Effect of a Pediatric Early Warning System on All-Cause Mortality in Hospitalized Pediatric Patients: The EPOCH Randomized Clinical Trial

The predictive performance and impact of pediatric early warning systems in hospitalized pediatric oncology patients-A systematic review

Pediatric early warning systems (PEWS) arewidely used to identify clinically deteriorating patients. Hospitalized pediatric oncology patients are particularly prone to clinical deterioration. We assessed the PEWS performance to predict early clinical deterioration and the effect of PEWS implementation on patient outcomes in pediatric oncology patients. PubMED, EMBASE, and CINAHL databases were systematically searched from inception up to March 2020. Quality assessment was performed using the Prediction model study Risk-Of-Bias Assessment Tool (PROBAST) and the Cochrane Risk-of-Bias Tool. Nine studies were included. Due to heterogeneity of study designs, outcome measures, and diversity of PEWS, it was not possible to conduct a meta-analysis. Although the studies reported high sensitivity, specificity, and area under the receiver operating characteristics curve (AUROC) of PEWS detecting inpatient deterioration, overall risk of bias of the studies was high. This review highlights limited evidence on the predictive performance of PEWS for clinical deterioration and the effect of PEWS implementation.

Nursing implications of an early warning system implemented to reduce adverse events: a qualitative study

BACKGROUND

Unrecognised changes in a hospitalised patient's clinical course may lead to a preventable adverse event. Early warning systems (EWS) use patient data, such as vital signs, nursing assessments and laboratory values, to aid in the detection of early clinical deterioration. In 2018, an EWS programme was deployed at an academic hospital that consisted of a commercially available EWS algorithm and a centralised virtual nurse team to monitor alerts. Our objective was to understand the nursing perspective on the use of an EWS programme with centralised monitoring.

METHODS

We conducted and audio-recorded semistructured focus groups during nurse staff meetings on six inpatient units, stratified by alert frequency (high: >100 alerts/month; medium: 50-100 alerts/month; low: <50 alerts/month). Discussion topics included EWS programme experiences, perception of EWS programme utility and EWS programme implementation. Investigators analysed the focus group transcripts using a grounded theory approach.

RESULTS

We conducted 28 focus groups with 227 bedside nurses across all shifts. We identified six principal themes: (1) Alert timeliness, nurses reported being aware of the patient's deterioration before the EWS alert, (2) Lack of accuracy, nurses perceived most alerts as false positives, (3) Workflow interruptions caused by EWS alerts, (4) Questions of actionability of alerts, nurses were often uncertain about next steps, (5) Concerns around an underappreciation of core nursing skills via reliance on the EWS programme and (6) The opportunity cost of deploying the EWS programme.

CONCLUSION

This qualitative study of nurses demonstrates the importance of earning user trust, ensuring timeliness and outlining actionable next steps when implementing an EWS. Careful attention to user workflow is required to maximise EWS impact on improving hospital quality and patient safety.

Modification of a children's hospital pediatric early warning score (EWS): An evaluation of inter-rater reliability, nurses' critical thinking and perceptions of the tool

Pediatric early warning scores (EWS) have been utilized to assist the identification of children at risk for clinically decompensating, experiencing a cardiac or respiratory arrest, or requiring a transfer to a higher level of care. Although their use is widespread, little consistency exists between tools and research evaluating the effectiveness of these tools is lacking. This quasi-experimental project evaluated twenty-five medical-surgical staff nurses' use and perceptions as well as the inter-rater reliability of a newly modified pediatric EWS tool at a free standing, academic Midwestern pediatric hospital. The tool was modified utilizing existing literature and an interdisciplinary team's expertise. Five fictionalized patients, presented in case studies, were developed and nurses were asked to score these patients using the newly modified tool with rationale. Inter-rater reliability was assessed utilizing Fleiss' Kappa and qualitative questionnaire data was analyzed for emerging themes. Overall, Fleiss' Kappa showed that there was moderate agreement between the nurses' judgments and scoring, with scores primarily differing due to the difficulty level of each case study. Nurses' responses to a questionnaire indicated differing levels of comfort identifying and managing children that present with mid-range total scores as opposed to those who scored in the lower or higher ranges. This project's findings highlight nurses' concerns that an objective tool may not accurately describe a subjective assessment. The results of this project indicated that use of this tool, with some modifications to address nursing concerns, may help to identify clinically decompensating pediatric patients being treated on medical-surgical units.

Development, implementation and evaluation of an evidence-based paediatric early warning system improvement programme: the PUMA mixed methods study

Background

Paediatric mortality rates in the United Kingdom are amongst the highest in Europe. Clinically missed deterioration is a contributory factor. Evidence to support any single intervention to address this problem is limited, but a cumulative body of research highlights the need for a systems approach.

Methods

An evidence-based, theoretically informed, paediatric early warning system improvement programme (PUMA Programme) was developed and implemented in two general hospitals (no onsite Paediatric Intensive Care Unit) and two tertiary hospitals (with onsite Paediatric Intensive Care Unit) in the United Kingdom. Designed to harness local expertise to implement contextually appropriate improvement initiatives, the PUMA Programme includes a propositional model of a paediatric early warning system, system assessment tools, guidance to support improvement initiatives and structured facilitation and support.

Each hospital was evaluated using interrupted time series and qualitative case studies. The primary quantitative outcome was a composite metric (adverse events), representing the number of children monthly that experienced one of the following: mortality, cardiac arrest, respiratory arrest, unplanned admission to Paediatric Intensive Care Unit, or unplanned admission to Higher Dependency Unit. System changes were assessed qualitatively through observations of clinical practice and interviews with staff and parents. A qualitative evaluation of implementation processes was undertaken.

Results

All sites assessed their paediatric early warning systems and identified areas for improvement. All made contextually appropriate system changes, despite implementation challenges. There was a decline in the adverse event rate trend in three sites; in one site where system wide changes were organisationally supported, the decline was significant (ß = -0.09 (95% CI: − 0.15, − 0.05); p = < 0.001). Changes in trends coincided with implementation of site-specific changes.

Conclusions

System level change to improve paediatric early warning systems can bring about positive impacts on clinical outcomes, but in paediatric practice, where the patient population is smaller and clinical outcomes event rates are low, alternative outcome measures are required to support research and quality improvement beyond large specialist centres, and methodological work on rare events is indicated. With investment in the development of alternative outcome measures and methodologies, programmes like PUMA could improve mortality and morbidity in paediatrics and other patient populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07314-2.

Validation of the Computerized Pediatric Triage Tool, pediaTRI, in the Pediatric Emergency Department of Lenval Children's Hospital in Nice: A Cross-Sectional Observational Study

INTRODUCTION

A reliable pediatric triage tool is essential for nurses working in pediatric emergency departments to quickly identify children requiring priority care (high-level emergencies) and those who can wait (low-level emergencies). In the absence of a gold standard in France, the objective of our study was to validate our 5-level pediatric triage tool -pediaTRI- against the reference tool: the Pediatric Early Warning Score (PEWS) System.

MATERIALS AND METHODS

We prospectively included 100,506 children who visited the Pediatric Emergency Department at Lenval Children's Hospital (Nice, France) in 2016 and 2017. The performance of pediaTRI to identify high-level emergencies (severity levels 1 and 2) was evaluated in comparison with a PEWS ≥ 4/9. Data from 2018-19 was used as an independent validation cohort.

RESULTS

pediaTRI agreed with the PEWS score for 84,896 of the patients (84.5%): 15.0% (14.8-15.2) of the patients were over-triaged and 0.5% (0.5-0.6) under-triaged compared with the PEWS score. pediaTRI had a sensitivity of 76.4% (74.6-78.2), a specificity of 84.7% (84.4-84.9), and positive and negative likelihood ratios of 5.0 (4.8-5.1) and 0.3 (0.3-0.3), respectively, for the identification of high-level emergencies. However, the positive likelihood ratios were lower for patients presenting with a medical complaint [4.1 (4.0-4.2) v 10.4 (7.9-13.7 for trauma), and for younger children [1.2 (1.1-1.2) from 0 to 28 days, and 1.9 (1.8-2.0) from 28 days to 3 months].

CONCLUSION

pediaTRI has a moderate to good validity to triage children in a Pediatric Emergency Department with a tendency to over-triage compared with the PEWS system. Its validity is lower for younger children and for children consulting for a medical complaint.

Death and Dying in Hospitalized Pediatric Patients: A Prospective Multicenter, Multinational Study

Background: For hospitalized children admitted outside of a critical care unit, the location, mode of death, "do-not-resuscitate" order (DNR) use, and involvement of palliative care teams have not been described across high-income countries. Objective: To describe location of death, patient and terminal care plan characteristics of pediatric inpatient deaths inside and outside the pediatric intensive care unit (PICU). Design: Secondary analysis of inpatient deaths in the Evaluating Processes of Care and Outcomes of Children in Hospital (EPOCH) randomized controlled trial. Setting/Subjects: Twenty-one centers from Canada, Belgium, the United Kingdom, Ireland, Italy, the Netherlands, and New Zealand. Measurement: Descriptive statistics were used to compare patient and terminal care plan characteristics. A multivariable generalized estimating equation examined if palliative care consult during hospital admission was associated with location of death. Results: A total of 365 of 144,539 patients enrolled in EPOCH died; 219 (60%) died in PICU and 143 (40%) died on another inpatient unit. Compared with other inpatient wards, patients who died in PICU were less likely to be expected to die, have a DNR or palliative care consult. Hospital palliative care consultation was more common in older children and independently associated with a lower adjusted odds (95% confidence interval) of dying in PICU [0.59 (0.52-0.68)]. Conclusion: Most pediatric inpatient deaths occur in PICU where patients were less likely to have a DNR or palliative care consult. Palliative care consultation could be better integrated into end-of-life care for younger children and those dying in PICU.

Outcome Differences Between Direct Admissions to the PICU From ED and Escalations From Floor

OBJECTIVES

To compare the outcomes (mortality and ICU length of stay) of patients with direct admissions to the PICU from the emergency department [ED]) versus as an escalation of care from the floor.

METHODS

A retrospective cohort study with a secondary analysis of registry data. Patient demographics and outcome variables collected from January 1, 2015, to December 31, 2019, were obtained from the Virtual Pediatric Systems database. Patients with a source of admission other than the hospital's ED or pediatric floor were excluded. Multivariable regression analysis controlling for age groups, sex, race, diagnostic categories, and severity of illness (Pediatric Index of Mortality III), with clustering for sites, was performed.

RESULTS

A total of 209 695 patients from 121 sites were included in the analysis. A total of 154 716 (73.7%) were admitted directly from the ED, and 54 979 were admitted (26.2%) as an escalation of care from the floor. Two groups differed in age and race distribution, medical complexity, diagnostic categories, and severity of illness. After controlling for measured confounders, patients with floor escalations had higher mortality (2.78% vs 1.95%; P < .001), with an odds ratio of 1.71 (95% CI 1.5 to 1.9) and longer PICU length of stay (4.9 vs 3.6 days; P < .001). The rates of most of the common ICU procedures and their durations were also significantly higher in patients with an escalation of care.

CONCLUSIONS

Compared with direct admissions to the PICU from the ED, patients who were initially triaged to the pediatric floor and then require escalation to the PICU have worse outcomes. Further research is needed to explore the potential causes of this difference.

Pediatric rapid response system innovations

Rapid Response Systems (RRSs) are an organizational approach to support the timely recognition and treatment of decompensating patients and are used in many pediatric hospitals. These systems are comprised of afferent and efferent Limbs, as well as oversight arms. When incorporated into an RRS, standardized care algorithms can be helpful in identifying deteriorating patients and improving behaviors of the multidisciplinary team. The aim of this paper is to provide an overview of pediatric RRS and provide an example in which standardized care algorithms developed for the efferent limb of a pediatric RRS were associated with improvement in early escalation of care.PLAIN LANGUAGE SUMMARYThe Rapid Response System (RRS) is used in hospitals to recognize and care for hospitalized patients that are decompensating outside of an Intensive Care Unit. RRSs are made up of two main response components. The afferent limb focuses on the recognition and calls for help; the efferent limb focuses on correcting the deteriorating patient's physiology. Much energy has been put into afferent limb development to identify worsening patients before they progress to full cardiac or respiratory arrest. Standardization of efferent limb care algorithms can assist in developing and maintaining a shared mental model of care to improve communication and function of the multidisciplinary team.

What can a learning healthcare system teach us about improving outcomes?

PURPOSE OF REVIEW

This review describes the learning healthcare system paradigm, recent examples, and future directions. Patients, clinicians, and health systems frequently encounter decisions between available treatments, technologies, and healthcare delivery methods with little or no evidence about the comparative effectiveness and safety of the available options. Learning healthcare systems endeavor to recognize such knowledge gaps, integrate comparative effectiveness research - including clinical trials - into clinical care to address the knowledge gaps, and seamlessly implement the results into practice to improve care and patient outcomes.

RECENT FINDINGS

Recent studies comparing the effectiveness of diagnostic tests and treatments, using information technology to identify patients likely to experience an outcome or benefit from an intervention, and evaluating models of healthcare delivery have demonstrated how a learning healthcare system approach can reduce arbitrary variation in care, decrease cost, and improve patient outcomes.

SUMMARY

Learning healthcare systems have the potential to answer questions of importance to patients, clinicians, and health system leaders, improve efficiency of healthcare delivery, and improve patient outcomes. Achieving this goal will require realignment of the culture around clinical care, institutional and federal investment, expanded stakeholder engagement, tailored ethical and regulatory guidance, and methodologic advances in information technology and biostatistics.

Adherence to the bedside paediatric early warning system (BedsidePEWS) in a pediatric tertiary care hospital

Background

The aim of this study is to describe the adherence to the Bedside Pediatric Early Warning System (BedsidePEWS) escalation protocol in children admitted to hospital wards in a large tertiary care children’s hospital in Italy.

Methods

This is a retrospective observational chart review. Data on the frequency and accuracy of BedsidePEWS score calculations, escalation of patient observations, monitoring and medical reviews were recorded.

Two research nurses performed weekly visits to the hospital wards to collect data on BedsidePEWS scores, medical reviews, type of monitoring and vital signs recorded. Data were described through means or medians according to the distribution. Inferences were calculated either with Chi-square, Student’s t test or Wilcoxon-Mann–Whitney test, as appropriate (P < 0.05 considered as significant).

Results

A total of 522 Vital Signs (VS) and score calculations [BedsidePEWS documentation events, (DE)] on 177 patient clinical records were observed from 13 hospital inpatient wards. Frequency of BedsidePEWS DE occurred < 3 times per day in 33 % of the observations. Adherence to the BedsidePEWS documentation frequency according to the hospital protocol was observed in 54 % of all patients; in children with chronic health conditions (CHC) it was significantly lower than children admitted for acute medical conditions (47 % vs. 69 %, P = 0.006). The BedsidePEWS score was correctly calculated and documented in 84 % of the BedsidePEWS DE. Patients in a 0–2 BedsidePEWS score range were all reviewed at least once a day by a physician. Only 50 % of the patients in the 5–6 score range were reviewed within 4 h and 42 % of the patients with a score ≥ 7 within 2 h.

Conclusions

Escalation of patient observations, monitoring and medical reviews matching the BedsidePEWS is still suboptimal. Children with CHC are at higher risk of lower compliance. Impact of adherence to predefined response algorithms on patient outcomes should be further explored.

Predicting Future Care Requirements Using Machine Learning for Pediatric Intensive and Routine Care Inpatients

Supplemental Digital Content is available in the text.

OBJECTIVES:

Develop and compare separate prediction models for ICU and non-ICU care for hospitalized children in four future time periods (6–12, 12–18, 18–24, and 24–30 hr) and assess these models in an independent cohort and simulated children’s hospital.

DESIGN:

Predictive modeling used cohorts from the Health Facts database (Cerner Corporation, Kansas City, MO).

SETTING:

Children hospitalized in ICUs.

PATIENTS:

Children with greater than or equal to one ICU admission (n = 20,014) and randomly selected routine care children without ICU admission (n = 20,130) from 2009 to 2016 were used for model development and validation. An independent 2017–2018 cohort consisted of 80,089 children.

INTERVENTIONS:

None.

MEASUREMENT AND MAIN RESULTS:

Initially, we undersampled non-ICU patients for development and comparison of the models. We randomly assigned 64% of patients for training, 8% for validation, and 28% for testing in both clinical groups. Two additional validation cohorts were tested: a simulated children’s hospitals and the 2017–2018 cohort. The main outcome was ICU care or non-ICU care in four future time periods based on physiology, therapy, and care intensity. Four independent, sequential, and fully connected neural networks were calibrated to risk of ICU care at each time period. Performance for all models in the test sample were comparable including sensitivity greater than or equal to 0.727, specificity greater than or equal to 0.885, accuracy greater than 0.850, area under the receiver operating characteristic curves greater than or equal to 0.917, and all had excellent calibration (all R²s > 0.98). Model performance in the 2017–2018 cohort was sensitivity greater than or equal to 0.545, specificity greater than or equal to 0.972, accuracy greater than or equal to 0.921, area under the receiver operating characteristic curves greater than or equal to 0.946, and R²s greater than or equal to 0.979. Performance metrics were comparable for the simulated children’s hospital and for hospitals stratified by teaching status, bed numbers, and geographic location.

CONCLUSIONS:

Machine learning models using physiology, therapy, and care intensity predicting future care needs had promising performance metrics. Notably, performance metrics were similar as the prediction time periods increased from 6–12 hours to 24–30 hours.

Anticipating Pediatric Patient Transfers From Intermediate to Intensive Care

OBJECTIVES

To explore characteristics of patients who were admitted to the intermediate care (IC) unit at a tertiary academic institution. In particular, we sought to compare the characteristics of IC patients who were transferred with the characteristics of those who were not transferred to PICU care and evaluate predictors of patient transfer.

METHODS

Data were collected on all admitted IC patients between July 2016 and June 2018. Patients whose index IC admission was from the PICU were excluded. Data collected included demographics and physiologic characteristics: heart rate, respiratory rate, temperature, oxygen therapy, as well as Bedside Pediatric Early Warning System (BPEWS) score.

RESULTS

In this time period, 427 eligible patient visits occurred, with 66 patients (15.46%) being transferred to the PICU. Patients were commonly transferred early in their IC course (1.41 days into admission [0.66-3.87]); transferred patients had higher median admission BPEWS scores (7 [4.25-9] vs 5 [3-7]; P < .01). In the univariate analysis, no individual physiologic characteristic was predictive for transfer. In the multivariate analysis, BPEWS (P < .001) and need for any form of respiratory support (P = .04) were significant predictive factors for transfer (R ² = 0.56).

CONCLUSIONS

The need for close monitoring of physiologic parameters remains paramount, especially in the first 48 hours of admission, in predicting the need for transfer from the IC to PICU. The need for any form of respiratory support is predictive of transfer. Situational awareness and assessment including BPEWS score is of critical importance.

Case for change: a standardised inpatient paediatric early warning system in England

Most children in hospital who are clinically deteriorating are monitored regularly, and their treatment is escalated effectively. However a small, but significant, number of deteriorating children experience suboptimal outcomes because of a failure to recognise and respond to acute deterioration early enough leading to unintended harm. Tragically this occasionally can have fatal consequences. Investigations into these rare events highlight common themes of missed early signs of deterioration in children, prompting regulatory agencies to suggest paediatric early warning systems (PEWS) to aid clinical practice. In England, track and trigger tools (TTT), which are one facet of PEWS have been widely rolled out but in a heterogeneous fashion. The evidence for TTT is mixed but they are complex interventions and current outcomes do not fully define the entirety of their potential impact. This article explains the rationale behind the decision of the NHS England and NHS Improvement, Royal College of Paediatrics and Child Health and Royal College of Nursing to implement a standardised inpatient PEWS as part of a system-wide paediatric observations tracking system in England and how this fits into a wider programme of activity.

Association of out of hospital paediatric early warning score with need for hospital admission in a Scottish emergency ambulance population

OBJECTIVE

Physiological derangement, as measured by paediatric early warning score (PEWS) is used to identify children with critical illness at an early point to identify and intervene in children at risk. PEWS has shown some utility as a track and trigger system in hospital and also as a predictor of adverse outcome both in and out of hospital. This study examines the relationship between prehospital observations, aggregated into an eight-point PEWS (Scotland), and hospital admission.

METHODS

A retrospective analysis of all patients aged less than 16 transported to hospital by the Scottish Ambulance Service between 2011 and 2015. Data were matched to outcome data regarding hospital admission or discharge and length of stay.

RESULTS

Full data were available for 21 202 paediatric patients, of whom 6340 (29.9%) were admitted to hospital. Prehospital PEWS Scotland was associated with an odds ratio for admission of 1.189 [95% confidence interval (CI): 1.176-1.202; P < 0.001]. The area under receiver operating curve of 0.617 (95% CI: 0.608-0.625; P < 0.001) suggests poorly predictive ability for hospital admission. There was no association between prehospital PEWS Scotland and length of hospital stay.

CONCLUSION

These data show that a single prehospital PEWS Scotland was a poor predictor of hospital admission for unselected patients in a prehospital population. The decision to admit a child to hospital is not solely based on the physiological derangement of vital signs, and hence physiological-based scoring systems such as PEWS Scotland cannot be used as the sole criteria for hospital admission, from an undifferentiated prehospital population.

Identifying the critically ill paediatric oncology patient: a study protocol for a prospective observational cohort study for validation of a modified Bedside Paediatric Early Warning System score in hospitalised paediatric oncology patients

INTRODUCTION

Hospitalised paediatric oncology patients are at risk to develop acute complications. Early identification of clinical deterioration enabling adequate escalation of care remains challenging. Various Paediatric Early Warning Systems (PEWSs) have been evaluated, also in paediatric oncology patients but mostly in retrospective or case-control study designs. This study protocol encompasses the first prospective cohort with the aim of evaluating the predictive performance of a modified Bedside PEWS score for non-elective paediatric intensive care unit (PICU) admission or cardiopulmonary resuscitation in hospitalised paediatric oncology patients.

METHODS AND ANALYSIS

A prospective cohort study will be conducted at the 80-bed Dutch paediatric oncology hospital, where all national paediatric oncology care has been centralised, directly connected to a shared 22-bed PICU. All patients between 1 February 2019 and 1 February 2021 admitted to the inpatient nursing wards, aged 0-18 years, with an International Classification of Diseases for Oncology (ICD-O) diagnosis of paediatric malignancy will be eligible. A Cox proportional hazard regression model will be used to estimate the association between the modified Bedside PEWS and time to non-elective PICU transfer or cardiopulmonary arrest. Predictive performance (discrimination and calibration) will be assessed internally using resampling validation. To account for multiple occurrences of the event of interest within each patient, the unit of study is a single uninterrupted ward admission (a clinical episode).

ETHICS AND DISSEMINATION

The study protocol has been approved by the institutional ethical review board of our hospital (MEC protocol number 16-572/C). We adapted our enrolment procedure to General Data Protection Regulation compliance. Results will be disseminated at scientific conferences, regional educational sessions and publication in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

Netherlands Trial Registry (NL8957).

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

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

Implementation of a paediatric early warning system as a complex health technology intervention

The national implementation groups of early warning systems in the UK and Ireland have identified a need to understand implementation, adoption and maintenance of these complex interventions. The literature on how to implement, scale, spread and sustain these systems is sparse. We describe a successful adoption and maintenance over 10 years of a paediatric early warning system as a sociotechnical intervention using the Nonadoption, Abandonment, Challenges to the Scale-Up, Spread, and Sustainability Framework for Health and Care Technologies. The requirement for iterative processes within environment, culture, policy, human action and the wider system context may explain the possible reasons for improved outcomes in small-scale implementation and meta-analyses that are not reported in multicentre randomised control trials of early warning systems.

A Quality Improvement Initiative to Reduce Unnecessary Rapid Responses Using Early Warning Scores

OBJECTIVES

The Pediatric Early Warning Score (PEWS) is an evidence-based tool that allows early collaborative assessment and intervention for a rapid response team (RRT) activation. The goal of our quality improvement initiative was to reduce the percentage of unnecessary RRT activations by 50% over 2 years without increasing PICU transfers or compromising patient safety and timely evaluation.

METHODS

A PEWS system replaced preexisting vital signs-based pediatric RRT criteria and was modified through plan-do-study-act cycles. Unnecessary RRT activations, total RRT activation rate, transfers to the PICU, total clinical interventions performed per RRT, and missed RRT activation rate were compared between intervention periods. Likert scale surveys were administered to measure satisfaction with each modification.

RESULTS

There was a significant decrease in the percentage of unnecessary RRT activations from 33% to 3.5% after the implementation of the PEWS and modified-PEWS systems (P < .05). The RRT activation rate decreased from 22.6 to 13.3 RRT activations per 1000 patient care days after implementation of the PEWS and modified-PEWS systems (P < .05), without changes in PICU transfer rates. Physicians reported that the PEWS system improved nursing communication and accuracy of RRT criteria (P < .05). Nursing reported that the PEWS system improved patient management and clinical autonomy (P < .05).

CONCLUSIONS

The PEWS systems have been an effective means of identifying deteriorating pediatric patients and reducing unnecessary RRT activations. The new system fosters collaboration and communication at the bedside to prevent acute deterioration, perform timely interventions, and ultimately improve patient safety and outcomes.

Pediatric In-Hospital Cardiac Arrest and Cardiopulmonary Resuscitation in the United States: A Review

IMPORTANCE

Pediatric in-hospital cardiac arrest (IHCA) occurs frequently and is associated with high morbidity and mortality. The objective of this narrative review is to summarize the current knowledge and recommendations regarding pediatric IHCA and cardiopulmonary resuscitation (CPR).

OBSERVATIONS

Each year, more than 15 000 children receive CPR for cardiac arrest during hospitalization in the United States. As many as 80% to 90% survive the event, but most patients do not survive to hospital discharge. Most IHCAs occur in intensive care units and other monitored settings and are associated with respiratory failure or shock. Bradycardia with poor perfusion is the initial rhythm in half of CPR events, and only about 10% of events have an initial shockable rhythm. Pre-cardiac arrest systems focus on identifying at-risk patients and ensuring that they are in monitored settings. Important components of CPR include high-quality chest compressions, timely defibrillation when indicated, appropriate ventilation and airway management, administration of epinephrine to increase coronary perfusion pressure, and treatment of the underlying cause of cardiac arrest. Extracorporeal CPR and measurement of physiological parameters are evolving areas in improving outcomes. Structured post-cardiac arrest care focused on targeted temperature management, optimization of hemodynamics, and careful intensive care unit management is associated with improved survival and neurological outcomes.

CONCLUSIONS AND RELEVANCE

Pediatric IHCA occurs frequently and has a high mortality rate. Early identification of risk, prevention, delivery of high-quality CPR, and post-cardiac arrest care can maximize the chances of achieving favorable outcomes. More research in this field is warranted.

Characteristics of Pediatric Rapid Response Systems: Results From a Survey of PRIS Hospitals

BACKGROUND

Many hospitals use rapid response systems (RRSs) to identify and intervene on hospitalized children at risk for deterioration.

OBJECTIVES

To describe RRS characteristics across hospitals in the Pediatric Research in Inpatient Settings (PRIS) network.

METHODS

We developed the survey through a series of prospective respondent, expert, and cognitive interviews. One institutional expert per PRIS hospital (n = 109) was asked to complete the web survey. We summarized responses using descriptive statistics with a secondary analysis of univariate associations between RRS characteristics and perceived effectiveness.

RESULTS

The response rate was 72% (79 of 109). Respondents represented diverse hospital types and were primarily physicians (97%) with leadership roles in care escalation. Many hospitals used an early warning score (77%) for identification with variable characteristics (46% automated versus 54% full or partially manual calculation; inputs included vital signs [98%], physical examination findings [88%], diagnoses [23%], medications [19%], and diagnostic tests [14%]). Few incorporated a validated prediction model (9%). Similarly, many RRSs used a rapid response team for intervention (93%) with variable team composition (respiratory therapists [94%], ICU nurses [93%], ICU providers [67%], and pharmacists [27%]). Some used the early warning score to trigger the rapid response team (50%). Only a few staffed a clinician to proactively surveil hospitalized children for risk of deterioration (18%), and these tended to be larger hospitals (annual admissions 12 000 vs 6000, P = .007). Most responding experts stated their RRSs improved patient outcomes (92%).

CONCLUSIONS

RRS characteristics varied across PRIS hospitals.

Update on early warning scores

Early warning scores (EWS) have the objective to provide a preventive approach for detecting those patients in general wards at risk of deterioration before it begins. Well implemented and combined with a tiered response, the EWS expect to be a relevant tool for patient safety. Most of the evidence for their use has been published for the general EWS. Their strengths, such as objectivity and systematic response, health provider training, universal applicability and automatization potential need to be highlighted to counterbalance the weakness and limitations that have also been described. The near future will probably increase availability of EWS, reliability and predictive value through the spread and acceptability of continuous monitoring in general ward, its integration in decision support algorithms with automatic alerts and the elaboration of temporal vital signs patterns that will finally allow to perform a personal modelling depending on individual patient characteristics.

Criticality: A New Concept of Severity of Illness for Hospitalized Children

OBJECTIVES

To validate the conceptual framework of "criticality," a new pediatric inpatient severity measure based on physiology, therapy, and therapeutic intensity calibrated to care intensity, operationalized as ICU care.

DESIGN

Deep neural network analysis of a pediatric cohort from the Health Facts (Cerner Corporation, Kansas City, MO) national database.

SETTING

Hospitals with pediatric routine inpatient and ICU care.

PATIENTS

Children cared for in the ICU (n = 20,014) and in routine care units without an ICU admission (n = 20,130) from 2009 to 2016. All patients had laboratory, vital sign, and medication data.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

A calibrated, deep neural network used physiology (laboratory tests and vital signs), therapy (medications), and therapeutic intensity (number of physiology tests and medications) to model care intensity, operationalized as ICU (versus routine) care every 6 hours of a patient's hospital course. The probability of ICU care is termed the Criticality Index. First, the model demonstrated excellent separation of criticality distributions from a severity hierarchy of five patient groups: routine care, routine care for those who also received ICU care, transition from routine to ICU care, ICU care, and high-intensity ICU care. Second, model performance assessed with statistical metrics was excellent with an area under the curve for the receiver operating characteristic of 0.95 for 327,189 6-hour time periods, excellent calibration, sensitivity of 0.817, specificity of 0.892, accuracy of 0.866, and precision of 0.799. Third, the performance in individual patients with greater than one care designation indicated as 88.03% (95% CI, 87.72-88.34) of the Criticality Indices in the more intensive locations was higher than the less intense locations.

CONCLUSIONS

The Criticality Index is a quantification of severity of illness for hospitalized children using physiology, therapy, and care intensity. This new conceptual model is applicable to clinical investigations and predicting future care needs.

Implementation of a Pediatric Early Warning Score to Improve Communication and Nursing Empowerment in a Rural District Hospital in Rwanda

Implementation of the Pediatric Early Warning Score for Resource-Limited Settings tool improved nurses’ competency and confidence in their triage capabilities. This tool has the potential to improve patient outcomes. However, staff turnover and limited physician buy-in were barriers to sustainability of the tool in low-resource settings.

Background:

Pediatric early warning (PEW) scores represent a “track-and-trigger system” that identifies clinical deterioration in a patient’s condition in the hours preceding a sentinel event. Before implementation, nurses reported feeling unprepared to identify and advocate for acutely ill patients owing to a lack of skills, vocabulary, and agency. We implemented a Pediatric Early Warning Score for Resource-Limited Settings (PEWS-RL) with nurses in a rural district hospital in Rwanda. Although PEW scores can improve clinical outcomes, empowering nurses in resource-limited settings to discuss patient acuity with physicians is a critical first step. Our primary aims were to train nurses to obtain more accurate vital signs and assess their importance as early warning signs of clinical deterioration and use PEW scores to improve communication between nurses and physicians.

Implementation:

The PEWS-RL tool implementation began with a training program that was created through discussions with nurses, physicians, and the medical director of the hospital. The program included lectures and application of learned skills through direct clinical mentorship of nurses, as well as training of physicians regarding PEWS-RL as a communication tool.

Evaluation:

The PEWS-RL protocol was evaluated based on pre- and post-tests to assess improvement in nurses’ knowledge and skill, as well as skills assessments of accurate recognition of clinical deterioration. All 6 nurses passed skill testing with >80% accuracy. Nurses’ feelings of empowerment to advocate for patients and to escalate care were assessed through pre- and post-training interviews. Nurses described increased confidence in calling for physician support.

Discussion:

Implementation of PEW scores increased nurses’ technical skills and feelings of confidence and empowerment; however, the low-resource setting presented major challenges. Barriers to sustainable implementation include the rapid ward staff turnover as well as limited physician buy-in. Nevertheless, the PEWS-RL tool has the potential to empower nurses and improve patient outcomes if fully embraced by staff.

Progression of vital signs during ambulance transport categorised by a paediatric triage model: a population-based historical cohort study

OBJECTIVES

To examine the severity and progression of acute illness or injury in children using vital signs obtained during ambulance transport and categorised according to a paediatric triage model.

DESIGN

A population-based historical cohort study using data from prehospital patient medical records linked to a national civil registration database.

SETTING

Emergency medical services providing ground-level transport in a mixed urban-rural region with three hospitals in Denmark.

PARTICIPANTS

25 039 events with patients aged <18 years attended by emergency medical services dispatched after a 1-1-2 emergency call during the years 2006-2018.

PRIMARY AND SECONDARY OUTCOME MEASURES

Distribution of the first observed vital signs according to a paediatric triage model: heart rate, Glasgow Coma Score, respiratory rate, oxygen saturation and oxygen treatment, and proportion of patients progressing to a triage score with a lower level of urgency during ambulance transport.

RESULTS

The proportion of patients with the first observed vital signs outside the normal age-specific range was as follows: 33.6% for heart rate, 15.3% for Glasgow Coma Score, 17.4% for respiratory rate and 37.4% for oxygen saturation regardless of oxygen treatment. The proportion of patients progressing to a triage score with a lower level of urgency during transport varied with age: 146/354 (41.2%) for age 0-2 months, 440/986 (44.6%) for age 3-11 months, 1278/3212 (39.8%) for age 1-2 years, 967/2814 (34.4%) for age 3-7 years and 4029/13 864 (29.1%) for age 8-17 years (p<0.001). One-day mortality was 3.05 deaths per 1000 patient-days (95% CI 2.43 to 3.83).

CONCLUSIONS

One third of the patients' condition progressed to a triage score with a lower level of urgency during ambulance transport. Vital sign documentation in paediatric patients was incomplete, and educational initiatives should be taken to increase documentation of vital signs, especially in patients aged ≤2 years.

Integrating a Machine Learning System Into Clinical Workflows: Qualitative Study

Background

Machine learning models have the potential to improve diagnostic accuracy and management of acute conditions. Despite growing efforts to evaluate and validate such models, little is known about how to best translate and implement these products as part of routine clinical care.

Objective

This study aims to explore the factors influencing the integration of a machine learning sepsis early warning system (Sepsis Watch) into clinical workflows.

Methods

We conducted semistructured interviews with 15 frontline emergency department physicians and rapid response team nurses who participated in the Sepsis Watch quality improvement initiative. Interviews were audio recorded and transcribed. We used a modified grounded theory approach to identify key themes and analyze qualitative data.

Results

A total of 3 dominant themes emerged: perceived utility and trust, implementation of Sepsis Watch processes, and workforce considerations. Participants described their unfamiliarity with machine learning models. As a result, clinician trust was influenced by the perceived accuracy and utility of the model from personal program experience. Implementation of Sepsis Watch was facilitated by the easy-to-use tablet application and communication strategies that were developed by nurses to share model outputs with physicians. Barriers included the flow of information among clinicians and gaps in knowledge about the model itself and broader workflow processes.

Conclusions

This study generated insights into how frontline clinicians perceived machine learning models and the barriers to integrating them into clinical workflows. These findings can inform future efforts to implement machine learning interventions in real-world settings and maximize the adoption of these interventions.

Pediatric Life Support: 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations

This 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations (CoSTR) for pediatric life support is based on the most extensive evidence evaluation ever performed by the Pediatric Life Support Task Force. Three types of evidence evaluation were used in this review: systematic reviews, scoping reviews, and evidence updates. Per agreement with the evidence evaluation recommendations of the International Liaison Committee on Resuscitation, only systematic reviews could result in a new or revised treatment recommendation. Systematic reviews performed for this 2020 CoSTR for pediatric life support included the topics of sequencing of airway-breaths-compressions versus compressions-airway-breaths in the delivery of pediatric basic life support, the initial timing and dose intervals for epinephrine administration during resuscitation, and the targets for oxygen and carbon dioxide levels in pediatric patients after return of spontaneous circulation. The most controversial topics included the initial timing and dose intervals of epinephrine administration (new treatment recommendations were made) and the administration of fluid for infants and children with septic shock (this latter topic was evaluated by evidence update). All evidence reviews identified the paucity of pediatric data and the need for more research involving resuscitation of infants and children.

Pediatric Life Support: 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations

This 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations (CoSTR) for pediatric life support is based on the most extensive evidence evaluation ever performed by the Pediatric Life Support Task Force. Three types of evidence evaluation were used in this review: systematic reviews, scoping reviews, and evidence updates. Per agreement with the evidence evaluation recommendations of the International Liaison Committee on Resuscitation, only systematic reviews could result in a new or revised treatment recommendation. Systematic reviews performed for this 2020 CoSTR for pediatric life support included the topics of sequencing of airway-breaths-compressions versus compressions-airway-breaths in the delivery of pediatric basic life support, the initial timing and dose intervals for epinephrine administration during resuscitation, and the targets for oxygen and carbon dioxide levels in pediatric patients after return of spontaneous circulation. The most controversial topics included the initial timing and dose intervals of epinephrine administration (new treatment recommendations were made) and the administration of fluid for infants and children with septic shock (this latter topic was evaluated by evidence update). All evidence reviews identified the paucity of pediatric data and the need for more research involving resuscitation of infants and children.

Part 7: Systems of Care: 2020 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care

Survival after cardiac arrest requires an integrated system of people, training, equipment, and organizations working together to achieve a common goal. Part 7 of the 2020 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care focuses on systems of care, with an emphasis on elements that are relevant to a broad range of resuscitation situations. Previous systems of care guidelines have identified a Chain of Survival, beginning with prevention and early identification of cardiac arrest and proceeding through resuscitation to post-cardiac arrest care. This concept is reinforced by the addition of recovery as an important stage in cardiac arrest survival. Debriefing and other quality improvement strategies were previously mentioned and are now emphasized. Specific to out-of-hospital cardiac arrest, this Part contains recommendations about community initiatives to promote cardiac arrest recognition, cardiopulmonary resuscitation, public access defibrillation, mobile phone technologies to summon first responders, and an enhanced role for emergency telecommunicators. Germane to in-hospital cardiac arrest are recommendations about the recognition and stabilization of hospital patients at risk for developing cardiac arrest. This Part also includes recommendations about clinical debriefing, transport to specialized cardiac arrest centers, organ donation, and performance measurement across the continuum of resuscitation situations.

More Than 500 Kids Could Be Saved Each Year! Ten Consensus Actions to Improve Quality of Pediatric Resuscitation in DACH-Countries (Austria, Germany, and Switzerland)

• Quality and outcome of pediatric resuscitation often does not achieve recommended goals. • Quality improvement initiatives with the aim of better survival rates and decreased morbidity of resuscitated children are urgently needed. • These initiatives should include an action framework for a comprehensive, fundamental, and interprofessional reorientation of clinical and organizational structures concerning resuscitation and post-resuscitation care of children. • The authors of this DACH position statement suggest the implementation of 10 evidence-based actions (for out-of-hospital and in-house cardiac arrests) that should improve survival rates and decrease morbidity of resuscitated children with better neurological outcome and quality of life.

Artificial intelligence algorithm for predicting cardiac arrest using electrocardiography

BACKGROUND

In-hospital cardiac arrest is a major burden in health care. Although several track-and-trigger systems are used to predict cardiac arrest, they often have unsatisfactory performances. We hypothesized that a deep-learning-based artificial intelligence algorithm (DLA) could effectively predict cardiac arrest using electrocardiography (ECG). We developed and validated a DLA for predicting cardiac arrest using ECG.

METHODS

We conducted a retrospective study that included 47,505 ECGs of 25,672 adult patients admitted to two hospitals, who underwent at least one ECG from October 2016 to September 2019. The endpoint was occurrence of cardiac arrest within 24 h from ECG. Using subgroup analyses in patients who were initially classified as non-event, we confirmed the delayed occurrence of cardiac arrest and unexpected intensive care unit transfer over 14 days.

RESULTS

We used 32,294 ECGs of 10,461 patients and 4483 ECGs of 4483 patients from a hospital were used as development and internal validation data, respectively. Additionally, 10,728 ECGs of 10,728 patients from another hospital were used as external validation data, which confirmed the robustness of the developed DLA. During internal and external validation, the areas under the receiver operating characteristic curves of the DLA in predicting cardiac arrest within 24 h were 0.913 and 0.948, respectively. The high risk group of the DLA showed a significantly higher hazard for delayed cardiac arrest (5.74% vs. 0.33%, P < 0.001) and unexpected intensive care unit transfer (4.23% vs. 0.82%, P < 0.001). A sensitivity map of the DLA displayed the ECG regions used to predict cardiac arrest, with the DLA focused most on the QRS complex.

CONCLUSIONS

Our DLA successfully predicted cardiac arrest using diverse formats of ECG. The results indicate that cardiac arrest could be screened and predicted not only with a conventional 12-lead ECG, but also with a single-lead ECG using a wearable device that employs our DLA.

High-impact RCTs without prospective informed consent: a systematic review

The prevalence of randomized controlled trials (RCTs) performed without fully informed prospective consent from subjects is unknown. We performed this study to estimate the prevalence of high-impact RCTs performed without informed consent from all subjects and examine whether such trials are becoming more prevalent. We performed a systematic review of English-language RCTs published from 2014 through 2018 identified in Scopus and sorted to identify the top 100 most highly cited RCTs each year. Text search of title and abstract included terms randomized controlled or clinical trial and spelling variants thereof, and excluded metaanalyses and systematic reviews. We independently identified the most highly cited RCTs based on predefined criteria and negotiated to agreement, then independently performed keyword searches, read, abstracted and coded information regarding informed consent from each paper and again negotiated to agreement. No quality indicators were assessed. We planned descriptive qualitative analysis and appropriate quantitative analysis to examine the prevalence and characteristics of trials enrolling subjects with other than fully informed prospective consent. We find that 44 (8.8%, binomial exact 95% CI 6.5% to 11.6%) of 500 high-impact RCTs did not secure informed consent from at least some subjects. The prevalence of such trials did not change over the 5 years (OR=1.09, z=0.78, p=0.44). A majority (66%) of the trials involved emergency situations, and 40 of 44 (90.9%) of the trials involved emergency interventions, pragmatic designs, were cluster randomized, or a combination of these factors. A qualitative analysis explores the methods of and justifications for waiving informed consent in our sample of RCTs.

Performance of Pediatric Mortality Prediction Models in Low- and Middle-Income Countries: A Systematic Review and Meta-Analysis

OBJECTIVE

To describe the performance of prognostic models for mortality or clinical deterioration events among hospitalized children developed or validated in low- and middle-income countries.

STUDY DESIGN

A medical librarian systematically searched EMBASE, Ovid Medline, Scopus, Cochrane Library, EBSCO Global Health, LILACS, African Index Medicus, African Journals Online, African Healthline, Med-Carib, and Global Index Medicus (from 2000 to October 2019). We included citations that described the development or validation of a pediatric prognostic model for hospital mortality or clinical deterioration events in low- and middle-income countries. In duplicate and independently, we extracted data on included populations and model prognostic performance and evaluated risk of bias using the Prediction model Risk Of Bias Assessment Tool.

RESULTS

Of 41 279 unique citations, we included 15 studies describing 15 prognostic models for mortality and 3 models for clinical deterioration events. Six models were validated in >1 external cohort. The Lambarene Organ Dysfunction Score (0.85 [0.77-0.92]) and Signs of Inflammation in Children that Kill (0.85 [0.82-0.88]) had the highest summary C-statistics (95% CI) for discrimination. Calibration and classification measures were poorly reported. All models were at high risk of bias owing to inappropriate selection of predictor variables and handling of missing data and incomplete performance measure reporting.

CONCLUSIONS

Several prognostic models for mortality and clinical deterioration events have been validated in single cohorts, with good discrimination. Rigorous validation that conforms to current standards for prediction model studies and updating of existing models are needed before clinical implementation.

A Vital Sign-Based Model to Predict Clinical Deterioration in Hospitalized Children

OBJECTIVES

Clinical deterioration in hospitalized children is associated with increased risk of mortality and morbidity. A prediction model capable of accurate and early identification of pediatric patients at risk of deterioration can facilitate timely assessment and intervention, potentially improving survival and long-term outcomes. The objective of this study was to develop a model utilizing vital signs from electronic health record data for predicting clinical deterioration in pediatric ward patients.

DESIGN

Observational cohort study.

SETTING

An urban, tertiary-care medical center.

PATIENTS

Patients less than 18 years admitted to the general ward during years 2009-2018.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The primary outcome of clinical deterioration was defined as a direct ward-to-ICU transfer. A discrete-time logistic regression model utilizing six vital signs along with patient characteristics was developed to predict ICU transfers several hours in advance. Among 31,899 pediatric admissions, 1,375 (3.7%) experienced the outcome. Data were split into independent derivation (yr 2009-2014) and prospective validation (yr 2015-2018) cohorts. In the prospective validation cohort, the vital sign model significantly outperformed a modified version of the Bedside Pediatric Early Warning System score in predicting ICU transfers 12 hours prior to the event (C-statistic 0.78 vs 0.72; p < 0.01).

CONCLUSIONS

We developed a model utilizing six commonly used vital signs to predict risk of deterioration in hospitalized children. Our model demonstrated greater accuracy in predicting ICU transfers than the modified Bedside Pediatric Early Warning System. Our model may promote opportunities for timelier intervention and risk mitigation, thereby decreasing preventable death and improving long-term health.

Development and validation of a Paediatric Early Warning Score for use in the emergency department: a multicentre study

BACKGROUND

Paediatric Early Warning Scores (PEWSs) are being used increasingly in hospital wards to identify children at risk of clinical deterioration, but few scores exist that were designed for use in emergency care settings. To improve the prioritisation of children in the emergency department (ED), we developed and validated an ED-PEWS.

METHODS

The TrIAGE project is a prospective European observational study based on electronic health record data collected between Jan 1, 2012, and Nov 1, 2015, from five diverse EDs in four European countries (Netherlands, the UK, Austria, and Portugal). This study included data from all consecutive ED visits of children under age 16 years. The main outcome measure was a three-category reference standard (high, intermediate, low urgency) that was developed as part of the TrIAGE project as a proxy for true patient urgency. The ED-PEWS was developed based on an ordinal logistic regression model, with cross-validation by setting. After completing the study, we fully externally validated the ED-PEWS in an independent cohort of febrile children from a different ED (Greece).

FINDINGS

Of 119 209 children, 2007 (1·7%) were of high urgency and 29 127 (24·4%) of intermediate urgency, according to our reference standard. We developed an ED-PEWS consisting of age and the predictors heart rate, respiratory rate, oxygen saturation, consciousness, capillary refill time, and work of breathing. The ED-PEWS showed a cross-validated c-statistic of 0·86 (95% prediction interval 0·82-0·90) for high-urgency patients and 0·67 (0·61-0·73) for high-urgency or intermediate-urgency patients. A cutoff of score of at least 15 was useful for identifying high-urgency patients with a specificity of 0·90 (95% CI 0·87-0·92) while a cutoff score of less than 6 was useful for identifying low-urgency patients with a sensitivity of 0·83 (0·81-0·85).

INTERPRETATION

The proposed ED-PEWS can assist in identifying high-urgency and low-urgency patients in the ED, and improves prioritisation compared with existing PEWSs.

FUNDING

Stichting de Drie Lichten, Stichting Sophia Kinderziekenhuis Fonds, and the European Union's Horizon 2020 research and innovation programme.

Association between hypotension and serious illness in the emergency department: an observational study

BACKGROUND

The value of routine blood pressure measurement in the emergency department (ED) is unclear.

OBJECTIVE

To determine the association between hypotension in addition to tachycardia and the Shock Index for serious illness.

DESIGN

Observational study.

SETTING

University ED (2009-2016).

PARTICIPANTS, METHODS AND MAIN OUTCOMES

Routine data collected from consecutive children <16 years. Using logistic regression, we assessed the association between hypotension (adjusted for tachycardia) and Shock Index (ratio heart rate/blood pressure [BP]) for serious illness. The predictive accuracy (sensitivity, specificity) for hypotension and Shock Index was determined for serious illness, defined as intensive care unit (ICU) and hospital admissions.

RESULTS

We included 10 698 children with measured BP. According to three age-adjusted clinical cut-offs (Advanced Paediatric Life Support, Paediatric Advanced Life Support and Paediatric Early Warning Score), hypotension was significantly associated with ICU admission when adjusted for tachycardia (range OR 2.6-5.3). Hypotension showed low sensitivity (range 0.05-0.12) and high specificity (range 0.95-0.99) for ICU admission. Combining hypotension and tachycardia did not change the predictive value for ICU admission. Similar results were found for hospitalisation. Shock index was associated with serious illness. However, no specific cut-off value was identified in different age groups.

CONCLUSIONS

Hypotension, adjusted for tachycardia, is associated with serious illness, although its sensitivity is limited. Shock index showed an association with serious illness, but no acceptable cut-off value could be identified. Routine BP measurement in all children to detect hypotension has limited value in the ED. Future studies need to confirm which patients could benefit from BP measurement.

Late Rescue Collaborative: Reducing Non-ICU Arrests

OBJECTIVE

To reduce the frequency of non-ICU arrests through the implementation of an intramural collaborative focused on patient deterioration.

DESIGN

Prospective quality improvement project.

SETTING

Single-center, free-standing, tertiary children's hospital.

PATIENTS

All patients admitted to acute care units.

INTERVENTIONS

The Late Rescue Collaborative was formed in 2014 to monitor compliance with hospital escalation protocols and evaluate episodes of patient deterioration. The collaborative is a multidisciplinary team of physicians, nurses, and respiratory care providers. Three monthly meetings occur: 1) individual acute care unit-based meetings to evaluate trends and performance; 2) hospital-wide multidisciplinary whole group meetings to review hospital trends in deterioration and share lessons learned; and 3) steering committee to determine areas of focus. Based on these three meetings, unit- and hospital-based interventions have been put in place to improve recognition of deterioration and promote early rescue.

MEASUREMENTS AND MAIN RESULTS

Rates of rapid response team activations, unplanned transfers, and non-ICU arrest are reported. Non-ICU arrest rates fell from a baseline of 0.31 per 1,000 non-ICU patient days to a new centerline of 0.11 and sustained for 36 months. Days between non-ICU arrests increased from a baseline of 15.5 days in year 2014 to a new centerline of 61.5 days and sustained for 37 months. Mortality following non-ICU arrests fell from four in 2014 and 2015 to zero in years 2016-2018.

CONCLUSION

The Late Rescue Collaborative is an effective tool to improve patient safety by reducing non-ICU arrests.

The Vitals Risk Index-Retrospective Performance Analysis of an Automated and Objective Pediatric Early Warning System

Supplemental Digital Content is available in the text.

Introduction:

Pediatric in-hospital cardiac arrests and emergent transfers to the pediatric intensive care unit (ICU) represent a serious patient safety concern with associated increased morbidity and mortality. Some institutions have turned to the electronic health record and predictive analytics in search of earlier and more accurate detection of patients at risk for decompensation.

Methods:

Objective electronic health record data from 2011 to 2017 was utilized to develop an automated early warning system score aimed at identifying hospitalized children at risk of clinical deterioration. Five vital sign measurements and supplemental oxygen requirement data were used to build the Vitals Risk Index (VRI) model, using multivariate logistic regression. We compared the VRI to the hospital’s existing early warning system, an adaptation of Monaghan’s Pediatric Early Warning Score system (PEWS). The patient population included hospitalized children 18 years of age and younger while being cared for outside of the ICU. This dataset included 158 case hospitalizations (102 emergent transfers to the ICU and 56 “code blue” events) and 135,597 control hospitalizations.

Results:

When identifying deteriorating patients 2 hours before an event, there was no significant difference between Pediatric Early Warning Score and VRI’s areas under the receiver operating characteristic curve at false-positive rates ≤ 10% (pAUC₁₀ of 0.065 and 0.064, respectively; P = 0.74), a threshold chosen to compare the 2 approaches under clinically tolerable false-positive rates.

Conclusions:

The VRI represents an objective, simple, and automated predictive analytics tool for identifying hospitalized pediatric patients at risk of deteriorating outside of the ICU setting.

Moral Distress of Clinicians in Canadian Pediatric and Neonatal ICUs

OBJECTIVE

To quantify moral distress in neonatal ICU and PICU clinicians and to identify associated factors.

DESIGN

A national cross-sectional survey of clinicians working in an neonatal ICU or PICU. Moral distress was assessed with the Moral Distress Scale-Revised and by self-rating. Depersonalization was assessed on the subscale of the Maslach Burnout Inventory. Respondents reported their attendance at each of six hospital supports that may serve to mitigate moral distress in frontline staff. Analyses compared outcomes across respondent characteristics and hierarchical linear regression evaluated individual, ICU, hospital, and regional effects.

SETTING

Eligible ICUs were PICUs and level-3 neonatal ICUs in Canada.

SUBJECTS

Eligible participants had worked in the participating ICU for more than 3 months.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We identified 54 eligible ICUs from 31 hospitals. Forty-nine Canadian neonatal ICUs and PICUs (91%) contributed 2,852 complete responses for a 45.2% response rate. Most respondents were nurses (64.9%) or from a neonatal ICU (66.5%). The median and interquartile range Moral Distress Scale-Revised were 79 (52-113); 997 respondents (34.2%) had Moral Distress Scale-Revised scores greater than or equal to 100, and 234 respondents (8.3%) strongly agreed that work caused them significant moral distress. Nurses had a median (interquartile range) Moral Distress Scale-Revised score of 85 (57-121), 19 points higher than physicians and 8 points higher than respiratory therapists (p < 0.0001). Moral Distress Scale-Revised scores increased from 53 (35-79) for those working in ICU less than 1 year to 83 (54-120) in those working in ICU more than 30 years (p < 0.0001); 22.5% reported high degrees of depersonalization, which was associated with moral distress (p < 0.0001). Variability in Moral Distress Scale-Revised scores was explained by individual-level (92%), hospital-level (5%), and ICU-level effects (1%). Frequency of participation in potentially mitigating hospital supports had small effects (< 10 points) on mean Moral Distress Scale-Revised scores.

CONCLUSIONS

Moral distress is common in clinicians working in ICUs for children. Addressing moral distress will require interventions tailored to individuals in higher-risk groups.

Abnormal Vital Signs Predict Critical Deterioration in Hospitalized Pediatric Hematology-Oncology and Post-hematopoietic Cell Transplant Patients

Introduction: Hospitalized pediatric hematology-oncology and post-hematopoietic cell transplant (HCT) patients have frequent deterioration requiring Pediatric Intensive Care Unit (PICU) care. Critical deterioration (CD), defined as unplanned PICU transfer requiring life-sustaining interventions within 12 h, is a pragmatic metric to evaluate emergency response systems (ERS) in pediatrics, however, it has not been investigated in these patients. The goal of this study was to evaluate if CD is an appropriate metric to assess effectiveness of ERS in pediatric hematology-oncology and post-HCT patients and if it is preceded by an actionable period of vital sign changes.

Methods: A retrospective review of all unplanned PICU transfers and floor cardiopulmonary arrests in a dedicated pediatric hematology-oncology hospital between August 2014 and July 2016. Vital signs and physical exam findings 48 h prior to events were converted to Pediatric Early Warning System-Like Scores (PEWS-LS) using cardiovascular, respiratory, and neurologic criteria.

Results: There were 220 deterioration events, with 107 (48.6%) meeting criteria for CD, representing a rate of 2.98 per 1,000-inpatient-days. Using the first event per hospitalization (n = 184), patients with CD had higher mortality (17.4 vs. 7.6%, p = 0.045), fewer median ICU-free-days (21 vs. 24, p = 0.011), ventilator-free-days (25 vs. 28, p < 0.001), and vasoactive-free-days (27 vs. 28, p < 0.001). Using vital sign data 48 h prior to deterioration events, those with CD had higher PEWS-LS on PICU admission (p < 0.001), spent more time with elevated PEWS-LS prior to PICU transfer (p = 0.008 to 0.023) and had a longer time from first abnormal PEWS-LS (p = 0.007 to 0.043). Significant difference between the two groups was observed as early as 4 h prior to the event (p = 0.047).

Conclusion: Hospitalized pediatric hematology-oncology and post-HCT patients have frequent deterioration resulting in a high mortality. In these patients, CD is over 13 times more common than floor cardiopulmonary arrests and associated with higher mortality and fewer event-free days, making it a useful metric in these patients. CD is preceded by a long duration of abnormal vital signs, making it potentially preventable through earlier recognition.

Surviving sepsis campaign international guidelines for the management of septic shock and sepsis-associated organ dysfunction in children

OBJECTIVES

To develop evidence-based recommendations for clinicians caring for children (including infants, school-aged children, and adolescents) with septic shock and other sepsis-associated organ dysfunction.

DESIGN

A panel of 49 international experts, representing 12 international organizations, as well as three methodologists and three public members was convened. Panel members assembled at key international meetings (for those panel members attending the conference), and a stand-alone meeting was held for all panel members in November 2018. A formal conflict-of-interest policy was developed at the onset of the process and enforced throughout. Teleconferences and electronic-based discussion among the chairs, co-chairs, methodologists, and group heads, as well as within subgroups, served as an integral part of the guideline development process.

METHODS

The panel consisted of six subgroups: recognition and management of infection, hemodynamics and resuscitation, ventilation, endocrine and metabolic therapies, adjunctive therapies, and research priorities. We conducted a systematic review for each Population, Intervention, Control, and Outcomes question to identify the best available evidence, statistically summarized the evidence, and then assessed the quality of evidence using the Grading of Recommendations Assessment, Development, and Evaluation approach. We used the evidence-to-decision framework to formulate recommendations as strong or weak, or as a best practice statement. In addition, "in our practice" statements were included when evidence was inconclusive to issue a recommendation, but the panel felt that some guidance based on practice patterns may be appropriate.

RESULTS

The panel provided 77 statements on the management and resuscitation of children with septic shock and other sepsis-associated organ dysfunction. Overall, six were strong recommendations, 49 were weak recommendations, and nine were best-practice statements. For 13 questions, no recommendations could be made; but, for 10 of these, "in our practice" statements were provided. In addition, 52 research priorities were identified.

CONCLUSIONS

A large cohort of international experts was able to achieve consensus regarding many recommendations for the best care of children with sepsis, acknowledging that most aspects of care had relatively low quality of evidence resulting in the frequent issuance of weak recommendations. Despite this challenge, these recommendations regarding the management of children with septic shock and other sepsis-associated organ dysfunction provide a foundation for consistent care to improve outcomes and inform future research.