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.

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.

scholarly journals Prognostic Accuracy of Early Warning Scores for Clinical Deterioration in Patients With COVID-19

2021 ◽  
Vol 7 ◽  
Author(s):  
Ying Su ◽  
Min-jie Ju ◽  
Rong-cheng Xie ◽  
Shen-ji Yu ◽  
Ji-li Zheng ◽  
...  
Keyword(s):  
Organ Failure ◽  
Early Warning ◽  
Scoring System ◽  
Characteristic Curve ◽  
Invasive Mechanical Ventilation ◽  
Clinical Deterioration ◽  
Early Warning Score ◽  
Prognostic Accuracy ◽  
Failure Assessment ◽  
Early Warning Scores

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.

The Use of Prognostic Prediction Models for Mortality or Clinical Deterioration among Hospitalized and Non-hospitalized Adults with COVID-19: A Systematic Review

2021 ◽  
Author(s):  
Patricia Pauline M. Remalante-Rayco ◽  
Evelyn Osio-Salido
Keyword(s):  
Systematic Review ◽  
Emergency Department ◽  
Early Warning ◽  
Prediction Models ◽  
External Validation ◽  
Risk Of Bias ◽  
Clinical Deterioration ◽  
Early Warning Score ◽  
Good Prediction ◽  
Prediction Of Mortality

Objective. To assess the performance of prognostic models in predicting mortality or clinical deterioration among patients with COVID-19, both hospitalized and non-hospitalized Methods. We conducted a systematic review of the literature until March 8, 2021. We included models for the prediction of mortality or clinical deterioration in COVID-19 with external validation. We used the Prediction model Risk Of Bias ASsessment Tool (PROBAST) and the GRADEpro Guideline Development Tool (GDT) to assess the evidence obtained. Results. We reviewed 33 cohort studies. Two studies had a low risk of bias, four unclear risks, and 27 with a high risk of bias due to participant selection and analysis. For the outcome of mortality, the QCOVID model had excellent prediction with high certainty of evidence but was specific for use in England. The COVID Outcome Prediction in the Emergency Department (COPE) model, the 4C Mortality Score, the Age, BUN, number of comorbidities, CRP, SpO2/FiO2 ratio, platelet count, heart rate (ABC2-SPH) risk score, the Confusion Urea Respiration Blood Pressure (CURB-65) severity score, the Rapid Emergency Medicine Score (REMS), and the Risk Stratification in the Emergency Department in Acutely Ill Older Patients (RISE UP) score had fair to good prediction of death among inpatients, while the quick Sepsis-related Organ Failure Assessment (qSOFA) score had poor to fair prediction. The certainty of evidence for these models was very low to low. For the outcome of clinical deterioration, the 4C Deterioration Score had fair prediction, the National Early Warning Score 2 (NEWS2) score poor to good, and the Modified Early Warning Score (MEWS) had poor prediction. The certainty of evidence for these three models was also very low to low. None of these models had been validated in the Philippine setting. Conclusion. The QCOVID, COPE, ABC2-SPH, 4C, CURB-65, REMS, RISE-UP models for prediction of mortality and the 4C Deterioration and NEWS2 models for prediction of clinical deterioration are potentially useful but need to be validated among patients with COVID-19 of varying severity in the Philippine setting.

scholarly journals Early identification of severe community-acquired pneumonia: a retrospective observational study

2019 ◽  
Vol 6 (1) ◽  
pp. e000438 ◽  
Author(s):  
Frances S Grudzinska ◽  
Kerrie Aldridge ◽  
Sian Hughes ◽  
Peter Nightingale ◽  
Dhruv Parekh ◽  
...  
Keyword(s):  
Early Warning ◽  
Assessment Tool ◽  
Characteristic Curve ◽  
Community Acquired Pneumonia ◽  
Adverse Outcomes ◽  
Assessment Tools ◽  
Early Warning Score ◽  
News Medium ◽  
Increased Risk ◽  
Early Warning Scores

BackgroundCommunity-acquired pneumonia (CAP) is a leading cause of sepsis worldwide. Prompt identification of those at high risk of adverse outcomes improves survival by enabling early escalation of care. There are multiple severity assessment tools recommended for risk stratification; however, there is no consensus as to which tool should be used for those with CAP. We sought to assess whether pneumonia-specific, generic sepsis or early warning scores were most accurate at predicting adverse outcomes.MethodsWe performed a retrospective analysis of all cases of CAP admitted to a large, adult tertiary hospital in the UK between October 2014 and January 2016. All cases of CAP were eligible for inclusion and were reviewed by a senior respiratory physician to confirm the diagnosis. The association between the CURB65, Lac-CURB-65, quick Sequential (Sepsis-related) Organ Failure Assessment tool (qSOFA) score and National Early Warning Score (NEWS) at the time of admission and outcome measures including intensive care admission, length of hospital stay, in-hospital, 30-day, 90-day and 365-day all-cause mortality was assessed.Results1545 cases were included with 30-day mortality of 19%. Increasing score was significantly associated with increased risk of poor outcomes for all four tools. Overall accuracy assessed by receiver operating characteristic curve analysis was significantly greater for the CURB65 and Lac-CURB-65 scores than qSOFA. At admission, a CURB65 ≥2, Lac-CURB-65 ≥moderate, qSOFA ≥2 and NEWS ≥medium identified 85.0%, 96.4%, 40.3% and 79.0% of those who died within 30 days, respectively. A Lac-CURB-65 ≥moderate had the highest negative predictive value: 95.6%.ConclusionAll four scoring systems can stratify according to increasing risk in CAP; however, when a confident diagnosis of pneumonia can be made, these data support the use of pneumonia-specific tools rather than generic sepsis or early warning scores.

Early Warning Score Communication Bundle: A Pilot Study

2018 ◽  
Vol 27 (3) ◽  
pp. 238-242
Author(s):  
Cheryl Gagne ◽  
Susan Fetzer
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Early Warning ◽  
Rapid Response Team ◽  
Rapid Response ◽  
Early Warning Score ◽  
Early Warning Scores ◽  
Response Team ◽  
Intensive Care Unit Nurses ◽  
The Impact

Background Unplanned admissions of patients to intensive care units from medical-surgical units often result from failure to recognize clinical deterioration. The early warning score is a clinical decision support tool for nurse surveillance but must be communicated to nurses and implemented appropriately. A communication process including collaboration with experienced intensive care unit nurses may reduce unplanned transfers. Objective To determine the impact of an early warning score communication bundle on medical-surgical transfers to the intensive care unit, rapid response team calls, and morbidity of patients upon intensive care unit transfer. Methods After an early warning score was electronically embedded into medical records, a communication bundle including notification of and telephone collaboration between medical-surgical and intensive care unit nurses was implemented. Data were collected 3 months before and 21 months after implementation. Results Rapid response team calls increased nonsignificantly during the study period (from 6.47 to 8.29 per 1000 patient-days). Rapid response team calls for patients with early warning scores greater than 4 declined (from 2.04 to 1.77 per 1000 patient-days). Intensive care unit admissions of patients after rapid response team calls significantly declined (P = .03), as did admissions of patients with early warning scores greater than 4 (P = .01), suggesting that earlier intervention for patient deterioration occurred. Documented reassessment response time declined significantly to 28 minutes (P = .002). Conclusion Electronic surveillance and collaboration with experienced intensive care unit nurses may improve care, control costs, and save lives. Critical care nurses have a role in coaching and guiding less experienced nurses.

scholarly journals Into the Night: Factors affecting response to abnormal Early Warning Scores out-of-hours and implications for service improvement

2014 ◽  
Vol 13 (2) ◽  
pp. 56-60
Author(s):  
C J Yiu ◽  
◽  
S U Khan ◽  
Christian P Subbe ◽  
K Tofeec ◽  
...  
Keyword(s):  
Nursing Staff ◽  
Early Warning ◽  
Service Evaluation ◽  
Early Warning Score ◽  
Service Improvement ◽  
Out Of Hours ◽  
Factors Affecting ◽  
Alarm Fatigue ◽  
Early Warning Scores ◽  
Medical Wards

Background: Early Warning Scores alert staff to preventable deterioration. Raised scores should lead to escalation of care. Aims: To establish response of staff to patients scoring National Early Warning Score (NEWS) of six or above and to identify patient and environmental factors affecting escalation by nursing staff. Methods: Service evaluation with prospective review of patient records of 118 beds on four medical wards during 20 night-shifts. Results: During 2360 observed bed days 109 patients triggered NEWS >=6 at least once during the observation period. Nursing staff escalated only 18 (17%) of these patients; nearly all of them had predefined chronic health conditions, the majority fulfilled criteria for frailty. Despite their higher 30-day mortality patients with COPD had lower escalation rates. Additionally wards that had more patients with a NEWS >=6 had lower escalation rates. Conclusion: Alarm fatigue and clinical judgement of staff might result in deviation from escalation protocols.

scholarly journals Accuracy and Monitoring of Pediatric Early Warning Score (PEWS) Scores Prior to Emergent Pediatric Intensive Care Unit (ICU) Transfer: Retrospective Analysis (Preprint)

2020 ◽  
Author(s):  
Rebecca L Kowalski ◽  
Laura Lee ◽  
Michael C Spaeder ◽  
J Randall Moorman ◽  
Jessica Keim-Malpass
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Pediatric Intensive Care Unit ◽  
Early Warning ◽  
Severity Of Illness ◽  
Pediatric Intensive Care ◽  
Clinical Deterioration ◽  
Early Warning Score ◽  
Transfer Event ◽  
Patients At Risk

BACKGROUND Current approaches to early detection of clinical deterioration in children have relied on intermittent track-and-trigger warning scores such as the Pediatric Early Warning Score (PEWS) that rely on periodic assessment and vital sign entry. There are limited data on the utility of these scores prior to events of decompensation leading to pediatric intensive care unit (PICU) transfer. OBJECTIVE The purpose of our study was to determine the accuracy of recorded PEWS scores, assess clinical reasons for transfer, and describe the monitoring practices prior to PICU transfer involving acute decompensation. METHODS We conducted a retrospective cohort study of patients ≤21 years of age transferred emergently from the acute care pediatric floor to the PICU due to clinical deterioration over an 8-year period. Clinical charts were abstracted to (1) determine the clinical reason for transfer, (2) quantify the frequency of physiological monitoring prior to transfer, and (3) assess the timing and accuracy of the PEWS scores 24 hours prior to transfer. RESULTS During the 8-year period, 72 children and adolescents had an emergent PICU transfer due to clinical deterioration, most often due to acute respiratory distress. Only 35% (25/72) of the sample was on continuous telemetry or pulse oximetry monitoring prior to the transfer event, and 47% (34/72) had at least one incorrectly documented PEWS score in the 24 hours prior to the event, with a score underreporting the actual severity of illness. CONCLUSIONS This analysis provides support for the routine assessment of clinical deterioration and advocates for more research focused on the use and utility of continuous cardiorespiratory monitoring for patients at risk for emergent transfer.

scholarly journals Comparison of early warning scores for sepsis early identification and prediction in the general ward setting

JAMIA Open ◽  
2021 ◽  
Vol 4 (3) ◽  
Author(s):  
Sean C Yu ◽  
Nirmala Shivakumar ◽  
Kevin Betthauser ◽  
Aditi Gupta ◽  
Albert M Lai ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Early Warning ◽  
Predictive Value ◽  
Early Identification ◽  
Academic Medical Center ◽  
Scoring Systems ◽  
General Ward ◽  
Early Warning Score ◽  
Patient Acuity ◽  
Early Warning Scores

Abstract The objective of this study was to directly compare the ability of commonly used early warning scores (EWS) for early identification and prediction of sepsis in the general ward setting. For general ward patients at a large, academic medical center between early-2012 and mid-2018, common EWS and patient acuity scoring systems were calculated from electronic health records (EHR) data for patients that both met and did not meet Sepsis-3 criteria. For identification of sepsis at index time, National Early Warning Score 2 (NEWS 2) had the highest performance (area under the receiver operating characteristic curve: 0.803 [95% confidence interval [CI]: 0.795–0.811], area under the precision recall curves: 0.130 [95% CI: 0.121–0.140]) followed NEWS, Modified Early Warning Score, and quick Sequential Organ Failure Assessment (qSOFA). Using validated thresholds, NEWS 2 also had the highest recall (0.758 [95% CI: 0.736–0.778]) but qSOFA had the highest specificity (0.950 [95% CI: 0.948–0.952]), positive predictive value (0.184 [95% CI: 0.169–0.198]), and F1 score (0.236 [95% CI: 0.220–0.253]). While NEWS 2 outperformed all other compared EWS and patient acuity scores, due to the low prevalence of sepsis, all scoring systems were prone to false positives (low positive predictive value without drastic sacrifices in sensitivity), thus leaving room for more computationally advanced approaches.

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