The aim of this study was to assess and compare the performance of NEWS2 and other commonly used clinical risk scores at ED admission to predict the development of severe disease and in-hospital mortality in patients with covid-19.
This is a prospective cohort study carried out at Bærum Hospital Vestre Viken Hospital Trust, a non-university hospital in the south-eastern part of Norway. The hospital serves approximately 185,000 inhabitants in two municipalities with more than 11,000 ED admissions per year. During the first weeks of the covid-19 outbreak in Norway, Bærum Hospital was among the hospitals in Norway with the highest rate of admission of covid-19 patients. The methods of the study and preliminary data have been previously published [6].
Study population
Patients admitted to the ED and with confirmed covid-19 infection from March 9th 2020 were consecutively included in the study. Patients that were discharged or deceased up until April27th 2020 were included in the current analysis. Covid-19 was confirmed by qualitative detection of nucleic acid from SARS-CoV-2 in throat or nasal secretions by use of real-time polymerase chain reaction [7]. Patients with confirmed infection who were admitted for other reasons than symptoms of covid-19 infection were excluded from the analysis based on clinical judgement.
Measures and definitions
The first author registered all data used in this analysis by review of clinical scoring charts and patient records. Clinical scores were based on the first recorded vital signs after admission, documented on charts or in the records.
NEWS2 is a standardised clinical scoring system developed to improve detection of deterioration in acutely ill patients (Fig. 1) [8]. It is based on aggregate scoring of six physiological parameters; respiratory rate, oxygen saturation, systolic blood pressure, pulse rate, level of consciousness or new confusion, and body temperature. In addition, two points are added for patients requiring supplementary oxygen treatment. A NEWS2 score of 5 or 6 is considered a key threshold that indicates clinical deterioration and should prompt increased monitoring and review by critical care staff [8]. The NEWS2 scoring chart is utilised as part of routine patient care practice at our hospital.
qSOFA has been recommended as the tool of choice to assess organ dysfunction in patients with suspected sepsis [9]. Three clinical variables: altered mental status, systolic blood pressure ≤ 100 mm Hg, and respiratory rate of ≥ 22/min; are scored with one point each. A qSOFA sum score ≥ 2 should prompt clinicians to investigate for organ dysfunction, initiate or escalate therapy, and to consider increased monitoring or referral to an ICU.
SIRS was defined as an evident infection with the presence of two or more of the criteria temperature > 38 °C or < 36 °C, heart rate > 90, respiratory rate > 20 or PaCO₂ < 32 mm Hg, and white blood cells > 12,000/mm³ or < 4,000/mm³ at admission [10].
CRB-65 is a clinical score developed for risk stratification of patients with community-acquired pneumonia. One point each is given for the clinical variables new confusion, respiratory rate ≥ 30, and systolic blood pressure < 90 mm Hg or diastolic blood pressure ≤ 60 mm Hg. In addition, age ≥ 65 years is scored with one point. A score of two or more indicates a need for hospitalisation and in-patient management [11].
We defined severe disease as a composite measure of death during hospitalization or ICU treatment for any reason during the hospital stay. In-hospital mortality was defined as death during hospital stay for any reason, related or unrelated to the covid-19 infection.
We used the Charlson Charlson Comorbidity Index (CCI) and the Clinical Frailty Scale (CFS) to characterise the premorbid status of the study population. CCI assesses chronic comorbidities such as heart failure, chronic kidney disease, chronic obstructive pulmonary disease (COPD) and malignancy, and predicts mortality in hospitalised patients [12]. CCI was scored based on comorbidities documented in patient records. CFS is tool that is used to rapidly summarise the overall level of fitness or frailty based on the functional capacity of the patient 14 days prior to the onset of acute illness [13]. CFS was scored based on information about the patients functional status documented in hospital records. Body mass index (BMI) was calculated based on patient height and weight registered during the hospital stay. Smoking habits were self-reported at admission.
Statistical methods
We used the registry tool EpiData entry client version 4.4.3.1 (The EpiData Association, Odense, Denmark). Continuous variables are presented as the mean ± standard deviation and categorical variables as the number (%). We used Student’s t test for means of continuous variables and Pearson’s Chi-square test of independence for categorical variables to compare characteristics of patient subgroups. Data was missing on smoking for six patients and BMI for 17 patients. To assess the ability of clinical tools to predict severe disease and in-hospital mortality, we calculated sensitivity, specificity, and positive and negative predictive values with 95% confidence intervals (CIs) using MEDCALC statistical software (http://www.medcalc.org). We used cut-off values that are recommended and commonly used; NEWS2 scores ≥ 5 and ≥ 6, qSOFA score ≥ 2, ≥2 SIRS criteria, and CRB-65 score ≥ 2. Areas under the curve (AUCs) for the clinical risk scores were compared using DeLong’s test implemented in the R package pROC (R version 3.6.1, The R Foundation) [14]. All other statistical analyses were conducted using SPSS version 25.0 (IBM, Armonk, NY, USA).
Patient and public involvement
Patient or public involvement in the design, execution or dissemination of results of the present study was not considered feasible or relevant.
Ethical considerations
The study was approved by the Vestre Viken Hospital Trust institutional review. Since only routine clinical data were collected from the electronic health records, the requirement for informed consent was waived. A letter with information about the study was sent by post to all patients, allowing the patient to withdraw their data. The study complies with the Declaration of Helsinki. Due to the proximity to real time, the interests of protection of privacy and the uncertainty implicit in a limited dataset, we refrained from detailed characterization of deceased patients, and analysed patients with severe disease and deceased patients as one category.