scholarly journals Early Warning Scores in Patients with Suspected COVID-19 Infection in Emergency Departments

2021 ◽  
Vol 11 (3) ◽  
pp. 170
Author(s):  
Francisco Martín-Rodríguez ◽  
José L. Martín-Conty ◽  
Ancor Sanz-García ◽  
Virginia Carbajosa Rodríguez ◽  
Guillermo Ortega Rabbione ◽  
...  
Keyword(s):  
Early Warning ◽  
Emergency Departments ◽  
Life Support ◽  
Area Under The Curve ◽  
Advanced Life Support ◽  
Early Mortality ◽  
Early Warning Score ◽  
Mortality Data ◽  
Early Warning Scores ◽  
National Early Warning Score

Early warning scores (EWSs) help prevent and recognize and thereby act as the first signs of clinical and physiological deterioration. The objective of this study is to evaluate different EWSs (National Early Warning Score 2 (NEWS2), quick sequential organ failure assessment score (qSOFA), Modified Rapid Emergency Medicine Score (MREMS) and Rapid Acute Physiology Score (RAPS)) to predict mortality within the first 48 h in patients suspected to have Coronavirus disease 2019 (COVID-19). We conducted a retrospective observational study in patients over 18 years of age who were treated by the advanced life support units and transferred to the emergency departments between March and July of 2020. Each patient was followed for two days registering their final diagnosis and mortality data. A total of 663 patients were included in our study. Early mortality within the first 48 h affected 53 patients (8.3%). The scale with the best capacity to predict early mortality was the National Early Warning Score 2 (NEWS2), with an area under the curve of 0.825 (95% CI: 0.75–0.89). The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive patients presented an area under the curve (AUC) of 0.804 (95% CI: 0.71–0.89), and the negative ones with an AUC of 0.863 (95% CI: 0.76–0.95). Among the EWSs, NEWS2 presented the best predictive power, even when it was separately applied to patients who tested positive and negative for SARS-CoV-2.

Accuracy of National Early Warning Score 2 (NEWS2) in Prehospital Triage on In-Hospital Early Mortality: A Multi-Center Observational Prospective Cohort Study

2019 ◽  
Vol 34 (6) ◽  
pp. 610-618 ◽  
Author(s):  
Francisco Martín-Rodríguez ◽  
Raúl López-Izquierdo ◽  
Carlos del Pozo Vegas ◽  
Juan F. Delgado Benito ◽  
Virginia Carbajosa Rodríguez ◽  
...  
Keyword(s):  
Early Warning ◽  
Life Support ◽  
Positive Likelihood Ratio ◽  
Early Mortality ◽  
Early Warning Score ◽  
Outcome Variable ◽  
Main Diagnosis ◽  
Ideal System ◽  
Prehospital Triage ◽  
National Early Warning Score

AbstractIntroduction:In cases of mass-casualty incidents (MCIs), triage represents a fundamental tool for the management of and assistance to the wounded, which helps discriminate not only the priority of attention, but also the priority of referral to the most suitable center.Hypothesis/Problem:The objective of this study was to evaluate the capacity of different prehospital triage systems based on physiological parameters (Shock Index [SI], Glasgow-Age-Pressure Score [GAP], Revised Trauma Score [RTS], and National Early Warning Score 2 [NEWS2]) to predict early mortality (within 48 hours) from the index event for use in MCIs.Methods:This was a longitudinal prospective observational multi-center study on patients who were attended by Advanced Life Support (ALS) units and transferred to the emergency department (ED) of their reference hospital. Collected were: demographic, physiological, and clinical variables; main diagnosis; and data on early mortality. The main outcome variable was mortality from any cause within 48 hours.Results:From April 1, 2018 through February 28, 2019, a total of 1,288 patients were included in this study. Of these, 262 (20.3%) participants required assistance for trauma and injuries by external agents. Early mortality within the first 48 hours due to any cause affected 69 patients (5.4%). The system with the best predictive capacity was the NEWS2 with an area under the curve (AUC) of 0.891 (95% CI, 0.84-0.94); a sensitivity of 79.7% (95% CI, 68.8-87.5); and a specificity of 84.5% (95% CI, 82.4-86.4) for a cut-off point of nine points, with a positive likelihood ratio of 5.14 (95% CI, 4.31-6.14) and a negative predictive value of 98.7% (95% CI, 97.8-99.2).Conclusion:Prehospital scores of the NEWS2 are easy to obtain and represent a reliable test, which make it an ideal system to help in the initial assessment of high-risk patients, and to determine their level of triage effectively and efficiently. The Prehospital Emergency Medical System (PhEMS) should evaluate the inclusion of the NEWS2 as a triage system, which is especially useful for the second triage (evacuation priority).

scholarly journals A Multicenter Observational Prospective Cohort Study of Association of the Prehospital National Early Warning Score 2 and Hospital Triage with Early Mortality

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Francisco Martín-Rodríguez ◽  
Raúl López-Izquierdo ◽  
Carlos del Pozo Vegas ◽  
Juan F. Delgado-Benito ◽  
Carmen del Pozo Pérez ◽  
...  
Keyword(s):  
Emergency Department ◽  
Cohort Study ◽  
Early Warning ◽  
Life Support ◽  
Early Mortality ◽  
Early Warning Score ◽  
Outcome Variable ◽  
Main Diagnosis ◽  
Index Event ◽  
National Early Warning Score

Aim of the Study. To evaluate the ability of the prehospital National Early Warning Score 2 scale (NEWS2) to predict early mortality (within 48 hours) after the index event based on the triage priority assigned for any cause in the emergency department. Methods. This is a multicenter longitudinal observational cohort study on patients attending Advanced Life Support units and transferred to the emergency department of their reference hospital. We collected demographic, physiological, and clinical variables, main diagnosis, and hospital triage level as well as mortality. The main outcome variable was mortality from any cause within two days of the index event. Results. Between April 1 and November 30, 2018, a total of 1054 patients were included in our study. Early mortality within the first 48 hours after the index event affected 55 patients (5.2%), of which 23 cases (41.8%) had causes of cardiovascular origin. In the stratification by triage levels, the AUC of the NEWS2 obtained for short-term mortality varied between 0.77 (95% CI: 0.65-0.89) for level I and 0.94 (95% CI: 0.79-1) for level III. Conclusions. The Prehospital Emergency Medical Services should evaluate the implementation of the NEWS2 as a routine evaluation, which, together with the structured hospital triage system, effectively serves to predict early mortality and detect high-risk patients.

Resuscitation

2018 ◽  
pp. 225-244
Author(s):  
Tim Raine ◽  
George Collins ◽  
Catriona Hall ◽  
Nina Hjelde ◽  
James Dawson ◽  
...  
Keyword(s):  
Intensive Care ◽  
Early Warning ◽  
Basic Life Support ◽  
Life Support ◽  
Advanced Life Support ◽  
Advanced Trauma Life Support ◽  
Early Warning Scores

This chapter explores resuscitation, including early warning scores, intensive care, peri-arrest, in-hospital resuscitation, Advanced Life Support (ALS), arrest equipment and tests, Advanced Trauma Life Support (ATLS), Paediatric Basic Life Support, Newborn Life Support (NLS), and obstetric arrest.

scholarly journals Use of paediatric early warning scores in intermediate care units

2019 ◽  
pp. archdischild-2019-317055
Author(s):  
Marie Emilie Lampin ◽  
Alain Duhamel ◽  
Hélène Behal ◽  
Morgan Recher ◽  
Francis Leclerc ◽  
...  
Keyword(s):  
Early Warning ◽  
Emergency Departments ◽  
Repeated Measures ◽  
Medical Intervention ◽  
Clinical Deterioration ◽  
Early Warning Score ◽  
Receiver Operating Curve ◽  
Intermediate Care ◽  
Derivation Cohort ◽  
Early Warning Scores

ObjectivePaediatric early warning scores (EWS) were developed to detect deterioration in paediatric wards or emergency departments. The aim of this study was to assess the relationship between three paediatric EWS and clinical deterioration detected by the nurse in paediatric intermediate care units (PImCU).MethodsThis was a prospective, observational, multicentre study at seven French regional hospitals that included all children <18 years of age. Clinical parameters included in three EWS (Paediatric Advanced Warning Score, Paediatric Early Warning Score and Bedside Paediatric Early Warning System) were prospectively recorded every 8 hours or in case of deterioration. The outcome was a call to physician by the nurse when a clinical deterioration was observed. The cohort was divided into derivation and validation cohorts. An updated methodology for repeated measures was used and discrimination was estimated by the area under the receiver-operating curve.ResultsA total of 2636 children were included for 14 708 observations to compute a posteriori the EWS. The discrimination of the three EWS for predicting calls to physicians by nurses was good (range: 0.87–0.91) for the derivation cohort and moderate (range: 0.71–0.76) for the validation cohort. Equations for probability thresholds of calls to physicians, taking into account the time t, the score at time t and the score at admission, are available.ConclusionThese three EWS developed for children in paediatric wards or emergency departments can be used in PImCU to detect a clinical deterioration and predict the need for medical intervention.

Resuscitation

2014 ◽  
Author(s):  
Tim Raine ◽  
James Dawson ◽  
Stephan Sanders ◽  
Simon Eccles
Keyword(s):  
Critical Care ◽  
Early Warning ◽  
Basic Life Support ◽  
Life Support ◽  
Advanced Life Support ◽  
Advanced Trauma Life Support ◽  
Improve Outcome ◽  
Early Warning Scores

Early warning scoresPeri-arrestIn-hospital resuscitationAdvanced Life Support (ALS)Arrest equipment and testsAdvanced Trauma Life Support (ATLS)Paediatric Basic Life SupportNewborn Life Support (NLS)Obstetric arrestof the ‘unwell’ patient has repeatedly been shown to improve outcome. Identification of such patients allows suitable changes in management, including early involvement of critical care teams or transfer to critical care areas (HDU/ICU) where necessary....

scholarly journals Development, Implementation, and Evaluation of an In-Hospital Optimized Early Warning Score for Patient Deterioration

2020 ◽  
Vol 5 (1) ◽  
pp. 238146831989966 ◽  
Author(s):  
Cara O’Brien ◽  
Benjamin A. Goldstein ◽  
Yueqi Shen ◽  
Matthew Phelan ◽  
Curtis Lambert ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Early Warning ◽  
Clinical Decision Making ◽  
Risk Model ◽  
Clinical Status ◽  
Area Under The Curve ◽  
Clinical Decision ◽  
Early Warning Score ◽  
Support Tool ◽  
National Early Warning Score

Background. Identification of patients at risk of deteriorating during their hospitalization is an important concern. However, many off-shelf scores have poor in-center performance. In this article, we report our experience developing, implementing, and evaluating an in-hospital score for deterioration. Methods. We abstracted 3 years of data (2014–2016) and identified patients on medical wards that died or were transferred to the intensive care unit. We developed a time-varying risk model and then implemented the model over a 10-week period to assess prospective predictive performance. We compared performance to our currently used tool, National Early Warning Score. In order to aid clinical decision making, we transformed the quantitative score into a three-level clinical decision support tool. Results. The developed risk score had an average area under the curve of 0.814 (95% confidence interval = 0.79–0.83) versus 0.740 (95% confidence interval = 0.72–0.76) for the National Early Warning Score. We found the proposed score was able to respond to acute clinical changes in patients’ clinical status. Upon implementing the score, we were able to achieve the desired positive predictive value but needed to retune the thresholds to get the desired sensitivity. Discussion. This work illustrates the potential for academic medical centers to build, refine, and implement risk models that are targeted to their patient population and work flow.

scholarly journals How to follow the NEWS

2014 ◽  
Vol 13 (3) ◽  
pp. 104-107
Author(s):  
John Kellett ◽  
◽  
Alan Murray ◽  
Keyword(s):  
Hospital Mortality ◽  
Early Warning ◽  
Fold Increase ◽  
Early Warning Score ◽  
Published Data ◽  
Initial Value ◽  
Early Warning Scores ◽  
Average Patient ◽  
Prognostic Importance ◽  
National Early Warning Score

Background: it is not known how best to respond to changes in the National Early Warning Score (NEWS) after hospital admission. This report manipulates and extrapolates previously published data on the trajectories of the abbreviated early warning score (AbEWS i.e. NEWS that does not include mental status). Methods: trajectories of averaged AbEWS for patients for their first 5 days in hospital and their last 5 days in hospital were combined to obtain an approximation of what happens to the average patient while in hospital. Results: the trajectories of patients admitted with a low score are different from those admitted with a high score. Patients should be observed for 12 to 24 hours before their outcome can be predicted. The score of most patients who die in hospital trends upward on the second or third day after admission. Patients admitted with a score of 0-2 who raise their score to >=3 have a ten-fold increase in-hospital mortality. Conclusions: the trajectories of early warning scores after admission are of prognostic importance, and escalation protocols should relate changes in the score to its initial value on admission.

scholarly journals National Early Warning Score 2 (NEWS2) to predict poor outcome in hospitalised COVID-19 patients in India

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261376
Author(s):  
Pugazhvannan CR ◽  
Ilavarasi Vanidassane ◽  
Dhivya Pownraj ◽  
Ravichandran Kandasamy ◽  
Aneesh Basheer
Keyword(s):  
Risk Stratification ◽  
Early Warning ◽  
Area Under The Curve ◽  
Clinical Score ◽  
Supplemental Oxygen ◽  
Early Warning Score ◽  
National Early Warning Score ◽  
Poor Outcomes ◽  
Indian Setting ◽  
Sensitivity Specificity

Background While several parameters have emerged as predictors of prognosis of COVID-19, a simple clinical score at baseline might help early risk stratification. We determined the ability of National Early Warning Score 2 (NEWS2) to predict poor outcomes among adults with COVID-19. Methods A prospective study was conducted on 399 hospitalised adults with confirmed SARS-CoV-2 infection between August and December 2020. Baseline NEWS2 score was determined. Primary outcome was poor outcomes defined as need for mechanical ventilation or death within 28 days. The sensitivity, specificity and Area under the curve were determined for NEWS2 scores of 5 and 6. Results Mean age of patients was 55.5 ± 14.8 years and 275 of 399 (68.9%) were male. Overall mortality was 3.8% and 7.5% had poor outcomes. Median (interquartile range) NEWS2 score at admission was 2 (0–6). Sensitivity and specificity of NEWS 2 of 5 or more in predicting poor outcomes was 93.3% (95% CI: 76.5–98.8) and 70.7% (95% CI: 65.7–75.3) respectively [area under curve 0.88 (95% CI: 0.847–0.927)]. Age, baseline pulse rate, baseline oxygen saturation, need for supplemental oxygen and ARDS on chest X ray were independently associated with poor outcomes. Conclusions NEWS2 score of 5 or more at admission predicts poor outcomes in patients with COVID-19 with good sensitivity and can easily be applied for risk stratification at baseline. Further studies are needed in the Indian setting to validate this simple score and recommend widespread use.

Sign in / Sign up

Export Citation Format

Share Document