Background: The emergence of new SARS-CoV-2 variants with significant immune-evasiveness, the relaxation of measures for reducing the number of infections, the waning of immune protection (particularly in high-risk population groups), and the low uptake of new vaccine boosters, forecast new waves of hospitalizations and admission to intensive care units (ICUs). There is an urgent need for easily implementable and clinically effective early warning scores (EWSs) that can predict the risk of complications within the next 24 to 48 hours. Although EWSs have been used in the evaluation of COVID-19 patients, there are several clinical limitations to their use. Moreover, no models have been tested on geographically distinct populations or population groups with varying levels of immune protection.
Methods: We developed and validated COEWS, an EWS that is automatically calculated solely from laboratory parameters that are widely available and affordable. We benchmarked COEWS against the widely used NEWS2. We also evaluated the predictive performance of vaccinated and unvaccinated patients.
Results: The variables of the COEWS predictive model were selected based on their predictive coefficients and on the wide availability of these laboratory variables. The final model included complete blood count, blood glucose, and oxygen saturation features. To make COEWS more actionable in real clinical situations, we transformed the predictive coefficients of the COEWS model into individual scores for each selected feature. The global score serves as an easy-to-calculate measure indicating the risk of a patient developing the combined outcome of mechanical ventilation or death within the next 48 hours. The discrimination in the external validation cohort was 0.743 (95% confidence interval [CI]: 0.703-0.784) for the COEWS score performed with coefficients and 0.700 (95% CI: 0.654-0.745) for the COEWS performed with scores. The area under the receiver operating characteristic curve (AUROC) was similar in vaccinated and unvaccinated patients. Additionally, we observed that the AUROC of the NEWS2 was 0.677 (95% CI: 0.601-0.752) in vaccinated patients and 0.648 (95% CI: 0.608-0.689) in unvaccinated patients.
Conclusions: The COEWS score predicts death or mechanical ventilation within the next 48 hours based on routine and widely available laboratory measurements. The extensive external validation, its high performance, its ease of use, and its positive benchmark in comparison with the widely used NEWS2 position COEWS as a new reference tool for assisting clinical decisions and improving patient care in the upcoming pandemic waves.
Funding: University of Vienna.
The databases used in this article are not freely available because they are the property of the '12 de Octubre University Hospital' from Spain and the 'Sociedad Argentina de Medicina' from Argentina. If any researcher wants to use this data, please send a message to either Dr. Antonio Lalueza (email@example.com) or to Dr. Ivan Alfredo Huespe (firstname.lastname@example.org) including a project proposal. The data will be only available for non-commercial proposals. The dataset used for Figure 2 can be found in the Supplementary data tables.
- David Gómez-Varela
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Human subjects: The SEMI-COVID-19 Registry and the COVID registries of 12 de Octubre and the Costa del Sol hospitals have been approved by the Provincial Research Ethics Committee of Malaga (Spain; C.I.F. number: 0-9150013-B). Institutional review boards approved each participating site in the Argentinian COVID-19 Network study (approval numbers: 1575, 5562, and 5606).
- Evangelos J Giamarellos-Bourboulis, National and Kapodistrian University of Athens, Medical School, Greece
© 2023, Klén et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Irregular sleep-wake timing may cause circadian disruption leading to several chronic age-related diseases. We examined the relationship between sleep regularity and risk of all-cause, cardiovascular disease (CVD), and cancer mortality in 88,975 participants from the prospective UK Biobank cohort.
The sleep regularity index (SRI) was calculated as the probability of an individual being in the same state (asleep or awake) at any two time points 24 hr apart, averaged over 7 days of accelerometry (range 0–100, with 100 being perfectly regular). The SRI was related to the risk of mortality in time-to-event models.
The mean sample age was 62 years (standard deviation [SD], 8), 56% were women, and the median SRI was 60 (SD, 10). There were 3010 deaths during a mean follow-up of 7.1 years. Following adjustments for demographic and clinical variables, we identified a non-linear relationship between the SRI and all-cause mortality hazard (p [global test of spline term]<0.001). Hazard ratios, relative to the median SRI, were 1.53 (95% confidence interval [CI]: 1.41, 1.66) for participants with SRI at the 5th percentile (SRI = 41) and 0.90 (95% CI: 0.81, 1.00) for those with SRI at the 95th percentile (SRI = 75), respectively. Findings for CVD mortality and cancer mortality followed a similar pattern.
Irregular sleep-wake patterns are associated with higher mortality risk.
National Health and Medical Research Council of Australia (GTN2009264; GTN1158384), National Institute on Aging (AG062531), Alzheimer’s Association (2018-AARG-591358), and the Banting Fellowship Program (#454104).
The Coronavirus Disease of 2019 (COVID-19) has impacted the health and day-to-day life of individuals, especially the elderly and people with certain pre-existing medical conditions, including cancer. The purpose of this study was to investigate how COVID-19 impacted access to cancer screenings and treatment, by studying the participants in the Multiethnic Cohort (MEC) study.
The MEC has been following over 215,000 residents of Hawai‘i and Los Angeles for the development of cancer and other chronic diseases since 1993–1996. It includes men and women of five racial and ethnic groups: African American, Japanese American, Latino, Native Hawaiian, and White. In 2020, surviving participants were sent an invitation to complete an online survey on the impact of COVID-19 on their daily life activities, including adherence to cancer screening and treatment. Approximately 7,000 MEC participants responded. A cross-sectional analysis was performed to investigate the relationships between the postponement of regular health care visits and cancer screening procedures or treatment with race and ethnicity, age, education, and comorbidity.
Women with more education, women with lung disease, COPD, or asthma, and women and men diagnosed with cancer in the past 5 years were more likely to postpone any cancer screening test/procedure due to the COVID-19 pandemic. Groups less likely to postpone cancer screening included older women compared to younger women and Japanese American men and women compared to White men and women.
This study revealed specific associations of race/ethnicity, age, education level, and comorbidities with the cancer-related screening and healthcare of MEC participants during the COVID-19 pandemic. Increased monitoring of patients in high-risk groups for cancer and other diseases is of the utmost importance as the chance of undiagnosed cases or poor prognosis is increased as a result of delayed screening and treatment.
This research was partially supported by the Omidyar 'Ohana Foundation and grant U01 CA164973 from the National Cancer Institute.