Early warning scores for sepsis identification and prediction of in-hospital mortality in adults with sepsis: A systematic review and meta-analysis

AIM

The early warning scores (EWS), quick Sequential Organ Failure Assessment (qSOFA) and systemic inflammatory response syndrome (SIRS) criteria have been proposed as sepsis screening tools. This review aims to summarise and compare the performance of EWS with the qSOFA and SIRS criteria for predicting sepsis diagnosis and in-hospital mortality in patients with sepsis.

DESIGN

A systematic review with meta-analysis.

REVIEW METHODS

Seven databases were searched from January 1, 2016 until March 10, 2022. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Sensitivity, specificity, likelihood ratios and diagnostic odd ratios were pooled by using the bivariate random effects model. Overall performance was summarised by using the hierarchical summary receiver-operating characteristics curve. This paper adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy Studies (PRISMA-DTA) guidelines.

RESULTS

Ten studies involving 52,474 subjects were included in the review. For predicting sepsis diagnosis, the pooled sensitivity of EWS (65%, 95% CI: 55, 75) was similar to SIRS ≥2 (70%, 95% CI: 49, 85) and higher than qSOFA ≥2 (37%, 95% CI: 20, 59). The pooled specificity of EWS (77%, 95% CI: 64, 86) was higher than SIRS ≥2 (62%, 95% CI: 41, 80) but lower than qSOFA ≥2 (94%, 95% CI: 86, 98). Results were similar for the secondary outcome of in-hospital mortality.

CONCLUSIONS

Although no one scoring system had both high sensitivity and specificity, the EWS had at least equivalent values in most measures of diagnostic accuracy compared with SIRS or qSOFA.

IMPLICATIONS FOR THE PROFESSION

Healthcare systems in which EWS is already in place should consider whether there is any clinical benefit in adopting qSOFA or SIRS.

NO PATIENT OR PUBLIC CONTRIBUTION

This systematic review did not directly involve patient or public contribution to the manuscript.

Evaluation of a modified paediatric early warning score for children with congenital heart disease

BACKGROUND

Paediatric early warning score systems are used for early detection of clinical deterioration of patients in paediatric wards. Several paediatric early warning scores have been developed, but most of them are not suitable for children with cyanotic CHD who are adapted to lower arterial oxygen saturation.

AIM

The present study compared the original paediatric early warning system of the Royal College of Physicians of Ireland with a modification for children with cyanotic CHD.

DESIGN

Retrospective single-centre study in a paediatric cardiology intermediate care unit at a German university hospital.

RESULTS

The distribution of recorded values showed a significant shift towards higher score values in patients with cyanotic CHD (p < 0.001) using the original score, but not with the modification. An analysis of sensitivity and specificity for the factor "requirement of action" showed an area under the receiver operating characteristic for non-cyanotic patients of 0.908 (95% CI 0.862-0.954). For patients with cyanotic CHD, using the original score, the area under the receiver operating characteristic was reduced to 0.731 (95% CI 0.637-0.824, p = 0.001) compared to 0.862 (95% CI 0.809-0.915, p = 0.207), when the modified score was used. Using the critical threshold of scores ≥ 4 in patients with cyanotic CHD, sensitivity and specificity for the modified score was higher than for the original (sensitivity 78.8 versus 72.7%, specificity 78.2 versus 58.4%).

CONCLUSION

The modified score is a uniform scoring system for identifying clinical deterioration, which can be used in children with and without cyanotic CHD.

External Validation of Deep Learning-Based Cardiac Arrest Risk Management System for Predicting In-Hospital Cardiac Arrest in Patients Admitted to General Wards Based on Rapid Response System Operating and Nonoperating Periods: A Single-Center Study

OBJECTIVES

The limitations of current early warning scores have prompted the development of deep learning-based systems, such as deep learning-based cardiac arrest risk management systems (DeepCARS). Unfortunately, in South Korea, only two institutions operate 24-hour Rapid Response System (RRS), whereas most hospitals have part-time or no RRS coverage at all. This study validated the predictive performance of DeepCARS during RRS operation and nonoperation periods and explored its potential beyond RRS operating hours.

DESIGN

Retrospective cohort study.

SETTING

In this 1-year retrospective study conducted at Yonsei University Health System Severance Hospital in South Korea, DeepCARS was compared with conventional early warning systems for predicting in-hospital cardiac arrest (IHCA). The study focused on adult patients admitted to the general ward, with the primary outcome being IHCA-prediction performance within 24 hours of the alarm.

PATIENTS

We analyzed the data records of adult patients admitted to a general ward from September 1, 2019, to August 31, 2020.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Performance evaluation was conducted separately for the operational and nonoperational periods of the RRS, using the area under the receiver operating characteristic curve (AUROC) as the metric. DeepCARS demonstrated a superior AUROC as compared with the Modified Early Warning Score (MEWS) and the National Early Warning Score (NEWS), both during RRS operating and nonoperating hours. Although the MEWS and NEWS exhibited varying performance across the two periods, DeepCARS showed consistent performance.

CONCLUSIONS

The accuracy and efficiency for predicting IHCA of DeepCARS were superior to that of conventional methods, regardless of whether the RRS was in operation. These findings emphasize that DeepCARS is an effective screening tool suitable for hospitals with full-time RRS, part-time RRS, and even those without any RRS.

An Evaluation of the National Early Warning Score 2 and the Laboratory Data Decision Tree Early Warning Score in Predicting Mortality in Geriatric Patients

BACKGROUND

Due to the high rate of geriatric patient visits, scoring systems are needed to predict increasing mortality rates.

OBJECTIVE

In this study, we aimed to investigate the in-hospital mortality prediction power of the National Early Warning Score 2 (NEWS2) and the Laboratory Data Decision Tree Early Warning Score (LDT-EWS), which consists of frequently performed laboratory parameters.

METHODS

We retrospectively analyzed 651 geriatric patients who visited the emergency department (ED), were not discharged on the same day from ED, and were hospitalized. The patients were categorized according to their in-hospital mortality status. The NEWS2 and LDT-EWS values of these patients were calculated and compared on the basis of deceased and living patients.

RESULTS

Median (interquartile range [IQR]) NEWS2 and LDT-EWS values of the 127 patients who died were found to be statistically significantly higher than those of the patients who survived (NEWS2: 5 [3-8] vs. 3 [1-5]; p < 0.001; LDT-EWS: 8 [7-10] vs. 6 [5-8]; p < 0.001). In the receiver operating characteristic curve analysis, the NEWS2, LDT-EWS, and NEWS2+LDT-EWS-formed by the sum of the two scoring systems-resulted in 0.717, 0.705, and 0.775 area under curve values, respectively.

CONCLUSIONS

The NEWS2 and LDT-EWS were found to be valuable for predicting in-hospital mortality in geriatric patients. The power of the NEWS2 to predict in-hospital mortality increased when used with the LDT-EWS.

Compliance with maternal sepsis guidelines in a tertiary hospital in the Netherlands

OBJECTIVES

Sepsis is a common cause of maternal mortality and morbidity. Early detection and rapid management are essential. In this study, we evaluate the compliance with the implemented maternity-specific Early Warning Score (EWS), Rapid Response Team (RRT) protocol and the Surviving Sepsis Campaign (SSC) Hour-1 Bundle in a tertiary hospital in the Netherlands.

METHODS

We performed a retrospective patient chart review from July 2019 to June 2020 at the Leiden University Medical Centre. We included women who received therapeutic antibiotics and were admitted for at least 24 hours.

RESULTS

We included 240 women: ten were admitted twice and one woman three times, comprising 252 admissions. A clinical diagnosis of sepsis was made in 22 women. The EWS was used in 29% (n = 73/252) of admissions. Recommendations on the follow-up of the EWS were carried out in 53% (n = 46/87). Compliance with the RRT protocol was highest for assessment by a medical doctor within 30 minutes (n = 98/117, 84%) and lowest for RRT involvement (n = 7/23, 30%). In women with sepsis, compliance with the SSC Bundle was highest for acquiring blood cultures (n = 19/22, 85%), while only 64% (n = 14/22) received antibiotics within 60 minutes of the sepsis diagnosis.

CONCLUSION

The adherence to the maternity-specific EWS and the SSC Hour-1 bundle was insufficient, even within this tertiary setting in a high-income country.

The Effect of Modified Early Warning Score (MEWS) and Nursing Guide Application on Postoperative Patient Outcomes: A Randomized Controlled Study

PURPOSE

The aim of this study is to determine the effect of nursing guide application (NGA) on patient outcomes in patients followed up according to the modified early warning score (MEWS) in the postoperative period.

DESIGN

A randomized controlled clinical trial.

METHODS

The sample of the study consisted of 252 patients who underwent surgical intervention under general anesthesia in a university hospital between July 29, 2022, and October 31, 2022.

FINDINGS

Results showed that the development of complications was less in the study group (SG) compared to the control group (CG) during anesthesia (P = .027), in the postanesthesia care unit (PACU) (P = .017), and in the clinic (P = .001). It was found that the duration of stay in PACU in the CG was significantly shorter than in the study group (P < .001), and as the duration of stay in PACU in CG decreased, the MEWS increased (r = -0.201, P = .024). We found that there were fewer patients transferred to the intensive care unit (ICU) after PACU (P = .007), the MEWS was lower, and the number of nursing interventions applied to patients was higher (P < .05).

CONCLUSIONS

In patients followed up according to MEWS, NGA had a positive effect on preventing the development of complications and shortening the intervention time for complications, decreasing ICU admission, decreasing MEWS and increasing the number of nursing interventions. Based on the results, it may be recommended to use MEWS+NGA in the early postoperative period as it positively affects patient outcomes.

Workload associated with manual assessment of vital signs as compared with continuous wireless monitoring

BACKGROUND

Vital sign monitoring is considered an essential aspect of clinical care in hospitals. In general wards, this relies on intermittent manual assessments performed by clinical staff at intervals of up to 12 h. In recent years, continuous monitoring of vital signs has been introduced to the clinic, with improved patient outcomes being one of several potential benefits. The aim of this study was to determine the workload difference between continuous monitoring and manual monitoring of vital signs as part of the National Early Warning Score (NEWS).

METHODS

Three wireless sensors continuously monitored blood pressure, heart rate, respiratory rate, and peripheral oxygen saturation in 20 patients admitted to the general hospital ward. The duration needed for equipment set-up and maintenance for continuous monitoring in a 24-h period was recorded and compared with the time spent on manual assessments and documentation of vital signs performed by clinical staff according to the NEWS.

RESULTS

The time used for continuous monitoring was 6.0 (IQR 3.2; 7.2) min per patient per day vs. 14 (9.7; 32) min per patient per day for the NEWS. Median difference in duration for monitoring of vital signs was 9.9 (95% CI 5.6; 21) min per patient per day between NEWS and continuous monitoring (p < .001). Time used for continuous monitoring in isolated patients was 6.6 (4.6; 12) min per patient per day as compared with 22 (9.7; 94) min per patient per day for NEWS.

CONCLUSION

The use of continuous monitoring was associated with a significant reduction in workload in terms of time for monitoring as compared with manual assessment of vital signs.

Surveillance of high-risk early postsurgical patients for real-time detection of complications using wireless monitoring (SHEPHERD study): results of a randomized multicenter stepped wedge cluster trial

Background

Vital signs measurements on the ward are performed intermittently. This could lead to failure to rapidly detect patients with deteriorating vital signs and worsens long-term outcome. The aim of this study was to test the hypothesis that continuous wireless monitoring of vital signs on the postsurgical ward improves patient outcome.

Methods

In this prospective, multicenter, stepped-wedge cluster randomized study, patients in the control group received standard monitoring. The intervention group received continuous wireless monitoring of heart rate, respiratory rate and temperature on top of standard care. Automated alerts indicating vital signs deviation from baseline were sent to ward nurses, triggering the calculation of a full early warning score followed. The primary outcome was the occurrence of new disability three months after surgery.

Results

The study was terminated early (at 57% inclusion) due to COVID-19 restrictions. Therefore, only descriptive statistics are presented. A total of 747 patients were enrolled in this study and eligible for statistical analyses, 517 patients in the control group and 230 patients in the intervention group, the latter only from one hospital. New disability at three months after surgery occurred in 43.7% in the control group and in 39.1% in the intervention group (absolute difference 4.6%).

Conclusion

This is the largest randomized controlled trial investigating continuous wireless monitoring in postoperative patients. While patients in the intervention group seemed to experience less (new) disability than patients in the control group, results remain inconclusive with regard to postoperative patient outcome due to premature study termination.

Clinical trial registration

ClinicalTrials.gov, ID: NCT02957825.

Use of Evidence-Based Vital Signs in Pediatric Early Warning Score to Predict Clinical Deterioration on Acute Care Units

The pediatric early warning score (PEWS) is a tool used to predict clinical deterioration. Referenced vital sign parameters are based on expert opinion but heart rate and respiratory rate percentiles in hospitalized children have been published. This retrospective case-control study of unplanned intensive care unit (ICU) transfers compares evidence-based vital signs (EBVS) effect on PEWS sensitivity and specificity, determines the impact of age categories on PEWS deterioration prediction, and evaluates whether EBVS PEWS is associated with need for invasive ICU supports. EBVS PEWS improved sensitivity (43%-71% vs 30%-63%) for unplanned transfers with slightly decreased specificity (88%-98% vs 93%-99%). Logistic regression analysis and odds ratios (ORs) demonstrated EBVS PEWS was associated with increased risk for ICU-specific supports (OR = 1.16, 95% confidence interval [CI] = 1.0-1.34, P = .0498). Evidence-based vital signs can improve PEWS sensitivity to identify unplanned ICU transfers and identify patients requiring ICU-specific interventions.

Development and Validation of a Machine Learning Algorithm Using Clinical Pages to Predict Imminent Clinical Deterioration

BACKGROUND

Early detection of clinical deterioration among hospitalized patients is a clinical priority for patient safety and quality of care. Current automated approaches for identifying these patients perform poorly at identifying imminent events.

OBJECTIVE

Develop a machine learning algorithm using pager messages sent between clinical team members to predict imminent clinical deterioration.

DESIGN

We conducted a large observational study using long short-term memory machine learning models on the content and frequency of clinical pages.

PARTICIPANTS

We included all hospitalizations between January 1, 2018 and December 31, 2020 at Vanderbilt University Medical Center that included at least one page message to physicians. Exclusion criteria included patients receiving palliative care, hospitalizations with a planned intensive care stay, and hospitalizations in the top 2% longest length of stay.

MAIN MEASURES

Model classification performance to identify in-hospital cardiac arrest, transfer to intensive care, or Rapid Response activation in the next 3-, 6-, and 12-hours. We compared model performance against three common early warning scores: Modified Early Warning Score, National Early Warning Score, and the Epic Deterioration Index.

KEY RESULTS

There were 87,783 patients (mean [SD] age 54.0 [18.8] years; 45,835 [52.2%] women) who experienced 136,778 hospitalizations. 6214 hospitalized patients experienced a deterioration event. The machine learning model accurately identified 62% of deterioration events within 3-hours prior to the event and 47% of events within 12-hours. Across each time horizon, the model surpassed performance of the best early warning score including area under the receiver operating characteristic curve at 6-hours (0.856 vs. 0.781), sensitivity at 6-hours (0.590 vs. 0.505), specificity at 6-hours (0.900 vs. 0.878), and F-score at 6-hours (0.291 vs. 0.220).

CONCLUSIONS

Machine learning applied to the content and frequency of clinical pages improves prediction of imminent deterioration. Using clinical pages to monitor patient acuity supports improved detection of imminent deterioration without requiring changes to clinical workflow or nursing documentation.

Developing an early warning system for detecting sepsis in patients with trauma

The purpose of this study was to analyse the risk factors for sepsis in patients with trauma and develop a new scoring system for predicting sepsis in patients with trauma based on these risk factors. This will provide a simple and effective early warning method for the rapid and accurate detection and evaluation of the probability of sepsis in patients with trauma to assist in planning timely clinical interventions. We undertook a retrospective analysis of the clinical data of 216 patients with trauma who were admitted to the emergency intensive care unit of the emergency medicine department of the Hebei Medical University Third Hospital, China, between November 2017 and October 2022. We conducted a preliminary screening of the relevant factors using univariate logistic regression analysis and included those factors with a p value of <0.075 in the multivariate logistic regression analysis, from which the risk factors were screened and assigned, and obtained a total score, which was the sepsis early warning score. The incidence of sepsis in patients in the intensive care unit with trauma was 36.9%, and the mortality rate due to sepsis was 19.4%. We found statistically significant differences in several factors for patients with sepsis. The risk factors for sepsis in patients with trauma were the activated partial thromboplastin time, the New Injury Severity Score, growth differentiation factor-15 levels, shock, mechanical ventilation and the Acute Physiology and Chronic Health Evaluation II score. The area under the receiver operating characteristic curve of the sepsis early warning score for predicting sepsis in patients with trauma was 0.725. When the cutoff value of the early warning score was set at 5.0 points, the sensitivity was 69.9% and the specificity was 60.3%. The incidence of sepsis in patients with trauma can be reduced by closely monitoring patients' hemodynamics, implementing adequate fluid resuscitation promptly and by early removal of the catheter to minimize the duration of unnecessary invasive mechanical ventilation. In this study, we found that the use of the sepsis early warning score helped in a more accurate and effective evaluation of the prognosis of patients with trauma.

Explainable hierarchical clustering for patient subtyping and risk prediction

We present a pipeline in which machine learning techniques are used to automatically identify and evaluate subtypes of hospital patients admitted between 2017 and 2021 in a large UK teaching hospital. Patient clusters are determined using routinely collected hospital data, such as those used in the UK's National Early Warning Score 2 (NEWS2). An iterative, hierarchical clustering process was used to identify the minimum set of relevant features for cluster separation. With the use of state-of-the-art explainability techniques, the identified subtypes are interpreted and assigned clinical meaning, illustrating their robustness. In parallel, clinicians assessed intracluster similarities and intercluster differences of the identified patient subtypes within the context of their clinical knowledge. For each cluster, outcome prediction models were trained and their forecasting ability was illustrated against the NEWS2 of the unclustered patient cohort. These preliminary results suggest that subtype models can outperform the established NEWS2 method, providing improved prediction of patient deterioration. By considering both the computational outputs and clinician-based explanations in patient subtyping, we aim to highlight the mutual benefit of combining machine learning techniques with clinical expertise.

Eleven years of experience in operating a pediatric rapid response system at a children's hospital in South Korea

BACKGROUND

Various rapid response systems have been developed to detect clinical deterioration in patients. Few studies have evaluated single-parameter systems in children compared to scoring systems. Therefore, in this study we evaluated a single-parameter system called the acute response system (ARS).

METHODS

This retrospective study was performed at a tertiary children's hospital. Patients under 18 years old admitted from January 2012 to August 2023 were enrolled. ARS parameters such as systolic blood pressure, heart rate, respiratory rate, oxygen saturation, and whether the ARS was activated were collected. We divided patients into two groups according to activation status and then compared the occurrence of critical events (cardiopulmonary resuscitation or unexpected intensive care unit admission). We evaluated the ability of ARS to predict critical events and calculated compliance. We also analyzed the correlation between each parameter that activates ARS and critical events.

RESULTS

The critical events prediction performance of ARS has a specificity of 98.5%, a sensitivity of 24.0%, a negative predictive value of 99.6%, and a positive predictive value of 8.1%. The compliance rate was 15.6%. Statistically significant increases in the risk of critical events were observed for all abnormal criteria except low heart rate. There was no significant difference in the incidence of critical events.

CONCLUSIONS

ARS, a single parameter system, had good specificity and negative predictive value for predicting critical events; however, sensitivity and positive predictive value were not good, and medical staff compliance was poor.

Performance of risk scores in patients with acute exacerbations of COPD

OBJECTIVE

Acute exacerbations of COPD (AECOPD) are common causes of hospitalization. Various scoring systems have been proposed to classify the risk of clinical deterioration or mortality in hospitalized patients with AECOPD. We sought to investigate whether clinical deterioration and mortality scores at admission can predict adverse events occurring during hospitalization and after discharge of patients with AECOPD.

METHODS

We performed a retrospective study of patients admitted with AECOPD. The National Early Warning Score 2 (NEWS2), the NEWS288-92%, the Dyspnea, Eosinopenia, Consolidation, Acidemia, and atrial Fibrillation (DECAF) score, and the modified DECAF (mDECAF) score were calculated at admission. We assessed the sensitivity, specificity, and overall performance of the scores for the following outcomes: in-hospital mortality; need for invasive mechanical ventilation or noninvasive ventilation (NIV); long hospital stays; hospital readmissions; and future AECOPD.

RESULTS

We included 119 patients admitted with AECOPD. The median age was 75 years, and 87.9% were male. The NEWS288-92% was associated with an 8.9% reduction in the number of individuals classified as requiring close, continuous observation, without an increased risk of death in the group of individuals classified as being low-risk patients. The NEWS288-92% and NEWS2 scores were found to be adequate in predicting the need for acute NIV and longer hospital stays. The DECAF and mDECAF scores were found to be better at predicting in-hospital mortality than the NEWS2 and NEWS288-92%.

CONCLUSIONS

The NEWS288-92% safely reduces the need for clinical monitoring in patients with AECOPD when compared with the NEWS2. The NEWS2 and NEWS288-92% appear to be good predictors of the length of hospital stay and need for NIV, but they do not replace the DECAF and mDECAF scores as predictors of mortality.

Nursing Training for Early Clinical Deterioration Risk Assessment: Protocol for an Implementation Study

BACKGROUND

During the hospitalization period, it is possible to observe considerable changes in the vital parameters of patients, which may require emergency interventions or intensive treatment. The alteration of signs and symptoms that lead to physiological instability that can worsen the clinical picture with progression to shock, respiratory failure, or cardiorespiratory arrest is currently defined as clinical deterioration. Identifying signs of clinical deterioration at an early stage can lead to substantial decreases in mortality rates, the need for emergency interventions, and unscheduled treatments in intensive care units. Identifying and appropriately referring patients who show signs of clinical deterioration can be facilitated by applying early warning systems that provide rapid responses. The nursing team is usually the first to identify clinical changes in patients. Although the literature demonstrates that early recognition of clinical deterioration is the key to early intervention and leads to better outcomes, we only sometimes pursue the most appropriate intervention.

OBJECTIVE

This study aims to implement and evaluate an evidence-based professional training program designed for nurses and coordinated by a nurse using the "just-in-time" methodology and the National Early Warning Score 2 (NEWS2) to assess the risk of early clinical deterioration and appropriate referral in inpatient units of a public university hospital in southeastern Brazil.

METHODS

This intervention protocol is structured according to the recommendations of the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) Declaration 2013. The type of training to be offered, "Just-in-Time Training," consists of a teaching modality that facilitates the delivery of a time-based and work-based education, with greater emphasis on providing on-the-job learning as needed. A qualitative stage will also be conducted through focus groups and interviews with nurses to verify the factors that influence the professional practice related to the early evaluation of the clinic. A script of previously tested questions will guide and standardize the different groups. The data will define the intervention's elements: the strategy, the type of training, the location, the teaching methodology, and the teaching material.

RESULTS

The study has received authorization from the ethics committee, and participants will be recruited in July 2023. Data collection should be completed in October of the same year. The results obtained at the end of this research will be shared with the participating nursing team through the presentation of reports. In addition, the research results will be submitted to scientific journals and presented at international scientific conferences.

CONCLUSIONS

This study will support nurses and possibly other clinicians to improve their approach to early recognition of clinical deterioration in patients.

TRIAL REGISTRATION

Brazilian Registry of Clinical Trials RBR-5hq9y3k; https://ensaiosclinicos.gov.br/rg/RBR-5hq9y3k.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/47293.

Modified Early Warning Score: Clinical Deterioration of Mexican Patients Hospitalized with COVID-19 and Chronic Disease

The objective was to evaluate the Modified Early Warning Score in patients hospitalized for COVID-19 plus chronic disease.

METHODS

Retrospective observational study, 430 hospitalized patients with COVID-19 and chronic disease. Instrument, Modified Early Warning Score (MEWS). Data analysis, with Cox and logistic regression, to predict survival and risk.

RESULTS

Of 430 patients, 58.6% survived, and 41.4% did not. The risk was: low 53.5%, medium 23.7%, and high 22.8%. The MEWS score was similar between survivors 3.02, p 0.373 (95% CI: -0.225-0.597) and non-survivors 3.20 (95% CI: -0.224-0.597). There is a linear relationship between MEWS and mortality risk R 0.920, ANOVA 0.000, constant 4.713, and coefficient 4.406. The Cox Regression p 0.011, with a risk of deterioration of 0.325, with a positive coefficient, the higher the risk, the higher the mortality, while the invasive mechanical ventilation coefficient was negative -0.757. By providing oxygen and ventilation, mortality is lower.

CONCLUSIONS

The predictive value of the modified early warning score in patients hospitalized for COVID-19 and chronic disease is not predictive with the MEWS scale. Additional assessment is required to prevent complications, especially when patients are assessed as low-risk.

Automated rapid response system activation-Impact on nurses' attitudes and perceptions towards recognising and responding to clinical deterioration: Mixed-methods study

AIM

To explore general ward nurses' attitudes and perceptions towards recognising and responding to clinical deterioration in a hospital with automated rapid response system activation.

BACKGROUND

There is growing interest in deploying automated clinical deterioration notification systems to reduce delayed or failed recognition and response to clinical deterioration of ward patients. However, little is known about its impact on ward nurses' perspectives and work patterns.

DESIGN

A mixed-methods study.

METHODS

Online survey of 168 registered nurses and individual interviews with 10 registered nurses in one acute hospital in Singapore. The study adhered to the STROBE checklist for cross-sectional studies and the COREQ guidelines for qualitative studies.

RESULTS

Many nurses (38.1%) rarely performed patient assessments or observations other than vital signs assessment to assess for early signs of clinical deterioration. About 30% were worried about being criticised for calling the primary team doctors. Four themes emerged from the qualitative analysis: automated rapid response system activation as a safety net, being more cautious with vital signs monitoring, the NEWS2 alone is inadequate, and ward nurses as the 'middleman' between the intensive care unit outreach nurse and primary team doctors.

CONCLUSIONS

Although nurses value the automated rapid response system activation as a safety net to minimise delays in accessing urgent critical care resources, it does not address the sociocultural barriers inherent in escalation of care. Although the automated system led nurses to be more cautious with vital signs monitoring, it does not encourage them to perform comprehensive patient assessments to detect early signs of deterioration.

RELEVANCE TO CLINICAL PRACTICE

Nurse education on assessing for clinical deterioration should focus on the use of broader patient assessment skills other than vital signs. Sociocultural barriers to escalation of care remain a key issue that needs to be addressed by hospital management.

NO PATIENT OR PUBLIC CONTRIBUTION

No patients, service users, care-givers or members of the public were involved in the study.

Continuous Remote Monitoring in Moderate and Severe COVID-19 Patients

Background COVID-19 steadily built up the pressure on healthcare systems worldwide, creating the need for novel methods to alleviate the burden. Continuous remote monitoring of vital parameters reduces morbidity and mortality in hospitals by providing real-time disease data that can be analyzed through web portals. It enables healthcare workers to identify which patients require prompt administration of healthcare. Patients remain under the purview of their doctors and can be notified early if there are any deteriorations in the parameters being monitored. Aims To evaluate the use of remote monitoring in moderate and severe COVID-19 patients and to correlate the Dozee Early Warning Score (DEWS) with severity and outcome in moderate and severe COVID-19 patients. Materials and methods We conducted a prospective study on adult (>18 years old) moderate and severe COVID-19 patients during the second wave of COVID-19. The vitals of the subjects were continuously monitored using Dozee, a contactless remote patient monitoring system enabled with DEWS that reflects the overall patient condition based on respiratory rate (RR), heart rate (HR), and oxygen saturation (SpO2). We assessed the correlation of DEWS with patients' clinical outcomes: deteriorated or recovered. Results Thirty-nine COVID-19 patients were recruited for the study, of whom 29 were discharged after recovery and 10 deteriorated and died. Respiratory rate trend, respiratory rate DEWS, SpO2 DEWS, and total DEWS showed a significant reduction in recovered patients, while the same parameters showed a significant increase followed by consistently high scores in patients who deteriorated and died due to the disease. Total DEWS was proportional to the risk of mortality in a patient. Conclusion We concluded that continuous vitals monitoring and the resulting DEWS in moderate and severe COVID-19 patients were indicators of their improvement or deterioration. DEWS uses continuous remote monitoring of routinely collected vitals (HR, RR, and SpO2) to serve as a predictor of patient outcome.

The reverse shock index multiplied by the Glasgow Coma Scale score can predict the need for initial resuscitation in patients suspected of sepsis

For patients suspected of sepsis, early recognition of the need for initial resuscitation is key in management. This study evaluated the ability of a modified shock index - the reverse shock index multiplied by the Glasgow Coma Scale score (rSIG) - to predict the need for initial resuscitation in patients with sepsis. This retrospective study involved adults with infection who were admitted to a Japanese tertiary care hospital from an emergency department between January and November 2020. The rSIG, modified Early Warning Score (MEWS), quick Sequential Organ Failure Assessment (qSOFA), and original shock index (SI) values were recorded using initial vital signs. The primary outcome was the area under the receiver-operating characteristic curve (AUROC) for the composite outcome consisting of vasopressor use, mechanical ventilation, and 72-h mortality. Secondary outcomes were the AUROCs for each component of the primary outcome and 28-day mortality. As a result, the primary outcome was met by 67 of the 724 patients (9%). The AUROC was significantly higher for the rSIG than for the other tools (rSIG 0.84 [0.78 - 0.88]; MEWS 0.78 [0.71 - 0.84]; qSOFA 0.72 [0.65 - 0.79]; SI 0.80 [0.74 - 0.85]). Compared with MEWS and qSOFA, the rSIG also had a higher AUROC for vasopressor use and mechanical ventilation, but not for 72-h mortality or in-hospital mortality. The rSIG could be a simple and reliable predictor of the need for initial resuscitation in patients suspected of sepsis.

Development and External Validation of the International Early Warning Score for Improved Age- and Sex-Adjusted In-Hospital Mortality Prediction in the Emergency Department

OBJECTIVES

Early Warning Scores (EWSs) have a great potential to assist clinical decision-making in the emergency department (ED). However, many EWS contain methodological weaknesses in development and validation and have poor predictive performance in older patients. The aim of this study was to develop and externally validate an International Early Warning Score (IEWS) based on a recalibrated National Early warning Score (NEWS) model including age and sex and evaluate its performance independently at arrival to the ED in three age categories (18-65, 66-80, > 80 yr).

DESIGN

International multicenter cohort study.

SETTING

Data was used from three Dutch EDs. External validation was performed in two EDs in Denmark.

PATIENTS

All consecutive ED patients greater than or equal to 18 years in the Netherlands Emergency department Evaluation Database (NEED) with at least two registered vital signs were included, resulting in 95,553 patients. For external validation, 14,809 patients were included from a Danish Multicenter Cohort (DMC).

MEASUREMENTS AND MAIN RESULTS

Model performance to predict in-hospital mortality was evaluated by discrimination, calibration curves and summary statistics, reclassification, and clinical usefulness by decision curve analysis. In-hospital mortality rate was 2.4% ( n = 2,314) in the NEED and 2.5% ( n = 365) in the DMC. Overall, the IEWS performed significantly better than NEWS with an area under the receiving operating characteristic of 0.89 (95% CIs, 0.89-0.90) versus 0.82 (0.82-0.83) in the NEED and 0.87 (0.85-0.88) versus 0.82 (0.80-0.84) at external validation. Calibration for NEWS predictions underestimated risk in older patients and overestimated risk in the youngest, while calibration improved for IEWS with a substantial reclassification of patients from low to high risk and a standardized net benefit of 5-15% in the relevant risk range for all age categories.

CONCLUSIONS

The IEWS substantially improves in-hospital mortality prediction for all ED patients greater than or equal to18 years.

Epic Sepsis Model Inpatient Predictive Analytic Tool: A Validation Study

Earlier treatment of sepsis leads to decreased mortality. Epic is an electronic medical record providing a predictive alert system for sepsis, the Epic Sepsis Model (ESM) Inpatient Predictive Analytic Tool. External validation of this system is lacking. This study aims to evaluate the ESM as a sepsis screening tool and determine whether an association exists between ESM alert system implementation and subsequent sepsis-related mortality.

DESIGN

Before-and-after study comparing baseline and intervention period.

SETTING

Urban 746-bed academic level 1 trauma center.

PATIENTS

Adult acute care inpatients discharged between January 12, 2018, and July 31, 2019.

INTERVENTIONS

During the before period, ESM was turned on in the background, but nurses and providers were not alerted of results. The system was then activated to alert providers of scores greater than or equal to 5, a set point determined using receiver operating characteristic curve analysis (area under the curve, 0.834; p < 0.001).

MEASUREMENTS AND MAIN RESULTS

Primary outcome was mortality during hospitalization; secondary outcomes were sepsis order set utilization, length of stay, and timing of administration of sepsis-appropriate antibiotics. Of the 11,512 inpatient encounters assessed by ESM, 10.2% (1,171) had sepsis based on diagnosis codes. As a screening test, the ESM had sensitivity, specificity, positive predictive value, and negative predictive value rates of 86.0%, 80.8%, 33.8%, and 98.11%, respectively. After ESM implementation, unadjusted mortality rates in patients with ESM score greater than or equal to 5 and who had not yet received sepsis-appropriate antibiotics declined from 24.3% to 15.9%; multivariable analysis yielded an odds ratio of sepsis-related mortality (95% CI) of 0.56 (0.39-0.80).

CONCLUSIONS

In this single-center before-and-after study, utilization of the ESM score as a screening test was associated with a 44% reduction in the odds of sepsis-related mortality. Due to wide utilization of Epic, this is a potentially promising tool to improve sepsis mortality in the United States. This study is hypothesis generating, and further work with more rigorous study design is needed.

Performance of early warning scoring systems regarding adverse events of unanticipated clinical deterioration in complementary and alternative medicine hospitals

PURPOSE

This study aimed to examine the performance of early warning scoring systems regarding adverse events of unanticipated clinical deterioration in complementary and alternative medicine hospitals.

METHODS

A medical record review of 500 patients from five-year patient data in two traditional Korean medicine hospitals was conducted. Unanticipated clinical deterioration events included unexpected in-hospital mortality, cardiac arrest, and unplanned transfers to acute-care conventional medicine hospitals. Scores of the Modified Early Warning Score (MEWS), National Early Warning Score (NEWS), and National Early Warning Score 2 (NEWS2) were calculated. Their performance was evaluated by calculating areas under the receiver-operating characteristic curve for the event occurrence. Multiple logistic regression analyses were performed to determine the factors associated with event occurrence.

RESULTS

The incidence of unanticipated clinical deterioration events was 1.1% (225/21101). The area under the curve of MEWS, NEWS, and NEWS2 was .68, .72, and .72 at 24 hours before the events, respectively. NEWS and NEWS2, with almost the same performance, were superior to MEWS (p=.009). After adjusting for other variables, patients at low-medium risk (OR=3.28; 95% CI=1.02-10.55) and those at medium and high risk (OR=25.03; 95% CI=2.78-225.46) on NEWS2 scores were more likely to experience unanticipated clinical deterioration than those at low risk. Other factors associated with the event occurrence included frailty risk scores, clinical worry scores, primary medical diagnosis, prescribed medicine administration, acupuncture treatment, and clinical department.

CONCLUSION

The three early warning scores demonstrated moderate-to-fair performance for clinical deterioration events. NEWS2 can be used for early identification of patients at high-risk of deterioration in complementary and alternative medicine hospitals. Additionally, patient, care, and system factors need to be considered to improve patient safety.

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.

Comparison of the Aotearoa New Zealand Early Warning Score and National Early Warning Score to predict adverse inpatient events in a vital sign dataset

Aotearoa New Zealand uses a single early warning score (EWS) across all public and private hospitals to detect adult inpatient physiological deterioration. This combines the aggregate weighted scoring of the UK National Early Warning Score with single parameter activation from Australian medical emergency team systems. We conducted a retrospective analysis of a large vital sign dataset to validate the predictive performance of the New Zealand EWS in discriminating between patients at risk of serious adverse events and compared this with the UK EWS. We also compared predictive performance for patients admitted under medical vs. surgical specialties. A total of 1,738,787 aggregate scores (13,910,296 individual vital signs) were obtained from 102,394 hospital admissions to six hospitals within the Canterbury District Health Board of New Zealand's South Island. Predictive performance of each scoring system was determined using area under the receiver operating characteristic curve. Analysis showed that the New Zealand EWS is equivalent to the UK EWS in predicting patients at risk of serious adverse events (cardiac arrest, death and/or unanticipated ICU admission). Area under the receiver operating characteristic curve for both EWSs for any adverse outcome was 0.874 (95%CI 0.871-0.878) and 0.874 (95%CI 0.870-0.877), respectively. Both EWSs showed superior predictive value for cardiac arrest and/or death in patients admitted under surgical rather than medical specialties. Our study is the first validation of the New Zealand EWS in predicting serious adverse events in a broad dataset and supports previous work showing the UK EWS has superior predictive performance in surgical rather than medical patients.

Continuous monitoring is superior to manual measurements in detecting vital sign deviations in patients with COVID-19

BACKGROUND

Patients admitted to the emergency care setting with COVID-19-infection can suffer from sudden clinical deterioration, but the extent of deviating vital signs in this group is still unclear. Wireless technology monitors patient vital signs continuously and might detect deviations earlier than intermittent measurements. The aim of this study was to determine frequency and duration of vital sign deviations using continuous monitoring compared to manual measurements. A secondary analysis was to compare deviations in patients admitted to ICU or having fatal outcome vs. those that were not.

METHODS

Two wireless sensors continuously monitored (CM) respiratory rate (RR), heart rate (HR), and peripheral arterial oxygen saturation (SpO₂ ). Frequency and duration of vital sign deviations were compared with point measurements performed by clinical staff according to regional guidelines, the National Early Warning Score (NEWS).

RESULTS

SpO₂  < 92% for more than 60 min was detected in 92% of the patients with CM vs. 40% with NEWS (p < .00001). RR > 24 breaths per minute for more than 5 min were detected in 70% with CM vs. 33% using NEWS (p = .0001). HR ≥ 111 for more than 60 min was seen in 51% with CM and 22% with NEWS (p = .0002). Patients admitted to ICU or having fatal outcome had longer durations of RR > 24 brpm (p = .01), RR > 21 brpm (p = .01), SpO₂  < 80% (p = .01), and SpO₂  < 85% (p = .02) compared to patients that were not.

CONCLUSION

Episodes of desaturation and tachypnea in hospitalized patients with COVID-19 infection are common and often not detected by routine measurements.

Early Warning Scores in Prehospital Care to Predict Major Adverse Cardiac Events in Acute Cardiovascular Disease

(1) Background: The Modified Sequential Organ Failure Assessment (mSOFA) is an Early Warning Score (EWS) that has proven to be useful in identifying patients at high risk of mortality in prehospital care. The main objective of this study was to evaluate the predictive validity of prehospital mSOFA in estimating 2- and 90-day mortality (all-cause) in patients with acute cardiovascular diseases (ACVD), and to compare this validity to that of four other widely-used EWS. (2) Methods: We conducted a prospective, observational, multicentric, ambulance-based study in adults with suspected ACVD who were transferred by ambulance to Emergency Departments (ED). The primary outcome was 2- and 90-day mortality (all-cause in- and out-hospital). The discriminative power of the predictive variable was assessed and evaluated by the area under the curve (AUC) of the receiver operating characteristic (ROC). (3) Results: A total of 1540 patients met the inclusion criteria. The 2- and 90-day mortality rates were 5.3% and 12.7%, respectively. The mSOFA showed the highest AUC of all the evaluated scores for both 2- and 90-day mortality, AUC = 0.943 (0.917-0.968) and AUC = 0.874 (0.847-0.902), respectively. (4) Conclusions: The mSOFA is a quick and easy-to-use EWS with an excellent ability to predict mortality at both 2 and 90 days in patients treated for ACVD, and has proved to be superior to the other EWS evaluated in this study.

ChroniSense National Early Warning Score Study: Comparison Study of a Wearable Wrist Device to Measure Vital Signs in Patients Who Are Hospitalized

BACKGROUND

Wearable devices could be used to continuously monitor vital signs in patients who are hospitalized, but they require validation.

OBJECTIVE

This study aimed to evaluate the clinical validity of the prototype of a semiautomated wearable wrist device (ChroniSense Polso) to measure vital signs and provide National Early Warning Scores (NEWSs).

METHODS

Vital signs and NEWSs measured using the wearable device were compared with standard, nurse-lead manual measurements. We enrolled adult patients (aged ≥18 years) who required vital sign measurements at least every 6 hours in a UK teaching district general hospital. Wearable device measurements were not used for clinical decision-making. The primary outcome was the agreement on the individual National Early Warning parameter scores and vital sign measurements: respiratory rate, oxygen saturation, body temperature, systolic blood pressure, and heart rate. Secondary outcomes were the agreement on the total NEWS, incidence of adverse events, and user acceptance. To compare the wearable device measurements with the standard measurements, we analyzed vital sign measurements by limits of agreement (Bland-Altman analysis) and conducted κ agreement analyses for NEWSs. A user experience survey was conducted with questions about comfort of the wrist device, safety, preference, and use.

RESULTS

We included 132 participants in the study, with a mean age of 62 (SD 15.81) years; most of them were men (102/132, 77.3%). The highest weighted κ values were found for heart rate (0.69, 95% CI 0.57-0.81 for all 385 measurements) and systolic blood pressure (0.39, 95% CI 0.30-0.47 for all 339 measurements). Weighted κ values were low for respiration rate (0.03, 95% CI -0.001 to 0.05 for all 445 measurements), temperature (0, 95% CI 0-0 for all 231 measurements), and oxygen saturation (-0.11, 95% CI -0.20 to -0.02 for all 187 measurements). Weighted κ using Cicchetti-Allison weights showed κ of 0.20 (95% CI 0.03-0.38) when using all 56 total NEWSs. The user acceptance survey found that approximately half (45/91, 49%) of the participants found it comfortable to wear the device and liked its appearance. Most (85/92, 92%) of them said that they would wear the device during their next hospital visit, and many (74/92, 80%) said that they would recommend it to others.

CONCLUSIONS

This study shows the promising use of a prototype wearable device to measure vital signs in a hospital setting. Agreement between the standard measurements and wearable device measurements was acceptable for systolic blood pressure and heart rate, but needed to be improved for respiration rate, temperature, and oxygen saturation. Future studies need to improve the clinical validity of this wearable device. Large studies are required to assess clinical outcomes and cost-effectiveness of wearable devices for vital sign measurement.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1136/bmjopen-2018-028219.

How nurses use National Early Warning Score and Individual Early Warning Score to support their patient risk assessment practice: A fieldwork study

AIM

To explore and describe how the National Early Warning Score (NEWS) and Individual Early Warning Score (I-EWS) are used and how they support nurses' patient risk assessment practice.

DESIGN

A qualitative observational fieldwork study drawing on ethnographical principles was performed in six hospitals in two regions of Denmark in 2019.

METHODS

Data were generated from participant observations and informal interviews with 32 nurses across 15 different wards in the hospitals. A total of 180 h of participant observation was performed. The observations lasted between 1.5 and 8 h and were conducted during day or evening shifts.

RESULTS

NEWS and I-EWS supported nurses' observations of patients, providing useful knowledge for planning patient care, and prompting critical thinking. However, the risk assessment task was sometimes delegated to less experienced staff members, such as nursing students and healthcare assistants. The Early Warning Score (EWS) systems were often adapted by nurses according to contextual aspects, such as the culture of the speciality in which the nurses worked and their levels of competency. In some situations, I-EWS had the effect of enhancing nurse autonomy and responsibility for decision-making in relation to patient care.

CONCLUSIONS

EWS systems support nurses' patient risk assessment practice, providing useful information. I-EWS makes it easier to factor the heterogeneity of patients and the clinical situation into the risk assessments. The delegation of risk assessment to other, less experienced staff members pose a risk to patient safety, which needs to be addressed in the ongoing debate regarding the shortage of nurses.

IMPACT

The findings of this study can help ward nurses, hospital managers and policymakers to develop and improve strategies for improved person-centred nursing care.

Continuous vital sign monitoring in patients after elective abdominal surgery: a retrospective study on clinical outcomes and costs

Aim: To assess changes in outcomes and costs upon implementation of continuous vital sign monitoring in postsurgical patients. Materials & methods: Retrospective analysis of clinical outcomes and in-hospital costs compared with a control period. Results: During the intervention period patients were less frequently admitted to the intensive care unit (ICU) (p = 0.004), had shorter length of stay (p < 0.001) and lower costs (p < 0.001). The intervention was associated with a lower odds of ICU admission (odds ratio: 0.422; p = 0.007) and ICU related costs (odds ratio: -662.4; p = 0.083). Conclusion: Continuous vital sign monitoring may have contributed to fewer ICU admissions and lower ICU costs in postsurgical patients.

The role of language barriers on efficacy of rapid response teams

OBJECTIVES

Rapid response (RR) systems are associated with decreased hospital mortality. Systemic biases and inequities can negatively impact RR outcomes. Language barriers between patients and providers are associated with worse outcomes, but it is unknown if language barriers are associated with RR outcomes.

METHODS

We analyzed all adult hospitalized patients who experienced a RR over one year (January 2020 to December 2020) at a tertiary care academic medical center. We used an objective scoring system to establish disease severity at the time of the event. We then compared disease severity and outcomes for patients who are primary language Spanish (PLS) and primary language English (PLE) using both univariable and multivariable analyses.

RESULTS

Of 1133 patients, 42 identified as PLS and 1091 as PLE. In multivariable analyses, PLS patients had significantly higher disease severity scores, as measured by deterioration index score (8.2, p = 0.021) at the time of their rapid responses. PLS patients also had 18.5% increase in length of stay (LOS) after RRs and this disparity was not mitigated when controlling for disease severity at the time of RRs. PLS was not a significant predictor for hospital mortality after RRs.

CONCLUSIONS

Our study found that PLS patients had increased disease severity at the time of RRs and increased LOS after RRs. However, the disparity in LOS was not mitigated when controlling for disease severity at the time of RRs. These findings suggest that language barriers may cause both delays in activation of RR systems, as well as the care provided during and after RRs.

Effect of Diurnal Variation of Heart Rate and Respiratory Rate on Activation of Rapid Response System and Clinical Outcome in Hospitalized Children

Heart rate and respiratory rate display circadian variation. Pediatric single-parameter rapid response system is activated when heart rate or respiratory rate deviate from age-specific criteria, though activation criteria do not differentiate between daytime and nighttime, and unnecessary activation has been reported due to nighttime bradycardia. We evaluated the relationship between rapid response system activation and the patient’s clinical outcome by separately applying the criteria to daytime and nighttime in patients < 18. The observation period was divided into daytime and nighttime (8:00−20:00, and 20:00 to 8:00), according to which measured heart rate and respiratory rate were divided and rapid response system activation criteria were applied. We classified lower nighttime than daytime values into the ‘decreased group’, and the higher ones into the ‘increased group’, to analyze their effect on cardiopulmonary resuscitation occurrence or intensive care unit transfer. Nighttime heart rate and respiratory rate were lower than the daytime ones in both groups (both p values < 0.001), with no significant association with cardiopulmonary resuscitation occurrence or intensive care unit transfer in either group. Heart rate and respiratory rate tend to be lower at nighttime; however, their effect on the patient’s clinical outcome is not significant.

Assessment of the disease severity in patients hospitalized for COVID-19 based on the National Early Warning Score (NEWS) using statistical and machine learning methods: An electronic health records database analysis

BACKGROUND

The coronavirus disease 2019 (COVID-19) was a cause of concern in the healthcare system and increased the need for disease severity indicators. However, they still vary in use to evaluate in-hospital outcomes and severity. The National Early Warning Score (NEWS) is routinely used to evaluate patient health status at the hospital. Further research is needed to ensure if NEWS can be a good instrument for an overall health status assessment with or without additional information like laboratory tests, intensive care needs, and history of chronic diseases.

OBJECTIVE

To evaluate if NEWS can be an indicator to measure COVID-19 patient status in-hospital.

METHODS

We used the fully anonymized Electronic Health Records (EHR) characterizing patients admitted to the hospital with COVID-19. Data was obtained from Vilnius University Hospital Santaros Klinikos EHR system (SANTA-HIS) from 01-03-2020 to 31-12-2022. The study sample included 3875 patients. We created several statistical and machine learning models for discrimination between in-hospital death/discharge for evaluation NEWS as a disease severity measure for COVID-19 patients. In these models, two variable sets were considered: median NEWS and its combination with clinical parameters and medians of laboratory test results. Assessment of models' performance was based on the scoring metrics: accuracy, sensitivity, specificity, area under the ROC curve (AUC), and F1-score.

RESULTS

Our analysis revealed that NEWS predictive ability for describing patient health status during the stay in the hospital can be increased by adding the patient's age at hospitalization, gender, clinical and laboratory variables (0.853 sensitivity, 0.992 specificity and F1-score - 0.859) in comparison with single NEWS (0.603, 0.995, 0.719, respectively). A comparison of different models showed that stepwise logistic regression was the best method for in-hospital mortality classification. Our findings suggest employing models like ours for advisory routine usage.

CONCLUSION

Our model demonstrated incremental value for COVID-19 patient's status evaluation.

Nurses' and Physicians' Ideas on Initiatives for Effective Use of the Early Warning Score: A Participatory Study

Ineffective use of the early warning score (EWS) can compromise recognition and response to patients' deteriorating condition. This study explores nurses' and physicians' ideas on initiatives for supporting the effective use of the EWS in a hospital setting. Participatory workshops were conducted, and data were analyzed using content analysis. Ideas generated for integrating new functions into the EWS protocol to facilitate effective use are described. Also recommended was that all users receive training and an update on how to use the EWS score to support acceptance and confidence using the protocol and thereby increase adherence to the EWS. Further research is needed on the efficiency of incorporating nurses' clinical judgment in the EWS protocol within different specialties and the effect on adherence to the tool.

Clinical indicators of acute deterioration in persons who reside in residential aged care facilities: A rapid review

PURPOSE

To identify the clinical indicators of acute deterioration in residents and the factors that influence residential aged care facility staff's identification of these.

DESIGN

Rapid review and narrative synthesis.

METHODS

The WHO and Cochrane Rapid Review Methods Group recommendations guided the review processes. CINAHL, Medline, PubMed, and the Cochrane Library were searched from 2000 to January 2022. Data related to clinical indicators of deterioration were categorized using the Airway, Breathing, Circulation, Disability, Exposure assessment framework, and factors influencing detection were grouped as consumer (resident and family), aged care workforce, and organization factors.

RESULTS

Twenty publications were included of which 14 informed clinical indicators; nine highlighted factors that influence staff's identification of these and three informed both. Included article were collectively below moderate quality. Most clinical indicators were grouped into the 'Disability' category with altered level of consciousness, behavior, and pain identified most frequently. Few studies reported more traditional indicators of deterioration used in the general population - changes in vital signs. The most common factors influencing the detection of acute deterioration were organizational and workforce-related including resource, knowledge, and confidence deficits.

CONCLUSION

Findings suggest subtle changes in resident's health status, rather than focusing primarily on physiologic parameters used in early warning tools for acute care settings, should be recognized and considered in the design of early warning tools for residential aged care facilities.

CLINICAL RELEVANCE

Early warning tools sensitive to the unique needs of residents and support for aged care facility staff are recommended to improve the capacity of aged care facility care staff to identify and manage acute deterioration early to avoid hospitalization.

A qualitative study of barriers and facilitators to pediatric early warning score (PEWS) implementation in a resource-limited setting

Objectives

Globally, pediatric hospitals have implemented Pediatric Early Warning Scores (PEWS) to standardize escalation of care and improve detection of clinical deterioration in pediatric patients. This study aims to utilize qualitative methodology to understand barriers and facilitators of PEWS implementation at Philippine Children's Medical Center (PCMC), a tertiary care hospital in Manila, Philippines.

Methods

Semi-structured interviews querying current processes for clinical monitoring, Pediatric Intensive Care Unit (PICU) transfer, and clinician attitudes towards PEWS implementation were audio recorded. In-person hospital observations served to triangulate interview findings. The Systems Engineering Initiative for Patient Safety (SEIPS) framework guided content coding of interviews to characterize work systems, processes, and outcomes related to patient monitoring and care escalation. Thematic coding was performed using Dedoose software. This model allowed identification of barriers and facilitators to PEWS implementation.

Results

Barriers within PCMC workflow included: limited bed capacity, delay in referral, patient overflow, limited monitoring equipment, and high patient to staff ratio. Facilitators of PEWS implementation included support for PEWS adaptation and existence of systems for vital sign monitoring. Observations by study personnel confirmed validity of themes.

Conclusion

Utilizing qualitative methodology to understand barriers and facilitators to PEWS in specific contexts can guide implementation at resource-limited hospitals.

Mid-Regional Pro-Adrenomedullin in Combination With Pediatric Early Warning Scores for Risk Stratification of Febrile Children Presenting to the Emergency Department: Secondary Analysis of a Nonprespecified United Kingdom Cohort Study

OBJECTIVES

Current sepsis guidelines do not provide good risk stratification of subgroups in whom prompt IV antibiotics and fluid resuscitation might of benefit. We evaluated the utility of mid-regional pro-adrenomedullin (MR-proADM) in identification of patient subgroups at risk of requiring PICU or high-dependency unit (HDU) admission or fluid resuscitation.

DESIGN

Secondary, nonprespecified analysis of prospectively collected dataset.

SETTING

Pediatric Emergency Department in a United Kingdom tertiary center.

PATIENTS

Children less than 16 years old presenting with fever and clinical indication for venous blood sampling ( n = 1,183).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Primary outcome measures were PICU/HDU admission or administration of fluid resuscitation, with a secondary outcome of definite or probable bacterial infection. Biomarkers were measured on stored plasma samples and children phenotyped into bacterial and viral groups using a previously published algorithm. Of the 1,183 cases, 146 children (12.3%) required fluids, 48 (4.1%) were admitted to the PICU/HDU, and 244 (20.6%) had definite or probable bacterial infection. Area under the receiver operating characteristic (AUC) was used to assess performance. MR-proADM better predicted fluid resuscitation (AUC, 0.73; 95% CI, 0.67-0.78), than both procalcitonin (AUC, 0.65; 95% CI, 0.59-0.71) and Pediatric Early Warning Score (PEWS: AUC, 0.62; 95% CI, 0.56-0.67). PEWS alone showed good accuracy for PICU/HDU admission 0.83 (0.78-0.89). Patient subgroups with high MR-proADM (≥ 0.7 nmol/L) and high procalcitonin (≥ 0.5 ng/mL) had increased association with PICU/HDU admission, fluid resuscitation, and bacterial infection compared with subgroups with low MR-proADM (< 0.7 nmol/L). For children with procalcitonin less than 0.5 ng/mL, high MR-proADM improved stratification for fluid resuscitation only.

CONCLUSIONS

High MR-proADM and high procalcitonin were associated with increased likelihood of subsequent disease progression. Incorporating MR-proADM into clinical risk stratification may be useful in clinician decision-making regarding initiation of IV antibiotics, fluid resuscitation, and escalation to PICU/HDU admission.

Evaluation of the utility of NEWS2 during the COVID-19 pandemic

The emergence of the COVID-19 pandemic resulted in a dramatic increase in acutely ill patients presenting to hospitals with life-threatening acute respiratory disease. There was an immediate need for effective triage systems to facilitate clinical decision making. This review assesses the performance of the National Early Warning Score 2 (NEWS2) in two contexts. Firstly, the ability to detect acute illness severity and likely clinical deterioration in patients presenting to hospitals with COVID-19. Secondly, the use of NEWS2 in the longitudinal monitoring to detect acute clinical deterioration in hospitalised patients with COVID-19. NEWS2 appeared to be at least comparable and, often, superior to other scoring systems (such as qSOFA and CURB-65), and provided an earlier alert of deterioration. A NEWS2 of 5 had high short-term sensitivity within and was unlikely to miss patients with COVID-19 who go on to deteriorate, but this comes with moderate specificity. However, the specificity of these systems is likely underestimated because preventing deterioration is their purpose. NEWS2 is an adjunct to clinical decision making and has served that purpose during the COVID-19 pandemic, playing an important role in communicating illness severity, clinical deterioration, triaging patients to appropriate levels of care and prompting completion of treatment escalation plans for those with high scores and at imminent risk of deterioration.

National Survey: How Do We Approach the Patient at Risk of Clinical Deterioration outside the ICU in the Spanish Context?

BACKGROUND

Anticipating and avoiding preventable intrahospital cardiac arrest and clinical deterioration are important priorities for international healthcare systems and institutions. One of the internationally followed strategies to improve this matter is the introduction of the Rapid Response Systems (RRS). Although there is vast evidence from the international community, the evidence reported in a Spanish context is scarce.

METHODS

A nationwide cross-sectional research consisting of a voluntary 31-question online survey was performed. The Spanish Society of Intensive, Critical and Coronary Care Medicine (SEMICYUC) supported the research.

RESULTS

We received 62 fully completed surveys distributed within 13 of the 17 regions and two autonomous cities of Spain. Thirty-two of the participants had an established Rapid Response Team (RRT). Common frequency on measuring vital signs was at least once per shift but other frequencies were contemplated (48.4%), usually based on professional criteria (69.4%), as only 12 (19.4%) centers used Early Warning Scores (EWS) or automated alarms on abnormal parameters. In the sample, doctors, nurses (55%), and other healthcare professionals (39%) could activate the RRT via telephone, but only 11.3% of the sample enacted this at early signs of deterioration. The responders on the RRT are the Intensive Care Unit (ICU), doctors, and nurses, who are available 24/7 most of the time. Concerning the education and training of general ward staff and RRT members, this varies from basic to advanced and specific-specialized level, simulating a growing educational methodology among participants. A great number of participants have emergency resuscitation equipment (drugs, airway adjuncts, and defibrillators) in their general wards. In terms of quality improvement, only half of the sample registered RRT activity indicators. In terms of the use of communication and teamwork techniques, the most used is clinical debriefing in 29 centers.

CONCLUSIONS

In terms of the concept of RRS, we found in our context that we are in the early stages of the establishment process, as it is not yet a generalized concept in most of our hospitals. The centers that have it are in still in the process of maturing the system and adapting themselves to our context.

The Clinical Implementation of NEWS, SOFA, and CALL Scores in Predicting the In-Hospital Outcome of Severe or Critical COVID-19 Patients

OBJECTIVE

To date, there is no specific validated coronavirus disease 2019 score to assess the disease severity. This study aimed to evaluate the performance of the National Early Warning Score, Sequential Organ Failure Assessment, and Comorbidity-Age-Lymphocyte count-Lactate dehydrogenase scores in predicting the in-hospital outcome of critical or severe coronavirus disease 2019 patients.

MATERIALS AND METHODS

Single-centered analytical study was carried out in the coronavirus disease 2019 high dependency unit from April to August 2020. National Early Warning Score, Sequential Organ Failure Assessment, and Comorbidity-Age-Lymphocyte count-Lactate dehydrogenase scores were calculated for each critical to severely ill coronavirus disease 2019 patient. The diagnostic accuracy of these 3 scores in determining the in-hospital outcome of coronavirus disease 2019 patients was assessed by area under the receiver operating characteristic curve. The cut-off value of each score along with sensitivity, specificity, and positive and negative likelihood ratio were calculated by Youden index. Predictors of outcome in coronavirus disease 2019 patients were analyzed by Cox-regression analysis.

RESULTS

The area under the curve was highest for the Comorbidity-Age-Lymphocyte count-Lactate dehydrogenase score (area under the curve=0.85) while the Sequential Organ Failure Assessment score had an area under the curve of 0.72. The cut-off values for National Early Warning Score score was 8 (sensitivity=72.34%, specificity=76.10%), Sequential Organ Failure Assessment score was 3 (sensitivity=68.97%, specificity=67.42%), and Comorbidity-Age-Lymphocyte count-Lactate dehydrogenase score was 8 (sensitivity=88.89%, specificity=66.67%). The pairwise comparison showed that the difference between the area under the curve of these 3 scores was statistically insignificant (P > .05). The rate of mortality and invasive ventilation was significantly high in groups with high National Early Warning Score, Sequential Organ Failure Assessment, and Comorbidity-Age-Lymphocyte count-Lactate dehydrogenase scores (P > .0001). These 3 scores, age, low platelets, and high troponin-T levels were found to be statistically significant predictors of outcome Conclusion:Comorbidity-Age-Lymphocyte count-Lactate dehydrogenase score had a good area under the curve, the highest sensitivity of its cut-off value, required only 4 parameters, and is easy to calculate so it may be a better tool among the 3 scores in outcome prediction for coronavirus disease 2019 patients.

What is the role of prognostic indexes in COVID-19 patients with diabetes mellitus? Data of patients from Turkey

Aim: We aimed to determine the prognostic performance of the Glasgow Prognostic Score (GPS), systemic immune-inflammation index and early warning score (the 'ANDC' system) in patients with diabetes mellitus who had COVID-19. Patients & methods: Patients were divided into two groups: with and without diabetes mellitus. Results: In the diabetic patient group, the rates of in-hospital mortality, intensive care unit hospitalization and corticosteroid treatment were higher compared with the nondiabetic patient group (p < 0.05). A GPS of 2 was useful for predicting in-hospital mortality in diabetic patients (p < 0.05). The ANDC score was significantly higher in diabetic patients (p < 0.05) and in diabetic patients with mortality and those who needed ICU hospitalization (p < 0.05). Conclusion: The presence of a GPS of 2 at the time of admission and a high ANDC value were associated with poor prognosis in diabetic COVID-19 patients.

Optimized simplified pediatric diabetes severity warning system for the early identification of diabetic ketoacidosis in children

OBJECTIVE

Diabetic ketoacidosis (DKA) is the leading cause of mortality in children with type 1 diabetes. Diagnosis of DKA is difficult in resource-limited areas owing to the unavailability of blood gas test, the gold standard for DKA diagnosis. The Simplified Pediatric Diabetes Severity Warning System (SPDSWS) has been developed to identify high-risk DKA patients with limited resources in China. Here we optimized and validated this system.

METHODS

This study included 835 children admitted between January 2011 and June 2020 with the principal diagnosis of type 1 diabetes. Data were collected based on demographic and clinical characteristics. DKA and its severity were defined according to the criteria of ISPAD. SPDSWS was optimized based on logistic regression analyses and then was validated in a validation cohort.

RESULTS

The 20-point optimized SPDSWS included strong positive urine ketone, young age, dehydration, fatigue, anorexia, vomiting, abdominal pain, abnormal pulse, and high blood glucose. The optimized SPDSWS predicted DKA with an AUC value of 0.882 in the derivation cohort. When the cut-point score ≥7 was used, the sensitivity and specificity were 75.5% and 86.0%, respectively, in the derivation cohort and were 90.0% and 85.8%, respectively, in the validation cohort. The optimized SPDSWS also predicted the moderate/severe DKA with an AUC value of 0.911 in the derivation cohort and 0.937 in the validation cohort. A score > 11 was associated with an extremely high incidence of DKA.

CONCLUSIONS

The optimized SPDSWS could assist health care practitioners in underdeveloped remote areas to identify the children at high risk of DKA as early as on admission.

Continuous monitoring of vital sign abnormalities; association to clinical complications in 500 postoperative patients

Background

Patients undergoing major surgery are at risk of complications, so‐called serious adverse events (SAE). Continuous monitoring may detect deteriorating patients by recording abnormal vital signs. We aimed to assess the association between abnormal vital signs inspired by Early Warning Score thresholds and subsequent SAEs in patients undergoing major abdominal surgery.

Methods

Prospective observational cohort study continuously monitoring heart rate, respiratory rate, peripheral oxygen saturation, and blood pressure for up to 96 h in 500 postoperative patients admitted to the general ward. Exposure variables were vital sign abnormalities, primary outcome was any serious adverse event occurring within 30 postoperative days. The primary analysis investigated the association between exposure variables per 24 h and subsequent serious adverse events.

Results

Serious adverse events occurred in 37% of patients, with 38% occurring during monitoring. Among patients with SAE during monitoring, the median duration of vital sign abnormalities was 272 min (IQR 110–447), compared to 259 min (IQR 153–394) in patients with SAE after monitoring and 261 min (IQR 132–468) in the patients without any SAE (p = .62 for all three group comparisons). Episodes of heart rate ≥110 bpm occurred in 16%, 7.1%, and 3.9% of patients in the time before SAE during monitoring, after monitoring, and without SAE, respectively (p < .002). Patients with SAE after monitoring experienced more episodes of hypotension ≤90 mm Hg/24 h (p = .001).

Conclusion

Overall duration of vital sign abnormalities at current thresholds were not significantly associated with subsequent serious adverse events, but more patients with tachycardia and hypotension had subsequent serious adverse events.

Trial registration

Clinicaltrials.gov, identifier NCT03491137.

Abstract No.: ABS2092: Study of perioperative modified early obstetric warning scores among pregnancy Induced hypertensive patients posted for caesarean deliveries

Background & Aims:

This study was aimed at identifying the usefulness of Modified Early Obstetric Warning Score (MEOWS) in predicting perioperative maternal outcome in patients with pregnancy induced hypertension (PIH) presenting for caesarean delivery (CD).

Methods:

A prospective observational study was conducted in a tertiary hospital in New Delhi, after approval by the institutional ethics committee. Data was collected using a predesigned proforma just before and 24 hours after CD, based on which the preoperative and postoperative MEOWS were determined. The mean of preoperative and postoperative MEOWS was taken as perioperative MEOWS. Sensitivity, specificity, positive and negative predictive value were derived and ROC analysis was done to find the discriminating power of MEOWS to predict the maternal outcome.

Results:

A total of 106 patients with PIH were analysed. A direct linear relationship was noted between increasing mean perioperative MEOWS and poor maternal outcome. A mean perioperative MEOWS ≥ 4.25 predicted maternal morbidity and mortality with a sensitivity of 70%, specificity of 91.86 %, positive predictive value of 66.67%, negative predictive value of 92.94 % and an accuracy of 87.74%.

Conclusion:

Our study suggested that MEOWS is a useful tool for predicting the maternal outcome in parturients with PIH presenting for CD.

Family-Assisted Severity of Illness Monitoring for Hospitalized Children in Low-Resource Settings-A Two-Arm Interventional Feasibility Study

INTRODUCTION

Pediatric mortality remains unacceptably high in many low-resource settings, with inpatient deaths often associated with delayed recognition of clinical deterioration. The Family-Assisted Severe Febrile Illness ThERapy (FASTER) tool has been developed for caregivers to assist in monitoring their hospitalized children and alert clinicians. This study evaluates feasibility of implementation by caregivers and clinicians.

METHODS

Randomized controlled feasibility study at Kenyatta National Hospital, Kenya. Children hospitalized with acute febrile illness with caregivers at the bedside for 24 h were enrolled. Caregivers were trained using the FASTER tool. The primary outcome was the frequency of clinician reassessments between intervention (FASTER) and standard care arms. Poisson regression with random intercept for grouping by patient was used, adjusting for admission pediatric early warning score, age, gender. Secondary outcomes included survey assessments of clinician and caregiver experiences with FASTER.

RESULTS

One hundred and fifty patient/caregiver pairs were enrolled, 139 included in the analysis, 74 in the intervention, 65 in the control arm. Patients' median age was 0.9 (range 0.2-10) and 1.1 years (range 0.2-12) in intervention vs. control arms. The most common diagnoses were pneumonia (80[58%]), meningitis (58[38%]) and malaria (34 [24%]). 134 (96%) caregivers were patients' mothers. Clinician visits/hour increased with patients' illness severity in both arms, but without difference in frequency between arms (point estimate for difference -0.9%, p = 0.97). Of the 16 deaths, 8 (four/arm) occurred within 2 days of enrollment. Forty clinicians were surveyed, 33 (82%) reporting that FASTER could improve outcomes of very sick children in low-resource settings; 26 (65%) rating caregivers as able to adequately capture patients' severity of illness. Of 70 caregivers surveyed, 63 (90%) reported that FASTER training was easy to understand; all (100%) agreed that the intervention would improve care of hospitalized children and help identify sick children in their community.

DISCUSSION

We observed no difference in recorded frequency of clinician visits with FASTER monitoring. However, the tool was rated positively by caregivers and clinicians., Implementation appears feasible but requires optimization. These feasibility data may inform a larger trial powered to measure morbidity and mortality outcomes to determine the utility of FASTER in detecting and responding to clinical deterioration in low-resource settings.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, identifier: NCT03513861.

Using an early warning score for nurse shift patient handover: Before-and-after study

PURPOSE

This study aimed to examine the impact of using an early warning score for shift patient handover on nurse and patient outcomes.

METHODS

A before-and-after study was conducted with nurses and patients in three general wards in a tertiary teaching hospital. A short-time nurse education on the National Early Warning Score 2 and the use of a checklist for score calculation were performed from June 4, 2019 to June 30, 2019. Outcomes of nurse response (safety competency, handover quality, teamwork, safety climate, and documentation of vital signs and clinical concerns), patient response (deterioration occurrence post-admission, hospitalization length, and discharge status), and adverse events (mortality, cardiopulmonary arrest, and unplanned intensive care unit admission) were measured using questionnaires and medical record reviews. Data from 89 nurses and 388 patients were analyzed.

RESULTS

Regarding nurse outcomes, handover quality (p <.001), teamwork (p = .004), safety climate (p = .018), and recordings of vital signs (p = .047) and clinical concerns (p = .008) increased after early warning score use. However, no significant change in the safety competency scores was observed. Regarding patient outcomes, there were no significant changes in the occurrence of deterioration, hospitalization length, discharge status, and occurrence of adverse events between pre-and-post intervention.

CONCLUSION

Despite no significant changes in patient outcomes, using a simple, evidence-based early warning score for patient handover enhanced socio-cultural factors for patient safety, with improved patient monitoring. The findings provide evidence that supports the active implementation of an early warning score to improve patient safety.

Associations of Clinical Characteristics and Intestinal Flora Imbalance in Stable Chronic Obstructive Pulmonary Disease (COPD) Patients and the Construction of an Early Warning Model

Objective

Establish a simple predictive model and scoring rule that is suitable for clinical medical staff in respiratory departments to assess intestinal flora imbalance occurrence in stable chronic obstructive pulmonary disease (COPD) patients.

Methods

From January 1, 2019, to December 31, 2020, COPD patients (195 cases) – who attended the Outpatient Department, Respiratory and Critical Care, Yixing Hospital, Jiangsu University – were enrolled in a cross-sectional study. Based on stool examination results, patients were divided into experimental (41 cases) and control (154 cases) groups. Single-factor and logistic regression analyses were performed with the baseline data of the two groups to obtain a new predictive model, which was further simplified.

Results

Five predictive factors composed the model: body mass index (BMI), serum albumin (ALB), Charlson’s Comorbidity Index (CCI), gastrointestinal symptom score (GSRs), and Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification. The model to predict intestinal flora imbalance in stable COPD patients had an area under the ROC curve (AUC) of 0.953 [95% CI (0.924, 0.982)]. After simplifying the scoring rules, the AUC was 0.767 [95% CI (0.676, 0.858)].

Conclusion

In the current study, we obtained a model that could effectively predict intestinal flora imbalance risk in stable COPD patients, being suitable for implementation in early treatments to improve the prognosis. Moreover, all indicators can be easily and simply obtained.

Predictive Value of an Age-Based Modification of the National Early Warning System in Hospitalized Patients With COVID-19

Background

Early recognition of high-risk patients with coronavirus disease 2019 (COVID-19) may improve outcomes. Although many predictive scoring systems exist, their complexity may limit utility in COVID-19. We assessed the prognostic performance of the National Early Warning Score (NEWS) and an age-based modification (NEWS+age) among hospitalized COVID-19 patients enrolled in a prospective, multicenter US Military Health System (MHS) observational cohort study.

Methods

Hospitalized adults with confirmed COVID-19 not requiring invasive mechanical ventilation at admission and with a baseline NEWS were included. We analyzed each scoring system's ability to predict key clinical outcomes, including progression to invasive ventilation or death, stratified by baseline severity (low [0-3], medium [4-6], and high [≥7]).

Results

Among 184 included participants, those with low baseline NEWS had significantly shorter hospitalizations (P < .01) and lower maximum illness severity (P < .001). Most (80.2%) of low NEWS vs 15.8% of high NEWS participants required no or at most low-flow oxygen supplementation. Low NEWS (≤3) had a negative predictive value of 97.2% for progression to invasive ventilation or death; a high NEWS (≥7) had high specificity (93.1%) but low positive predictive value (42.1%) for such progression. NEWS+age performed similarly to NEWS at predicting invasive ventilation or death (NEWS+age: area under the receiver operating characteristics curve [AUROC], 0.69; 95% CI, 0.65-0.73; NEWS: AUROC, 0.70; 95% CI, 0.66-0.75).

Conclusions

NEWS and NEWS+age showed similar test characteristics in an MHS COVID-19 cohort. Notably, low baseline scores had an excellent negative predictive value. Given their easy applicability, these scoring systems may be useful in resource-limited settings to identify COVID-19 patients who are unlikely to progress to critical illness.

Ambivalence in nurses' use of the early warning score: A focussed ethnography in a hospital setting

AIM

This study describes and explores the influences in registered nurses' use of early warning scores to support clinical decisions in a hospital setting.

DESIGN

A focussed ethnography allowed for the investigation of registered nurses' clinical practices in two wards in a Danish University Hospital. The study adhered to the 'Standards for Reporting Qualitative Research'.

METHODS

Participant observation and ethnographic interviews were conducted from March 2019 to August 2019. Ten registered nurses were observed and interviewed, and four physicians were interviewed. Data were analysed using LeCompte and Schensul's ethnographic analysis.

FINDINGS

The findings show the registered nurses' ambivalence towards the early warning score as a decision support system. Early warning score monitoring created a space for registered nurses to identify and initiate optimized care. However, when early warning scores contradicted registered nurses' clinical judgments, the latter were given priority in decisions even though elevated scores were not always accounted for in the situation. Moreover, we found unspoken expectations in the collaboration between physicians and registered nurses, which influenced the registered nurses' workloads and decisions regarding early warning scores.

CONCLUSION

Registered nurses' clinical judgment is essential to clinical decisions on the care and safety of patients if used combined with the early warning score. Interprofessional collaboration between registered nurses and physicians about the early warning score is challenged. Future research may address this challenge to explore how it should be operated as a collaboration tool.

IMPACT

The study adds knowledge to the evidence base of registered nurses' use of early warning score and the advantages and challenges associated with the use of these scoring systems. The study may provide valuable knowledge for the future development of policies or implementation strategies.