Performance of digital early warning score (NEWS2) in a cardiac specialist setting: retrospective cohort study

INTRODUCTION

Patients with cardiovascular diseases (CVD) are at significant risk of developing critical events. Early warning scores (EWS) are recommended for early recognition of deteriorating patients, yet their performance has been poorly studied in cardiac care settings. Standardisation and integrated National Early Warning Score 2 (NEWS2) in electronic health records (EHRs) are recommended yet have not been evaluated in specialist settings.

OBJECTIVE

To investigate the performance of digital NEWS2 in predicting critical events: death, intensive care unit (ICU) admission, cardiac arrest and medical emergencies.

METHODS

Retrospective cohort analysis.

STUDY COHORT

Individuals admitted with CVD diagnoses in 2020; including patients with COVID-19 due to conducting the study during the COVID-19 pandemic.

MEASURES

We tested the ability of NEWS2 in predicting the three critical outcomes from admission and within 24 hours before the event. NEWS2 was supplemented with age and cardiac rhythm and investigated. We used logistic regression analysis with the area under the receiver operating characteristic curve (AUC) to measure discrimination.

RESULTS

In 6143 patients admitted under cardiac specialties, NEWS2 showed moderate to low predictive accuracy of traditionally examined outcomes: death, ICU admission, cardiac arrest and medical emergency (AUC: 0.63, 0.56, 0.70 and 0.63, respectively). Supplemented NEWS2 with age showed no improvement while age and cardiac rhythm improved discrimination (AUC: 0.75, 0.84, 0.95 and 0.94, respectively). Improved performance was found of NEWS2 with age for COVID-19 cases (AUC: 0.96, 0.70, 0.87 and 0.88, respectively).

CONCLUSION

The performance of NEWS2 in patients with CVD is suboptimal, and fair for patients with CVD with COVID-19 to predict deterioration. Adjustment with variables that strongly correlate with critical cardiovascular outcomes, that is, cardiac rhythm, can improve the model. There is a need to define critical endpoints, engagement with clinical experts in development and further validation and implementation studies of EHR-integrated EWS in cardiac specialist settings.

The value of Pediatric Early Warning Score combined with SBAR in neonatal pneumonia nursing: A retrospective cohort study

To observe the effect of the Pediatric Early Warning System (PEWS) score combined with the situation-background-assessment-recommendation (SBAR) shift communication system in neonates with severe pneumonia in the pediatric intensive care unit. A total of 230 neonates admitted to the pediatric intensive care unit of our hospital from January 2018 to January 2021 were enrolled in this study. Participants were divided into an experimental group (110 patients, PEWS score combined with SBAR shift communication system) and a control group (120 patients, routine diagnosis and treatment and shift change). The early recognition rate, incidence of handover problems, and prognosis of critically ill children in the 2 groups were analyzed. Compared to the control group, the correct recognition rate of disease observation and early recognition rate of critically ill children in the experimental group were significantly higher, and the incidence of handover problems was significantly lower (P < .05). There was no significant difference in the incidence of asphyxia, heart failure, and toxic encephalopathy between both groups. The application of the PEWS score combined with the SBAR shift communication system can facilitate timely identification of deterioration of the condition of children with severe pneumonia, reduce handover problems, and help to implement interventions or rescue according to the changes in a patient's condition, which may be beneficial in improving the patient's prognosis.

The United Kingdom's National Early Warning Score: should everyone use it? A narrative review

This review critiques the benefits and drawbacks of the United Kingdom's National Early Warning Score (NEWS). Potential developments for the future are considered, as well as the role for NEWS in an emergency department (ED). The ability of NEWS to predict death within 24 h has been well validated in multiple clinical settings. It provides a common language for the assessment of clinical severity and can be used to trigger clinical interventions. However, it should not be used as the only metric for risk stratification as its ability to predict mortality beyond 24 h is not reliable and greatly influenced by other factors. The main drawbacks of NEWS are that measuring it requires trained professionals, it is time consuming and prone to calculation error. NEWS is recommended for use in acute UK hospitals, where it is linked to an escalation policy that reflects postgraduate experience; patients with lower NEWS are first assessed by a junior clinician and those with higher scores by more senior staff. This policy was based on expert opinion that did not consider workload implications. Nevertheless, its implementation has been shown to improve the efficient recording of vital signs. How and who should respond to different NEWS levels is uncertain and may vary according to the clinical setting and resources available. In the ED, simple triage scores which are quicker and easier to use may be more appropriate determinants of acuity. However, any alternative to NEWS should be easier and cheaper to use and provide evidence of outcome improvement.

Evaluation of Short-Term Mortality Prediction Using Initial Lactate and NEWS+L at Admission in COVID-19 Patients

OBJECTIVE

To predict the short-term mortality of the serum lactate level and the National Early Warning Score + lactate (NEWS+L) at the time of first admission to the emergency department in COVID-19 patients.

MATERIALS AND METHODS

This retrospective analysis was performed by screening the data of COVID-19 patients over a 6-month period (from January 15, 2021, to June 15, 2021). The demographic, comorbidities, vital parameters, and lactate values, as well as C- reactive protein (CRP), blood urea nitrogen (BUN), and 28-day mortality data were recorded.

RESULTS

A total of 70 patients were included in our study. The median (25^th - 75th percentile) age was 58 (47.3 - 73.5) years, and 33 (47.1%) patients were female. The mean lactate value was 1.6 (1.2 - 1.98) mmol/L, the mean NEWS was 6 (4-7.75), and the mean NEWS+L was 7.24 ± 2.54. Mortality occurred in 13 (18.2%) of the 70 patients at 28 days. Lactate, NEWS, and NEWS+L had no significant relationship with mortality. None of these parameters was able to predict mortality (P = 0.132, 0.670, and 0.994, respectively).

CONCLUSION

Our findings showed that the NEWS+L, NEWS, and lactate level could not predict short-term mortality in COVID-19 patients at the time of first admission.

Early plasma interferon-β levels as a predictive marker of COVID-19 severe clinical events in adult patients

We assessed relationships between early peripheral blood type I interferons (IFN) levels, clinical new early warning scores (NEWS), and clinical outcomes in hospitalized coronavirus disease-19 (COVID-19) adult patients. Early IFN-β levels were lower among patients who further required intensive care unit (ICU) admission than those measured in patients who did not require an ICU admission during severe acute respiratory syndrome coronavirus type 2 infection. IFN-β levels were inversely correlated with NEWS only in the subgroup of patients who further required ICU admission. To assess whether peripheral blood IFN-β levels could be a potential relevant biomarker to predict further need for ICU admission, we performed receiver operating characteristic (ROC) curve analyses that showed for all study patients an area under ROC curve of 0.77 growing to 0.86 (p = 0.003) when the analysis was restricted to a subset of patients with NEWS ≥5 at the time of hospital admission. Overall, our findings indicated that early peripheral blood IFN-β levels might be a relevant predictive marker of further need for an ICU admission in hospitalized COVID-19 adult patients, specifically when clinical score (NEWS) was graded as upper than 5 at the time of hospital admission.

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.

Emergency admissions' diagnoses and risk of in-hospital death according to the primary ICD-10 chapter assigned at discharge and the National Early Warning Score on admission

BACKGROUND

The relationship between diagnosis, illness severity, and mortality risk for unselected emergency admissions is poorly defined.

AIM

To define primary ICD-10 diagnostic chapters at discharge, admission illness severity by the National Early Warning Score, and in-hospital mortality for all unselected emergency admissions.

METHOD

Retrospective, observational, cohort study of 122,259 unselected, adult emergency admissions to Salford Royal Hospital between 2014 and 2022.

RESULTS

In-hospital mortality was 4.3% but most patients had an ICD-10 chapter associated with a lower risk of death. 60% of in-hospital deaths were in four chapters, infections, circulatory and respiratory diseases, or neoplasms. An admission NEWS ≥3 was associated with earlier mortality and an eight-fold increased risk of in-hospital mortality. 45% of all in-hospital deaths occurred in patients with an admission NEWS <3.

CONCLUSION

Mortality in emergency hospital admissions is associated with illness severity and four diagnostic chapters. NEWS should not be the only arbiter of hospital admission, as for certain diagnostic chapters the risk of death is high even if vital signs on presentation are normal.

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

OBJECTIVES

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

DESIGN

Retrospective cohort analyses of medical and surgical inpatient admissions.

SETTING

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

PARTICIPANTS

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

OUTCOME MEASURES

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

RESULTS

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

CONCLUSIONS

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

Predicting outcome in acute respiratory admissions using patterns of National Early Warning Scores

AIMS

Accurately predicting risk of patient deterioration is vital. Altered physiology in chronic disease affects the prognostic ability of vital signs based early warning score systems. We aimed to assess the potential of early warning score patterns to improve outcome prediction in patients with respiratory disease.

METHODS

Patients admitted under respiratory medicine between April 2015 and March 2017 had their National Early Warning Score 2 (NEWS2) calculated retrospectively from vital sign observations. Prediction models (including temporal patterns) were constructed and assessed for ability to predict death within 24 hours using all observations collected not meeting exclusion criteria. The best performing model was tested on a validation cohort of admissions from April 2017 to March 2019.

RESULTS

The derivation cohort comprised 7,487 admissions and the validation cohort included 8,739 admissions. Adding the maximum score in the preceding 24 hours to the most recently recorded NEWS2 improved area under the receiver operating characteristic curve for death in 24 hours from 0.888 (95% confidence interval (CI) 0.881-0.895) to 0.902 (95% CI 0.895-0.909) in the overall respiratory population.

CONCLUSION

Combining the most recently recorded score and the maximum NEWS2 score from the preceding 24 hours demonstrated greater accuracy than using snapshot NEWS2. This simple inclusion of a scoring pattern should be considered in future iterations of early warning scoring systems.

The Impact of a Machine Learning Early Warning Score on Hospital Mortality: A Multicenter Clinical Intervention Trial

OBJECTIVES

To determine the impact of a machine learning early warning risk score, electronic Cardiac Arrest Risk Triage (eCART), on mortality for elevated-risk adult inpatients.

DESIGN

A pragmatic pre- and post-intervention study conducted over the same 10-month period in 2 consecutive years.

SETTING

Four-hospital community-academic health system.

PATIENTS

All adult patients admitted to a medical-surgical ward.

INTERVENTIONS

During the baseline period, clinicians were blinded to eCART scores. During the intervention period, scores were presented to providers. Scores greater than or equal to 95th percentile were designated high risk prompting a physician assessment for ICU admission. Scores between the 89th and 95th percentiles were designated intermediate risk, triggering a nurse-directed workflow that included measuring vital signs every 2 hours and contacting a physician to review the treatment plan.

MEASUREMENTS AND MAIN RESULTS

The primary outcome was all-cause inhospital mortality. Secondary measures included vital sign assessment within 2 hours, ICU transfer rate, and time to ICU transfer. A total of 60,261 patients were admitted during the study period, of which 6,681 (11.1%) met inclusion criteria (baseline period n = 3,191, intervention period n = 3,490). The intervention period was associated with a significant decrease in hospital mortality for the main cohort (8.8% vs 13.9%; p < 0.0001; adjusted odds ratio [OR], 0.60 [95% CI, 0.52-0.71]). A significant decrease in mortality was also seen for the average-risk cohort not subject to the intervention (0.49% vs 0.26%; p < 0.05; adjusted OR, 0.53 [95% CI, 0.41-0.74]). In subgroup analysis, the benefit was seen in both high- (17.9% vs 23.9%; p = 0.001) and intermediate-risk (2.0% vs 4.0 %; p = 0.005) patients. The intervention period was also associated with a significant increase in ICU transfers, decrease in time to ICU transfer, and increase in vital sign reassessment within 2 hours.

CONCLUSIONS

Implementation of a machine learning early warning score-driven protocol was associated with reduced inhospital mortality, likely driven by earlier and more frequent ICU transfer.

Development and validation of an early warning score to identify COVID-19 in the emergency department based on routine laboratory tests: a multicentre case-control study

OBJECTIVES

Identifying patients with a possible SARS-CoV-2 infection in the emergency department (ED) is challenging. Symptoms differ, incidence rates vary and test capacity may be limited. As PCR-testing all ED patients is neither feasible nor effective in most centres, a rapid, objective, low-cost early warning score to triage ED patients for a possible infection is developed.

DESIGN

Case-control study.

SETTING

Secondary and tertiary hospitals in the Netherlands.

PARTICIPANTS

The study included patients presenting to the ED with venous blood sampling from July 2019 to July 2020 (n=10 417, 279 SARS-CoV-2-positive). The temporal validation cohort covered the period from July 2020 to October 2021 (n=14 080, 1093 SARS-CoV-2-positive). The external validation cohort consisted of patients presenting to the ED of three hospitals in the Netherlands (n=12 061, 652 SARS-CoV-2-positive).

PRIMARY OUTCOME MEASURES

The primary outcome was one or more positive SARS-CoV-2 PCR test results within 1 day prior to or 1 week after ED presentation.

RESULTS

The resulting 'CoLab-score' consists of 10 routine laboratory measurements and age. The score showed good discriminative ability (AUC: 0.930, 95% CI 0.909 to 0.945). The lowest CoLab-score had high sensitivity for COVID-19 (0.984, 95% CI 0.970 to 0.991; specificity: 0.411, 95% CI 0.285 to 0.520). Conversely, the highest score had high specificity (0.978, 95% CI 0.973 to 0.983; sensitivity: 0.608, 95% CI 0.522 to 0.685). The results were confirmed in temporal and external validation.

CONCLUSIONS

The CoLab-score is based on routine laboratory measurements and is available within 1 hour after presentation. Depending on the prevalence, COVID-19 may be safely ruled out in over one-third of ED presentations. Highly suspect cases can be identified regardless of presenting symptoms. The CoLab-score is continuous, in contrast to the binary outcome of lateral flow testing, and can guide PCR testing and triage ED patients.

Applying Healthcare Failure Mode and Effect Analysis and the Development of a Real-Time Mobile Application for Modified Early Warning Score Notification to Improve Patient Safety During Hemodialysis

OBJECTIVE

Patients undergoing hemodialysis are a high-risk population. This study identified possible errors by using a healthcare failure mode and effect analysis system to improve patient safety during hemodialysis.

METHODS

A multidisciplinary collaborative team, including physicians, nurses, information technicians, and medical staff members, was assembled. A flow diagram was used to indicate each process of the hemodialysis procedure from evaluating patient condition to transporting the patient back to the ward from the hemodialysis center. We scored all possible failure modes using the hazard scoring method as a combination of the occurrence frequency and severity. These potential failure modes were used to identify and evaluate possible risks by using a risk scoring matrix.

RESULTS

Thirty failure modes were identified across 6 processes, and their potential causes were explored. Four major strategies for addressing most of the failure modes were implemented: establishment of a mobile application that sends real-time automated alerts to the medical team based on the Modified Early Warning Score, design of a modified dialysis Identify-Situation-Background-Assessment-Recommendation checklist for dialysis, technician education and training, and internal auditing and monitoring of the implementation of the entire process. After the implementation of the strategies, the hazard scores of patients during dialysis dropped by 71.2% from 170 points to 49 points.

CONCLUSIONS

The healthcare failure mode and effect analysis system was useful for evaluating potential risk during dialysis. Using the mobile application reduced the occurrence of emergency resuscitation during hemodialysis and significantly improved the communication between medical personnel.

Predictive value of the New Zealand Early Warning Score for early mortality in low-acuity patients discharged at scene by paramedics: an observational study

OBJECTIVES

The utility of New Zealand Early Warning Score (NZEWS) for prediction of adversity in low-acuity patients discharged at scene by paramedics has not been investigated. The objective of this study was to evaluate the association between the NZEWS risk-assessment tool and adverse outcomes of early mortality or ambulance reattendance within 48 hours in low-acuity, prehospital patients not transported by ambulance.

DESIGN

A retrospective cohort study.

SETTING

Prehospital emergency medical service provided by St John New Zealand over a 2-year period (1 July 2016 through 30 June 2018).

PARTICIPANTS

83 171 low-acuity, adult patients who were attended by an ambulance and discharged at scene. Of these, 41 406 had sufficient recorded data to calculate an NZEWS.

PRIMARY AND SECONDARY OUTCOMES AND MEASURES

Binary logistic regression modelling was used to investigate the association between the NZEWS and adverse outcomes of reattendance within 48 hours, mortality within 2 days, mortality within 7 days and mortality within 30 days.

RESULTS

An NZEWS greater than 0 was significantly associated with all adverse outcomes studied (p<0.01), compared with the reference group (NZEWS=0). There was a startling correlation between 2-day, 7-day and 30-day mortality and higher early warning scores; the odds of 2-day mortality in patients with an early warning score>10 was 70 times that of those scoring 0 (adjusted OR 70.64, 95% CI: 30.73 to 162.36). The best predictability for adverse outcome was observed for 2-day and 7-day mortality, with moderate area under the receiver operating characteristic curve scores of 0.78 (95% CI: 0.73 to 0.82) and 0.74 (95% CI: 0.71 to 0.77), respectively.

CONCLUSIONS

Adverse outcomes in low-acuity non-transported patients show a significant association with risk prediction by the NZEWS. There was a very high association between large early warning scores and 2-day mortality in this patient group. These findings suggest that NZEWS has significant utility for decision support and improving safety when determining the appropriateness of discharging low-acuity patients at the scene.

Effectiveness of Early Warning Scores for Early Severity Assessment in Outpatient Emergency Care: A Systematic Review

Background and Objectives

Patient assessment and possible deterioration prediction are a healthcare priority. Increasing demand for outpatient emergency care services requires the implementation of simple, quick, and effective systems of patient evaluation and stratification. The purpose of this review is to identify the most effective Early Warning Score (EWS) for the early detection of the risk of complications when screening emergency outpatients for a potentially serious condition.

Materials and Methods

Systematic review of the bibliography made in 2022. Scientific articles in Spanish and English were collected from the databases and search engines of Pubmed, Cochrane, and Dialnet, which were published between 2017 and 2021 about EWSs and their capacity to predict complications.

Results

For analysis eleven articles were selected. Eight dealt with the application of different early warning scores in outpatient situations, concluding that all the scoring systems they studied were applicable. Three evaluated the predictive ability of various scoring systems and found no significant differences in their results. The eight articles evaluated the suitability of NEWS/NEWS2 to outpatient conditions and concluded it was the most suitable in pre-hospital emergency settings.

Conclusions

The early warning scores that were studied can be applied at the pre-hospital level, as they can predict patient mortality in the short term (24 or 48 h) and support clinical patient evaluation and medical decision making. Among them, NEWS2 is the most suitable for screening potentially deteriorating medical emergency outpatients.

Understanding the use of the National Early Warning Score 2 in acute care settings: a realist review protocol

INTRODUCTION

Failure to recognise and respond to patient deterioration in an appropriate and timely manner has been highlighted as a global patient safety concern. Early Warning Scores (EWSs) using vital signs were introduced to address this concern, with the aim of getting the patient timely and appropriate treatment. The National Early Warning Score 2 (NEWS2) is in use across the NHS, and many other settings globally. While patient improvements have been shown, research has identified that the NEWS2 is not always used as intended. Therefore, this review will use a realist approach to understand what the mechanisms are that influence appropriate use (or not) of the NEWS2 in acute care settings, how, for whom and in which contexts. The findings will inform clinicians of what helps and/or hinders appropriate use of the NEWS2 in clinical practice, thus helping to facilitate successful implementation.

METHODS AND ANALYSIS

Our realist review will follow Pawson's iterative six step process: (1) Development of initial programme theory. (2) Searching the literature; an information scientist will develop, pilot and refine the search strategy. A systematic search will be completed, based on subject relevancy on the following databases: Cumulative Index to Nursing and Allied Health Literature (CINAHL), Medline, Embase (OvidSP), Web of Science (Science Citation Index and Social Science Citation), Cochrane Database of Systematic Reviews, Joanna Briggs Institute, Ethos, Proquest Dissertations and Theses Global, and Google Scholar for documents dating from 1997 (date of the first published EWS) to present. To retrieve additional relevant data 'snowballing' (finding references and authors by hand, contacting authors, searching reference lists and citation-tracking using Google Scholar) will be used. Inclusion criteria include all documents (including grey literature) that relate to the use of EWSs/NEWS2 in the English language only. Documents set in the paediatric, maternity and primary care settings will be excluded. (3) Selecting documents and quality appraisal. (4) Extracting and organising the data. (5) Synthesising the data. (6) Disseminating the findings. We will recruit a group of stakeholders comprised of experienced clinicians who use the NEWS2 as part of their clinical practice to provide feedback throughout the review. Step 1 has already begun with the development of an initial programme theory. This initial programme theory presents how the NEWS2 is supposed to work (or not), it will now be developed, tested and refined.

ETHICS AND DISSEMINATION

Ethical approval is not required for this study as it is secondary research. Dissemination will include a peer-reviewed publication and conference presentations. Findings will also be amplified through social media platforms with user friendly summaries. Our stakeholder group will also contribute to dissemination of findings in their clinical areas and among existing networks.

PROSPERO REGISTRATION NUMBER

CRD42022304497.

The impact of pediatric early warning score and rapid response algorithm training and implementation on interprofessional collaboration in a resource-limited setting

Introduction

Improved teamwork and communication have been associated with improved quality of care. Early Warning Scores (EWS) and rapid response algorithms are a way of identifying deteriorating patients and providing a common framework for communication and response between physicians and nurses. The impact of EWS implementation on interprofessional collaboration (IPC) has been minimally studied, especially in resource-limited settings.

Methods

The study took place in the Pediatric Department of the main academic referral hospital in Rwanda between April 2019 and January 2020. Pediatric nurses and residents were trained on the use of the Pediatric Warning Score for Resource-Limited Settings (PEWS-RL) and a rapid response algorithm. Training included vital sign collection, PEWS-RL calculation, IPC and rapid response algorithm implementation. Prior to training, participants completed surveys on IPC with Likert scale responses (from “strongly disagree” to “strongly agree”). Follow-up surveys were then administered nine months later and also included an open-response question on the impact of the PEWS-RL implementation on IPC.

Results

Sixty-five (96%) nurses were trained and completed the pre-survey and thirty-seven (54%) of the trained nurses completed the post-survey. Twenty-two (59%) pediatric residents were trained in the workshop and completed the pre-survey and twenty-four physicians (4 pediatricians (40%) and 20 pediatric residents (53%)) completed the post-implementation survey. There was a statistically significant increase in the percent of nurses indicating strong agreement across all domains of communication and collaboration from the pre- to the post-survey. Although the percent of physicians indicating strong agreement increased in the post-survey for all items, only the “share information” item was statistically significant.

Conclusion

Training and implementation of a PEWS-RL and a rapid response algorithm at a tertiary hospital in Rwanda resulted in significant improvement of nurse and physician ratings of IPC nine months later.

Prediction of Pediatric Patient Admission/Discharge in the Emergency Department: Irish Pediatric Early Warning Score, Pediatric Observation Priority Score, and Irish Children's Triage System

OBJECTIVE

The aim of this study was to evaluate the ability of the Irish Paediatric Early Warning Score (PEWS), the Paediatric Observation Priority Score (POPS), and the Irish Children's Triage System (ICTS) to predict patient disposition pathways in an emergency department (ED) setting.

METHODS

Data were prospectively collected on patients aged less than 16 years presenting to an Irish mixed adult/pediatric ED over 3 weeks during December 2018. After calculating a once-off PEWS, POPS, and ICTS, we investigated the ability of the scoring systems to predict admission or discharge from the ED. Primary comparison of the index tests was conducted using receiver operating characteristic (ROC) curves.

RESULTS

A total of 550 patients were included in this study. There were 114 admissions (20.7%) and 436 discharges (79.3%). The POPS had an area under the ROC curve of 0.7 [95% confidence interval (CI), 0.65-0.75]. The PEWS had an area under the ROC curve of 0.58 (95% CI, 0.53-0.64). The ICTS had an area under the ROC curve of 0.58 (95% CI, 0.53-0.63).

CONCLUSIONS

The POPS has greater accuracy as a predictor of admission from the ED than PEWS and ICTS. Possible future implementation of POPS into pediatric EDs as a cognitive prompt before admission decision seems to be merited. Further multicenter validation in Ireland would be helpful.

Evaluation of a Pediatric Early Warning Score as a Predictor of Occult Invasive Bacterial Infection in the Pediatric Emergency Department

OBJECTIVES

The aims of the study were to evaluate the diagnostic performance of Pediatric Early Warning Score (PEWS) to predict occult invasive bacterial infection (IBI) in well-appearing pediatric emergency department (PED) patients without known risk factors for bacterial infection and to compare PEWS to heart rate (HR) and Emergency Severity Index (ESI).

METHODS

We performed a retrospective case-control analysis of febrile PED patients aged 60 days to 18 years over a 2-year period. Subjects were excluded if they were ill appearing, admitted to an intensive care unit, or had a known high-risk condition. Cases of occult IBI were included if they had a noncontaminant positive culture other than an isolated positive urine culture. Two febrile control subjects were identified for each case. Odds ratios and receiver operating characteristic curves were evaluated to determine performance characteristics of PEWS at triage and disposition, age-adjusted HR at triage and disposition, and ESI at triage.

RESULTS

Compared with 178 controls, 89 cases had higher disposition PEWS, higher disposition HR, lower ESI, and higher rate of hospital admission. Disposition PEWS ≥3 (odds ratio, 2.57; 95% confidence interval, 1.08-6.18), disposition HR > 99th percentile, and ESI demonstrated increased odds of occult IBI. Area under the receiver operating characteristic curve for disposition PEWS (0.56) was similar to triage PEWS (0.54), triage HR (0.54), disposition HR (0.58), and ESI (0.65).

CONCLUSIONS

Subjects with PEWS ≥3 at PED disposition have increased odds of occult IBI; however, PEWS has poor discriminative ability at all cutoffs. We cannot recommend PEWS used in isolation to predict occult IBI.

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

OBJECTIVES

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

DESIGN

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

SETTING

One university hospital and two regional hospitals in Finland.

PARTICIPANTS

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

PRIMARY AND SECONDARY OUTCOME MEASURES

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

RESULTS

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

CONCLUSIONS

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

TRIAL REGISTRATION NUMBER

NCT04055350.

Quick Sequential Organ Failure Assessment Score and the Modified Early Warning Score for Predicting Clinical Deterioration in General Ward Patients Regardless of Suspected Infection

BACKGROUND

The quick sequential organ failure assessment (qSOFA) score is suggested to use for screening patients with a high risk of clinical deterioration in the general wards, which could simply be regarded as a general early warning score. However, comparison of unselected admissions to highlight the benefits of introducing qSOFA in hospitals already using Modified Early Warning Score (MEWS) remains unclear. We sought to compare qSOFA with MEWS for predicting clinical deterioration in general ward patients regardless of suspected infection.

METHODS

The predictive performance of qSOFA and MEWS for in-hospital cardiac arrest (IHCA) or unexpected intensive care unit (ICU) transfer was compared with the areas under the receiver operating characteristic curve (AUC) analysis using the databases of vital signs collected from consecutive hospitalized adult patients over 12 months in five participating hospitals in Korea.

RESULTS

Of 173,057 hospitalized patients included for analysis, 668 (0.39%) experienced the composite outcome. The discrimination for the composite outcome for MEWS (AUC, 0.777; 95% confidence interval [CI], 0.770-0.781) was higher than that for qSOFA (AUC, 0.684; 95% CI, 0.676-0.686; P < 0.001). In addition, MEWS was better for prediction of IHCA (AUC, 0.792; 95% CI, 0.781-0.795 vs. AUC, 0.640; 95% CI, 0.625-0.645; P < 0.001) and unexpected ICU transfer (AUC, 0.767; 95% CI, 0.760-0.773 vs. AUC, 0.716; 95% CI, 0.707-0.718; P < 0.001) than qSOFA. Using the MEWS at a cutoff of ≥ 5 would correctly reclassify 3.7% of patients from qSOFA score ≥ 2. Most patients met MEWS ≥ 5 criteria 13 hours before the composite outcome compared with 11 hours for qSOFA score ≥ 2.

CONCLUSION

MEWS is more accurate that qSOFA score for predicting IHCA or unexpected ICU transfer in patients outside the ICU. Our study suggests that qSOFA should not replace MEWS for identifying patients in the general wards at risk of poor outcome.

Comparison of Quick Sequential Organ Failure Assessment (Qsofa) and National Early Warning Score (News) in Covid-19 Patients and its Correlation with the Outcome

The recent outbreak of COVID 19 is a great threat to public health. Because of limitation of resources, the number of patients that can be monitored and treated in Intensive Care Units is restricted. Hence identifying medical patients at risk of deterioration at the initial stage by means of simple protocols based on physiological parameters is crucial. The qSOFA score was introduced as a rapid bedside clinical score to identify patients with a suspected infection that are at greater risk for a poor outcome. The National Early Warning Score (NEWS) was developed to improve the detection of and response to clinical deterioration in patients with acute illness. There is paucity of literature regarding the use of these scores in patients with COVID 19 infection. This study aims at comparing the scoring systems qSOFA and NEWS in the setting of COVID-19 infection and its correlation with the final outcome of the illness.

MATERIAL

It is a retrospective study in which patients presenting with COVID 19 infection(diagnosed by RT-PCR testing of nasopharyngeal and oral swab) between April 2021 to June 2021 were included. Scoring was done using both the scores at admission and the patients were followed up till the outcome. Outcome was defined as 5-day, 10-day and 15-day mortality after presentation. Predictive performance was expressed as discrimination (AUC). Subsequently, sensitivity and specificity were calculated.

OBSERVATION

A total of 100 patients were included in the study, of whom 17 died within 5 days and 37 died within 10 days and 30 died within 15 days after presentation. q SOFA had the best performance, compared to NEWS (5 day auc : .668, .621, 10-day auc: .580, .569, 15-day auc: .625, .511) with q SOFA having sensitivity of 90.2% while that of news being 95.1% where as specificity of q SOFA is 40.7% and that of NEWS is 47.5%.

CONCLUSION

qSOFA score is more accurate in predicting 5, 10 and 15-day mortality than NEWS score in COVID 19 patients. In resource limited settings, it is an inexpensive and simple tool for early identification of high risk COVID 19 patients.

A systematic review of the discrimination and absolute mortality predicted by the National Early Warning Scores according to different cut-off values and prediction windows

BACKGROUND

Although early warning scores were intended to simply identify patients in need of life-saving interventions, prediction has become their commonest metric. This review examined variation in the ability of the National Early Warning Scores (NEWS) in adult patients to predict absolute mortality at different times and cut-offs values.

METHOD

Following PRISMA guidelines, all studies reporting NEWS and NEWS2 providing enough information to fulfil the review's aims were included.

RESULTS

From 121 papers identified, the average area under the Receiver Operating Characteristic curve (AUC) for mortality declined from 0.90 at 24-hours to 0.76 at 30-days. Studies with a low overall mortality had a higher AUC for 24-hour mortality, as did general ward patients compared to patients seen earlier in their treatment. 24-hour mortality increased from 1.8% for a NEWS ≥3 to 7.8% for NEWS ≥7. Although 24-hour mortality for NEWS <3 was only 0.07% these deaths accounted for 9% of all deaths within 24-hours; for NEWS <7 24-hour mortality was 0.23%, which accounted for 44% of all 24-hour deaths. Within 30-days of a NEWS recording 22% of all deaths occurred in patients with a NEWS <3, 52% in patients with a NEWS <5, and 75% in patient with a NEWS <7.

CONCLUSION

NEWS reliably identifies patients most and least likely to die within 24-hours, which is what it was designed to do. However, many patients identified to have a low risk of imminent death die within 30-days. NEWS mortality predictions beyond 24-hours are unreliable.

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

OBJECTIVE

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

SETTING

Adult acute hospital in England.

DESIGN

Retrospective observational cohort study.

PARTICIPANTS

100 362 consecutive admissions between November 2018 and July 2019.

OUTCOME

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Performance Assessment of the Universal Vital Assessment Score vs Other Illness Severity Scores for Predicting Risk of In-Hospital Death Among Adult Febrile Inpatients in Northern Tanzania, 2016-2019

IMPORTANCE

Severity scores are used to improve triage of hospitalized patients in high-income settings, but the scores may not translate well to low- and middle-income settings such as sub-Saharan Africa.

OBJECTIVE

To assess the performance of the Universal Vital Assessment (UVA) score, derived in 2017, compared with other illness severity scores for predicting in-hospital mortality among adults with febrile illness in northern Tanzania.

DESIGN, SETTING, AND PARTICIPANTS

This prognostic study used clinical data collected for the duration of hospitalization among patients with febrile illness admitted to Kilimanjaro Christian Medical Centre or Mawenzi Regional Referral Hospital in Moshi, Tanzania, from September 2016 through May 2019. All adult and pediatric patients with a history of fever within 72 hours or a tympanic temperature of 38.0 °C or higher at screening were eligible for enrollment. Of 3761 eligible participants, 1132 (30.1%) were enrolled in the parent study; of those, 597 adults 18 years or older were included in this analysis. Data were analyzed from December 2019 to September 2021.

EXPOSURES

Modified Early Warning Score (MEWS), National Early Warning Score (NEWS), quick Sequential Organ Failure Assessment (qSOFA), Systemic Inflammatory Response Syndrome (SIRS) assessment, and UVA.

MAIN OUTCOMES AND MEASURES

The main outcome was in-hospital mortality during the same hospitalization as the participant's enrollment. Crude risk ratios and 95% CIs for in-hospital death were calculated using log-binomial risk regression for proposed score cutoffs for each of the illness severity scores. The area under the receiver operating characteristic curve (AUROC) for estimating the risk of in-hospital death was calculated for each score.

RESULTS

Among 597 participants, the median age was 43 years (IQR, 31-56 years); 300 participants (50.3%) were female, 198 (33.2%) were HIV-infected, and in-hospital death occurred in 55 (9.2%). By higher risk score strata for each score, compared with lower risk strata, risk ratios for in-hospital death were 3.7 (95% CI, 2.2-6.2) for a MEWS of 5 or higher; 2.7 (95% CI, 0.9-7.8) for a NEWS of 5 or 6; 9.6 (95% CI, 4.2-22.2) for a NEWS of 7 or higher; 4.8 (95% CI, 1.2-20.2) for a qSOFA score of 1; 15.4 (95% CI, 3.8-63.1) for a qSOFA score of 2 or higher; 2.5 (95% CI, 1.2-5.2) for a SIRS score of 2 or higher; 9.1 (95% CI, 2.7-30.3) for a UVA score of 2 to 4; and 30.6 (95% CI, 9.6-97.8) for a UVA score of 5 or higher. The AUROCs, using all ordinal values, were 0.85 (95% CI, 0.80-0.90) for the UVA score, 0.81 (95% CI, 0.75-0.87) for the NEWS, 0.75 (95% CI, 0.69-0.82) for the MEWS, 0.73 (95% CI, 0.67-0.79) for the qSOFA score, and 0.63 (95% CI, 0.56-0.71) for the SIRS score. The AUROC for the UVA score was significantly greater than that for all other scores (P < .05 for all comparisons) except for NEWS (P = .08).

CONCLUSIONS AND RELEVANCE

This prognostic study found that the NEWS and the UVA score performed favorably compared with other illness severity scores in predicting in-hospital mortality among a hospitalized cohort of adults with febrile illness in northern Tanzania. Given its reliance on readily available clinical data, the UVA score may have utility in the triage and prognostication of patients admitted to the hospital with febrile illness in low- to middle-income settings such as sub-Saharan Africa.

The Effect of Pediatric Early Warning Score Use on Emergency Response Calls After Admission From the Pediatric Emergency Department

OBJECTIVES

Pediatric Early Warning Scores (PEWS) are an easy-to-use diagnostic tool for patient evaluation. The goal of this study was to determine if using PEWS in our pediatric emergency department (PED) at the time of admission to the hospital was associated with a decrease in the number of emergency response calls within 6 hours of admission.

METHODS

A retrospective chart review of 6 months before (May 2013-October 2013) and after (December 2013-May 2014) initiation of PEWS upon inpatient admission from our urban, tertiary care PED was conducted to determine the number of patients who had emergency response calls within 6 hours of admission.

RESULTS

The percentage of patients admitted from the PED who required an emergency response call within 6 hours of admission dropped from 1.77% in the 6 months before assigning PEWS to 0.79% in the 6 months after, a 55% reduction (P = 0.0070).

CONCLUSIONS

Assigning PEWS to patients being admitted to our hospital from the PED was associated with a reduced number of emergency response calls in the period immediately after admission.

Can Routinely Collected, Patient-Reported Wellness Predict National Early Warning Scores? A Multilevel Modeling Approach

OBJECTIVE

Measures exist to improve early recognition of and response to deteriorating patients in hospital. However, management of critical illness remains a problem globally; in the United Kingdom, 7% of the deaths reported to National Reporting and Learning System from acute hospitals in 2015 related to failure to recognize or respond to deterioration. The current study explored whether routinely recording patient-reported wellness is associated with objective measures of physiology to support early recognition of hospitalized deteriorating patients.

METHODS

A prospective observation study design was used. Nurses on four inpatient wards were invited to participate and record patient-reported wellness during every routine observation (where possible) using an electronic observation system. Linear multilevel modeling was used to examine the relationship between patient-reported wellness, and national early warning scores (NEWS), and whether patient-reported wellness predicted subsequent NEWS.

RESULTS

A significant positive relationship was found between patient-reported wellness and NEWS recorded at the next observation while controlling for baseline NEWS (β = 0.180, P = 0.033). A significant positive relationship between patient-reported wellness and NEWS (β = 0.229, P = 0.005) recorded during an observation 24 hours later while controlling for baseline NEWS was also found. Patient-reported wellness added to the predictive model for subsequent NEWS.

CONCLUSIONS

The preliminary findings suggest that patient-reported wellness may predict subsequent improvement or decline in their condition as indicated by objective measurements of physiology (NEWS). Routinely recording patient-reported wellness during observation shows promise for supporting the early recognition of clinical deterioration in practice, although confirmation in larger-scale studies is required.

Early warning scores to assess the probability of critical illness in patients with COVID-19

OBJECTIVE

Validated clinical risk scores are needed to identify patients with COVID-19 at risk of severe disease and to guide triage decision-making during the COVID-19 pandemic. The objective of the current study was to evaluate the performance of early warning scores (EWS) in the ED when identifying patients with COVID-19 who will require intensive care unit (ICU) admission for high-flow-oxygen usage or mechanical ventilation.

METHODS

Patients with a proven SARS-CoV-2 infection with complete resuscitate orders treated in nine hospitals between 27 February and 30 July 2020 needing hospital admission were included. Primary outcome was the performance of EWS in identifying patients needing ICU admission within 24 hours after ED presentation.

RESULTS

In total, 1501 patients were included. Median age was 71 (range 19-99) years and 60.3% were male. Of all patients, 86.9% were admitted to the general ward and 13.1% to the ICU within 24 hours after ED admission. ICU patients had lower peripheral oxygen saturation (86.7% vs 93.7, p≤0.001) and had a higher body mass index (29.2 vs 27.9 p=0.043) compared with non-ICU patients. National Early Warning Score 2 (NEWS2) ≥ 6 and q-COVID Score were superior to all other studied clinical risk scores in predicting ICU admission with a fair area under the receiver operating characteristics curve of 0.740 (95% CI 0.696 to 0.783) and 0.760 (95% CI 0.712 to 0.800), respectively. NEWS2 ≥6 and q-COVID Score ≥3 discriminated patients admitted to the ICU with a sensitivity of 78.1% and 75.9%, and specificity of 56.3% and 61.8%, respectively.

CONCLUSION

In this multicentre study, the best performing models to predict ICU admittance were the NEWS2 and the Quick COVID-19 Severity Index Score, with fair diagnostic performance. However, due to the moderate performance, these models cannot be clinically used to adequately predict the need for ICU admission within 24 hours in patients with SARS-CoV-2 infection presenting at the ED.

Validation of the National Early Warning Score (NEWS)-2 for adults in the emergency department in a tertiary-level clinic in Colombia: Cohort study

The National Early Warning Score (NEWS)-2 is an early warning scale that is used in emergency departments to identify patients at risk of clinical deterioration and to help establish rapid and timely management. The objective of this study was to determine the validity and prediction of mortality using the NEWS2 scale for adults in the emergency department of a tertiary clinic in Colombia.A prospective observational study was conducted between August 2018 and June 2019 at the Universidad de La Sabana Clinic.The nursing staff in the triage classified the patients admitted to the emergency room according to Emergency Severity Index and NEWS2. Demographic data, physiological variables, admission diagnosis, mortality outcome, and comorbidities were extracted.Three thousand nine hundred eighty-six patients were included in the study. Ninety-two (2%) patients required intensive care unit management, with a mean NEWS2 score of 7. A total of 158 patients died in hospital, of which 63 were women (40%). Of these 65 patients required intensive care unit management. The receiver operating characteristic curve for NEWS2 had an area of 0.90 (CI 95%: 0.87-0.92). A classification and score equivalency analysis was performed between triage and the NEWS2 scale in terms of mortality. Of the patients classified as triage I, 32.3% died, and those who obtained a NEWS2 score greater than or equal to 10 had a mortality of 38.6%.Among our population, NEWS2 was not inferior in its area under the receiver operating characteristic curve when predicting mortality than triage, and the cutoff point for NEWS2 to predict in-hospital mortality was higher.

A Trend-Based Early Warning Score Can Be Implemented in a Hospital Electronic Medical Record to Effectively Predict Inpatient Deterioration

OBJECTIVES

To determine whether a statistically derived, trend-based, deterioration index is superior to other early warning scores at predicting adverse events and whether it can be integrated into an electronic medical record to enable real-time alerts.

DESIGN

Forty-three variables and their trends from cases and controls were used to develop a logistic model and deterioration index to predict patient deterioration greater than or equal to 1 hour prior to an adverse event.

SETTING

Two large Australian teaching hospitals.

PATIENTS

Cases were considered as patients who suffered adverse events (unexpected death, unplanned ICU transfer, urgent surgery, and rapid-response alert) between August 1, 2016, and April 1, 2019.

INTERVENTIONS

The logistic model and deterioration index were tested on historical data and then integrated into an electronic medical record for a 6-month prospective "silent" validation.

MEASUREMENTS AND MAIN RESULTS

Data were acquired from 258,732 admissions. There were 8,002 adverse events. The addition of vital sign and laboratory trend values to the logistic model increased the area under the curve from 0.84 to 0.89 and the sensitivity to predict an adverse event 1-48 hours prior from 0.35 to 0.41. A 48-hour simulation showed that the logistic model had a higher area under the curve than the Modified Early Warning Score and National Early Warning Score (0.87 vs 0.74 vs 0.71). During the silently run prospective trial, the sensitivity of the deterioration index to detect adverse event any time prior to the adverse event was 0.474, 0.369 1 hour prior, and 0.327 4 hours prior, with a specificity of 0.972.

CONCLUSIONS

A deterioration prediction model was developed using patient demographics, ward-based observations, laboratory values, and their trends. The model's outputs were converted to a deterioration index that was successfully integrated into a live hospital electronic medical record. The sensitivity and specificity of the tool to detect inpatient deterioration were superior to traditional early warning scores.

National Early Warning Score 2 Lactate (NEWS2-L) in Predicting Early Clinical Deterioration in Patients with Dyspnoea in Prehospital Care

OBJECTIVES

To evaluate the ability of the NEWS2-L (National Early Warning Score 2 Lactate) scale to predict the risk of early clinical deterioration (mortality within 48 hours) in patients with dyspnoea treated by the Medical Emergency Services compared with NEWS2 and lactate in isolation.

METHODS

Prospective, multi-centre study of a cohort of 638 patients with dyspnoea treated in the ambulance and priority-transferred to a hospital emergency service in the cities of Valladolid, Salamanca, Segovia or Burgos (Spain). We collected clinical, analytical and demographic data. The main outcome measure was all-cause mortality within 48 hours. The recommendations of the Royal College of Physicians were followed to calculate NEWS2. When NEWS2 and LA prehospital values were obtained, the two values were added together to obtain the NEWS2-L.

RESULTS

Mortality within 48 hours was fifty-six patients (8.8%). The NEWS2-L scale obtained an area under the curve (AUC) of the receiver operating characteristics (ROC) for mortality within 48 hours of 0.854 (CI 95% 0.790-0.917), at seven days of 0.788 (CI 95% 0.729-0.848) and at 30 days of 0.744 (CI 95% 0.692-0.796); in all cases p<0.001, with a significant decrease between the value at 48 hours and at 30 days.

CONCLUSIONS

The NEWS2-L scale was found to be significantly superior to the NEWS2 scale and similar to lactate in predicting early clinical deterioration in patients with dyspnoea. This scale can help a nurse detect these patients early, as part of their regular practice, and thus guide therapeutic efforts.

National Early Warning Scores and COVID-19 deaths in care homes: an ecological time-series study

OBJECTIVES

To investigate whether National Early Warning Scores (NEWS/NEWS2) could contribute to COVID-19 surveillance in care homes.

SETTING

460 care home units using the same software package to collect data on residents, from 46 local authority areas in England.

PARTICIPANTS

6464 care home residents with at least one NEWS recording.

EXPOSURE MEASURE

29 656 anonymised person-level NEWS from 29 December 2019 to 20 May 2020 with component physiological measures: systolic blood pressure, respiratory rate, pulse rate, temperature and oxygen saturation. Baseline values for each measure calculated using 80th and 20th centile scores before March 2020.

OUTCOME MEASURE

Cross-correlation comparison of time series with Office for National Statistics weekly reported registered deaths of care home residents where COVID-19 was the underlying cause of death, and all other deaths (excluding COVID-19) up to 10 May 2020.

RESULTS

Deaths due to COVID-19 were registered from 23 March 2020 in the local authority areas represented in the study. Between 23 March 2020 and 10 May 2020, there were 5753 deaths (1532 involving COVID-19 and 4221 other causes). We observed a rise in the proportion of above-baseline NEWS beginning 16 March 2020, followed 2 weeks later by an increase in registered deaths (cross-correlation of r=0.82, p<0.05 for a 2 week lag) in corresponding local authorities. The proportion of above-baseline oxygen saturation, respiratory rate and temperature measurements also increased approximately 2 weeks before peaks in deaths.

CONCLUSIONS

NEWS could contribute to COVID-19 disease surveillance in care homes during the pandemic. Oxygen saturation, respiratory rate and temperature could be prioritised as they appear to signal rise in mortality almost as well as NEWS. This study reinforces the need to collate data from care homes, to monitor and protect residents' health. Further work using individual level outcome data is needed to evaluate the role of NEWS in the early detection of resident illness.

Establishing a warning index for evaluating the physiological stress of sanitation workers in high temperature weather

High temperature weather occurs frequently in recent years. As a heat-vulnerable group, sanitation workers suffer great physiological safety risks in high temperature weather. In this paper, a physiological warning index (PWI) is established to quantify the physiological stress of the sanitation workers. Firstly, the dynamic weights of the physiological parameters are calculated by the norm grey correlation method. Secondly, the PWI is established by the efficacy coefficient method and the warning level of the PWI is divided based on the relationships between the PWI and thermal sensation vote (TSV). Finally, the reasonability of the PWI is verified. The results show that the weights of the physiological parameters are dynamic, changing with the environments and the physiological states. The weight ranges of the mean skin temperature (MST), tympanic temperature (TT), systolic blood pressure (SBP), diastolic blood pressure (DBP) and heart rate (HR) are 0.036-0.538, 0.000-0.369, 0.000-0.362, 0.018-0.367 and 0.009-0.348. And the MST and DBP are more affected by the high temperature than the TT, SBP and HR. The warning interval of PWI is: (0, 0.25] (no warning), (0.25, 0.45] (mild warning), (0.45, 0.7] (moderate warning), and (0.7, 1.0] (severe warning). The PWI can provide simple real-time physiological warning and guarantee physiological health for sanitation workers in high temperature weather.

Prognostic accuracy of emergency department triage tools for adults with suspected COVID-19: the PRIEST observational cohort study

BACKGROUND

The WHO and National Institute for Health and Care Excellence recommend various triage tools to assist decision-making for patients with suspected COVID-19. We aimed to compare the accuracy of triage tools for predicting severe illness in adults presenting to the ED with suspected COVID-19.

METHODS

We undertook a mixed prospective and retrospective observational cohort study in 70 EDs across the UK. We collected data from people attending with suspected COVID-19 and used presenting data to determine the results of assessment with the WHO algorithm, National Early Warning Score version 2 (NEWS2), CURB-65, CRB-65, Pandemic Modified Early Warning Score (PMEWS) and the swine flu adult hospital pathway (SFAHP). We used 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome.

RESULTS

We analysed data from 20 891 adults, of whom 4611 (22.1%) died or received organ support (primary outcome), with 2058 (9.9%) receiving organ support and 2553 (12.2%) dying without organ support (secondary outcomes). C-statistics for the primary outcome were: CURB-65 0.75; CRB-65 0.70; PMEWS 0.77; NEWS2 (score) 0.77; NEWS2 (rule) 0.69; SFAHP (6-point rule) 0.70; SFAHP (7-point rule) 0.68; WHO algorithm 0.61. All triage tools showed worse prediction for receipt of organ support and better prediction for death without organ support. At the recommended threshold, PMEWS and the WHO criteria showed good sensitivity (0.97 and 0.95, respectively) at the expense of specificity (0.30 and 0.27, respectively). The NEWS2 score showed similar sensitivity (0.96) and specificity (0.28) when a lower threshold than recommended was used.

CONCLUSION

CURB-65, PMEWS and the NEWS2 score provide good but not excellent prediction for adverse outcome in suspected COVID-19, and predicted death without organ support better than receipt of organ support. PMEWS, the WHO criteria and NEWS2 (using a lower threshold than usually recommended) provide good sensitivity at the expense of specificity.

TRIAL REGISTRATION NUMBER

ISRCTN56149622.

Experiences of a National Early Warning Score (NEWS) intervention in care homes during the COVID-19 pandemic: a qualitative interview study

BACKGROUND

The COVID-19 pandemic has taken a heavy toll on the care home sector, with residents accounting for up to half of all deaths in Europe. The response to acute illness in care homes plays a particularly important role in the care of residents during a pandemic. Digital recording of a National Early Warning Score (NEWS), which involves the measurement of physical observations, started in care homes in one area of England in 2016. Implementation of a NEWS intervention (including equipment, training and support) was accelerated early in the pandemic, despite limited evidence for its use in the care home setting.

OBJECTIVES

To understand how a NEWS intervention has been used in care homes in one area of North-East England during the COVID-19 pandemic, and how it has influenced resident care, from the perspective of stakeholders involved in care delivery and commissioning.

METHODS

A qualitative interview study with care home (n=10) and National Health Service (n=7) staff. Data were analysed using thematic analysis.

RESULTS

Use of the NEWS intervention in care homes in this area accelerated during the COVID-19 pandemic. Stakeholders felt that NEWS, and its associated education and support package, improved the response of care homes and healthcare professionals to deterioration in residents' health during the pandemic. Healthcare professionals valued the ability to remotely monitor resident observations, which facilitated triage and treatment decisions. Care home staff felt empowered by NEWS, providing a common clinical language to communicate concerns with external services, acting as an adjunct to staff intuition of resident deterioration.

CONCLUSIONS

The NEWS intervention formed an important part of the care home response to COVID-19 in the study area. Positive staff perceptions now need to be supplemented with data on the impact on resident health and well-being, workload, and service utilisation, during the pandemic and beyond.

Incidence of in-hospital cardiac arrest at general wards before and after implementation of an early warning score

BACKGROUND

In order to reduce the incidence of in-hospital cardiac arrest (IHCA) at general wards, medical emergency teams (MET) were implemented in the Capital Region of Denmark in 2012 as the efferent part of a track and trigger system. The National Early Warning Score (NEWS) system became the afferent part. This study aims at investigating the incidence of IHCA at general wards before and after the implementation of the NEWS system.

MATERIAL AND METHODS

We included patients at least 18 years old with IHCA at general wards in our hospital in the periods of 2006 to 2011 (pre-EWS group) and 2013 to 2018 (post-EWS group). Data was obtained from a local database and the National In-Hospital Cardiac Arrest Registry (DANARREST). We calculated incidence rate ratios (IRR) for IHCA at general wards with 95% confidence interval (95% CI). Odds ratios (OR) for return of spontaneous circulation (ROSC) and 30-day survival were also calculated with 95% CI.

RESULTS

A total of 444 IHCA occurred before the implementation of NEWS at general wards while 494 IHCA happened afterwards. The incidence rate of IHCA at general wards was 1.13 IHCA per 1000 admissions in the pre-EWS group (2006-2011) and 1.11 IHCA per 1000 admissions in the post-EWS group (2013-2018). The IRR between the two groups was 0.98 (95% CI [0.86;1.11], p = 0.71). The implementation did not affect the chance of ROSC with a crude OR of 1.14 (95% CI [0.88;1.47], p = 0.32) nor did it change the 30-day survival with a crude OR 1.30 (95% CI [0.96;1.75], p = 0.09).

CONCLUSION

Implementation of the EWS system at our hospital did not decrease the incidence rate of in-hospital cardiac arrest at general wards.

Maternity Nurses' Responses to Maternal Early Warning Criteria

OBJECTIVE

The purpose of this study was to assess the influence of nursing care on implementing perinatal risk-appropriate care in the context of maternal early warning criteria.

DESIGN

Medical record review and survey of maternity nurses in a three-hospital system in Wisconsin with two level I hospitals and 1 level III hospital.

PARTICIPANTS

Seven maternity nurses from the level III hospital conducted the medical record reviews and all maternity staff nurses from two level I hospitals were invited to complete the survey.

MEASUREMENTS

All medical records in 2017 that met these inclusion criteria: hypertension, sepsis, preeclampsia, hemorrhage, low Apgar scores, and transport were reviewed to assess identification and response time for maternal early warning signs using the Nurses Contribution to Maternal Mortality Worksheet. The survey included questions about influences on the nurses' confidence when interpreting early warning indicators.

RESULTS

Thirty-two medical records met inclusion criteria and were reviewed. The number of maternal early warning signs recorded ranged from one to four, with a mean of 1.75 indicators. Eighty percent of records documented increased evaluation as a nursing response to the maternal early warning signs. Time-lapse between notifying a provider and bedside evaluation was less than 15 minutes in 54% of cases. Of the 31 eligible nurses, 18 completed the survey (58% response rate). Personal knowledge (90%) was reported by nurses as being the greatest influence on nursing confidence. Sixty-nine percent of nurses reported not receiving patient information from team members at the transporting hospital.

CONCLUSION

A systematic record review by frontline nurses can monitor identification and response to maternal early warning signs. Feedback on patient transports can reinforce nurses' decision-making that has the potential to improve responsiveness to clinical warning signs.

Predicting outcomes of COVID-19 from admission biomarkers: a prospective UK cohort study

INTRODUCTION

COVID-19 has an unpredictable clinical course, so prognostic biomarkers would be invaluable when triaging patients on admission to hospital. Many biomarkers have been suggested using large observational datasets but sample timing is crucial to ensure prognostic relevance. The DISCOVER study prospectively recruited patients with COVID-19 admitted to a UK hospital and analysed a panel of putative prognostic biomarkers on the admission blood sample to identify markers of poor outcome.

METHODS

Consecutive patients admitted to hospital with proven or clinicoradiological suspected COVID-19 were consented. Admission bloods were extracted from the clinical laboratory. A panel of biomarkers (interleukin-6 (IL-6), soluble urokinase plasminogen activator receptor (suPAR), Krebs von den Lungen 6, troponin, ferritin, lactate dehydrogenase, B-type natriuretic peptide, procalcitonin) were performed in addition to routinely performed markers (C reactive protein (CRP), neutrophils, lymphocytes, neutrophil:lymphocyte ratio). Age, National Early Warning Score (NEWS2), CURB-65 and radiographic severity score on initial chest radiograph were included as comparators. All biomarkers were tested in logistic regression against a composite outcome of non-invasive ventilation, intensive care admission or death, with area under the curve (AUC) (figures calculated).

RESULTS

187 patients had 28-day outcomes at the time of analysis. CRP (AUC: 0.69, 95% CI: 0.59 to 0.78), lymphocyte count (AUC: 0.62, 95% CI: 0.53 to 0.72) and other routine markers did not predict the primary outcome. IL-6 (AUC: 0.77, 0.65 to 0.88) and suPAR (AUC: 0.81, 0.72 to 0.88) showed some promise, but simple clinical features alone such as NEWS2 score (AUC: 0.70, 0.60 to 0.79) or age (AUC: 0.70, 0.62 to 0.77) performed nearly as well.

DISCUSSION

Admission blood biomarkers have only moderate predictive value for predicting COVID-19 outcomes, while simple clinical features such as age and NEWS2 score outperform many biomarkers. IL-6 and suPAR had the best performance, and further studies should focus on the additive value of these biomarkers to routine care.

Nurses' Experiences and Perceptions of two Early Warning Score systems to Identify Patient Deterioration-A Focus Group Study

AIMS

To explore Registered Nurses' experiences and perceptions with National Early Warning Score and Individual Early Warning Score to identify patient deterioration.

DESIGN

A qualitative exploratory design.

METHODS

Six focus groups were conducted at six Danish hospitals from February to June 2019. Registered Nurses from both medical, surgical and emergency departments participated. The focus groups were analysed using content analysis.

RESULTS

One theme and four categories were identified. Theme: Meaningful in identifying patient deterioration but causing frustration due to lack of flexibility. Categories: (a) Inter-professional collaboration strengthened through the use of Early Warning Score systems, (b) Enhanced professional development and communication among nurses when using Early Warning Score systems, (c) Detecting patient deterioration by integrating nurses' clinical gaze with Early Warning Score systems and (d) Modification and fear of making mistakes when using Early Warning Score systems.

Detecting Deteriorating Patients in the Hospital: Development and Validation of a Novel Scoring System

Rationale: Late recognition of patient deterioration in hospital is associated with worse outcomes, including higher mortality. Despite the widespread introduction of early warning score (EWS) systems and electronic health records, deterioration still goes unrecognized. Objectives: To develop and externally validate a Hospital- wide Alerting via Electronic Noticeboard (HAVEN) system to identify hospitalized patients at risk of reversible deterioration. Methods: This was a retrospective cohort study of patients 16 years of age or above admitted to four UK hospitals. The primary outcome was cardiac arrest or unplanned admission to the ICU. We used patient data (vital signs, laboratory tests, comorbidities, and frailty) from one hospital to train a machine-learning model (gradient boosting trees). We internally and externally validated the model and compared its performance with existing scoring systems (including the National EWS, laboratory-based acute physiology score, and electronic cardiac arrest risk triage score). Measurements and Main Results: We developed the HAVEN model using 230,415 patient admissions to a single hospital. We validated HAVEN on 266,295 admissions to four hospitals. HAVEN showed substantially higher discrimination (c-statistic, 0.901 [95% confidence interval, 0.898-0.903]) for the primary outcome within 24 hours of each measurement than other published scoring systems (which range from 0.700 [0.696-0.704] to 0.863 [0.860-0.865]). With a precision of 10%, HAVEN was able to identify 42% of cardiac arrests or unplanned ICU admissions with a lead time of up to 48 hours in advance, compared with 22% by the next best system. Conclusions: The HAVEN machine-learning algorithm for early identification of in-hospital deterioration significantly outperforms other published scores such as the National EWS.

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

OBJECTIVE

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

STUDY DESIGN

Retrospective cohort study.

SETTING AND PARTICIPANTS

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

PRIMARY OUTCOME MEASURES

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

RESULTS

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

CONCLUSION

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

National early warning score to predict intensive care unit transfer and mortality in COVID-19 in a French cohort

BACKGROUND

No risk stratification tool has been validated in hospitalised patients with coronavirus disease 2019 (COVID-19), despite a high rate of intensive care requirement and in-hospital mortality. We aimed to determine whether the National Early Warning Score (NEWS) at admission can accurately predict in-hospital mortality and ICU transfer.

METHODS

This was a retrospective cohort study from January 24 to April 16, 2020, at Lille University Hospital. All consecutive adult patients with laboratory-confirmed COVID-19 who were initially admitted to non-ICU wards were included. The primary outcome was a composite criterion consisting of ICU transfer or in-hospital mortality. We evaluated the prognostic performance of NEWS by calculating the area under (AUC) the receiver operating characteristic curve, the optimal threshold value of NEWS, and its association with the primary outcome.

RESULTS

Of the 202 COVID-19 patients, the median age was 65 (interquartile range 52-78), 38.6% were women and 136 had at least one comorbidity. The median NEWS was 4 (2-6). A total of 65 patients were transferred to the ICU or died in the hospital. Compared with patients with favourable outcome, these patients were significantly older, had more comorbidities and higher NEWS. The AUC for NEWS was 0.68 (0.60-0.77) and the best cutoff value was 6. Adjusted odds ratio for NEWS ≥ 6 as an independent predictor was 3.78 (1.94-7.09).

CONCLUSIONS

In hospitalised COVID-19 patients, NEWS was an independent predictor of ICU transfer and in-hospital death. In daily practice, NEWS ≥ 6 at admission may help to identify patients who are at risk to deteriorate.

National early warning score on admission as risk factor for invasive mechanical ventilation in COVID-19 patients: A STROBE-compliant study

The coronavirus disease (COVID-19) has become a global pandemic. Invasive mechanical ventilation is recommended for the management of patients with COVID-19 who have severe respiratory symptoms. However, various complications can develop after its use. The efficient and appropriate management of patients requires the identification of factors associated with an aggravation of COVID-19 respiratory symptoms to a degree where invasive mechanical ventilation becomes necessary, thereby enabling clinicians to prevent such ventilation. This retrospective study included 138 inpatients with COVID-19 at a tertiary hospital. We evaluated the differences in the demographic and clinical data between 27 patients who required invasive mechanical ventilation and 111 patients who did not. Multivariate logistic regression analysis indicated that the duration of fever, national early warning score (NEWS), and lactate dehydrogenase (LDH) levels on admission were significantly associated with invasive mechanical ventilation in this cohort. The optimal cut-off values were: fever duration ≥1 day (sensitivity 100.0%, specificity 54.95%), NEWS ≥7 (sensitivity 72.73%, specificity 92.52%), and LDH >810 mg/dL (sensitivity 56.0%, specificity 90.29%). These findings can assist in the early identification of patients who will require invasive mechanical ventilation. Further studies in larger patient populations are recommended to validate our findings.

Performance of seven different paediatric early warning scores to predict critical care admission in febrile children presenting to the emergency department: a retrospective cohort study

OBJECTIVE

Paediatric Early Warning Scores (PEWS) are widely used in the UK, but the heterogeneity across tools and the limited data on their predictive performance represent obstacles to improving best practice. The standardisation of practice through the proposed National PEWS will rely on robust validation. Therefore, we compared the performance of the National PEWS with six other PEWS currently used in NHS hospitals, for their ability to predict critical care (CC) admission in febrile children attending the emergency department (ED).

DESIGN

Retrospective single-centre cohort study.

SETTING

Tertiary hospital paediatric ED.

PARTICIPANTS

A total of 11 449 eligible febrile ED attendances were identified from the electronic patient record over a 2-year period. Seven PEWS scores were calculated (Alder Hey, Bedside, Bristol, National, Newcastle and Scotland PEWS, and the Paediatric Observation Priority Score, using the worst observations recorded during their ED stay.

OUTCOMES

The primary outcome was CC admission within 48 hours, the secondary outcomes were hospital length of stay (LOS) >48 hours and sepsis-related mortality.

RESULTS

Of 11 449 febrile children, 134 (1.2%) were admitted to CC within 48 hours of ED presentation, 606 (5.3%) had a hospital LOS >48 hours. 10 (0.09%) children died, 5 (0.04%) were sepsis-related. All seven PEWS demonstrated excellent discrimination for CC admission (range area under the receiver operating characteristic curves (AUC) 0.91-0.95) and sepsis-related mortality (range AUC 0.95-0.99), most demonstrated moderate discrimination for hospital LOS (range AUC 0.69-0.75). In CC admission threshold analyses, bedside PEWS (AUC 0.90; 95% CI 0.86 to 0.93) and National PEWS (AUC 0.90; 0.87-0.93) were the most discriminative, both at a threshold of ≥6.

CONCLUSIONS

Our results support the use of the proposed National PEWS in the paediatric ED for the recognition of suspected sepsis to improve outcomes, but further validation is required in other settings and presentations.

Outcome of noncritical COVID-19 patients with early hospitalization and early antiviral treatment outside the ICU

Background/aim

Despite the fact that the COVID-19 pandemic has been going on for over 5 months, there is yet to be a standard management policy for all patients including those with mild-to-moderate cases. We evaluated the role of early hospitalization in combination with early antiviral therapy with COVID-19 patients in a tertiary care university hospital.

Materials and methods

This was a prospective, observational, single-center study on probable/confirmed COVID-19 patients hospitalized in a tertiary care hospital on COVID-19 wards between March 20 and April 30, 2020. The demographic, laboratory, and clinical data were collected.

Results

We included 174 consecutive probable/confirmed COVID-19 adult patients hospitalized in the Internal Medicine wards of the University Adult Hospital between March 20 and April 30, 2020. The median age was 45.5 (19–92) years and 91 patients (52.3%) were male. One hundred and twenty (69%) were confirmed microbiologically, 41 (23.5%) were radiologically diagnosed, and 13 (7.5%) were clinically suspected (negative microbiological and radiological findings compatible with COVID-19); 35 (20.1%) had mild, 107 (61.5%) moderate disease, and 32 (18.4%) had severe pneumonia. Out of 171 cases, 130 (74.3%) showed pneumonia; 80 were typical, and 50 showed indeterminate infiltration for COVID-19. Patients were admitted within a median of 3 days (0-14 days) after symptoms appear. The median duration of hospitalization was 4 days (0-28 days). In this case series, 13.2% patients were treated with hydroxychloroquine alone, 64.9% with hydroxychloroquine plus azithromycin, and 18.4% with regimens including favipiravir. A total of 15 patients (8.5%) were transferred to the ICU. Four patients died (2.2%).

Conclusion

In our series, 174 patients were admitted to the hospital wards for COVID-19, 69% were confirmed with PCR and/or antibody test. At the time of admission, nearly one fifth of the patients had severe diseases. Of the patients, 95.4% received hydroxychloroquine alone or in combination. The overall case fatality rate was 2.2%.