Performance of digital early warning score (NEWS2) in a cardiac specialist setting: retrospective cohort study. Issue 3 (13th March 2023)

• Record Type: Journal Article
• Authors: Alhmoud, Baneen; Bonnici, Tim; Melley, Daniel; Patel, Riyaz; Banerjee, Amitava
• Is Part Of: BMJ open. Volume 13:Issue 3(2023)
• Publication Date: 2023-03-13
• Subjects: COVID-19 -- adult cardiology -- adult intensive & critical care -- risk management -- health informatics; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2022-066131
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : Introduction: Patients with cardiovascular diseases (CVD) are at significant risk of developing critical events. Early warning scores (EWS) are recommended for early recognition of deteriorating patients, yet their performance has been poorly studied in cardiac care settings. Standardisation and integrated National Early Warning Score 2 (NEWS2) in electronic health records (EHRs) are recommended yet have not been evaluated in specialist settings. Objective: To investigate the performance of digital NEWS2 in predicting critical events: death, intensive care unit (ICU) admission, cardiac arrest and medical emergencies. Methods: Retrospective cohort analysis. Study cohort: Individuals admitted with CVD diagnoses in 2020; including patients with COVID-19 due to conducting the study during the COVID-19 pandemic. Measures: We tested the ability of NEWS2 in predicting the three critical outcomes from admission and within 24 hours before the event. NEWS2 was supplemented with age and cardiac rhythm and investigated. We used logistic regression analysis with the area under the receiver operating characteristic curve (AUC) to measure discrimination. Results: In 6143 patients admitted under cardiac specialties, NEWS2 showed moderate to low predictive accuracy of traditionally examined outcomes: death, ICU admission, cardiac arrest and medical emergency (AUC: 0.63, 0.56, 0.70 and 0.63, respectively). Supplemented NEWS2 with age showed no improvement while age and cardiac rhythm improved discrimination (AUC: 0.75, 0.84, 0.95 and 0.94, respectively). Improved performance was found of NEWS2 with age for COVID-19 cases (AUC: 0.96, 0.70, 0.87 and 0.88, respectively). Conclusion: The performance of NEWS2 in patients with CVD is suboptimal, and fair for patients with CVD with COVID-19 to predict deterioration. Adjustment with variables that strongly correlate with critical cardiovascular outcomes, that is, cardiac rhythm, can improve the model. There is a need to define critical endpoints, engagement with clinical experts in development and further validation and implementation studies of EHR-integrated EWS in cardiac specialist settings.