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Predictive Value of 5 Early Warning Scores for Critical COVID-19 Patients.

ABSTRACT: OBJECTIVES:A simple evaluation tool for patients with novel coronavirus disease 2019 (COVID-19) could assist the physicians to triage COVID-19 patients effectively and rapidly. This study aimed to evaluate the predictive value of 5 early warning scores based on the admission data of critical COVID-19 patients. METHODS:Overall, medical records of 319 COVID-19 patients were included in the study. Demographic and clinical characteristics on admission were used for calculating the Standardized Early Warning Score (SEWS), National Early Warning Score (NEWS), National Early Warning Score2 (NEWS2), Hamilton Early Warning Score (HEWS), and Modified Early Warning Score (MEWS). Data on the outcomes (survival or death) were collected for each case and extracted for overall and subgroup analysis. Receiver operating characteristic curve analyses were performed. RESULTS:The area under the receiver operating characteristic curve for the SEWS, NEWS, NEWS2, HEWS, and MEWS in predicting mortality were 0.841 (95% CI: 0.765-0.916), 0.809 (95% CI: 0.727-0.891), 0.809 (95% CI: 0.727-0.891), 0.821 (95% CI: 0.748-0.895), and 0.670 (95% CI: 0.573-0.767), respectively. CONCLUSIONS:SEWS, NEWS, NEWS2, and HEWS demonstrated moderate discriminatory power and, therefore, offer potential utility as prognostic tools for screening severely ill COVID-19 patients. However, MEWS is not a good prognostic predictor for COVID-19.

SUBMITTER: Hu H

PROVIDER: S-EPMC7596567 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Predictive Value of 5 Early Warning Scores for Critical COVID-19 Patients.

Hu Hai H Yao Ni N Qiu Yanru Y

Disaster medicine and public health preparedness 20200909 1

<h4>Objectives</h4>A simple evaluation tool for patients with novel coronavirus disease 2019 (COVID-19) could assist the physicians to triage COVID-19 patients effectively and rapidly. This study aimed to evaluate the predictive value of 5 early warning scores based on the admission data of critical COVID-19 patients.<h4>Methods</h4>Overall, medical records of 319 COVID-19 patients were included in the study. Demographic and clinical characteristics on admission were used for calculating the Sta ...[more]

PMID: 32900406

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Project description:Background: Early Warning Scores (EWS), including the National Early Warning Score 2 (NEWS2) and Modified NEWS (NEWS-C), have been recommended for triage decision in patients with COVID-19. However, the effectiveness of these EWS in COVID-19 has not been fully validated. The study aimed to investigate the predictive value of EWS to detect clinical deterioration in patients with COVID-19. Methods: Between February 7, 2020 and February 17, 2020, patients confirmed with COVID-19 were screened for this study. The outcomes were early deterioration of respiratory function (EDRF) and need for intensive respiratory support (IRS) during the treatment process. The EDRF was defined as changes in the respiratory component of the sequential organ failure assessment (SOFA) score at day 3 (ΔSOFAresp = SOFA resp at day 3-SOFAresp on admission), in which the positive value reflects clinical deterioration. The IRS was defined as the use of high flow nasal cannula oxygen therapy, noninvasive or invasive mechanical ventilation. The performances of EWS including NEWS, NEWS 2, NEWS-C, Modified Early Warning Scores (MEWS), Hamilton Early Warning Scores (HEWS), and quick sepsis-related organ failure assessment (qSOFA) for predicting EDRF and IRS were compared using the area under the receiver operating characteristic curve (AUROC). Results: A total of 116 patients were included in this study. Of them, 27 patients (23.3%) developed EDRF and 24 patients (20.7%) required IRS. Among these EWS, NEWS-C was the most accurate scoring system for predicting EDRF [AUROC 0.79 (95% CI, 0.69-0.89)] and IRS [AUROC 0.89 (95% CI, 0.82-0.96)], while NEWS 2 had the lowest accuracy in predicting EDRF [AUROC 0.59 (95% CI, 0.46-0.720)] and IRS [AUROC 0.69 (95% CI, 0.57-0.81)]. A NEWS-C ≥ 9 had a sensitivity of 59.3% and a specificity of 85.4% for predicting EDRF. For predicting IRS, a NEWS-C ≥ 9 had a sensitivity of 75% and a specificity of 88%. Conclusions: The NEWS-C was the most accurate scoring system among common EWS to identify patients with COVID-19 at risk for EDRF and need for IRS. The NEWS-C could be recommended as an early triage tool for patients with COVID-19.

Project description:ObjectivesTo investigate whether National Early Warning Scores (NEWS/NEWS2) could contribute to COVID-19 surveillance in care homes.Setting460 care home units using the same software package to collect data on residents, from 46 local authority areas in England.Participants6464 care home residents with at least one NEWS recording.Exposure measure29 656 anonymised person-level NEWS from 29 December 2019 to 20 May 2020 with component physiological measures: systolic blood pressure, respiratory rate, pulse rate, temperature and oxygen saturation. Baseline values for each measure calculated using 80th and 20th centile scores before March 2020.Outcome measureCross-correlation comparison of time series with Office for National Statistics weekly reported registered deaths of care home residents where COVID-19 was the underlying cause of death, and all other deaths (excluding COVID-19) up to 10 May 2020.ResultsDeaths due to COVID-19 were registered from 23 March 2020 in the local authority areas represented in the study. Between 23 March 2020 and 10 May 2020, there were 5753 deaths (1532 involving COVID-19 and 4221 other causes). We observed a rise in the proportion of above-baseline NEWS beginning 16 March 2020, followed 2 weeks later by an increase in registered deaths (cross-correlation of r=0.82, p<0.05 for a 2 week lag) in corresponding local authorities. The proportion of above-baseline oxygen saturation, respiratory rate and temperature measurements also increased approximately 2 weeks before peaks in deaths.ConclusionsNEWS could contribute to COVID-19 disease surveillance in care homes during the pandemic. Oxygen saturation, respiratory rate and temperature could be prioritised as they appear to signal rise in mortality almost as well as NEWS. This study reinforces the need to collate data from care homes, to monitor and protect residents' health. Further work using individual level outcome data is needed to evaluate the role of NEWS in the early detection of resident illness.

Project description:OBJECTIVE:To provide an overview and critical appraisal of early warning scores for adult hospital patients. DESIGN:Systematic review. DATA SOURCES:Medline, CINAHL, PsycInfo, and Embase until June 2019. ELIGIBILITY CRITERIA FOR STUDY SELECTION:Studies describing the development or external validation of an early warning score for adult hospital inpatients. RESULTS:13?171 references were screened and 95 articles were included in the review. 11 studies were development only, 23 were development and external validation, and 61 were external validation only. Most early warning scores were developed for use in the United States (n=13/34, 38%) and the United Kingdom (n=10/34, 29%). Death was the most frequent prediction outcome for development studies (n=10/23, 44%) and validation studies (n=66/84, 79%), with different time horizons (the most frequent was 24 hours). The most common predictors were respiratory rate (n=30/34, 88%), heart rate (n=28/34, 83%), oxygen saturation, temperature, and systolic blood pressure (all n=24/34, 71%). Age (n=13/34, 38%) and sex (n=3/34, 9%) were less frequently included. Key details of the analysis populations were often not reported in development studies (n=12/29, 41%) or validation studies (n=33/84, 39%). Small sample sizes and insufficient numbers of event patients were common in model development and external validation studies. Missing data were often discarded, with just one study using multiple imputation. Only nine of the early warning scores that were developed were presented in sufficient detail to allow individualised risk prediction. Internal validation was carried out in 19 studies, but recommended approaches such as bootstrapping or cross validation were rarely used (n=4/19, 22%). Model performance was frequently assessed using discrimination (development n=18/22, 82%; validation n=69/84, 82%), while calibration was seldom assessed (validation n=13/84, 15%). All included studies were rated at high risk of bias. CONCLUSIONS:Early warning scores are widely used prediction models that are often mandated in daily clinical practice to identify early clinical deterioration in hospital patients. However, many early warning scores in clinical use were found to have methodological weaknesses. Early warning scores might not perform as well as expected and therefore they could have a detrimental effect on patient care. Future work should focus on following recommended approaches for developing and evaluating early warning scores, and investigating the impact and safety of using these scores in clinical practice. SYSTEMATIC REVIEW REGISTRATION:PROSPERO CRD42017053324.

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Predictive Value of 5 Early Warning Scores for Critical COVID-19 Patients.

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Predictive Value of 5 Early Warning Scores for Critical COVID-19 Patients.

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