Comparison of the National Early Warning Score in non-elective medical and surgical patients

Impact of continuous and wireless monitoring of vital signs on clinical outcomes: a propensity-matched observational study of surgical ward patients

BACKGROUND

Continuous and wireless vital sign monitoring is superior to intermittent monitoring in detecting vital sign abnormalities; however, the impact on clinical outcomes has not been established.

METHODS

We performed a propensity-matched analysis of data describing patients admitted to general surgical wards between January 2018 and December 2019 at a single, tertiary medical centre in the USA. The primary outcome was a composite of in-hospital mortality or ICU transfer during hospitalisation. Secondary outcomes were the odds of individual components of the primary outcome, and heart failure, myocardial infarction, acute kidney injury, and rapid response team activations. Data are presented as odds ratios (ORs) with 95% confidence intervals (CIs) and n (%).

RESULTS

We initially screened a population of 34,636 patients (mean age 58.3 (Range 18-101) yr, 16,456 (47.5%) women. After propensity matching, intermittent monitoring (n=12 345) was associated with increased risk of a composite of mortality or ICU admission (OR 3.42, 95% CI 3.19-3.67; P<0.001), and heart failure (OR 1.48, 95% CI 1.21-1.81; P<0.001), myocardial infarction (OR 3.87, 95% CI 2.71-5.71; P<0.001), and acute kidney injury (OR 1.32, 95% CI 1.09-1.57; P<0.001) compared with continuous wireless monitoring (n=7955). The odds of rapid response team intervention were similar in both groups (OR 0.86, 95% CI 0.79-1.06; P=0.726).

CONCLUSIONS

Patients who received continuous ward monitoring were less likely to die or be admitted to ICU than those who received intermittent monitoring. These findings should be confirmed in prospective randomised trials.

Safer and more efficient vital signs monitoring protocols to identify the deteriorating patients in the general hospital ward: an observational study

Background

The frequency at which patients should have their vital signs (e.g. blood pressure, pulse, oxygen saturation) measured on hospital wards is currently unknown. Current National Health Service monitoring protocols are based on expert opinion but supported by little empirical evidence. The challenge is finding the balance between insufficient monitoring (risking missing early signs of deterioration and delays in treatment) and over-observation of stable patients (wasting resources needed in other aspects of care).

Objective

Provide an evidence-based approach to creating monitoring protocols based on a patient's risk of deterioration and link these to nursing workload and economic impact.

Design

Our study consisted of two parts: (1) an observational study of nursing staff to ascertain the time to perform vital sign observations; and (2) a retrospective study of historic data on patient admissions exploring the relationships between National Early Warning Score and risk of outcome over time. These were underpinned by opinions and experiences from stakeholders.

Setting and participants

Observational study: observed nursing staff on 16 randomly selected adult general wards at four acute National Health Service hospitals. Retrospective study: extracted, linked and analysed routinely collected data from two large National Health Service acute trusts; data from over 400,000 patient admissions and 9,000,000 vital sign observations.

Results

Observational study found a variety of practices, with two hospitals having registered nurses take the majority of vital sign observations and two favouring healthcare assistants or student nurses. However, whoever took the observations spent roughly the same length of time. The average was 5:01 minutes per observation over a 'round', including time to locate and prepare the equipment and travel to the patient area. Retrospective study created survival models predicting the risk of outcomes over time since the patient was last observed. For low-risk patients, there was little difference in risk between 4 hours and 24 hours post observation.

Conclusions

We explored several different scenarios with our stakeholders (clinicians and patients), based on how 'risk' could be managed in different ways. Vital sign observations are often done more frequently than necessary from a bald assessment of the patient's risk, and we show that a maximum threshold of risk could theoretically be achieved with less resource. Existing resources could therefore be redeployed within a changed protocol to achieve better outcomes for some patients without compromising the safety of the rest. Our work supports the approach of the current monitoring protocol, whereby patients' National Early Warning Score 2 guides observation frequency. Existing practice is to observe higher-risk patients more frequently and our findings have shown that this is objectively justified. It is worth noting that important nurse-patient interactions take place during vital sign monitoring and should not be eliminated under new monitoring processes. Our study contributes to the existing evidence on how vital sign observations should be scheduled. However, ultimately, it is for the relevant professionals to decide how our work should be used.

Study registration

This study is registered as ISRCTN10863045.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 17/05/03) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 6. See the NIHR Funding and Awards website for further award information.

Effect of a lower target oxygen saturation range on the risk of hypoxaemia and elevated NEWS2 scores at a university hospital: a retrospective study

BACKGROUND

The optimal target oxygen saturation (SpO2) range for hospital inpatients not at risk of hypercapnia is unknown. The objective of this study was to assess the impact on oxygen usage and National Early Warning Score 2 (NEWS2) of changing the standard SpO2 target range from 94-98% to 92-96%.

METHODS

In a metropolitan UK hospital, a database of electronic bedside SpO2 measurements, oxygen prescriptions and NEWS2 records was reviewed. Logistic regression was used to compare the proportion of hypoxaemic SpO2 values (<90%) and NEWS2 records ≥5 in 2019, when the target SpO2 range was 94-98%; with 2022, when the target range was 92-96%.

RESULTS

In 2019, 218 of 224 936 (0.10%) observations on room air and 162 of 11 328 (1.43%) on oxygen recorded an SpO2 <90%, and in 2022, 251 of 225 970 (0.11%) and 233 of 12 845 (1.81%), respectively (risk difference 0.04%, 95% CI 0.02% to 0.07%). NEWS2 ≥5 was observed in 3009 of 236 264 (1.27%) observations in 2019 and 4061 of 238 815 (1.70%) in 2022 (risk difference 0.43%, 0.36% to 0.50%; p<0.001). The proportion of patients using supplemental oxygen with hyperoxaemia (SpO2 100%) was 5.4% in 2019 and 3.9% in 2022 (OR 0.71, 0.63 to 0.81; p<0.001).

DISCUSSION

The proportion of observations with SpO2 <90% or NEWS2 ≥5 was greater with the 92-96% range; however, absolute differences were very small and of doubtful clinical relevance, in contrast to hyperoxaemia for which the proportion was markedly less in 2022. These findings support proposals that the British Thoracic Society oxygen guidelines could recommend a lower target SpO2 range.

Evaluating the performance of the National Early Warning Score in different diagnostic groups

BACKGROUND

The National Early Warning Score (NEWS) is used in hospitals across the UK to detect deterioration of patients within care pathways. It is used for most patients, but there are relatively few studies validating its performance in groups of patients with specific conditions.

METHODS

The performance of NEWS was evaluated against 36 other Early Warning Scores, in 123 patient groups, through use of the area under the receiver operating characteristic (AUROC) curve technique, to compare the abilities of each Early Warning Score to discriminate an outcome within 24hrs of vital sign recording. Outcomes evaluated were death, ICU admission, or a combined outcome of either death or ICU admission within 24 hours of an observation set.

RESULTS

The National Early Warning Score 2 performs either best or joint best within 120 of the 123 patient groups evaluated and is only outperformed in prediction of unanticipated ICU admission. When outperformed by other Early Warning Scores in the remaining 3 patient groups, the performance difference was marginal.

CONCLUSIONS

Consistently high performance indicates that NEWS is a suitable early warning score to use for all diagnostic groups considered by this analysis, and patients are not disadvantaged through use of NEWS in comparison to any of the other evaluated Early Warning Scores.

Comparison of prognosis of five scoring systems in emphysematous pyelonephritis patients requiring intensive care

INTRODUCTION

Our study aimed to evaluate the performance of Quick Sepsis-related Organ Failure Assessment (qSOFA), Modified Early Warning Score (MEWS), National Early Warning Score (NEWS), Systemic Inflammatory Response Syndrome (SIRS), and Global Research in the Emphysematous Pyelonephritis group (GREMP) in predicting the need of admission in intensive care units (ICU) for emphysematous pyelonephritis (EPN) patient.

PATIENTS AND METHODS

In this retrospective study, we reviewed 70 patients admitted to our department from January 2008 to October 2022. Data on clinical presentation and EPN management were noted. The five scoring systems were calculated by one investigator. Univariate and multivariate analyses were used to assess predictive factors of severe sepsis and mortality. Statistical analysis was made using SPSS version 22.

RESULTS

Mean age was 61.83 years with 65.7% diabetes. As per Huang and Tseng classification, 41 patients had class I EPN, 7 had class II EPN, 8 had class IIIa, 6 class IIIB EPN, and 8 had class IV EPN. Seventeen patients (24.28%) were admitted to ICU with an 18.57 mortality rate. Univariate analysis showed that ICU admission was significantly associated with higher respiration rate and heart rate, lower systolic blood pressure, confusion, CRP, lactate and creatinine serum (p = 0.0001, p = 0.0001, p = 0.001, p = 0.007, p = 0.004, p = 0.001, p = 0.001, respectively). All five scores and Huang and Tseng classification were significantly predictive of admission to ICU. All five scores showed good results under the area curves to predict ICU entry with 0.915, 0.895, 0.968, 0.887, and 0.846 for qSOFA, MEWS score, NEWS score, SIRS, and GREMP score, respectively.

CONCLUSION

NEWS score seemed to be the best performing physiologic score among the five scoring systems studied and may help with biological and radiological findings to quickly identify EPN patients that need intensive care unit.

Association between Intraoperative Early Warning Score and Mortality and In-Hospital Stay in Lower Gastrointestinal Spontaneous Perforation

Background

Early warning scores (EWSs) can be easily calculated from physiological indices; however, the extent to which intraoperative EWSs and the corresponding changes are associated with patient prognosis is unknown. In this study, we investigated whether EWS and the corresponding time-related changes are associated with patient outcomes during the anesthetic management of lower gastrointestinal perforation.

Methods

This was a single-center, retrospective cohort study conducted at a tertiary emergency care center. Adult patients who underwent surgery for spontaneous lower gastrointestinal perforations between September 1, 2012, and December 31, 2019, were included. The National Early Warning Score (NEWS) and Modified Early Warning Score (MEWS) were calculated based on the intraoperative physiological indices, and the associations with in-hospital death and length of hospital stay were investigated.

Results

A total of 101 patients were analyzed. The median age was 70 years, and there were 11 cases of in-hospital death (mortality rate: 10.9%). There was a significant association between the intraoperative maximum NEWS and in-hospital death (odds ratio (OR): 1.60, 95% confidence interval (CI): 1.10-2.32, p=0.013) and change from initial to maximum NEWS (OR: 1.60, 95% CI: 1.07-2.40, p=0.023) in the crude analysis. However, when adjustments were made for confounding factors, no statistically significant associations were found. Other intraoperative EWS values and changes were not significantly associated with the investigated outcomes. The preoperative sepsis-related organ failure assessment score and the intraoperative base excess value were significantly associated with in-hospital death.

Conclusions

No clear association was observed between EWSs and corresponding changes and in-hospital death in cases of lower gastrointestinal perforation. The preoperative sepsis-related organ failure assessment score and intraoperative base excess value were significantly associated with in-hospital death.

National Early Warning Score Deployment in a Veterans Affairs Facility: A Quality Improvement Initiative and Analysis

Early warning scores are algorithms designed to identify clinical deterioration. Current literature is predominantly in non-Veteran populations. Studies in Veterans are lacking. This study was a prospective quality improvement project deploying and assessing the National Early Warning Score (NEWS) at Kansas City VA Medical Center. Performance of NEWS was assessed as follows: discrimination for predicting a composite outcome of intensive care unit transfer or mortality within 24 hours via area under the receiver operating curve. A total of 4781 Veterans with 142 375 NEWS values were included. The NEWS area under the receiver operating curve for the composite outcome was 0.72 (95% CI, 0.71-0.74), indicating acceptable predictive accuracy. A NEWS of ≥7 was more likely associated with the composite outcome versus <7 (13.6% vs 0.8%; P < 0.001). This is one of the first studies to demonstrate successful deployment of NEWS in a Veteran population, with resultant important implications across the Veterans Health Administration.

Novel predictors of mortality in emergency bowel surgery: a single-centre cohort study

Pre-operative risk stratification is a key part of the care pathway for emergency bowel surgery, as it facilitates the identification of high-risk patients. Several novel risk scores have recently been published that are designed to identify patients who are frail or significantly unwell. They can also be calculated pre-operatively from routinely collected clinical data. This study aimed to investigate the ability of these scores to predict 30-day mortality after emergency bowel surgery. A single centre cohort study was performed using our local data from the National Emergency Laparotomy Audit database. Further data were extracted from electronic hospital records (n = 1508). The National Early Warning Score, Laboratory Decision Tree Early Warning Score and Hospital Frailty Risk Score were then calculated. The most abnormal National or Laboratory Decision Tree Early Warning Score in the 24 or 72 h before surgery was used in analysis. Individual scores were reasonable predictors of mortality (c-statistic 0.699-0.740) but all were poorly calibrated. A National Early Warning Score ≥ 4 was associated with a high overall mortality rate (> 10%). A logistic regression model was developed using age, National Early Warning Score, Laboratory Decision Tree Early Warning Score and Hospital Frailty Risk Score as predictor variables, and its performance compared with other established risk models. The model demonstrated good discrimination and calibration (c-statistic 0.827) but was marginally outperformed by the National Emergency Laparotomy Audit score (c-statistic 0.861). All other models compared performed less well (c-statistics 0.734-0.808). Pre-operative patient vital signs, blood tests and markers of frailty can be used to accurately predict the risk of 30-day mortality after emergency bowel surgery.

Use of the National Early Warning Score for predicting deterioration of patients with acute pulmonary embolism: a post-hoc analysis of the YEARS Study

BACKGROUND

The Pulmonary Embolism Severity Index (PESI) and the simplified PESI (sPESI) are validated scores for mortality prediction in patients with pulmonary embolism (PE). National Early Warning Score (NEWS) is a general prognostic risk score for multiple clinical settings. We investigated whether the NEWS had a comparable performance with the PESI and sPESI, for predicting intensive care unit (ICU) admission and death in patients with acute PE.

METHODS

In haemodynamically stable patients with confirmed PE from the YEARS Study (2013-2015), we evaluated the performance of the NEWS, PESI and sPESI for predicting 7-day ICU admission and 30-day mortality. Receiver operating characteristic curves were plotted and the area under the curve (AUC) was calculated.

RESULTS

Of 352 patients, 12 (3.4%) were admitted to the ICU and 5 (1.4%) died. The AUC of the NEWS for ICU admission was 0.80 (95% CI 0.66 to 0.94) and 0.92 (95% CI 0.82 to 1.00) for 30-day mortality. At a threshold of 3 points, NEWS yielded a sensitivity and specificity of 92% and 53% for ICU admission and 100% and 52% for 30-day mortality. The AUC of the PESI was 0.64 (95% CI 0.48 to 0.79) for ICU admission and 0.94 (95% CI 0.87 to 1.00) for mortality. At a threshold of 66 points, PESI yielded a sensitivity of 75% and a specificity of 38% for ICU admission. For mortality, these were 100% and 37%, respectively. The performance of the sPESI was similar to that of PESI.

CONCLUSION

In comparison with PESI and sPESI, NEWS adequately predicted 7-day ICU admission as well as 30-day mortality, supporting its potential relevance for clinical practice.

Effect of implementing the NEWS2 escalation protocol in a large acute NHS trust: a retrospective cohort analysis of mortality, workload and ability of early warning score to predict death within 24 hours

OBJECTIVES

To describe the inpatient population, establish patterns in admission and mortality over a 4-year period in different cohorts and assess the prognostic ability and workload implications of introducing the National Early Warning Score 2 (NEWS2) and associated escalation protocol.

DESIGN

Retrospective cohort analyses of medical and surgical inpatient admissions.

SETTING

Large teaching hospital with tertiary inpatient care and a major trauma centre employing an electronic observations platform, initially with a local early warning score, followed by NEWS2 introduction in June 2019.

PARTICIPANTS

332 682 adult patients were admitted between 1 January 2016 and 31 December 2019.

OUTCOME MEASURES

Mortality, workload and ability of early warning score to predict death within 24 hours.

RESULTS

Admissions rose by 19% from 76 055 in 2016 to 90 587 in 2019. Total bed days rose by 10% from 433 382 to 477 485. Mortality fell from 3.7% to 3.1% and was significantly lower in patients discharged from a surgical specialty, 1.0%-1.2% (p<0.001). Total observations recorded increased by 14% from 1 976 872 in 2016 to 2 249 118 in 2019. 65% of observations were attributable to patients under medical specialties, 34% to patients under surgical specialties. Recorded escalations to the registrar were stable from January 2016 to May 2019 but trebled following the introduction of NEWS2 in June 2019.

CONCLUSIONS

There was an increase in hospital inpatient activity between 2016 and 2019, associated with a reduction in mortality and percentage of observations calculated as reaching threshold NEWS2 score of 7 for escalation to the registrar. The introduction of the NEWS2, with a higher sensitivity and lower specificity, when allied to its escalation protocol, was associated with a significant increase in actual recorded escalations to the registrar. This was more marked in the surgical population and would support refining threshold scores based on admission characteristics when developing the next iteration of NEWS.

Ability of combined soluble urokinase plasminogen activator receptor to predict preventable emergency attendance in older patients in Japan: a prospective pilot study

Soluble urokinase plasminogen activator receptor (suPAR) is a strong and nonspecific inflammatory biomarker that reflects various immunologic reactions, organ damage, and risk of mortality in the general population. Although prior research in acute medical patients showed that an elevation in suPAR is related to intensive care unit admission and risk of readmission and mortality, no studies have focused on the predictive value of suPAR for preventable emergency attendance (PEA). This study aims to evaluate the predictive value of suPAR, which consists of a combination of white blood cell count (WBC), C-reactive protein (CRP), and the National Early Warning Score (NEWS), for PEA in older patients (>65 years) without trauma who presented to the emergency department (ED). This single-center prospective pilot study was conducted in the ED of the Association of EISEIKAI Medical and Healthcare Corporation Minamitama Hospital, in Hachiouji City, Tokyo, Japan, from September 16, 2020, to June 21, 2022. The study included all patients without trauma aged 65 years or older who were living in their home or a facility and presented to the ED when medical professionals decided an emergency consultation was required. Discrimination was assessed by plotting the receiver-operating characteristic (ROC) curve and calculating the area under the ROC curve (AUC). During the study period, 49 eligible older patients were included, and thirteen (26.5%) PEA cases were detected. The median suPAR was significantly lower in the PEA group than in the non-PEA group (p < 0.05). For suPAR, the AUC for the prediction of PEA was 0.678 (95% CI 0.499-0.842, p < 0.05), and there was no significant difference from other variables as follows: 0.801 (95% CI 0.673-0.906, p < 0.001) for WBC, 0.833 (95% CI 0.717-0.934, p < 0.001) for CRP, and 0.693 (95% CI 0.495-0.862, p < 0.05) for NEWS. Furthermore, the AUC for predicting PEA was 0.867 (95% CI 0.741-0.959, p < 0.001) for suPAR + WBC + CRP + NEWS, which was significantly higher than that of the original suPAR (p < 0.01). The cutoff values, sensitivity, specificity, and odds ratio of suPAR and suPAR + WBC + CRP + NEWS were 7.5 and 22.88, 80.6% and 83.3%, 53.8% and 76.9%, and 4.83 and 16.67, respectively. This study has several limitations. First, this was pilot study, and we included a small number of older patients. Second, the COVID-19 pandemic occurred during the study period, so that there may be selection bias in the study population. Third, our hospital is a secondary emergency medical institution, and as such, we did not treat very fatal cases, which could be another cause of selection bias. Our single-center study has demonstrated the moderate utility of the combined suPAR as a triage tool for predicting PEA in older patients without trauma receiving home medical care. Before introducing suPAR to the prehospital setting, evidence from multicenter studies is needed.

Ability of the National Early Warning Score and its respiratory and haemodynamic subcomponents to predict short-term mortality on general wards: a prospective three-centre observational study in Finland

OBJECTIVES

To validate the ability of the National Early Warning Score (NEWS) to predict short-term mortality on hospital wards, with a special reference to the NEWS's respiratory and haemodynamic subcomponents.

DESIGN

A large, 1-year, prospective, observational three-centre study. First measured vital sign datasets on general wards were prospectively collected using a mobile solution system during routine patient care. Area under receiver operator characteristic curves were constructed, and comparisons between ROC curves were conducted with Delong's test for two correlated ROC curves.

SETTING

One university hospital and two regional hospitals in Finland.

PARTICIPANTS

All 19 001 adult patients admitted to 45 general wards in the three hospitals over the 1-year study period. After excluding 102/19 001 patients (0.53%) with data on some vital signs missing, the final cohort consisted of 18 889 patients with full datasets.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome measure was 1-day mortality and secondary outcomes were 2-day and 30-day mortality rates.

RESULTS

Patients' median age was 70 years, 51% were male and 31% had a surgical reason for admission. The 1-day mortality was 0.36% and the 30-day mortality was 3.9%. The NEWS discriminated 1-day non-survivors with excellent accuracy (AUROC 0.91, 95% CI 0.87 to 0.95) and 30-day mortality with acceptable accuracy (0.75, 95% CI 0.73 to 0.77). The NEWS's respiratory rate component discriminated 1-day non-survivors better (0.78, 95% CI 0.72 to 0.84) as compared with the oxygen saturation (0.66, 95% CI 0.59 to 0.73), systolic blood pressure (0.65, 95% CI 0.59 to 0.72) and heart rate (0.67, 95% CI 0.61 to 0.74) subcomponents (p<0.01 in all ROC comparisons). As with the total NEWS, the discriminative performance of the individual score components decreased substantially for the 30-day mortality.

CONCLUSIONS

NEWS discriminated general ward patients at risk for acute death with excellent statistical accuracy. The respiratory rate component is especially strongly associated with short-term mortality.

TRIAL REGISTRATION NUMBER

NCT04055350.

Evaluation of NEWS2 response thresholds in a retrospective observational study from a UK acute hospital

OBJECTIVE

Use of National Early Warning Score 2 (NEWS2) has been mandated in adults admitted to acute hospitals in England. Urgent clinical review is recommended at NEWS2 ≥5. This policy is recognised as requiring ongoing evaluation. We assessed NEWS2 acquisition, alerting at key thresholds and patient outcomes, to understand how response recommendations would affect clinical resource allocation.

SETTING

Adult acute hospital in England.

DESIGN

Retrospective observational cohort study.

PARTICIPANTS

100 362 consecutive admissions between November 2018 and July 2019.

OUTCOME

Death or admission to intensive care unit within 24 hours of a score.

METHODS

NEWS2 were assembled as single scores from consecutive 24-hour time frames, (the first NEWS2 termed 'Index-NEWS2'), or as all scores from the admission (termed All-NEWS2). Scores were excluded when a patient was in intensive care, in the presence of a decision not to attempt cardiopulmonary resuscitation, or on day 1 of elective admission.

RESULTS

A mean of 4.5 NEWS2 were acquired per patient per day. The outcome rate following an Index-NEWS2 was 0.22/100 patient-days. The sensitivity of outcome prediction at Index-NEWS2 ≥5=0.46, and number needed to evaluate (NNE)=52. At this threshold, a mean of 37.6 alerts/100 patient-days would be generated, occurring in 12.3% of patients on any single day. Threshold changes to increase sensitivity by 0.1, would result in a twofold increase in alert rate and 1.5-fold increase in NNE. Overall, NEWS2 classification performance was significantly worse on Index-scores than All-scores (c-statistic=0.78 vs 0.85; p<0.001).

CONCLUSIONS

The combination of low event-rate, high alert-rate and low sensitivity, in patients for cardiopulmonary resuscitation, means that at current NEWS2 thresholds, resource demand would be sufficient to meaningfully compete with other pathways to clinical evaluation. In analyses that epitomise in-patient screening, NEWS2 performance suggests a need for re-evaluation of current response recommendations in this population.

Triggers and Interventions of Patients Who Require Medical Emergency Team Reviews: A Cross-Sectional Analysis of Single Versus Multiple Reviews

BACKGROUND

Medical emergency teams constitute part of the escalation protocol of early warning systems in many hospitals. The literature indicates that medical emergency teams may reduce hospital mortality and cardiac arrest. A greater understanding of pathways of patients who experience multiple medical emergency team reviews will inform clinical decision-making.

OBJECTIVES

To explore differences between patients who require a single medical emergency team review and those who require multiple reviews, and to identify any differences between patients who were reviewed only once during admission and patients who required multiple reviews.

METHODS

Data for this retrospective cross-sectional review, including demographic data, call triggers, outcomes, and interventions, were routinely collected from January 2013 through December 2015. The study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) collaborative's cross-sectional studies checklist (version 4).

RESULTS

Of 54 787 admitted patients, 1274 (2%) required a call to a medical emergency team; of those, 260 patients (20%) needed multiple calls. Patients requiring multiple calls demonstrated higher mortality (odds ratio, 1.49 [95% CI, 1.12-1.98]). A logistic regression model identified surgical patients and those receiving antibiotics and respiratory interventions at the first medical emergency team review as being more likely to require multiple reviews. Patients transferred to a higher level of care after the first review were less likely to require another review.

CONCLUSIONS

Patients requiring multiple medical emergency team reviews have higher mortality. Surgical patients have a higher risk of requiring multiple reviews. Hospitals need to include more details on surgical patients when auditing medical emergency team activation.

National Early Warning Score for predicting intensive care unit admission among elderly patients with influenza infections in the emergency department: an effective disposition tool during the influenza season

OBJECTIVE

During the influenza epidemic season, the fragile elderlies are not only susceptible to influenza infections, but are also more likely to develop severe symptoms and syndromes. Such circumstances may pose a significant burden to the medical resources especially in the emergency department (ED). Disposition of the elderly patients with influenza infections to either the ward or intensive care unit (ICU) accurately is therefore a crucial issue.

STUDY DESIGN

Retrospective cohort study.

SETTING AND PARTICIPANTS

Elderly patients (≥65 years) with influenza visiting the ED of a medical centre between 1 January 2010 and 31 December 2015.

PRIMARY OUTCOME MEASURES

Demographic data, vital signs, medical history, subtype of influenza, national early warning score (NEWS) and outcomes (mortality) were analysed. We investigated the ability of NEWS to predict ICU admission via logistic regression and the receiver operating characteristic (ROC) analysis.

RESULTS

We included 409 geriatric patients in the ED with a mean age of 79.5 years and approximately equal sex ratio. The mean NEWS ±SD was 3.4±2.9, and NEWS ≥8 was reported in 11.0% of the total patients. Logistic regression revealed that NEWS ≥8 predicted ICU admission with an OR of 5.37 (95% CI 2.61 to 11.04). The Hosmer-Lemeshow goodness-of-fit test was calculated as 0.95, and the adjusted area under the ROC was 0.72. An NEWS ≥8 is associated with ICU-admission and may help to triage elderly patients with influenza infections during the influenza epidemic season.

CONCLUSION

The high specificity of NEWS ≥8 to predict ICU admission in elderly patients with influenza infection during the epidemic season may avoid unnecessary ICU admissions and ensure proper medical resource allocation.

In-hospital cardiac arrest and preceding National Early Warning Score (NEWS): A retrospective case-control study

We aimed to describe and evaluate the National Early Warning Score (NEWS) in the 24 hours preceding an in-hospital cardiac arrest among general somatic ward patients.The 24 hours preceding the in-hospital cardiac arrest were divided into four timespans and analysed by a medical record review of 127:254 matched case-control patients. The median NEWS ranged from 3 (2-6) to 6 (3-9) points for cases vs 1 (0-3) to 1 (0-3) point for controls. The proportion of cases ranged from 23-45% at high risk vs 3-6% for controls. The NEWS high-risk category was associated with an increase of 3.17 (95% confidence interval (CI) 1.66-6.04) to 4.43 (95% CI 2.56-7.67) in odds of in-hospital cardiac arrest compared to the low-risk category.NEWS, with its intuitive and for healthcare staff easy to interpret risk classification, is suitable for discriminating deteriorating patients with major deviating vital signs scoring high risk on NEWS.

Guidelines for Perioperative Care for Emergency Laparotomy Enhanced Recovery After Surgery (ERAS) Society Recommendations: Part 1-Preoperative: Diagnosis, Rapid Assessment and Optimization

BACKGROUND

Enhanced Recovery After Surgery (ERAS) protocols reduce length of stay, complications and costs for a large number of elective surgical procedures. A similar, structured approach appears to improve outcomes, including mortality, for patients undergoing high-risk emergency general surgery, and specifically emergency laparotomy. These are the first consensus guidelines for optimal care of these patients using an ERAS approach.

METHODS

Experts in aspects of management of the high-risk and emergency general surgical patient were invited to contribute by the International ERAS® Society. Pubmed, Cochrane, Embase, and MEDLINE database searches on English language publications were performed for ERAS elements and relevant specific topics. Studies on each item were selected with particular attention to randomized controlled trials, systematic reviews, meta-analyses and large cohort studies, and reviewed and graded using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system. Recommendations were made on the best level of evidence, or extrapolation from studies on non-emergency patients when appropriate. The Delphi method was used to validate final recommendations. The guideline has been divided into two parts: Part 1-Preoperative Care and Part 2-Intraoperative and Postoperative management. This paper provides guidelines for Part 1.

RESULTS

Twelve components of preoperative care were considered. Consensus was reached after three rounds.

CONCLUSIONS

These guidelines are based on the best available evidence for an ERAS approach to patients undergoing emergency laparotomy. Initial management is particularly important for patients with sepsis and physiological derangement. These guidelines should be used to improve outcomes for these high-risk patients.

Patient Outcomes Following Emergency Bowel Resection for Inflammatory Bowel Disease and the Impact of Surgical Subspecialisation in the North of England: A Retrospective Cohort Study

BACKGROUND

Management of inflammatory bowel disease (IBD) has changed considerably over recent years, which has coincided with increased subspecialisation amongst general surgeons. This study evaluated the demographics and outcomes of patients with IBD undergoing bowel resection and assessed for the potential impact of surgical subspecialisation.

METHODS

Patient demographic, operative and outcome data were collected for patients undergoing a bowel resection secondary to IBD, admitted acutely to NHS trusts in the North of England between 2002 and 2016. The primary outcome of interest was 30-day post-operative mortality, with secondary outcomes: length of stay, stoma and anastomosis rates.

RESULTS

A total of 913 patients were included in the study cohort. A reduction in the number of resections was noted over time (2002-2006: 361 vs. 2012-2016: 262). No change was observed for 30-day mortality over the study period (3.9%, p = 0.233). Length of stay was also unchanged (p = 0.949). Laparoscopic surgery was increasingly utilised (0.6% vs. 17.2%, p < 0.001) in recent years, and by colorectal subspecialists (p = 0.003). More patients were managed by a colorectal consultant latterly (2002-2006: 45.4% vs. 2012-2016: 63.7%, p < 0.001). There was no difference between colorectal and other subspecialists in mortality (p = 0.156), length of stay (p = 0.201), stoma (p = 0.629) or anastomosis (p = 0.659) rates, including following multivariable adjustment.

CONCLUSION

The study demonstrated a significant reduction in the number of resections over time, increased utilisation of a laparoscopic approach and a shift towards the care of IBD surgical patients being by a colorectal subspecialist. However, these changes do not correspond with improved surgical outcomes.

Dynamic individual vital sign trajectory early warning score (DyniEWS) versus snapshot national early warning score (NEWS) for predicting postoperative deterioration

Aims

International early warning scores (EWS) including the additive National Early Warning Score (NEWS) and logistic EWS currently utilise physiological snapshots to predict clinical deterioration. We hypothesised that a dynamic score including vital sign trajectory would improve discriminatory power.

Methods

Multicentre retrospective analysis of electronic health record data from postoperative patients admitted to cardiac surgical wards in four UK hospitals. Least absolute shrinkage and selection operator-type regression (LASSO) was used to develop a dynamic model (DyniEWS) to predict a composite adverse event of cardiac arrest, unplanned intensive care re-admission or in-hospital death within 24 h.

Results

A total of 13,319 postoperative adult cardiac patients contributed 442,461 observations of which 4234 (0.96%) adverse events in 24 h were recorded. The new dynamic model (AUC = 0.80 [95% CI 0.78−0.83], AUPRC = 0.12 [0.10−0.14]) outperforms both an updated snapshot logistic model (AUC = 0.76 [0.73−0.79], AUPRC = 0.08 [0.60−0.10]) and the additive National Early Warning Score (AUC = 0.73 [0.70−0.76], AUPRC = 0.05 [0.02−0.08]). Controlling for the false alarm rates to be at current levels using NEWS cut-offs of 5 and 7, DyniEWS delivers a 7% improvement in balanced accuracy and increased sensitivities from 41% to 54% at NEWS 5 and 18% to –30% at NEWS 7.

Conclusions

Using an advanced statistical approach, we created a model that can detect dynamic changes in risk of unplanned readmission to intensive care, cardiac arrest or in-hospital mortality and can be used in real time to risk-prioritise clinical workload.

The performance of the National Early Warning Score and National Early Warning Score 2 in hospitalised patients infected by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

INTRODUCTION

Since the introduction of the UK's National Early Warning Score (NEWS) and its modification, NEWS2, coronavirus disease 2019 (COVID-19), has caused a worldwide pandemic. NEWS and NEWS2 have good predictive abilities in patients with other infections and sepsis, however there is little evidence of their performance in COVID-19.

METHODS

Using receiver-operating characteristics analyses, we used the area under the receiver operating characteristic (AUROC) curve to evaluate the performance of NEWS or NEWS2 to discriminate the combined outcome of either death or intensive care unit (ICU) admission within 24 h of a vital sign set in five cohorts (COVID-19 POSITIVE, n = 405; COVID-19 NOT DETECTED, n = 1716; COVID-19 NOT TESTED, n = 2686; CONTROL 2018, n = 6273; CONTROL 2019, n = 6523).

RESULTS

The AUROC values for NEWS or NEWS2 for the combined outcome were: COVID-19 POSITIVE, 0.882 (0.868-0.895); COVID-19 NOT DETECTED, 0.875 (0.861-0.89); COVID-19 NOT TESTED, 0.876 (0.85-0.902); CONTROL 2018, 0.894 (0.884-0.904); CONTROL 2019, 0.842 (0.829-0.855).

CONCLUSIONS

The finding that NEWS or NEWS2 performance was good and similar in all five cohorts (range = 0.842-0.894) suggests that amendments to NEWS or NEWS2, such as the addition of new covariates or the need to change the weighting of existing parameters, are unnecessary when evaluating patients with COVID-19. Our results support the national and international recommendations for the use of NEWS or NEWS2 for the assessment of acute-illness severity in patients with COVID-19.

Value of laboratory results in addition to vital signs in a machine learning algorithm to predict in-hospital cardiac arrest: A single-center retrospective cohort study

BACKGROUND

Although machine learning-based prediction models for in-hospital cardiac arrest (IHCA) have been widely investigated, it is unknown whether a model based on vital signs alone (Vitals-Only model) can perform similarly to a model that considers both vital signs and laboratory results (Vitals+Labs model).

METHODS

All adult patients hospitalized in a tertiary care hospital in Japan between October 2011 and October 2018 were included in this study. Random forest models with/without laboratory results (Vitals+Labs model and Vitals-Only model, respectively) were trained and tested using chronologically divided datasets. Both models use patient demographics and eight-hourly vital signs collected within the previous 48 hours. The primary and secondary outcomes were the occurrence of IHCA in the next 8 and 24 hours, respectively. The area under the receiver operating characteristic curve (AUC) was used as a comparative measure. Sensitivity analyses were performed under multiple statistical assumptions.

RESULTS

Of 141,111 admitted patients (training data: 83,064, test data: 58,047), 338 had an IHCA (training data: 217, test data: 121) during the study period. The Vitals-Only model and Vitals+Labs model performed comparably when predicting IHCA within the next 8 hours (Vitals-Only model vs Vitals+Labs model, AUC = 0.862 [95% confidence interval (CI): 0.855-0.868] vs 0.872 [95% CI: 0.867-0.878]) and 24 hours (Vitals-Only model vs Vitals+Labs model, AUC = 0.830 [95% CI: 0.825-0.835] vs 0.837 [95% CI: 0.830-0.844]). Both models performed similarly well on medical, surgical, and ward patient data, but did not perform well for intensive care unit patients.

CONCLUSIONS

In this single-center study, the machine learning model predicted IHCAs with good discrimination. The addition of laboratory values to vital signs did not significantly improve its overall performance.

Early warning score validation methodologies and performance metrics: a systematic review

Background

Early warning scores (EWS) have been developed as clinical prognostication tools to identify acutely deteriorating patients. In the past few years, there has been a proliferation of studies that describe the development and validation of novel machine learning-based EWS. Systematic reviews of published studies which focus on evaluating performance of both well-established and novel EWS have shown conflicting conclusions. A possible reason is the heterogeneity in validation methods applied. In this review, we aim to examine the methodologies and metrics used in studies which perform EWS validation.

Methods

A systematic review of all eligible studies from the MEDLINE database and other sources, was performed. Studies were eligible if they performed validation on at least one EWS and reported associations between EWS scores and inpatient mortality, intensive care unit (ICU) transfers, or cardiac arrest (CA) of adults. Two reviewers independently did a full-text review and performed data abstraction by using standardized data-worksheet based on the TRIPOD (Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) checklist. Meta-analysis was not performed due to heterogeneity.

Results

The key differences in validation methodologies identified were (1) validation dataset used, (2) outcomes of interest, (3) case definition, time of EWS use and aggregation methods, and (4) handling of missing values. In terms of case definition, among the 48 eligible studies, 34 used the patient episode case definition while 12 used the observation set case definition, and 2 did the validation using both case definitions. Of those that used the patient episode case definition, 18 studies validated the EWS at a single point of time, mostly using the first recorded observation. The review also found more than 10 different performance metrics reported among the studies.

Conclusions

Methodologies and performance metrics used in studies performing validation on EWS were heterogeneous hence making it difficult to interpret and compare EWS performance. Standardizing EWS validation methodology and reporting can potentially address this issue.

Early warning scores for detecting deterioration in adult hospital patients: systematic review and critical appraisal of methodology

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.

Nurses' judgments of patient risk of deterioration at change-of-shift handoff: Agreement between nurses and comparison with early warning scores

BACKGROUND

Nurses begin forming judgments regarding patients' clinical stability during change-of-shift handoffs.

OBJECTIVES

To examine the agreement between incoming and outgoing nurses' judgments of deterioration risk following handoff and compare these judgments to commonly used early warning scores (MEWS, NEWS, ViEWS).

METHODS

Following handoffs on three medical/surgical units, nurses completed the Patient Acuity Rating. Nurse ratings were compared with computed early warning scores based on clinical data. In follow-up interviews, nurses were invited to describe their experiences of using the rating scale.

RESULTS

Sixty-two nurses carried out 444 handoffs for 158 patients. While the agreement between incoming and outgoing nurses was fair, correlations with early warning scores were low. Nurses struggled with predicting risk and used their impressions of differential risk across all the patients to whom they had been assigned to arrive at their ratings.

CONCLUSION

Nurses shared information that influenced their clinical judgments at handoff; not all of these cues may necessarily be captured in early warning scores.

National Early Warning Score: A survey of registered nurses' perceptions, experiences and barriers

AIMS & OBJECTIVES

To describe registered nurses' perceptions, experiences and barriers for using the National Early Warning Score in relation to their work experience and medical affiliation.

BACKGROUND

Indications of inconsistencies in adherence to the National Early Warning Score have emerged.

DESIGN

Web-based questionnaire study.

METHODS

The questionnaire was sent to 3,165 registered nurses working in somatic hospitals in the southern part of Sweden. Strengthening the Reporting of Observational Studies in Epidemiology was adhered.

RESULTS

Seventy-one per cent of the 1,044 respondents reported adherence to the National Early Warning Score guidelines recommended frequency of monitoring and 74% to the clinical response scale. The shorter the working experience, the higher the proportion of registered nurses who answered positively to the National Early Warning Score allowing them to better prioritise their care with short nursing experience. When categorising nurses according to their workplace's medical affiliation, adherence to the National Early Warning Score guidelines recommended frequency of monitoring was reported highest in surgery and orthopaedics (66%) and lowest in the cardiac high dependency unit (52%). Corresponding proportions of reported adherence to the clinical response scale were highest in orthopaedics (82%) and lowest in the cardiac high dependency unit (48%). Lack of response from the doctor was reported as one of the main reasons for not adhering to the National Early Warning Score by 50% of the registered nurse.

CONCLUSION

In general, registered nurses perceived the National Early Warning Score as a useful tool, supporting their gut feeling about an unstable patient. Barriers to the National Early Warning Score were found in doctors and the most experienced registered nurses, indicating the need for resources to be focused on the adherence of these members of the healthcare team.

RELEVANCE TO CLINICAL PRACTICE

In general, the registered nurses answered positively to the National Early Warning Score. We found indications that there is a need to focus resources on the adherence of the most experienced registered nurse and the doctors.

Predicting need for intensive care unit admission in adult emphysematous pyelonephritis patients at emergency departments: comparison of five scoring systems

This study assesses the performance of National Early Warning Score (NEWS), Quick Sepsis-related Organ Failure Assessment (qSOFA), Modified Early Warning Score (MEWS), Rapid Emergency Medicine Score (REMS), and Rapid Acute Physiology Score (RAPS) in predicting emphysematous pyelonephritis (EPN) patients' need for intensive care unit (ICU) admission. A retrospective analysis was conducted at four training and research hospitals' emergency departments (EDs) on all EPN adult patients from January 2007 to August 2017. Data extracted were used to calculate raw scores for five physiologic scoring systems. Mann-Whitney U tests and χ² tests were done for numerical and categorical variables respectively to examine differences between characteristics of ICU and non-ICU patient populations. Predictability of ICU admission was evaluated with AUROC analysis. ICU patients had lower GCS scores, SpO2, platelet counts, and estimated glomerular filtration rate; and higher bands, blood urea nitrogen, creatinine, and incidences of septic shock and nephrectomy. NEWS performed best, with 73.85% accuracy at optimal cut-off of 3. In this multicentre ED EPN series, we recommend using NEWS in early identification of critical EPN patients and advance planning for ICU admission. This would reduce delays in ICU transfer and ultimately improve patient outcomes.

Impact of using data from electronic protocols in nursing performance management: A qualitative interview study

Aim

To explore the impact of using electronic data in performance management to improve nursing compliance with a protocol.

Background

Electronic data are increasingly used to monitor protocol compliance but little is known about the impact on nurses’ practice in hospital wards.

Method

Seventeen acute hospital nursing staff participated in semi‐structured interviews about compliance with an early warning score (EWS) protocol delivered by a bedside electronic handheld device.

Results

Before electronic EWS data was used to monitor compliance, staff combined protocol‐led actions with clinical judgement. However, some observations were missed to reduce noise and disruption at night. After compliance monitoring was introduced, observations were sometimes covertly omitted using a loophole. Interviewees described a loss of autonomy but acknowledged the EWS system sometimes flagged unexpected patient deterioration.

Conclusions

Introducing automated electronic systems to support nursing tasks can decrease nursing burden but remove the ability to record legitimate reasons for missing observations. This can result in covert resistance that could reduce patient safety.

Implications for nursing management

Providing the ability to log legitimate reasons for missing observations would allow nurses to balance professional judgement with the use of electronic data in performance management of protocol compliance.

Minimal Impact of Implemented Early Warning Score and Best Practice Alert for Patient Deterioration

OBJECTIVES

Previous studies have looked at National Early Warning Score performance in predicting in-hospital deterioration and death, but data are lacking with respect to patient outcomes following implementation of National Early Warning Score. We sought to determine the effectiveness of National Early Warning Score implementation on predicting and preventing patient deterioration in a clinical setting.

DESIGN

Retrospective cohort study.

SETTING

Tertiary care academic facility and a community hospital.

PATIENTS

Patients 18 years old or older hospitalized from March 1, 2014, to February 28, 2015, during preimplementation of National Early Warning Score to August 1, 2015, to July 31, 2016, after National Early Warning Score was implemented.

INTERVENTIONS

Implementation of National Early Warning Score within the electronic health record and associated best practice alert.

MEASUREMENTS AND MAIN RESULTS

In this study of 85,322 patients (42,402 patients pre-National Early Warning Score and 42,920 patients post-National Early Warning Score implementation), the primary outcome of rate of ICU transfer or death did not change after National Early Warning Score implementation, with adjusted hazard ratio of 0.94 (0.84-1.05) and 0.90 (0.77-1.05) at our academic and community hospital, respectively. In total, 175,357 best practice advisories fired during the study period, with the best practice advisory performing better at the community hospital than the academic at predicting an event within 12 hours 7.4% versus 2.2% of the time, respectively. Retraining National Early Warning Score with newly generated hospital-specific coefficients improved model performance.

CONCLUSIONS

At both our academic and community hospital, National Early Warning Score had poor performance characteristics and was generally ignored by frontline nursing staff. As a result, National Early Warning Score implementation had no appreciable impact on defined clinical outcomes. Refitting of the model using site-specific data improved performance and supports validating predictive models on local data.

A Comparison of the Quick Sequential (Sepsis-Related) Organ Failure Assessment Score and the National Early Warning Score in Non-ICU Patients With/Without Infection

OBJECTIVES

The Sepsis-3 task force recommended the quick Sequential (Sepsis-Related) Organ Failure Assessment score for identifying patients with suspected infection who are at greater risk of poor outcomes, but many hospitals already use the National Early Warning Score to identify high-risk patients, irrespective of diagnosis. We sought to compare the performance of quick Sequential (Sepsis-Related) Organ Failure Assessment and National Early Warning Score in hospitalized, non-ICU patients with and without an infection.

DESIGN

Retrospective cohort study.

SETTING

Large U.K. General Hospital.

PATIENTS

Adults hospitalized between January 1, 2010, and February 1, 2016.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We applied the quick Sequential (Sepsis-Related) Organ Failure Assessment score and National Early Warning Score to 5,435,344 vital signs sets (241,996 hospital admissions). Patients were categorized as having no infection, primary infection, or secondary infection using International Classification of Diseases, 10th Edition codes. National Early Warning Score was significantly better at discriminating in-hospital mortality, irrespective of infection status (no infection, National Early Warning Score 0.831 [0.825-0.838] vs quick Sequential [Sepsis-Related] Organ Failure Assessment 0.688 [0.680-0.695]; primary infection, National Early Warning Score 0.805 [0.799-0.812] vs quick Sequential [Sepsis-Related] Organ Failure Assessment 0.677 [0.670-0.685]). Similarly, National Early Warning Score performed significantly better in all patient groups (all admissions, emergency medicine admissions, and emergency surgery admissions) for all outcomes studied. Overall, quick Sequential (Sepsis-Related) Organ Failure Assessment performed no better, and often worse, in admissions with infection than without.

CONCLUSIONS

The National Early Warning Score outperforms the quick Sequential (Sepsis-Related) Organ Failure Assessment score, irrespective of infection status. These findings suggest that quick Sequential (Sepsis-Related) Organ Failure Assessment should be reevaluated as the system of choice for identifying non-ICU patients with suspected infection who are at greater risk of poor outcome.

Logistic early warning scores to predict death, cardiac arrest or unplanned intensive care unit re-admission after cardiac surgery

NHS England recently mandated that the National Early Warning Score of vital signs be used in all acute hospital trusts in the UK despite limited validation in the postoperative setting. We undertook a multicentre UK study of 13,631 patients discharged from intensive care after risk‐stratified cardiac surgery in four centres, all of which used VitalPAC^TM to electronically collect postoperative National Early Warning Score vital signs. We analysed 540,127 sets of vital signs to generate a logistic score, the discrimination of which we compared with the national additive score for the composite outcome of: in‐hospital death; cardiac arrest; or unplanned intensive care admission. There were 578 patients (4.2%) with an outcome that followed 4300 sets of observations (0.8%) in the preceding 24 h: 499 out of 578 (86%) patients had unplanned re‐admissions to intensive care. Discrimination by the logistic score was significantly better than the additive score. Respective areas (95%CI) under the receiver‐operating characteristic curve with 24‐h and 6‐h vital signs were: 0.779 (0.771–0.786) vs. 0.754 (0.746–0.761), p < 0.001; and 0.841 (0.829–0.853) vs. 0.813 (0.800–0.825), p < 0.001, respectively. Our proposed logistic Early Warning Score was better than the current National Early Warning Score at discriminating patients who had an event after cardiac surgery from those who did not.

Validating the Electronic Cardiac Arrest Risk Triage (eCART) Score for Risk Stratification of Surgical Inpatients in the Postoperative Setting: Retrospective Cohort Study

OBJECTIVE

Assess the accuracy of 3 early warning scores for predicting severe adverse events in postoperative inpatients.

SUMMARY OF BACKGROUND DATA

Postoperative clinical deterioration on inpatient hospital services is associated with increased morbidity, mortality, and cost. Early warning scores have been developed to detect inpatient clinical deterioration and trigger rapid response activation, but knowledge regarding the application of early warning scores to postoperative inpatients is limited.

METHODS

This was a retrospective cohort study of adult patients hospitalized on the wards after surgical procedures at an urban academic medical center from November, 2008 to January, 2016. The accuracies of the Modified Early Warning Score (MEWS), National Early Warning Score (NEWS), and the electronic cardiac arrest risk triage (eCART) score were compared in predicting severe adverse events (ICU transfer, ward cardiac arrest, or ward death) in the postoperative period using the area under the receiver operating characteristic curve (AUC).

RESULTS

Of the 32,537 patient admissions included in the study, 3.8% (n = 1243) experienced a severe adverse outcome after the procedure. The accuracy for predicting the composite outcome was highest for eCART [AUC 0.79 (95% CI: 0.78-0.81)], followed by NEWS [AUC 0.76 (95% CI: 0.75-0.78)], and MEWS [AUC 0.75 (95% CI: 0.73-0.76)]. Of the individual vital signs and labs, maximum respiratory rate was the most predictive (AUC 0.67) and maximum temperature was an inverse predictor (AUC 0.46).

CONCLUSION

Early warning scores are predictive of severe adverse events in postoperative patients. eCART is significantly more accurate in this patient population than both NEWS and MEWS.

Automated continuous noninvasive ward monitoring: future directions and challenges

Automated continuous noninvasive ward monitoring may enable subtle changes in vital signs to be recognized. There is already some evidence that automated ward monitoring can improve patient outcome. Before automated continuous noninvasive ward monitoring can be implemented in clinical routine, several challenges and problems need to be considered and resolved; these include the meticulous validation of the monitoring systems with regard to their measurement performance, minimization of artifacts and false alarms, integration and combined analysis of massive amounts of data including various vital signs, and technical problems regarding the connectivity of the systems.

Comparison of the National Early Warning Score (NEWS) and the Modified Early Warning Score (MEWS) for predicting admission and in-hospital mortality in elderly patients in the pre-hospital setting and in the emergency department

The aim of this study is to evaluate the usefulness of the pre-hospital National Early Warning Score (pNEWS) and the pre-hospital Modified Early Warning Score (pMEWS) for predicting admission and in-hospital mortality in elderly patients presenting to the emergency department (ED). We also compare the value of the pNEWS with that of the ED NEWS (eNEWS) and ED MEWS (eMEWS) for predicting admission and in-hospital mortality. This retrospective, single-centre observational study was carried out in the ED of Jikei University Kashiwa Hospital, in Chiba, Japan, from 1st April 2017 to 31st March 2018. All patients aged 65 years or older were included in this study. The pNEWS/eNEWS were derived from seven common physiological vital signs: respiratory rate, peripheral oxygen saturation, the presence of inhaled oxygen parameters, body temperature, systolic blood pressure, pulse rate and Alert, responds to Voice, responds to Pain, Unresponsive (AVPU) score, whereas the pMEWS/eMEWS were derived from six common physiological vital signs: respiratory rate, peripheral oxygen saturation, body temperature, systolic blood pressure, pulse rate and AVPU score. Discrimination was assessed by plotting the receiver operating characteristic (ROC) curve and calculating the area under the ROC curve (AUC). The median pNEWS, pMEWS, eNEWS and eMEWS were significantly higher at admission than at discharge (p < 0.001). The median pNEWS, pMEWS, eNEWS and eMEWS of non-survivors were significantly higher than those of the survivors (p < 0.001). The AUC for predicting admission was 0.559 for the pNEWS and 0.547 for the pMEWS. There was no significant difference between the AUCs of the pNEWS and the pMEWS for predicting admission (p = 0.102). The AUCs for predicting in-hospital mortality were 0.678 for the pNEWS and 0.652 for the pMEWS. There was no significant difference between the AUCs of the pNEWS and the pMEWS for predicting in-hospital mortality (p = 0.081). The AUC for predicting admission was 0.628 for the eNEWS and 0.591 for the eMEWS. The AUC of the eNEWS was significantly greater than that of the eMEWS for predicting admission (p < 0.001). The AUC for predicting in-hospital mortality was 0.789 for the eNEWS and 0.720 for the eMEWS. The AUC of the eNEWS was significantly greater than that of the eMEWS for predicting in-hospital mortality (p < 0.001). For admission and in-hospital mortality, the AUC of the eNEWS was significantly greater than that of the pNEWS (p < 0.001, p < 0.001), and the AUC of the eMEWS was significantly greater than that of the pMEWS (p < 0.01, p < 0.05). Our single-centre study has demonstrated the low utility of the pNEWS and the pMEWS as predictors of admission and in-hospital mortality in elderly patients, whereas the eNEWS and the eMEWS predicted admission and in-hospital mortality more accurately. Evidence from multicentre studies is needed before introducing pre-hospital versions of risk-scoring systems.

Prehospital National Early Warning Score predicts early mortality

BACKGROUND

National Early Warning Score (NEWS) has been shown to be the best early warning score to predict in-hospital mortality but there is limited information on its predictive value in a prehospital setting. The aim of the current study was to investigate the diagnostic accuracy of NEWS in a prehospital setting using large population-based databases in terms of short-term mortality.

METHODS

We calculated the NEWS scores from retrospective prehospital electronic patient record data and analysed their possible relationship to mortality. We included all patient records for patients 18 years or older with sufficient prehospital data to calculate NEWS from 17 August 2008 to 18 December 2015 encountered by the emergency medical services (EMS) in the Hospital District of Helsinki and Uusimaa, Finland. The primary outcome measure was death within 1 day of EMS dispatch.

RESULTS

35 800 patients were included. Their mean (SD) age was 65.8 (19.9) years. The median value of NEWS was 3 (IQR 1-6). The primary outcome of death within 1 day of EMS dispatch occurred in 378 (1.1%) cases. Area under receiver operating characteristic curve (AUROC) for primary outcome of death within 1 day was 0.840 (95% CI 0.823-0.858). AUROC for 1 day mortality in trauma subgroup was 0.901 (95% CI 0.859-0.942).

CONCLUSION

Prehospital NEWS predicts mortality within 1 day of EMS dispatch with good diagnostic accuracy.

Combination of the National Early Warning Score (NEWS) and inflammatory biomarkers for early risk stratification in emergency department patients: results of a multinational, observational study

OBJECTIVES

The National Early Warning Score (NEWS) helps to estimate mortality risk in emergency department (ED) patients. This study aimed to investigate whether the prognostic value of the NEWS at ED admission could be further improved by adding inflammatory blood markers (ie, white cell count (WCC), procalcitonin (PCT) and midregional-proadrenomedullin (MR-proADM).

DESIGN

Secondary analysis of a multinational, observational study (TRIAGE study, March 2013-October 2014).

SETTING

Three tertiary care centres in France, Switzerland and the USA.

PARTICIPANTS

A total of 1303 adult medical patients with complete NEWS data seeking ED care were included in the final analysis. NEWS was calculated retrospectively based on admission data.

MAIN OUTCOME MEASURES

The primary outcome was all-cause 30-day mortality. Secondary outcome was intensive care unit (ICU) admission. We used multivariate regression analyses to investigate associations of NEWS and blood markers with outcomes and area under the receiver operating curve (AUC) as a measure of discrimination.

RESULTS

Of the 1303 included patients, 54 (4.1%) died within 30 days. The NEWS alone showed fair prognostic accuracy for all-cause 30-day mortality (AUC 0.73), with a multivariate adjusted OR of 1.26 (95% CI 1.13 to 1.40, p<0.001). The AUCs for the prediction of mortality using the inflammatory markers WCC, PCT and MR-proADM were 0.64, 0.71 and 0.78, respectively. Combining NEWS with all three blood markers or only with MR-proADM clearly improved discrimination with an AUC of 0.82 (p=0.002). Combining the three inflammatory markers with NEWS improved prediction of ICU admission (AUC 0.70vs0.65 when using NEWS alone, p=0.006).

CONCLUSION

NEWS is helpful in risk stratification of ED patients and can be further improved by the addition of inflammatory blood markers. Future studies should investigate whether risk stratification by NEWS in addition to biomarkers improve site-of-care decision in this patient population.

TRIAL REGISTRATION NUMBER

NCT01768494; Post-results.

The National Early Warning Score predicts mortality in hospital ward patients with deviating vital signs: A retrospective medical record review study

AIMS AND OBJECTIVES

To evaluate whether the scale used for assessment of hospital ward patients could predict in-hospital and 30-day mortality amongst those with deviating vital signs; that is, that patients classified as medium or high risk would have increased risk of in-hospital and 30-day mortality compared to patients with low risk.

BACKGROUND

The National Early Warning Score (NEWS) is a widely adopted scale for assessing deviating vital signs. A clinical risk scale that comes with the NEWS divides the risk for critical illness into three risk categories, low, medium and high.

DESIGN

Retrospective analysis of vital sign data.

METHODS

Logistic regression models for age-adjusted in-hospital and 30-day mortality were used for analyses of 1,107 patients with deviating vital signs.

RESULTS

Patients classified as medium or high risk by NEWS experienced a 2.11 or 3.40 increase, respectively, in odds of in-hospital death (95% CI: 1.27-3.51, p = 0.004% and 95% CI: 1.90-6.01, p < 0.001) compared to low-risk patients. Moreover, those with NEWS medium or high risk were associated with a 1.98 or 3.19 increase, respectively, in odds of 30-day mortality (95% CI: 1.32-2.97, p = 0.001% and 95% CI: 1.97-5.18, p < 0.001).

CONCLUSION

The NEWS risk classification seems to be a reliable predictor of mortality on patients in hospital wards.

RELEVANCE TO CLINICAL PRACTICE

The NEWS risk classification offers a simple way to identify deteriorating patients and can aid the healthcare staff to prioritise amongst patients.

A comparison of the ability of the National Early Warning Score and the National Early Warning Score 2 to identify patients at risk of in-hospital mortality: A multi-centre database study

Aims

To compare the ability of the National Early Warning Score (NEWS) and the National Early Warning Score 2 (NEWS2) to identify patients at risk of in-hospital mortality and other adverse outcomes.

Methods

We undertook a multi-centre retrospective observational study at five acute hospitals from two UK NHS Trusts. Data were obtained from completed adult admissions who were not fit enough to be discharged alive on the day of admission. Diagnostic coding and oxygen prescriptions were used to identify patients with type II respiratory failure (T2RF). The primary outcome was in-hospital mortality within 24 h of a vital signs observation. Secondary outcomes included unanticipated intensive care unit admission or cardiac arrest within 24 h of a vital signs observation. Discrimination was assessed using the c-statistic.

Results

Among 251,266 adult admissions, 48,898 were identified to be at risk of T2RF by diagnostic coding. In this group, NEWS2 showed statistically significant lower discrimination (c-statistic, 95% CI) for identifying in-hospital mortality within 24 h (0.860, 0.857–0.864) than NEWS (0.881, 0.878-0.884). For 1394 admissions with documented T2RF, discrimination was similar for both systems: NEWS2 (0.841, 0.827-0.855), NEWS (0.862, 0.848–0.875). For all secondary endpoints, NEWS2 showed no improvements in discrimination.

Conclusions

NEWS2 modifications to NEWS do not improve discrimination of adverse outcomes in patients with documented T2RF and decrease discrimination in patients at risk of T2RF. Further evaluation of the relationship between SpO₂ values, oxygen therapy and risk should be investigated further before wide-scale adoption of NEWS2.

Predicting in-hospital mortality and unanticipated admissions to the intensive care unit using routinely collected blood tests and vital signs: Development and validation of a multivariable model

Aim

The National Early Warning System (NEWS) is based on vital signs; the Laboratory Decision Tree Early Warning Score (LDT-EWS) on laboratory test results. We aimed to develop and validate a new EWS (the LDTEWS:NEWS risk index) by combining the two and evaluating the discrimination of the primary outcome of unanticipated intensive care unit (ICU) admission or in-hospital mortality, within 24 h.

Methods

We studied emergency medical admissions, aged 16 years or over, admitted to Oxford University Hospitals (OUH) and Portsmouth Hospitals (PH). Each admission had vital signs and laboratory tests measured within their hospital stay. We combined LDT-EWS and NEWS values using a linear time-decay weighting function imposed on the most recent blood tests. The LDTEWS:NEWS risk index was developed using data from 5 years of admissions to PH, and validated on a year of data from both PH and OUH. We tested the risk index’s ability to discriminate the primary outcome using the c-statistic.

Results

The development cohort contained 97,933 admissions (median age = 73 years) of which 4723 (4.8%) resulted inhospital death and 1078 (1.1%) in unanticipated ICU admission. We validated the risk index using data from PH (n = 21,028) and OUH (n = 16,383). The risk index showed a higher discrimination in the validation sets (c-statistic value (95% CI)) (PH, 0.901 (0.898–0.905); OUH, 0.916 (0.911–0.921)), than NEWS alone (PH, 0.877 (0.873–0.882); OUH, 0.898 (0.893–0.904)).

Conclusions

The LDTEWS:NEWS risk index increases the ability to identify patients at risk of deterioration, compared to NEWS alone.

Manual centile-based early warning scores derived from statistical distributions of observational vital-sign data

AIMS OF STUDY

To develop and validate a centile-based early warning score using manually-recorded data (mCEWS). To compare mCEWS performance with a centile-based early warning score derived from continuously-acquired data (from bedside monitors, cCEWS), and with other published early warning scores.

MATERIALS AND METHODS

We used an unsupervised approach to investigate the statistical properties of vital signs in an in-hospital patient population and construct an early-warning score from a "development" dataset. We evaluated scoring systems on a separate "validation" dataset. We assessed the ability of scores to discriminate patients at risk of cardiac arrest, unanticipated intensive care unit admission, or death, each within 24 h of a given vital-sign observation, using metrics including the area under the receiver-operating characteristic curve (AUC).

RESULTS

The development dataset contained 301,644 vital sign observations from 12,153 admissions (median age (IQR): 63 (49-73); 49.2% females) March 2014-September 2015. The validation dataset contained 1,459,422 vital-sign observations from 53,395 admissions (median age (IQR): 68 (48-81), 51.4% females) October 2015-May 2017. The AUC (95% CI) for the mCEWS was 0.868 (0.864-0.872), comparable with the National EWS, 0.867 (0.863-0.871), and other recently proposed scores. The AUC for cCEWS was 0.808 (95% CI, 0.804-0.812). The improvement in performance in comparison to the continuous CEWS was mainly explained by respiratory rate threshold differences.

CONCLUSIONS

Performance of an EWS is highly dependent on the database from which itis derived. Our unsupervised statistical approach provides a straightforward, reproducible method to enable the rapid development of candidate EWS systems.

NICE guidance on sepsis is of limited value in postoperative colorectal patients: the scores that cry 'wolf!'

Background and aims Late recognition of sepsis and consequent death remains a problem. To address this, the National Institute for Health and Care Excellence has published updated guidance recommending the use of the Quick Sequential Organ Failure Assessment (Q-SOFA) score when assessing patients at risk of sepsis following the publication of the Third International Consensus Definitions for Sepsis and Septic Shock. The trauma from major surgery produces a systemic inflammatory response syndrome (SIRS) postoperatively as part of its natural history, which may falsely trigger scoring systems. We aimed to assess the accuracy of Q-SOFA and SIRS criteria as recommended scores for early detection of sepsis and septic complications in the first 48hrs after colorectal cancer surgery. Methods We reviewed all elective major colorectal operations in a single centre during a 12-month period from prospectively maintained electronic records. Results One hundred and thirty nine patients were included in this study. In all, 29 patients developed postoperative infective complications in hospital. Nineteen patients triggered on SIRS without developing infective complications, while 42 patients triggered on Q-SOFA with no infective complications. The area under the ROC curve was 0.52 for Q-SOFA and 0.67 for SIRS. Discussion Q-SOFA appears to perform little better than a coin toss at identifying postoperative sepsis after colorectal cancer resection and is inferior to the SIRS criteria. More work is required to assess whether a combination of scoring criteria, biochemical markers and automated tools could increase accurate detection of postoperative infection and trigger early intervention.