the main reason for them not to be willing to vaccinate. In addition, in both groups, participants had mostly similar beliefs as their friends and family. CONCLUSION: This research provides insights in the specific beliefs of the young adult population of the UK regarding COVID-19 vaccinations, which could have implications for health communication interventions. The findings suggest that such interventions should focus on reducing the uncertainty regarding short- and long-term effects and potentially having a focus on the entire social environment of young adults.

Clinical prediction models for diagnosis of COVID-19 among adult patients: a validation and agreement study.

BACKGROUND: Since the beginning of the pandemic, hospitals have been constantly overcrowded, with several observed waves of infected cases and hospitalisations. To avoid as much as possible this situation, efficient tools to facilitate the diagnosis of COVID-19 are needed. OBJECTIVE: To evaluate and compare prediction models to diagnose COVID-19 identified in a systematic review published recently using performance indicators such as discrimination and calibration measures. METHODS: A total of 1618 adult patients present at two Emergency Department triage centers and for whom qRT-PCR tests had been performed were included in this study. Six previously published models were reconstructed and assessed using diagnostic tests as sensitivity (Se) and negative predictive value (NPV), discrimination (Area Under the Roc Curve (AUROC)) and calibration measures. Agreement was also measured between them using Kappa's coefficient and IntraClass Correlation Coefficient (ICC). A sensitivity analysis has been conducted by waves of patients. RESULTS: Among the 6 selected models, those based only on symptoms and/or risk exposure were found to be less efficient than those based on biological parameters and/or radiological examination with smallest AUROC values (< 0.80). However, all models showed good calibration and values above > 0.75 for Se and NPV but poor agreement (Kappa and ICC < 0.5) between them. The results of the first wave were similar to those of the second wave. CONCLUSION: Although quite acceptable and similar results were found between all models, the importance of radiological examination was also emphasized, making it difficult to find an appropriate triage system to classify patients at risk for COVID-19.

Impact of microprocessor prosthetic knee on mobility and quality of life in patients with lower limb amputation: a systematic review of the literature.

INTRODUCTION: Advanced technologies have made available the development of microprocessor prosthetic knee (MPK) to improve autonomy of patients with lower limb amputation. In the present systematic review, we aimed to evaluate the impact of the use of all types of MPK on patients' functional status and quality of life. EVIDENCE ACQUISITION: We conducted this review according to the PRISMA Guidelines on Medline (via Ovid), Scopus and SportDiscuss. All identified articles were screened for their eligibility by two reviewers using Covidence software. The Cochrane Risk of Bias (RoB) or the NIH Quality Assessment Tool were used to assess the quality of the studies. EVIDENCE SYNTHESIS: Eighteen articles were included in the present review (7 randomized controlled trials - RCT), 6 cross-sectional and 5 follow-up studies). Number of participants included varied from 20 to 602, protocols' length varied from a single session to 12 weeks of use of MPK. Taken together, MPK users compared to NMPK users tend to present better functional status and mobility. Quality of life was also positively impacted in MPK users. On the other hand, the superiority of more advanced MPKs such as the Genium® is less clear, especially given the improvements over time of other MPKs such as the C-leg® and the Rheo knee®. CONCLUSIONS: Based on our results, while it is clear that MPKs outperform NMPKs both for functional status and quality of life, additional benefits of one MPK over another is less clear. Future studies are needed to clarify these aspects.

Frailty but not sarcopenia nor malnutrition increases the risk of developing COVID-19 in older community-dwelling adults.

BACKGROUND: The identification of coronavirus disease 2019 (COVID-19) risk factors is requested to implement prevention strategies. AIM: To explore the associations between the COVID-19 incidence and malnutrition, sarcopenia, and frailty, identified as potential risk factors in previous cross-sectional studies. METHODS: Malnutrition, sarcopenia, and frailty were assessed at the last available follow-up from the Sarcopenia and Physical Impairments with Advancing Age (SarcoPhAge) cohort (i.e., the fifth year that ended in 2019) according to the Mini-Nutritional Assessment short-form, the European Working Group on Sarcopenia in Older People (EWGSOP2), and the Fried criteria, respectively. Information regarding the COVID-19 was gathered by phone calls interviews in April 2021 to measure its self-declared incidence. Adjusted Cox regressions and Kaplan-Meier curves were performed. RESULTS: The present study included 241 participants [median age 75.6 (73.0-80.6) years, 63.1% women]. Among them, 27 participants (11.2%) developed the non-fatal Covid-19. No significant increased risks of COVID-19 were observed in patients with malnutrition [adjusted HR 1.14 (0.26-5.07)] and sarcopenia [adjusted HR 1.25 (0.35-4.42)]. Nevertheless, the incidence of COVID-19 was significantly higher in frail (44.4%) than in robust participants (8.5%) [Adjusted HR 7.01 (2.69-18.25)], which was confirmed by the Kaplan-Meier curves (p < 0.001). Among the frailty syndrome components, a low physical activity level was the only one significantly associated with an increased risk of COVID-19 [adjusted HR 5.18 (1.37-19.54)]. CONCLUSION: Despite some limitations in the methodology of this study (i.e., limited sample size, COVID-19 incidence self-reported and not assessed systematically using objective measurements) requiring careful  consideration, an increased risk to develop COVID-19 was observed in the presence of the frailty syndrome. Further investigations are needed to elaborate on our findings.

A systematic review of prediction models to diagnose COVID-19 in adults admitted to healthcare centers.

BACKGROUND: The COVID-19 pandemic is putting significant pressure on the hospital system. To help clinicians in the rapid triage of patients at high risk of COVID-19 while waiting for RT-PCR results, different diagnostic prediction models have been developed. Our objective is to identify, compare, and evaluate performances of prediction models for the diagnosis of COVID-19 in adult patients in a health care setting. METHODS: A search for relevant references has been conducted on the MEDLINE and Scopus databases. Rigorous eligibility criteria have been established (e.g., adult participants, suspicion of COVID-19, medical setting) and applied by two independent investigators to identify suitable studies at 2 different stages: (1) titles and abstracts screening and (2) full-texts screening. Risk of bias (RoB) has been assessed using the Prediction model study Risk of Bias Assessment Tool (PROBAST). Data synthesis has been presented according to a narrative report of findings. RESULTS: Out of the 2334 references identified by the literature search, 13 articles have been included in our systematic review. The studies, carried out all over the world, were performed in 2020. The included articles proposed a model developed using different methods, namely, logistic regression, score, machine learning, XGBoost. All the included models performed well to discriminate adults at high risks of presenting COVID-19 (all area under the ROC curve (AUROC) > 0.500). The best AUROC was observed for the model of Kurstjens et al (AUROC = 0.940 (0.910-0.960), which was also the model that achieved the highest sensitivity (98%). RoB was evaluated as low in general. CONCLUSION: Thirteen models have been developed since the start of the pandemic in order to diagnose COVID-19 in suspected patients from health care centers. All these models are effective, to varying degrees, in identifying whether patients were at high risk of having COVID-19.