Ethics of ICU triage during COVID-19

What are the views of Quebec and Ontario citizens on the tiebreaker criteria for prioritizing access to adult critical care in the extreme context of a COVID-19 pandemic?

BACKGROUND

The prioritization protocols for accessing adult critical care in the extreme pandemic context contain tiebreaker criteria to facilitate decision-making in the allocation of resources between patients with a similar survival prognosis. Besides being controversial, little is known about the public acceptability of these tiebreakers. In order to better understand the public opinion, Quebec and Ontario's protocols were presented to the public in a democratic deliberation during the summer of 2022.

OBJECTIVES

(1) To explore the perspectives of Quebec and Ontario citizens regarding tiebreakers, identifying the most acceptable ones and their underlying values. (2) To analyze these results considering other public consultations held during the pandemic on these criteria.

METHODS

This was an exploratory qualitative study. The design involved an online democratic deliberation that took place over two days, simultaneously in Quebec and Ontario. Public participants were selected from a community sample which excluded healthcare workers. Participants were first presented the essential components of prioritization protocols and their related issues (training session day 1). They subsequently deliberated on the acceptability of these criteria (deliberation session day 2). The deliberation was then subject to thematic analysis.

RESULTS

A total of 47 participants from the provinces of Quebec (n = 20) and Ontario (n = 27) took part in the online deliberation. A diverse audience participated excluding members of the healthcare workforce. Four themes were identified: (1) Priority to young patients - the life cycle - a preferred tiebreaker; (2) Randomization - a tiebreaker of last resort; (3) Multiplier effect of most exposed healthcare workers - a median acceptability tiebreaker, and (4) Social value - a less acceptable tiebreaker.

CONCLUSION

Life cycle was the preferred tiebreaker as this criterion respects intergenerational equity, which was considered relevant when allocating scarce resources to adult patients in a context of extreme pandemic. Priority to young patients is in line with other consultations conducted around the world. Additional studies are needed to further investigate the public acceptability of tiebreaker criteria.

Rapid triage and transfer system for patients with proven Covid-19 at emergency department

BACKGROUND

COVID-19 is a viral disease notorious for frequent worldwide outbreaks. It is difficult to control, thereby resulting in overload of the healthcare system. A possible solution to prevent overcrowding is rapid triage of patients, which makes it possible to focus care on the high-risk patients and minimize the impact of crowding on patient prognosis.

METHODS

The triage algorithm assessed self-sufficiency, oximetry, systolic blood pressure, and the Glasgow coma scale. Compliance with the triage protocol was defined as fulfillment of all protocol steps, including assignment of the correct level of care. Triage was considered successful if there was no change in the scope of care (e.g., unscheduled hospital admission, transfer to different level of care) or if there was unexpected death within 48 hours.

RESULTS

A total of 929 patients were enrolled in the study. Triage criteria were fulfilled in 825 (88.8%) patients. Within 48 hours, unscheduled hospital admission, transfer to different level of care, or unexpected death occurred in 56 (6.0%), 6 (0.6%), and 5 (0.5%) patients, respectively. The risk of unscheduled hospital admission or transfer to different level of care was significantly increased if triage criteria were not fulfilled [13.1% vs. 76.1%, RR 5.8 (3.8-8.3), p < 0.001; 0.5% vs. 5.2%, RR 11.4 (2.3-57.7), p = 0.036, respectively].

CONCLUSION

The proposed algorithm for triage of patients with proven COVID-19 is a simple, fast, and reliable tool for rapid sorting for outpatient treatment, hospitalization on a standard ward, or assignment to an intensive care unit.

Nucleated red blood cells are a late biomarker in predicting intensive care unit mortality in patients with COVID-19 acute respiratory distress syndrome: an observational cohort study

Background

Nucleated red blood cells (nRBC) are precursor cells of the erythropoiesis that are absent from the peripheral blood under physiological conditions. Their presence is associated with adverse outcomes in critically ill patients. This study aimed to evaluate the predictive value of nRBC on mortality in intensive care unit (ICU) patients with COVID-19 acute respiratory distress syndrome (ARDS).

Material and methods

This retrospective, observational cohort study analyzed data on 206 ICU patients diagnosed with COVID-19 ARDS between March 2020 and March 2022. The primary endpoint was ICU mortality, and secondary endpoints included ICU and hospital stay lengths, ventilation hours, and the time courses of disease severity scores and clinical and laboratory parameters.

Results

Among the included patients, 68.9% tested positive for nRBC at least once during their ICU stay. A maximum nRBC of 105 µl-1 had the highest accuracy in predicting ICU mortality (area under the curve of the receiver operating characteristic [AUCROC] 0.780, p < 0.001, sensitivity 69.0%, specificity 75.5%). Mortality was significantly higher among patients with nRBC >105 µl-1 than ≤105 µl-1 (86.5% vs. 51.3%, p = 0.008). Compared to patients negative for nRBC in their peripheral blood, those positive for nRBC required longer mechanical ventilation (127 [44 - 289] h vs. 517 [255 - 950] h, p < 0.001), ICU stays (12 [8 - 19] vs. 27 [13 - 51] d, p < 0.001), and hospital stays (19 [12 - 29] d vs. 31 [16 - 58] d, p < 0.001). Peak Sepsis-related Organ Failure Assessment (SOFA), Simplified Acute Physiology Score, PaO2/FiO2, interleukin-6, and procalcitonin values were reached before the peak nRBC level. However, the predictive performance of the SOFA (AUCROC 0.842, p < 0.001) was considerably improved when a maximum SOFA score >8 and nRBC >105 µl-1 were combined.

Discussion

nRBC predict ICU mortality and indicate disease severity among patients with COVID-19 ARDS, and they should be considered a clinical alarm signal for a worse outcome. nRBC are a late predictor of ICU mortality compared to other established clinical scoring systems and laboratory parameters but improve the prediction accuracy when combined with the SOFA score.

Optimizing artificial intelligence in sepsis management: Opportunities in the present and looking closely to the future

Sepsis remains a major challenge internationally for healthcare systems. Its incidence is rising due to poor public awareness and delays in its recognition and subsequent management. In sepsis, mortality increases with every hour left untreated. Artificial intelligence (AI) is transforming worldwide healthcare delivery at present. This review has outlined how AI can augment strategies to address this global disease burden. AI and machine learning (ML) algorithms can analyze vast quantities of increasingly complex clinical datasets from electronic medical records to assist clinicians in diagnosing and treating sepsis earlier than traditional methods. Our review highlights how these models can predict the risk of sepsis and organ failure even before it occurs. This gives providers additional time to plan and execute treatment plans, thereby avoiding increasing complications associated with delayed diagnosis of sepsis. The potential for cost savings with AI implementation is also discussed, including improving workflow efficiencies, reducing administrative costs, and improving healthcare outcomes. Despite these advantages, clinicians have been slow to adopt AI into clinical practice. Some of the limitations posed by AI solutions include the lack of diverse data sets for model building so that they are widely applicable for routine clinical use. Furthermore, the subsequent algorithms are often based on complex mathematics leading to clinician hesitancy to embrace such technologies. Finally, we highlight the need for robust political and regulatory frameworks in this area to achieve the trust and approval of clinicians and patients to implement this transformational technology.

The influence of explainable vs non-explainable clinical decision support systems on rapid triage decisions: a mixed methods study

BACKGROUND

During the COVID-19 pandemic, a variety of clinical decision support systems (CDSS) were developed to aid patient triage. However, research focusing on the interaction between decision support systems and human experts is lacking.

METHODS

Thirty-two physicians were recruited to rate the survival probability of 59 critically ill patients by means of chart review. Subsequently, one of two artificial intelligence systems advised the physician of a computed survival probability. However, only one of these systems explained the reasons behind its decision-making. In the third step, physicians reviewed the chart once again to determine the final survival probability rating. We hypothesized that an explaining system would exhibit a higher impact on the physicians' second rating (i.e., higher weight-on-advice).

RESULTS

The survival probability rating given by the physician after receiving advice from the clinical decision support system was a median of 4 percentage points closer to the advice than the initial rating. Weight-on-advice was not significantly different (p = 0.115) between the two systems (with vs without explanation for its decision). Additionally, weight-on-advice showed no difference according to time of day or between board-qualified and not yet board-qualified physicians. Self-reported post-experiment overall trust was awarded a median of 4 out of 10 points. When asked after the conclusion of the experiment, overall trust was 5.5/10 (non-explaining median 4 (IQR 3.5-5.5), explaining median 7 (IQR 5.5-7.5), p = 0.007).

CONCLUSIONS

Although overall trust in the models was low, the median (IQR) weight-on-advice was high (0.33 (0.0-0.56)) and in line with published literature on expert advice. In contrast to the hypothesis, weight-on-advice was comparable between the explaining and non-explaining systems. In 30% of cases, weight-on-advice was 0, meaning the physician did not change their rating. The median of the remaining weight-on-advice values was 50%, suggesting that physicians either dismissed the recommendation or employed a "meeting halfway" approach. Newer technologies, such as clinical reasoning systems, may be able to augment the decision process rather than simply presenting unexplained bias.

Intelligent decision support in medical triage: are people robust to biased advice?

BACKGROUND

Intelligent artificial agents ('agents') have emerged in various domains of human society (healthcare, legal, social). Since using intelligent agents can lead to biases, a common proposed solution is to keep the human in the loop. Will this be enough to ensure unbiased decision making?

METHODS

To address this question, an experimental testbed was developed in which a human participant and an agent collaboratively conduct triage on patients during a pandemic crisis. The agent uses data to support the human by providing advice and extra information about the patients. In one condition, the agent provided sound advice; the agent in the other condition gave biased advice. The research question was whether participants neutralized bias from the biased artificial agent.

RESULTS

Although it was an exploratory study, the data suggest that human participants may not be sufficiently in control to correct the agent's bias.

CONCLUSIONS

This research shows how important it is to design and test for human control in concrete human-machine collaboration contexts. It suggests that insufficient human control can potentially result in people being unable to detect biases in machines and thus unable to prevent machine biases from affecting decisions.

Triage of Critically Ill Patients: Characteristics and Outcomes of Patients Refused as Too Well for Intensive Care

BACKGROUND

The appropriate selection of patients for the intensive care unit (ICU) is a concern in acute care settings. However, the description of patients deemed too well for the ICU has been rarely reported.

METHODS

We conducted a single-centre retrospective observational study of all patients either deemed "too well" for or admitted to the ICU during one year. Refused patients were screened for unexpected events within 7 days, defined as either ICU admission without another indication, or death without treatment limitations. Patients' characteristics and organisational factors were analysed according to refusal status, outcome and delay in ICU admission.

RESULTS

Among 2219 enrolled patients, the refusal rate was 10.4%. Refusal was associated with diagnostic groups, treatment limitations, patients' location on a ward, night time and ICU occupancy. Unexpected events occurred in 16 (6.9%) refused patients. A worse outcome was associated with time spent in hospital before refusal, patients' location on a ward, SOFA score and physician's expertise. Delayed ICU admissions were associated with ICU and hospital length of stay.

CONCLUSIONS

ICU triage selected safely most patients who would have probably not benefited from the ICU. We identified individual and organisational factors associated with ICU refusal, subsequent ICU admission or death.

The positive impact of COVID-19 on critical care: from unprecedented challenges to transformative changes, from the perspective of young intensivists

Over the past 2 years, SARS-CoV-2 infection has resulted in numerous hospitalizations and deaths worldwide. As young intensivists, we have been at the forefront of the fight against the COVID-19 pandemic and it has been an intense learning experience affecting all aspects of our specialty. Critical care was put forward as a priority and managed to adapt to the influx of patients and the growing demand for beds, financial and material resources, thereby highlighting its flexibility and central role in the healthcare system. Intensivists assumed an essential and unprecedented role in public life, which was important when claiming for indispensable material and human investments. Physicians and researchers around the world worked hand-in-hand to advance research and better manage this disease by integrating a rapidly growing body of evidence into guidelines. Our daily ethical practices and communication with families were challenged by the massive influx of patients and restricted visitation policies, forcing us to improve our collaboration with other specialties and innovate with new communication channels. However, the picture was not all bright, and some of these achievements are already fading over time despite the ongoing pandemic and hospital crisis. In addition, the pandemic has demonstrated the need to improve the working conditions and well-being of critical care workers to cope with the current shortage of human resources. Despite the gloomy atmosphere, we remain optimistic. In this ten-key points review, we outline our vision on how to capitalize on the lasting impact of the pandemic to face future challenges and foster transformative changes of critical care for the better.

Validation of the Acute Physiology and Chronic Health Evaluation (APACHE) II Score in COVID-19 Patients Admitted to the Intensive Care Unit in Times of Resource Scarcity

Introduction During the coronavirus disease 2019 (COVID-19) pandemic, a high number of patients needed to be admitted to the intensive care units (ICUs). Such a high demand led to periods where resources were insufficient and the triage of patients was needed. This study aims to evaluate the performance of the Acute Physiology and Chronic Health Evaluation (APACHE) II as a predictor of mortality in periods where triage protocols were implemented. Methods A single-center, longitudinal, retrospective cohort study was performed on patients admitted to the ICU between January 2020 and December 2021. Patients were divided into two periods: Period 1 (where patients needing ICU admission outnumbered the available resources) and Period 2 (where resources were adequate). The discriminative power of the APACHE II was checked using the receiver operating characteristic (ROC) curves. Calibration was accessed, and survival analysis was performed. Results Data from 428 patients were analyzed (229 in Period 1 and 199 in Period 2). The area under the ROC curve (AUROC) was 0.763 for Period 1 and 0.761 for Period 2, reflecting a good discriminative power. Logistic regression showed the APACHE II to be a significant predictor of mortality. The Hosmer-Lemeshow test demonstrated good calibration. The Youden index was determined, and a log-rank test showed a significantly lower survival for patients with higher APACHE II scores in both periods. Conclusions The APACHE II score is an effective tool in predicting mortality in patients with COVID-19 admitted to the ICU in a period where resource allocation and triage of patients are needed, paving a way for the future development of better and improved triage systems.

Public voices on tie-breaking criteria and underlying values in COVID-19 triage protocols to access critical care: a scoping review

Background

To reduce the arbitrariness in the allocation of rare resources in intensive care units (ICU) in the context of the pandemic, tiebreakers were considered in some COVID-19 triage algorithms. They were also contemplated to facilitate the tragic decisions of healthcare workers when faced with two patients with similar prognosis and only one ICU bed available. Little is known about the public's perspective on tiebreakers.

Objectives

To consolidate the available scientific literature on public consultations, particularly on tiebreakers and their underlying values. Also, to obtain an overview of the key arguments presented by the participating public and to identify potential gaps related to this topic.

Methods

The steps described by Arksey and O'Malley was the preferred method to our approach. Seven electronic databases were searched from January 2020 to April 2022, using keywords for each database: PubMed, Medline, EMBASE, Web of Science, PsycINFO, EBM reviews, CINAHL complete. We also searched in Google and Google Scholar, and in the references of the articles found. Our analysis was mainly qualitative. A thematic analysis was performed to consider the public's perspectives on tiebreakers and their underlying values, according to these studies.

Results

Of 477 publications found, 20 were selected. They carried out public consultations through various methods: surveys (80%), interviews (20%), deliberative processes (15%) and others (5%) in various countries: Australia, Brazil, Canada, China, France, Germany, India, Iran, Italy, Japan, Korea, Netherlands, Portugal, Spain, Switzerland, Thailand, United Kingdom, and United States. Five themes emerged from our analysis. The public favored the life cycle (50%) and absolute age (45%) as a tiebreaker. Other values considered important were reciprocity, solidarity, equality, instrumental value, patient merit, efficiency, and stewardship. Among the new findings were a preference for patient nationality and those affected by COVID-19.

Conclusions

There is a preference for favoring younger patients over older patients when there is a tie between similar patients, with a slight tendency to favor intergenerational equity. Variability was found in the public's perspectives on tiebreakers and their values. This variability was related to socio-cultural and religious factors. More studies are needed to understand the public's perspective on tiebreakers.

Supplementary Information

The online version contains supplementary material available at 10.1007/s44250-023-00027-9.

A Mobile Application-Based Relational Agent as a Health Professional for COVID-19 Patients: Design, Approach, and Implications

Relational Agents' (RAs) ability to maintain socio-emotional relationships with users can be an asset to COVID-19 patients. The goal of this research was to identify principles for designing an RA that can act as a health professional for a COVID-19 patient. We first identified tasks that such an RA can provide by interviewing 33 individuals, who had recovered from COVID-19. The transcribed interviews were analyzed using qualitative thematic analysis. Based on the findings, four sets of hypothetical conversations were handcrafted to illustrate how the proposed RA will execute the identified tasks. These conversations were then evaluated by 43 healthcare professionals in a qualitative study. Thematic analysis was again used to identify characteristics that would be suitable for the proposed RA. The results suggest that the RA must: model clinical protocols; incorporate evidence-based interventions; inform, educate, and remind patients; build trusting relationships, and support their socio-emotional needs. The findings have implications for designing RAs for other healthcare contexts beyond the pandemic.

Validation of a simple risk stratification tool for COVID-19 mortality

Risk prediction is an essential part of clinical care, in order to allocate resources and provide care appropriately. During the COVID-19 pandemic risk prediction became a matter of political and public debate as a major clinical need to guide medical and organizational decisions. We previously presented a simplified risk stratification score based on a nomogram developed in Wuhan, China in the early phase of the pandemic. Here we aimed to validate this simplified risk stratification score in a larger patient cohort from one city in Austria. Age, oxygen saturation, C-reactive protein levels and creatinine levels were used to estimate the in-hospital mortality risk for COVID-19 patients in a point based score: 1 point per age decade, 4 points for oxygen saturation <92%, 8 points for CRP > 10 mg/l and 4 points for creatinine > 84 μmol/l. Between June 2020 and March 2021, during the “second wave” of the pandemic, 1,472 patients with SARS-CoV-2 infection were admitted to two hospitals in Graz, Austria. In 961 patients the necessary dataset to calculate the simplified risk stratification score was available. In this cohort, as in the cohort that was used to develop the score, a score above 22 was associated with a significantly higher mortality (p < 0.001). Cox regression confirmed that an increase of one point in the risk stratification score increases the 28-day-mortality risk approximately 1.2-fold. Patients who were categorized as high risk (≥22 points) showed a 3–4 fold increased mortality risk. Our simplified risk stratification score performed well in a separate, larger validation cohort. We therefore propose that our risk stratification score, that contains only two routine laboratory parameter, age and oxygen saturation as variables can be a useful and easy to implement tool for COVID-19 risk stratification and beyond. The clinical usefulness of a risk prediction/stratification tool needs to be assessed prospectively (https://www.cbmed.at/covid-19-risk-calculator/).

A Relational Agent for the COVID-19 Patients: Design, Approach, and Implications

BACKGROUND

Relational agents (RAs) have shown effectiveness in various health interventions with and without doctors and hospital facilities. We suggest that in situations such as a pandemic like the COVID-19 when healthcare professionals (HCPs) and facilities are unable to cope with increased demands, RAs can play a major role in ameliorating the situation.

OBJECTIVE

The goal of this research was to seek design validation on a prototypical RA to address healthcare needs of the COVID-19 patients.

METHODS

Therefore, RAs can deliver health interventions during COVID-19 pandemic, but they have not been well-explored in this domain. To address this gap, a prototypical RA is iteratively designed and developed in collaboration with infected patients (n=21) and two groups of HCPs (n=19 and n=16 respectively) to aid COVID-19 patients at various stages by performing four main tasks: testing guidance, support during self-isolation, handling emergency situations, and promoting post-recovery mental well-being.

RESULTS

A survey with 98 individuals was used to evaluate the usability of the prototype by system usability scale (SUS) and it received an average score of 58.82. Moreover, participants indicated perceived usefulness and acceptability of the system on Likert Scales where 89.65% perceived it to be helpful, 68.97% accepted it as a viable alternative to HCPs.

CONCLUSIONS

The prototypical RA received favorable feedback from the participants and they were inclined to accept it as an alternative to HCPs in non-life-threatening scenarios despite the usability rating falling below the acceptable threshold. Based on participants' feedback, we recommend further development of the RA with improved automation and emotional support, ability to provide information, tracking, and specific recommendations.

The citizen preferences-positive externality trade-off: A survey study of COVID-19 vaccine deployment in Japan

Objective

Medicine is a scarce resource and a public good that benefits others by bettering patients’ health. COVID-19 vaccines in shortage are, 1) a scarce resource and 2) a public good with the positive externality of building herd immunity. These features are expected to drive citizens’ attitudes in opposite directions, exclusionist and inclusionist, respectively. Scarcity would drive citizens’ exclusionism, while the positive externality might mitigate exclusionism.

Setting and design

We recruited 15,000 Japanese adults and asked them to rank, in the context of a COVID-19 vaccine shortage, the deservingness of hypothetical vaccine recipients who differed according to 1) citizenship status, 2) visa type and duration of stay (if foreign), 3) occupation, 4) age, 5) whether they lived with a child, and 6) whether they lived with an elderly individual. Citizenship options were Japanese, Chinese, Taiwanese, South Korean, American, or European. The occupations were healthcare, education, other employed, self-employed, or not employed. The 6 attributes were randomly combined, and respondents were shown 3 hypothetical vaccine recipients: one was Japanese, and the others were foreigners.

Treatments

First, through a conjoint design, we created hypothetical vaccine recipients whose attributes were randomized except for the benchmark citizenship, Japanese national. Second, we randomly presented two scenarios for vaccination payments: 1) billed at cost or 2) fully subsidized by the government.

Results

1) Whether the vaccines were billed at cost or fully subsidized did not affect the rankings of deservingness. 2) Japanese citizenship was prioritized. 3) The penalty for being a foreigner was higher for individuals from nations with which Japan has geopolitical tensions. 4) Working in health or education reduced the penalty on foreigners, indicating that the positive externality related to occupation amplifies the positive externality associated with vaccination and mitigates exclusionist attitudes.

Conclusions

The positive occupational externalities that amplify the positive externality of vaccination substantially allay the foreigner penalty.

Non-COVID outcomes associated with the coronavirus disease-2019 (COVID-19) pandemic effects study (COPES): A systematic review and meta-analysis

BACKGROUND

As the Coronavirus Disease-2019 (COVID-19) pandemic continues, healthcare providers struggle to manage both COVID-19 and non-COVID patients while still providing high-quality care. We conducted a systematic review/meta-analysis to describe the effects of the COVID-19 pandemic on patients with non-COVID illness and on healthcare systems compared to non-pandemic epochs.

METHODS

We searched Ovid MEDLINE/EMBASE/Cochrane Database of Systematic Reviews/CENTRAL/CINAHL (inception to December 31, 2020). All study types with COVID-pandemic time period (after December 31, 2019) with comparative non-pandemic time periods (prior to December 31, 2019). Data regarding study characteristics/case-mix/interventions/comparators/ outcomes (primary: mortality; secondary: morbidity/hospitalizations/disruptions-to-care. Paired reviewers conducted screening and abstraction, with conflicts resolved by discussion. Effect sizes for specific therapies were pooled using random-effects models. Risk of bias was assessed by Newcastle-Ottawa Scale, with evidence rating using GRADE methodology.

RESULTS

Of 11,581 citations, 167 studies met eligibility. Our meta-analysis showed an increased mortality of 16% during the COVID pandemic for non-COVID illness compared with 11% mortality during the pre-pandemic period (RR 1.38, 95% CI: 1.28-1.50; absolute risk difference: 5% [95% CI: 4-6%], p<0.00001, very low certainty evidence). Twenty-eight studies (17%) reported significant changes in morbidity (where 93% reported increases), while 30 studies (18%) reported no significant change (very low certainty). Thirty-nine studies (23%) reported significant changes in hospitalizations (97% reporting decreases), while 111 studies (66%) reported no significant change (very low certainty). Sixty-two studies (37%) reported significant disruptions in standards-to-care (73% reporting increases), while 62 studies (37%) reported no significant change (very low certainty).

CONCLUSIONS

There was a significant increase in mortality during the COVID pandemic compared to pre-pandemic times for non-COVID illnesses. When significant changes were reported, there was increased morbidity, decreased hospitalizations and increased disruptions in standards-of-care.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020201256 (Sept 2, 2020).

Exploration of the Experience of Care Home Managers of COVID-19 Vaccination Programme Implementation and Uptake by Residents and Staff in Care Homes in Northern Ireland

The Coronavirus 2019 (COVID-19) pandemic disproportionately affected people living and working in care homes. This study aimed to explore the experience of care home managers on the implementation and uptake of the COVID-19 vaccination programme by residents and staff in care homes in Northern Ireland. An exploratory mixed methods approach was used, i.e., semi-structured interviews to design the cross-sectional survey and content analysis of statements using open ended questions. Care home managers were approached and sixty-seven valid quantitative and forty-nine descriptive responses were analysed. The study identified eight themes which described factors that motivated residents (family visits and relationship with managers and staff), and staff vaccine uptake (return to normal life at work and trust in care home managers). The identified themes also confirmed that vaccine uptake is negatively influenced by perceived side effects. The findings indicated that social media can promote or decelerate the uptake of vaccine despite the accessibility to a successful vaccination programme. The study highlights the important role of managers in handling the challenges through building trust and establishing relationships with staff and residents. The findings identified challenges to the uptake of the COVID-19 vaccine by staff and residents that can inform the implementation of future vaccination programmes.

Direct Comparison of Clinical Characteristics, Outcomes, and Risk Prediction in Patients with COVID-19 and Controls-A Prospective Cohort Study

Most studies investigating early risk predictors in coronavirus disease 19 (COVID-19) lacked comparison with controls. We aimed to assess and directly compare outcomes and risk predictors at time of emergency department (ED) presentation in COVID-19 and controls. Consecutive patients presenting to the ED with suspected COVID-19 were prospectively enrolled. COVID-19-patients were compared with (i) patients tested negative (overall controls) and (ii) patients tested negative, who had a respiratory infection (respiratory controls). Primary outcome was the composite of intensive care unit (ICU) admission and death at 30 days. Among 1081 consecutive cases, 191 (18%) were tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and 890 (82%) were tested negative (overall controls), of which 323 (30%) had a respiratory infection (respiratory controls). Incidence of the composite outcome was significantly higher in COVID-19 (23%) as compared with the overall control group (10%, adjusted-HR 2.45 (95%CI, 1.61–3.74), p < 0.001) or the respiratory control group (10%, adjusted-HR 2.93 (95%CI, 1.66–5.17), p < 0.001). Blood oxygen saturation, age, high-sensitivity troponin, c-reactive protein, and lactate dehydrogenase were identified as the strongest predictors of poor outcome available at time of ED presentation in COVID-19 with highly comparable prognostic utility in overall and respiratory controls. In conclusion, patients presenting to the ED with COVID-19 have a worse outcome than controls, even after adjustment for differences in baseline characteristics. Most predictors of poor outcome in COVID-19 were not restricted to COVID-19, but of comparable prognostic utility in controls and therefore generalizable to unselected patients with suspected COVID-19.