Risk Stratification Model for Severe COVID-19 Disease: A Retrospective Cohort Study

Accuracy of the Canadian COVID-19 Mortality Score (CCMS) to predict in-hospital mortality among vaccinated and unvaccinated patients infected with Omicron: a cohort study

OBJECTIVE

The objective is to externally validate and assess the opportunity to update the Canadian COVID-19 Mortality Score (CCMS) to predict in-hospital mortality among consecutive non-palliative COVID-19 patients infected with Omicron subvariants at a time when vaccinations were widespread.

DESIGN

This observational study validated the CCMS in an external cohort at a time when Omicron variants were dominant. We assessed the potential to update the rule and improve its performance by recalibrating and adding vaccination status in a subset of patients from provinces with access to vaccination data and created the adjusted CCMS (CCMSadj). We followed discharged patients for 30 days after their index emergency department visit or for their entire hospital stay if admitted.

SETTING

External validation cohort for CCMS: 36 hospitals participating in the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN). Update cohort for CCMSadj: 14 hospitals in CCEDRRN in provinces with vaccination data.

PARTICIPANTS

Consecutive non-palliative COVID-19 patients presenting to emergency departments.

MAIN OUTCOME MEASURES

In-hospital mortality.

RESULTS

Of 39 682 eligible patients, 1654 (4.2%) patients died. The CCMS included age, sex, residence type, arrival mode, chest pain, severe liver disease, respiratory rate and level of respiratory support and predicted in-hospital mortality with an area under the curve (AUC) of 0.88 (95% CI 0.87 to 0.88) in external validation. Updating the rule by recalibrating and adding vaccination status to create the CCMSadj changed the weights for age, respiratory status and homelessness, but only marginally improved its performance, while vaccination status did not. The CCMSadj had an AUC of 0.91 (95% CI 0.89 to 0.92) in validation. CCMSadj scores of <10 categorised patients as low risk with an in-hospital mortality of <1.6%. A score>15 had observed mortality of >56.8%.

CONCLUSIONS

The CCMS remained highly accurate in predicting mortality from Omicron and improved marginally through recalibration. Adding vaccination status did not improve the performance. The CCMS can be used to inform patient prognosis, goals of care conversations and guide clinical decision-making for emergency department patients with COVID-19.

Use of a Virtual Multi-Disciplinary Clinic for the Treatment of Post-COVID-19 Patients

Post-COVID-19 has been recognized as possibly affecting millions of people worldwide. In order to optimize care and ensure equality, we established a multidisciplinary virtual Post-COVID-19 clinic (VPCC) within Maccabi Healthcare Services, the second largest HMO in Israel. This study aims to describe the structure, process and patient satisfaction with this clinic. The multidisciplinary team consisted of physicians, physiotherapists, social workers, occupational therapists and dieticians. Patient entry was to be at least four weeks after COVID-19 infection. A patient satisfaction survey was carried out 7-8 months after the clinic was closed. Demographic data were collected and compared to the general Maccabi COVID-19 population. The clinic treated 1614 patients, aged 16-91, over a period of 18 months. In total, 679 family physicians referred patients. In comparison to the general COVID-19 population, a higher percentage of the VPCC patients lived in the periphery of Israel, South (14.9% compared to 17.8%) and North (17.1% compared to 18.2%). In total, 249 patients answered the survey, and of them, 75% were highly satisfied with the medical care of the physician in the VPCC. A total of 54% of respondents would have preferred a face-to-face consultation, but 50% felt that communication was good in the virtual mode. In conclusion, the VPCC provided a dedicated service for patients, and the virtual format made it equally accessible to all parts of the country.

Factors associated with COVID-19 autumn 2022 booster uptake in the Netherlands among older adults aged ≥ 60 years and younger adults with chronic conditions

BACKGROUND

A booster with bivalent COVID-19 vaccine was offered in the Netherlands in autumn, 2022. We aimed to investigate vaccine uptake during the autumn 2022 booster round among the population subgroups at risk for severe COVID-19 that were specifically targeted by this campaign: the medical risk group aged 18-59 years and individuals ≥ 60 years. We calculated booster uptake in both populations and analyzed determinants of booster uptake among those who had received at least one prior COVID-19 vaccination.

METHODS

Having had an autumn 2022 booster dose was defined as having received a COVID-19 vaccination between 19 September 2022 and 7 March 2023. The study population included individuals who received at least one previous COVID-19 vaccination. National registries of sociodemographic determinants and COVID-19 vaccination were linked by a unique person identifier. Voting proportions for political parties were included at neighborhood level. Determinants of COVID-19 vaccine autumn booster uptake were ranked by importance by random forest analyses.

RESULTS

Booster uptake was 68 % among those aged ≥ 60 and 30 % among those aged 18-59 years with a medical risk factor for severe disease. For both target groups the most important determinant for booster uptake was age (15 % in 18-29 years to 72 % in 80 + years). Voting proportions for progressive liberal political parties ranked second in the random forest analysis in both groups, with an increasing proportion of votes associated with higher uptake. In the 60 + group, household type ranked third, with highest vaccine uptake among married couples without children (72 %) and the lowest uptake among unmarried couples with children (47 %). In the medical risk group, migration status ranked third. Migrants with two parents born abroad had the lowest uptake (18 %), whereas migrants with both parents born in the Netherlands had the highest uptake (35 %).

CONCLUSION

The target group of people aged ≥ 60 years was much better reached than the target group of people with a medical risk aged 18-59 years. Uptake varied considerably among subgroups in both target groups. The findings of this study can be used in future vaccination strategies as well as for further research to better understand the drivers and barriers of vaccine uptake among the subgroups with notably low uptake.

The Buzz Surrounding Precision Medicine: The Imperative of Incorporating It into Evidence-Based Medical Practice

Precision medicine (PM), through the integration of omics and environmental data, aims to provide a more precise prevention, diagnosis, and treatment of disease. Currently, PM is one of the emerging approaches in modern healthcare and public health, with wide implications for health care delivery, public health policy making formulation, and entrepreneurial endeavors. In spite of its growing popularity and the buzz surrounding it, PM is still in its nascent phase, facing considerable challenges that need to be addressed and resolved for it to attain the acclaim for which it strives. In this article, we discuss some of the current methodological pitfalls of PM, including the use of big data, and provide a perspective on how these challenges can be overcome by bringing PM closer to evidence-based medicine (EBM). Furthermore, to maximize the potential of PM, we present real-world illustrations of how EBM principles can be integrated into a PM approach.