Background BNT162b2 mRNA and ChAdOx1 nCOV-19 adenoviral vector vaccines have been rapidly rolled out in the UK from December, 2020. We aimed to determine the factors associated with vaccine coverage for both vaccines and documented the vaccine effectiveness of the BNT162b2 mRNA vaccine in a cohort of health-care workers undergoing regular asymptomatic testing. MethodsThe SIREN study is a prospective cohort study among staff (aged ≥18 years) working in publicly-funded hospitals in the UK. Participants were assigned into either the positive cohort (antibody positive or history of infection [indicated by previous positivity of antibody or PCR tests]) or the negative cohort (antibody negative with no previous positive test) at the beginning of the follow-up period. Baseline risk factors were collected at enrolment, symptom status was collected every 2 weeks, and vaccination status was collected through linkage to the National Immunisations Management System and questionnaires. Participants had fortnightly asymptomatic SARS-CoV-2 PCR testing and monthly antibody testing, and all tests (including symptomatic testing) outside SIREN were captured. Data cutoff for this analysis was Feb 5, 2021. The follow-up period was Dec 7, 2020, to Feb 5, 2021. The primary outcomes were vaccinated participants (binary ever vacinated variable; indicated by at least one vaccine dose recorded by at least one of the two vaccination data sources) for the vaccine coverage analysis and SARS-CoV-2 infection confirmed by a PCR test for the vaccine effectiveness analysis. We did a mixed-effect logistic regression analysis to identify factors associated with vaccine coverage. We used a piecewise exponential hazard mixed-effects model (shared frailty-type model) using a Poisson distribution to calculate hazard ratios to compare time-to-infection in unvaccinated and vaccinated participants and estimate the impact of the BNT162b2 vaccine on all PCR-positive infections (asymptomatic and symptomatic). This study is registered with ISRCTN, number ISRCTN11041050, and is ongoing.Findings 23 324 participants from 104 sites (all in England) met the inclusion criteria for this analysis and were enrolled. Included participants had a median age of 46•1 years (IQR 36•0-54•1) and 19 692 (84%) were female; 8203 (35%) were assigned to the positive cohort at the start of the analysis period, and 15 121 (65%) assigned to the negative cohort. Total follow-up time was 2 calendar months and 1 106 905 person-days (396 318 vaccinated and 710 587 unvaccinated). Vaccine coverage was 89% on Feb 5, 2021, 94% of whom had BNT162b2 vaccine. Significantly lower coverage was associated with previous infection, gender, age, ethnicity, job role, and Index of Multiple Deprivation score. During follow-up, there were 977 new infections in the unvaccinated cohort, an incidence density of 14 infections per 10 000 person-days; the vaccinated cohort had 71 new infections 21 days or more after their first dose (incidence density of eight infections per 10 000 person-days) and nine infecti...

Prognostication, along with diagnosis and treatment, is a traditional core clinical skill of the physician. Many patients and families receiving palliative care want information about life expectancy to help plan realistically for their futures. Although underappreciated, prognosis is, or at least should be, part of every clinical decision. Despite this crucial role, expertise in the art and science of prognostication diminished during the twentieth century, due largely to the ascendancy of accurate diagnostic tests and effective therapies. Consequently, "Doctor, how long do I have?" is a question most physicians find unprepared to answer effectively. As we focus on palliative care in the twenty-first century, prognostication will need to be restored as a core clinical proficiency. The discipline of palliative medicine can provide leadership in this direction. This paper begins by discussing a framework for understanding prognosis and how its different domains might be applied to all patients with life limiting illness, although the main focus of the paper is predicting survival in patients with cancer. Examples of prognostic tools are provided, although the subjective assessment of prognosis remains important in the terminally ill. Other issues addressed include: the importance of prognostication in terms of clinical decision-making, discharge planning, and care planning; the impact of prognosis on hospice referrals and patient/family satisfaction; and physicians' willingness to prognosticate.

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Context-Many clinical disciplines report high rates of burnout, which lead to low quality of care. Palliative care clinicians routinely manage patients with significant suffering, aiming to improve quality of life. As a major role of palliative care clinicians involves educating patients and caregivers regarding identifying priorities and balancing stress, we wondered how clinician selfmanagement of burnout matches against the emotionally exhaustive nature of the work. Objectives-We sought to understand the prevalence and predictors of burnout using a discipline-wide survey. Methods-We asked American Academy of Hospice and Palliative Medicine clinician members to complete an electronic survey querying demographic factors, job responsibilities, and the Maslach Burnout Inventory. We performed univariate and multivariate regression analyses to identify predictors of high rates of burnout. Results-We received 1357 responses (response rate 30%). Overall, we observed a burnout rate of 62%, with higher rates reported by nonphysician clinicians. Most burnout stemmed from emotional exhaustion, with depersonalization comprising a minor portion. Factors associated with higher rates of burnout include working in smaller organizations, working longer hours, being younger than 50 years, and working weekends. We did not observe different rates between palliative care clinicians and hospice clinicians. Higher rated self-management activities to mitigate burnout include participating in interpersonal relationships and taking vacations.

Context Many clinical disciplines report high rates of burnout, which lead to low quality of care. Palliative care clinicians routinely manage patients with significant suffering, aiming to improve quality of life. As a major role of palliative care clinicians involves educating patients and caregivers regarding identifying priorities and balancing stress, we wondered how clinician self-management of burnout matches against the emotionally exhaustive nature of the work. Objectives We sought to understand the prevalence and predictors of burnout using a discipline-wide survey. Methods We asked American Academy of Hospice and Palliative Medicine clinician members to complete an electronic survey querying demographic factors, job responsibilities, and the Maslach Burnout Inventory. We performed univariate and multivariate regression analyses to identify predictors of high rates of burnout. Results We received 1357 responses (response rate 30%). Overall, we observed a burnout rate of 62%, with higher rates reported by nonphysician clinicians. Most burnout stemmed from emotional exhaustion, with depersonalization comprising a minor portion. Factors associated with higher rates of burnout include working in smaller organizations, working longer hours, being younger than 50 years, and working weekends. We did not observe different rates between palliative care clinicians and hospice clinicians. Higher rated self-management activities to mitigate burnout include participating in interpersonal relationships and taking vacations. Conclusions Burnout is a major issue facing the palliative care clinician workforce. Strategies at the discipline-wide and individual levels are needed to sustain the delivery of responsive, available, high-quality palliative care for all patients with serious illness.