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

European survey on Paediatric Early Warning Systems, and other processes used to aid the recognition and response to children's deterioration on hospital wards

BACKGROUND

Internationally, there is an increasing trend in using Rapid Response Systems (RRS) to stabilize in-patient deterioration. Despite a growing evidence base, there remains limited understanding of the processes in place to aid the early recognition and response to deteriorating children in hospitals across Europe.

AIM/S

To describe the processes in place for early recognition and response to in-patient deterioration in children in European hospitals.

STUDY DESIGN

A cross-sectional opportunistic multi-centre European study, of hospitals with paediatric in-patients, using a descriptive self-reported, web-based survey, was conducted between September 2021 and March 2022. The sampling method used chain referral through members of European and national societies, led by country leads. The survey instrument was an adaptation to the survey of Recognition and Response Systems in Australia. The study received ethics approval. Descriptive analysis and Chi-squared tests were performed to compare results in European regions.

RESULTS

A total of 185 questionnaires from 21 European countries were received. The majority of respondents (n = 153, 83%) reported having written policies, protocols, or guidelines, regarding the measurement of physiological observations. Over half (n = 120, 65%) reported that their hospital uses a Paediatric Early Warning System (PEWS) and 75 (41%) reported having a Rapid Response Team (RRT). Approximately one-third (38%) reported that their hospital collects specific data about the effectiveness of their RRS, while 100 (54%) reported providing regular training and education to support it. European regional differences existed in PEWS utilization (North = 98%, Centre = 25%, South = 44%, p < .001) and process evaluation (North = 49%, Centre = 6%, South = 36%, p < .001).

CONCLUSIONS

RRS practices in European hospitals are heterogeneous. Differences in the uptake of PEWS and RRS process evaluation emerged across Europe.

RELEVANCE TO CLINICAL PRACTICE

It is important to scope practices for the safe monitoring and management of deteriorating children in hospital across Europe. To reduce variance in practice, a consensus statement endorsed by paediatric and intensive care societies could provide guidance and resources to support PEWS implementation and for the operational governance required for continuous quality improvement.

Risk Factors for Deterioration Events in the Pediatric Acute Care Setting

OBJECTIVES

Rapid response system (RRS) activations resulting in emergency transfers (ETs) and codes outside the ICU are associated with increased mortality and length of stay. We aimed to evaluate the patient and care team characteristics of RRS activations resulting in ETs and codes outside the ICU (together classified as "deterioration events") versus those that did not result in a deterioration event.

METHODS

For each RRS activation at our institution from 2019 to 2021, data were gathered on patient demographics and medical diagnoses, care team and treatment factors, and ICU transfer. Descriptive statistics, bivariate analyses, and multivariable logistic regression using a backward elimination model selection method were performed to assess potential risk factors for deterioration events.

RESULTS

Over the 3-year period, 1765 RRS activations were identified. Fifty-three (3%) activations were deemed acute care codes, 64 (4%) were noncode ETs, 921 (52%) resulted in nonemergent transfers to an ICU, and 727 (41%) patients remained in an acute care unit. In a multivariable model, any complex chronic condition (adjusted odds ratio, 6.26; 95% confidence interval, 2.83-16.60) and hematology/oncology service (adjusted odds ratio, 2.19; 95% confidence interval, 1.28-3.74) were independent risk factors for a deterioration event.

CONCLUSIONS

Patients with medical complexity and patients on the hematology/oncology service had a higher risk of deterioration events than other patients with RRS activations. Further analyzing how our hospital evaluates and treats these specific patient populations is critical as we develop targeted interventions to reduce deterioration events.

Parents' Trigger Tool for Children with Medical Complexity - PAT-CMC: Development of a recognition tool for clinical deterioration at home

AIM

To develop a trigger tool for parents and lay caregivers of children with medical complexity (CMC) at home and to validate its content.

DESIGN

This was a multi-method study, using qualitative data, a Delphi method and a concept mapping approach.

METHODS

A three-round electronic Delphi was performed from December 2021 to April 2022 with a panel of 23 expert parents and 30 healthcare providers, supplemented by a preliminary qualitative exploration of children's signs of deterioration and three consensus meetings to develop the PArents' Trigger Tool for Children with Medical Complexity (PAT-CMC). Cognitive interviews with parents were performed to assess the comprehensiveness and comprehensibility of the tool. The COREQ checklist, the COSMIN guidelines and the CREDES guidelines guided the reporting respectively of the qualitative study, the development and content validity of the trigger tool and the Delphi study.

RESULTS

The PAT-CMC was developed and its content validated to recognize clinical deterioration at home. The tool consists of 7 main clusters of items: Breathing, Heart, Devices, Behaviour, Neuro-Muscular, Nutrition/Hydration and Other Concerns. A total of 23 triggers of deterioration were included and related to two recommendations for escalation of care, using a traffic light coding system.

CONCLUSION

Priority indicators of clinical deterioration of CMC were identified and integrated into a validated trigger tool designed for parents or other lay caregivers at home, to recognize signs of acute severe illness and initiate healthcare interventions.

IMPACT

The PAT-CMC was developed to guide families in recognizing signs of deterioration in CMC and has potential for initiating an early escalation of care. This tool may also be useful to support education provided by healthcare providers to families before hospital discharge.

PATIENT OR PUBLIC CONTRIBUTION

Parents of CMC were directly involved in the selection of relevant indicators of children's clinical deterioration and the development of the trigger tool. They were not involved in the design, conducting, reporting or dissemination plans of this research.

Predicting transfers to intensive care in children using CEWT and other early warning systems

Background and Objective

The Children's Early Warning Tool (CEWT), developed in Australia, is widely used in many countries to monitor the risk of deterioration in hospitalized children. Our objective was to compare CEWT prediction performance against a version of the Bedside Pediatric Early Warning Score (Bedside PEWS), Between the Flags (BTF), and the pediatric Calculated Assessment of Risk and Triage (pCART).

Methods

We conducted a retrospective observational study of all patient admissions to the Comer Children's Hospital at the University of Chicago between 2009-2019. We compared performance for predicting the primary outcome of a direct ward-to-intensive care unit (ICU) transfer within the next 12 h using the area under the receiver operating characteristic curve (AUC). Alert rates at various score thresholds were also compared.

Results

Of 50,815 ward admissions, 1,874 (3.7%) experienced the primary outcome. Among patients in Cohort 1 (years 2009-2017, on which the machine learning-based pCART was trained), CEWT performed slightly worse than Bedside PEWS but better than BTF (CEWT AUC 0.74 vs. Bedside PEWS 0.76, P < 0.001; vs. BTF 0.66, P < 0.001), while pCART performed best for patients in Cohort 2 (years 2018-2019, pCART AUC 0.84 vs. CEWT AUC 0.79, P < 0.001; vs. BTF AUC 0.67, P < 0.001; vs. Bedside PEWS 0.80, P < 0.001). Sensitivity, specificity, and positive predictive values varied across all four tools at the examined thresholds for alerts.

Conclusion

CEWT has good discrimination for predicting which patients will likely be transferred to the ICU, while pCART performed the best.

Impact of Rapid Response Teams on Pediatric Care: An Interrupted Time Series Analysis of Unplanned PICU Admissions and Cardiac Arrests

Pediatric rapid response teams (RRTs) are expected to significantly lower pediatric mortality in healthcare settings. This study evaluates RRTs' effectiveness in decreasing cardiac arrests and unexpected Pediatric Intensive Care Unit (PICU) admissions. A quasi-experimental study (2014-2017) at King Abdulaziz University Hospital, Jeddah, Saudi Arabia, involved 3261 pediatric inpatients, split into pre-intervention (1604) and post-intervention (1657) groups. Baseline pediatric warning scores and monthly data on admissions, transfers, arrests, and mortality were analyzed pre- and post-intervention. Statistical methods including bootstrapping, segmented regression, and a Zero-Inflation Poisson model were employed to ensure a comprehensive evaluation of the intervention's impact. RRT was activated 471 times, primarily for respiratory distress (29.30%), sepsis (22.30%), clinical anxiety (13.80%), and hematological abnormalities (6.7%). Family concerns triggered 0.1% of activations. Post-RRT implementation, unplanned PICU admissions significantly reduced (RR = 0.552, 95% CI 0.485-0.628, p < 0.0001), and non-ICU cardiac arrests were eliminated (RR = 0). Patient care improvement was notable, with a -9.61 coefficient for PICU admissions (95% CI: -12.65 to -6.57, p < 0.001) and a -1.641 coefficient for non-ICU cardiac arrests (95% CI: -2.22 to -1.06, p < 0.001). Sensitivity analysis showed mixed results for PICU admissions, while zero-inflation Poisson analysis confirmed a reduction in non-ICU arrests. The deployment of pediatric RRTs is associated with fewer unexpected PICU admissions and non-ICU cardiopulmonary arrests, indicating improved PICU management. Further research using robust scientific methods is necessary to conclusively determine RRTs' clinical benefits.

External evaluation of the Dynamic Criticality Index: A machine learning model to predict future need for ICU care in hospitalized pediatric patients

OBJECTIVE

To assess the single site performance of the Dynamic Criticality Index (CI-D) models developed from a multi-institutional database to predict future care. Secondarily, to assess future care-location predictions in a single institution when CI-D models are re-developed using single-site data with identical variables and modeling methods. Four CI-D models were assessed for predicting care locations >6-12 hours, >12-18 hours, >18-24 hours, and >24-30 hours in the future.

DESIGN

Prognostic study comparing multi-institutional CI-D models' performance in a single-site electronic health record dataset to an institution-specific CI-D model developed using identical variables and modelling methods. The institution did not participate in the multi-institutional dataset.

PARTICIPANTS

All pediatric inpatients admitted from January 1st 2018 -February 29th 2020 through the emergency department.

MAIN OUTCOME(S) AND MEASURE(S)

The main outcome was inpatient care in routine or ICU care locations.

RESULTS

A total of 29,037 pediatric hospital admissions were included, with 5,563 (19.2%) admitted directly to the ICU, 869 (3.0%) transferred from routine to ICU care, and 5,023 (17.3%) transferred from ICU to routine care. Patients had a median [IQR] age 68 months (15-157), 47.5% were female and 43.4% were black. The area under the receiver operating characteristic curve (AUROC) for the multi-institutional CI-D models applied to a single-site test dataset was 0.493-0.545 and area under the precision-recall curve (AUPRC) was 0.262-0.299. The single-site CI-D models applied to an independent single-site test dataset had an AUROC 0.906-0.944 and AUPRC range from 0.754-0.824. Accuracy at 0.95 sensitivity for those transferred from routine to ICU care was 72.6%-81.0%. Accuracy at 0.95 specificity was 58.2%-76.4% for patients who transferred from ICU to routine care.

CONCLUSION AND RELEVANCE

Models developed from multi-institutional datasets and intended for application to individual institutions should be assessed locally and may benefit from re-development with site-specific data prior to deployment.

Development and Temporal Validation of a Machine Learning Model to Predict Clinical Deterioration

OBJECTIVES

Early warning scores detecting clinical deterioration in pediatric inpatients have wide-ranging performance and use a limited number of clinical features. This study developed a machine learning model leveraging multiple static and dynamic clinical features from the electronic health record to predict the composite outcome of unplanned transfer to the ICU within 24 hours and inpatient mortality within 48 hours in hospitalized children.

METHODS

Using a retrospective development cohort of 17 630 encounters across 10 388 patients, 2 machine learning models (light gradient boosting machine [LGBM] and random forest) were trained on 542 features and compared with our institutional Pediatric Early Warning Score (I-PEWS).

RESULTS

The LGBM model significantly outperformed I-PEWS based on receiver operating characteristic curve (AUROC) for the composite outcome of ICU transfer or mortality for both internal validation and temporal validation cohorts (AUROC 0.785 95% confidence interval [0.780-0.791] vs 0.708 [0.701-0.715] for temporal validation) as well as lead-time before deterioration events (median 11 hours vs 3 hours; P = .004). However, LGBM performance as evaluated by precision recall curve was lesser in the temporal validation cohort with associated decreased positive predictive value (6% vs 29%) and increased number needed to evaluate (17 vs 3) compared with I-PEWS.

CONCLUSIONS

Our electronic health record based machine learning model demonstrated improved AUROC and lead-time in predicting clinical deterioration in pediatric inpatients 24 to 48 hours in advance compared with I-PEWS. Further work is needed to optimize model positive predictive value to allow for integration into clinical practice.

Association between mortality and critical events within 48 hours of transfer to the pediatric intensive care unit

Introduction

Critical deterioration in hospitalized children, defined as ward to pediatric intensive care unit (PICU) transfer followed by mechanical ventilation (MV) or vasoactive infusion (VI) within 12 h, has been used as a primary metric to evaluate the effectiveness of clinical interventions or quality improvement initiatives. We explore the association between critical events (CEs), i.e., MV or VI events, within the first 48 h of PICU transfer from the ward or emergency department (ED) and in-hospital mortality.

Methods

We conducted a retrospective study of a cohort of PICU transfers from the ward or the ED at two tertiary-care academic hospitals. We determined the association between mortality and occurrence of CEs within 48 h of PICU transfer after adjusting for age, gender, hospital, and prior comorbidities.

Results

Experiencing a CE within 48 h of PICU transfer was associated with an increased risk of mortality [OR 12.40 (95% CI: 8.12-19.23, P < 0.05)]. The increased risk of mortality was highest in the first 12 h [OR 11.32 (95% CI: 7.51-17.15, P < 0.05)] but persisted in the 12-48 h time interval [OR 2.84 (95% CI: 1.40-5.22, P < 0.05)]. Varying levels of risk were observed when considering ED or ward transfers only, when considering different age groups, and when considering individual 12-h time intervals.

Discussion

We demonstrate that occurrence of a CE within 48 h of PICU transfer was associated with mortality after adjusting for confounders. Studies focusing on the impact of quality improvement efforts may benefit from using CEs within 48 h of PICU transfer as an additional evaluation metric, provided these events could have been influenced by the initiative.

Expert opinion on evidence after the 2020 Korean Cardiopulmonary Resuscitation Guidelines: a secondary publication

Considerable evidence has been published since the 2020 Korean Cardiopulmonary Resuscitation Guidelines were reported. The International Liaison Committee on Resuscitation (ILCOR) also publishes the Consensus on CPR and Emergency Cardiovascular Care Science with Treatment Recommendations (CoSTR) summary annually. This review provides expert opinions by reviewing the recent evidence on CPR and ILCOR treatment recommendations. The authors reviewed the CoSTR summary published by ILCOR in 2021 and 2022. PICO (patient, intervention, comparison, outcome) questions for each topic were reviewed using a systemic or scoping review methodology. Two experts were appointed for each question and reviewed the topic independently. Topics suggested by the reviewers for revision or additional description of the guidelines were discussed at a consensus conference. Forty-three questions were reviewed, including 15 on basic life support, seven on advanced life support, two on pediatric life support, 11 on neonatal life support, six on education and teams, one on first aid, and one related to COVID-19. Finally, the current Korean CPR Guideline was maintained for 28 questions, and expert opinions were suggested for 15 questions.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Pediatric vital signs monitoring in hospital wards: Recognition systems and factors influencing nurses' attitudes and practices

AIMS

To describe: 1) systems in place for recognition and response to deteriorating children in Italy, 2) attitudes and practices of registered nurses (RN) towards vital signs (VS) monitoring in pediatric wards, 3) the associations of nurses attitudes and pratices with nurses' and organizational characteristics.

DESIGN AND METHODS

A multicentre cross-sectional correlational study. Data were collected between January-May 2020 using: an adapted version of the 'Survey on Recognition and Response Systems in Australia', and the 'Ped-V Scale'. Descriptive and adjusted linear regression analysis was performed, accounting for clustering.

RESULTS

Ten Italian hospitals participated, 432 RNs responded to the Ped-V scale (response rate = 52%). Five (50%) hospitals had a VS policy in place, three hospitals (30%) had a Pediatric Early Warning System (PEWS), almost all hospitals had a system in place to respond to deteriorating children. Following multivariate regression analysis, having a PEWS was significantly associated with Ped-V scale 'Workload', 'Clinical competence', 'Standardization' dimensions; gender was associated with 'key indicators' and pediatric surgical ward with 'Clinical competence'.

CONCLUSIONS

The use of VS policies and PEWS was not consistent across hospitals caring for children in Italy. Nurses' attitudes and practices (i.e., perception of workload, and clinical competence) were significantly lower in hospitals with increased complexity of care/PEWS. Gender was significantly associated with knowledge scores.

PRACTICE IMPLICATIONS

System strategies to improve nurses' attitudes and practices towards VS monitoring and education are warranted to support effective behaviors towards VS monitoring, their interpretation, and appropriate communication to activate the efferent limb of the rapid response system.

Evaluating the Validity of the Responses to Illness Severity Quantification Score to Discriminate Illness Severity and Level of Care Transitions in Hospitalized Children with Severe Acute Malnutrition

OBJECTIVE

To evaluate the validity of the Responses to Illness Severity Quantification (RISQ) score to discriminate illness severity and transitions between levels of care during hospitalization.

STUDY DESIGN

A prospective observational study conducted in Maiduguri, Nigeria, enrolled inpatients aged 1-59 months with severe acute malnutrition. The primary outcome was the RISQ score associated with the patient state. Heart and respiratory rate, oxygen saturation, respiratory effort, oxygen use, temperature, and level of consciousness are summed to calculate the RISQ score. Five states were defined by levels of care and hospital discharge outcome. The states were classified hierarchically, reflecting illness severity: hospital mortality was the most severe state, then intensive care unit (ICU), care in the stabilization phase (SP), care in the rehabilitation phase (RP), and lowest severity, survival at hospital discharge. A multistate statistical model examined performance of the RISQ score in predicting clinical states and transitions.

RESULTS

Of 903 children enrolled (mean age, 14.6 months), 63 (7%) died. Mean RISQ scores during care in each phase were 3.5 (n = 2265) in the ICU, 1.7 (n = 6301) in the SP, and 1.5 (n = 2377) in the RP. Mean scores and HRs for a 3-point change in score at transitions: ICU to death, 6.9 (HR, 1.80); SP to ICU, 2.8 (HR, 2.00); ICU to SP, 2.0 (HR, 0.5); and RP to discharge, 1.4 (HR, 0.91).

CONCLUSIONS

The RISQ score can discriminate between points of escalation or de-escalation of care and reflects illness severity in hospitalized children with severe acute malnutrition. Evaluation of clinical implementation and demonstration of benefit will be important before widespread adoption.

The Need for a Standard Outcome for Clinical Deterioration in Children's Hospitals

Unrecognized clinical deterioration is a common and significant source of preventable harm to hospitalized children. Yet, unlike other sources of preventable harm, clinical deterioration outside of the ICU lacks a clear, "gold standard" outcome to guide prevention efforts. This gap limits multicenter learning, which is crucial for identifying effective and generalizable interventions for harm prevention. In fact, to date, no coordinated safety/quality initiative currently exists targeting prevention of harm from unrecognized clinical deterioration in hospitalized pediatric patients, which is startling given the morbidity and mortality risk patients incur. In this article, we compare existing outcomes for evaluating clinical deterioration outside of the ICU, highlighting sources of variation and vulnerability. The broader aim of this article is to highlight the need for a standard, consensus outcome for evaluating clinical deterioration outside of the ICU, which is a critical first step to preventing this type of harm.

Effect of paediatric early warning systems (PEWS) implementation on clinical deterioration event mortality among children with cancer in resource-limited hospitals in Latin America: a prospective, multicentre cohort study

BACKGROUND

Paediatric early warning systems (PEWS) aid in the early identification of clinical deterioration events in children admitted to hospital. We aimed to investigate the effect of PEWS implementation on mortality due to clinical deterioration in children with cancer in 32 resource-limited hospitals across Latin America.

METHODS

Proyecto Escala de Valoración de Alerta Temprana (Proyecto EVAT) is a quality improvement collaborative to implement PEWS in hospitals providing childhood cancer care. In this prospective, multicentre cohort study, centres joining Proyecto EVAT and completing PEWS implementation between April 1, 2017, and May 31, 2021, prospectively tracked clinical deterioration events and monthly inpatient-days in children admitted to hospital with cancer. De-identified registry data reported between April 17, 2017, and Nov 30, 2021, from all hospitals were included in analyses; children with limitations on escalation of care were excluded. The primary outcome was clinical deterioration event mortality. Incidence rate ratios (IRRs) were used to compare clinical deterioration event mortality before and after PEWS implementation; multivariable analyses assessed the correlation between clinical deterioration event mortality and centre characteristics.

FINDINGS

Between April 1, 2017, and May 31, 2021, 32 paediatric oncology centres from 11 countries in Latin America successfully implemented PEWS through Proyecto EVAT; these centres documented 2020 clinical deterioration events in 1651 patients over 556 400 inpatient-days. Overall clinical deterioration event mortality was 32·9% (664 of 2020 events). The median age of patients with clinical deterioration events was 8·5 years (IQR 3·9-13·2), and 1095 (54·2%) of 2020 clinical deterioration events were reported in male patients; data on race or ethnicity were not collected. Data were reported per centre for a median of 12 months (IQR 10-13) before PEWS implementation and 18 months (16-18) after PEWS implementation. The mortality rate due to a clinical deterioration event was 1·33 events per 1000 patient-days before PEWS implementation and 1·09 events per 1000 patient-days after PEWS implementation (IRR 0·82 [95% CI 0·69-0·97]; p=0·021). In the multivariable analysis of centre characteristics, higher clinical deterioration event mortality rates before PEWS implementation (IRR 1·32 [95% CI 1·22-1·43]; p<0·0001), being a teaching hospital (1·18 [1·09-1·27]; p<0·0001), not having a separate paediatric haematology-oncology unit (1·38 [1·21-1·57]; p<0·0001), and having fewer PEWS omissions (0·95 [0·92-0·99]; p=0·0091) were associated with a greater reduction in clinical deterioration event mortality after PEWS implementation; no association was found with country income level (IRR 0·86 [95% CI 0·68-1·09]; p=0·22) or clinical deterioration event rates before PEWS implementation (1·04 [0·97-1·12]; p=0·29).

INTERPRETATION

PEWS implementation was associated with reduced clinical deterioration event mortality in paediatric patients with cancer across 32 resource-limited hospitals in Latin America. These data support the use of PEWS as an effective evidence-based intervention to reduce disparities in global survival for children with cancer.

FUNDING

American Lebanese Syrian Associated Charities, US National Institutes of Health, and Conquer Cancer Foundation.

TRANSLATIONS

For the Spanish and Portuguese translations of the abstract see Supplementary Materials section.

Using technology to reduce critical deterioration (the DETECT study): a cost analysis of care costs at a tertiary children's hospital in the United Kingdom

BACKGROUND

Electronic early warning systems have been used in adults for many years to prevent critical deterioration events (CDEs). However, implementation of similar technologies for monitoring children across the entire hospital poses additional challenges. While the concept of such technologies is promising, their cost-effectiveness is not established for use in children. In this study we investigate the potential for direct cost savings arising from the implementation of the DETECT surveillance system.

METHODS

Data were collected at a tertiary children's hospital in the United Kingdom. We rely on the comparison between patients in the baseline period (March 2018 to February 2019) and patients in the post-intervention period (March 2020 to July 2021). These provided a matched cohort of 19,562 hospital admissions for each group. From these admissions, 324 and 286 CDEs were observed in the baseline and post-intervention period, respectively. Hospital reported costs and Health Related Group (HRG) National Costs were used to estimate overall expenditure associated with CDEs for both groups of patients.

RESULTS

Comparing post-intervention with baseline data we found a reduction in the total number of critical care days, driven by an overall reduction in the number of CDEs, however without statistical significance. Using hospital reported costs adjusted for the Covid-19 impact, we estimate a non-significant reduction of total expenditure from £16.0 million to £14.3 million (corresponding to £1.7 million of savings - 11%). Additionally, using HRG average costs, we estimated a non-significant reduction of total expenditure from £8.2 million to £ 7.2 million (corresponding to £1.1 million of savings - 13%).

DISCUSSION AND CONCLUSION

Unplanned critical care admissions for children not only impose a substantial burden on patients and families but are also costly for hospitals. Interventions aimed at reducing emergency critical care admissions can be crucial to contribute to the reduction of these episodes' costs. Even though cost reductions were identified in our sample, our results do not support the hypothesis that reducing CDEs using technology leads to a significant reduction on hospital costs.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN61279068, date of registration 07/06/2019, retrospectively registered.

Multimodality Video Acquisition System for the Assessment of Vital Distress in Children

In children, vital distress events, particularly respiratory, go unrecognized. To develop a standard model for automated assessment of vital distress in children, we aimed to construct a prospective high-quality video database for critically ill children in a pediatric intensive care unit (PICU) setting. The videos were acquired automatically through a secure web application with an application programming interface (API). The purpose of this article is to describe the data acquisition process from each PICU room to the research electronic database. Using an Azure Kinect DK and a Flir Lepton 3.5 LWIR attached to a Jetson Xavier NX board and the network architecture of our PICU, we have implemented an ongoing high-fidelity prospectively collected video database for research, monitoring, and diagnostic purposes. This infrastructure offers the opportunity to develop algorithms (including computational models) to quantify vital distress in order to evaluate vital distress events. More than 290 RGB, thermographic, and point cloud videos of each 30 s have been recorded in the database. Each recording is linked to the patient's numerical phenotype, i.e., the electronic medical health record and high-resolution medical database of our research center. The ultimate goal is to develop and validate algorithms to detect vital distress in real time, both for inpatient care and outpatient management.

Opportunities to improve diagnosis in emergency transfers to the pediatric intensive care unit

BACKGROUND

Late recognition of in-hospital deterioration is a source of preventable harm. Emergency transfers (ET), when hospitalized patients require intensive care unit (ICU) interventions within 1 h of ICU transfer, are a proximal measure of late recognition associated with increased mortality and length of stay (LOS).

OBJECTIVE

To apply diagnostic process improvement frameworks to identify missed opportunities for improvement in diagnosis (MOID) in ETs and evaluate their association with outcomes.

DESIGN, SETTINGS, AND PARTICIPANTS

A single-center retrospective cohort study of ETs, January 2015 to June 2019. ET criteria include intubation, vasopressor initiation, or≥ $\ge \phantom{\rule{}{0ex}}$ 60 mL/kg fluid resuscitation 1 h before to 1 h after ICU transfer. The primary exposure was the presence of MOID, determined using SaferDx. Cases were screened by an ICU and non-ICU physician. Final determinations were made by an interdisciplinary group. Diagnostic process improvement opportunities were identified.

MAIN OUTCOME AND MEASURES

Primary outcomes were in-hospital mortality and posttransfer LOS, analyzed by multivariable regression adjusting for age, service, deterioration category, and pretransfer LOS.

RESULTS

MOID was identified in 37 of 129 ETs (29%, 95% confidence interval [CI] 21%-37%). Cases with MOID differed in originating service, but not demographically. Recognizing the urgency of an identified condition was the most common diagnostic process opportunity. ET cases with MOID had higher odds of mortality (odds ratio 5.5; 95% CI 1.5-20.6; p = .01) and longer posttransfer LOS (rate ratio 1.7; 95% CI 1.1-2.6; p = .02).

CONCLUSION

MOID are common in ETs and are associated with increased mortality risk and posttransfer LOS. Diagnostic improvement strategies should be leveraged to support earlier recognition of clinical deterioration.

The Deterioration Risk Index: Developing and Piloting a Machine Learning Algorithm to Reduce Pediatric Inpatient Deterioration

OBJECTIVES

Develop and deploy a disease cohort-based machine learning algorithm for timely identification of hospitalized pediatric patients at risk for clinical deterioration that outperforms our existing situational awareness program.

DESIGN

Retrospective cohort study.

SETTING

Nationwide Children's Hospital, a freestanding, quaternary-care, academic children's hospital in Columbus, OH.

PATIENTS

All patients admitted to inpatient units participating in the preexisting situational awareness program from October 20, 2015, to December 31, 2019, excluding patients over 18 years old at admission and those with a neonatal ICU stay during their hospitalization.

INTERVENTIONS

We developed separate algorithms for cardiac, malignancy, and general cohorts via lasso-regularized logistic regression. Candidate model predictors included vital signs, supplemental oxygen, nursing assessments, early warning scores, diagnoses, lab results, and situational awareness criteria. Model performance was characterized in clinical terms and compared with our previous situational awareness program based on a novel retrospective validation approach. Simulations with frontline staff, prior to clinical implementation, informed user experience and refined interdisciplinary workflows. Model implementation was piloted on cardiology and hospital medicine units in early 2021.

MEASUREMENTS AND MAIN RESULTS

The Deterioration Risk Index (DRI) was 2.4 times as sensitive as our existing situational awareness program (sensitivities of 53% and 22%, respectively; p < 0.001) and required 2.3 times fewer alarms per detected event (121 DRI alarms per detected event vs 276 for existing program). Notable improvements were a four-fold sensitivity gain for the cardiac diagnostic cohort (73% vs 18%; p < 0.001) and a three-fold gain (81% vs 27%; p < 0.001) for the malignancy diagnostic cohort. Postimplementation pilot results over 18 months revealed a 77% reduction in deterioration events (three events observed vs 13.1 expected, p = 0.001).

CONCLUSIONS

The etiology of pediatric inpatient deterioration requires acknowledgement of the unique pathophysiology among cardiology and oncology patients. Selection and weighting of diverse candidate risk factors via machine learning can produce a more sensitive early warning system for clinical deterioration. Leveraging preexisting situational awareness platforms and accounting for operational impacts of model implementation are key aspects to successful bedside translation.

2022 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Pediatric Life Support; Neonatal Life Support; Education, Implementation, and Teams; and First Aid Task Forces

This is the sixth annual summary of the International Liaison Committee on Resuscitation International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations. This summary addresses the most recently published resuscitation evidence reviewed by International Liaison Committee on Resuscitation Task Force science experts. Topics covered by systematic reviews include cardiopulmonary resuscitation during transport; approach to resuscitation after drowning; passive ventilation; minimizing pauses during cardiopulmonary resuscitation; temperature management after cardiac arrest; use of diagnostic point-of-care ultrasound during cardiac arrest; use of vasopressin and corticosteroids during cardiac arrest; coronary angiography after cardiac arrest; public-access defibrillation devices for children; pediatric early warning systems; maintaining normal temperature immediately after birth; suctioning of amniotic fluid at birth; tactile stimulation for resuscitation immediately after birth; use of continuous positive airway pressure for respiratory distress at term birth; respiratory and heart rate monitoring in the delivery room; supraglottic airway use in neonates; prearrest prediction of in-hospital cardiac arrest mortality; basic life support training for likely rescuers of high-risk populations; effect of resuscitation team training; blended learning for life support training; training and recertification for resuscitation instructors; and recovery position for maintenance of breathing and prevention of cardiac arrest. Members from 6 task forces have assessed, discussed, and debated the quality of the evidence using Grading of Recommendations Assessment, Development, and Evaluation criteria and generated consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence-to-Decision Framework Highlights sections, and priority knowledge gaps for future research are listed.

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

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

Prehospital vital sign monitoring in paediatric patients: an interregional study of educational interventions

BACKGROUND

Prehospital vital sign documentation in paediatric patients is incomplete, especially in patients ≤ 2 years. The aim of the study was to increase vital sign registration in paediatric patients through specific educational initiatives.

METHODS

Prospective quasi-experimental study with interrupted time-series design in the North Denmark and South Denmark regions. The study consecutively included all children aged < 18 years attended by the emergency medical service (EMS) from 1 July 2019 to 31 December 2021. Specific educational initiatives were conducted only in the North Denmark EMS and included video learning and classroom training based on the European Paediatric Advanced Life Support principles. The primary outcome was the proportion of patients who had their respiratory rate, peripheral capillary oxygen saturation, heart rate and level of consciousness recorded at least twice. We used a binomial regression model stratified by age groups to compare proportions of the primary outcome in the pre- and post-intervention periods in each region.

RESULTS

In North Denmark, 7551 patients were included, while 15,585 patients from South Denmark were used as a reference. Virtually all of the North Denmark EMS providers completed the video learning (98.7%). The total study population involved patients aged ≤ 2 months (5.5%), 3-11 months (7.4%), 1-2 years (18.8%), 3-7 years (16.2%) and ≥ 8 years (52.1%). In the intervention region, the primary outcome increased from the pre- to the post-intervention period from 35.3% to 40.5% [95% CI for difference 3.0;7.4]. There were large variations in between age groups with increases from 18.8% to 27.4% [95% CI for difference 5.3;12.0] among patients aged ≤ 2 years, from 33.5% to 43.7% [95% CI for difference 4.9;15.5] among patients aged 3-7 years and an insignificant increase among patients aged ≥ 8 years (from 46.4% to 47.9% [95% CI for difference - 1.7;4.7]). In the region without the specific educational interventions, proportions were steady for all age groups throughout the entire study period.

CONCLUSIONS

Mandatory educational initiatives for EMS providers were associated with an increase in the extent of vital sign registration in paediatric patients ≤ 7 years. Incomplete vital registration was associated with, but not limited to non-urgent cases.

Validation of a modified bedside Pediatric Early Warning System score for detection of clinical deterioration in hospitalized pediatric oncology patients: A prospective cohort study

BACKGROUND

Hospitalized pediatric oncology patients are at risk of severe clinical deterioration. Yet Pediatric Early Warning System (PEWS) scores have not been prospectively validated in these patients. We aimed to determine the predictive performance of the modified BedsidePEWS score for unplanned pediatric intensive care unit (PICU) admission and cardiopulmonary resuscitation (CPR) in this patient population.

METHODS

We performed a prospective cohort study in an 80-bed pediatric oncology hospital in the Netherlands, where care has been nationally centralized. All hospitalized pediatric oncology patients aged 0-18 years were eligible for inclusion. A Cox proportional hazard model was estimated to study the association between BedsidePEWS score and unplanned PICU admissions or CPR. The predictive performance of the model was internally validated by bootstrapping.

RESULTS

A total of 1137 patients were included. During the study, 103 patients experienced 127 unplanned PICU admissions and three CPRs. The hazard ratio for unplanned PICU admission or CPR was 1.65 (95% confidence interval [CI]: 1.59-1.72) for each point increase in the modified BedsidePEWS score. The discriminative ability was moderate (D-index close to 0 and a C-index of 0.83 [95% CI: 0.79-0.90]). Positive and negative predictive values of modified BedsidePEWS score at the widely used cutoff of 8, at which escalation of care is required, were 1.4% and 99.9%, respectively.

CONCLUSION

The modified BedsidePEWS score is significantly associated with requirement of PICU transfer or CPR. In pediatric oncology patients, this PEWS score may aid in clinical decision-making for timing of PICU transfer.

2022 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Pediatric Life Support; Neonatal Life Support; Education, Implementation, and Teams; and First Aid Task Forces

This is the sixth annual summary of the International Liaison Committee on Resuscitation International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations. This summary addresses the most recently published resuscitation evidence reviewed by International Liaison Committee on Resuscitation Task Force science experts. Topics covered by systematic reviews include cardiopulmonary resuscitation during transport; approach to resuscitation after drowning; passive ventilation; minimizing pauses during cardiopulmonary resuscitation; temperature management after cardiac arrest; use of diagnostic point-of-care ultrasound during cardiac arrest; use of vasopressin and corticosteroids during cardiac arrest; coronary angiography after cardiac arrest; public-access defibrillation devices for children; pediatric early warning systems; maintaining normal temperature immediately after birth; suctioning of amniotic fluid at birth; tactile stimulation for resuscitation immediately after birth; use of continuous positive airway pressure for respiratory distress at term birth; respiratory and heart rate monitoring in the delivery room; supraglottic airway use in neonates; prearrest prediction of in-hospital cardiac arrest mortality; basic life support training for likely rescuers of high-risk populations; effect of resuscitation team training; blended learning for life support training; training and recertification for resuscitation instructors; and recovery position for maintenance of breathing and prevention of cardiac arrest. Members from 6 task forces have assessed, discussed, and debated the quality of the evidence using Grading of Recommendations Assessment, Development, and Evaluation criteria and generated consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence-to-Decision Framework Highlights sections, and priority knowledge gaps for future research are listed.

Utility of Pediatric Early Warning Sign Score in Predicting Outcome of PICU Admissions at a Suburban Tertiary Care Hospital

Assessment of the severity of illness is very important in intensive care unit care for quality assessment, assessing prognosis, and proper counseling. The goal of the study was to see how well the Pediatric Early Warning Sign (PEWS) score predicted the outcome of pediatric intensive care unit patients. This prospective cross-sectional study included children younger than 18 years. PEWS was calculated at presentation. The outcomes analyzed were mortality (primary outcome), need for mechanical ventilation, inotropic support, and length of stay (LOS). A median score was calculated and compared across the outcome groups. The performance of the PEWS was assessed for calibration and discrimination, and the best cutoff was determined. This study included 237 patients with a median score of 6 (range 4–9). Twenty-two (9.3%) patients required ventilator support and 66 (26.6%) inotropic support. The overall mortality rate was 5.1%, and 16.4% had prolonged LOS (>4 days). The median score of patients was significantly higher among those who died (8.5 vs. 6; p = 0.001), required ventilator support (8 vs. 6; p = 0.001), inotropic support (7 vs. 6; p = 0.030), and prolonged LOS (7 vs. 6; p = 0.001). On calibration, PEWS was found to have a good fit to predict mortality, the need for ventilator support, inotropic support, and prolonged LOS. Receiver operating characteristic curves for the PEWS model yield an area under the curve of 0.966 for mortality, 0.951 for ventilator support, 0.626 for inotropic support, and 0.760 for prolonged LOS. A cutoff value of > 7 was found to be the best to predict the outcome. PEWS is a robust tool to easily prognosticate the patient on the basis of clinical parameters.

Characteristics of Adult Rapid Response Events in a Freestanding Children's Hospital

OBJECTIVES

To describe nonhospitalized adult rapid response events (adult RREs) in a freestanding children's hospital and examine the relationship between various demographic and clinical factors with the final patient disposition.

METHODS

We retrospectively reviewed records for nonhospitalized patients ≥18 years of age from events that occurred in a freestanding pediatric hospital between January 2011 through December 2020. We examined the relationship between adult RREs and patient demographic information, medical history, interventions, and patient disposition following an adult RRE.

RESULTS

Four hundred twenty-nine events met inclusion criteria for analysis. Most events (69%) occurred in females, 49% of events occurred in family members of patients, and 47% occurred on inpatient floor and ICU areas. The most common presenting complaint was syncope or dizziness (36%). Delivery of bad news or grief response was associated with 14% of adult RREs. Overall, 46% (n = 196) of patients were transferred to the pediatric emergency department (ED). Patients requiring acute intervention or with cardiac or neurologic past medical histories were more likely to be transferred to the pediatric ED. Acute advanced cardiac life support interventions were infrequent but, of the patients taken to the pediatric ED, 1 died, and 3 were admitted to the ICU.

CONCLUSIONS

Adult RREs are common in freestanding children's hospitals and, although rare, some patients required critical care. Expertise in adult critical care management should be available to the rapid response team and additional training for the pediatric rapid response team in caring for adult nonpatients may be warranted.

2022 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Pediatric Life Support; Neonatal Life Support; Education, Implementation, and Teams; and First Aid Task Forces

This is the sixth annual summary of the International Liaison Committee on Resuscitation International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations. This summary addresses the most recently published resuscitation evidence reviewed by International Liaison Committee on Resuscitation Task Force science experts. Topics covered by systematic reviews include cardiopulmonary resuscitation during transport; approach to resuscitation after drowning; passive ventilation; minimising pauses during cardiopulmonary resuscitation; temperature management after cardiac arrest; use of diagnostic point-of-care ultrasound during cardiac arrest; use of vasopressin and corticosteroids during cardiac arrest; coronary angiography after cardiac arrest; public-access defibrillation devices for children; pediatric early warning systems; maintaining normal temperature immediately after birth; suctioning of amniotic fluid at birth; tactile stimulation for resuscitation immediately after birth; use of continuous positive airway pressure for respiratory distress at term birth; respiratory and heart rate monitoring in the delivery room; supraglottic airway use in neonates; prearrest prediction of in-hospital cardiac arrest mortality; basic life support training for likely rescuers of high-risk populations; effect of resuscitation team training; blended learning for life support training; training and recertification for resuscitation instructors; and recovery position for maintenance of breathing and prevention of cardiac arrest. Members from 6 task forces have assessed, discussed, and debated the quality of the evidence using Grading of Recommendations Assessment, Development, and Evaluation criteria and generated consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence-to-Decision Framework Highlights sections, and priority knowledge gaps for future research are listed.

Implementing a complex hospital innovation: conceptual underpinnings, program design and implementation of a complex innovation in an international multi-site hospital trial

Background

Designing implementation programs that effectively integrate complex healthcare innovations into complex settings is a fundamental aspect of knowledge translation. We describe the development of a conceptually grounded implementation program for a complex healthcare innovation and its subsequent application in pediatric hospital settings.

Methods

We conducted multiple case observations of the application of the Phased Reciprocal Implementation Synergy Model (PRISM) framework in the design and operationalization of an implementation program for a complex hospital wide innovation in pediatric hospital settings.

Results

PRISM informed the design and delivery of 10 international hospital wide implementations of the complex innovation, BedsidePEWS. Implementation and innovation specific goals, overarching implementation program design principles, and a phased-based, customizable, and context responsive implementation program including innovation specific tools and evaluation plans emerged from the experience.

Conclusion

Theoretically grounded implementation approaches customized for organizational contexts are feasible for the adoption and integration of this complex hospital-wide innovation. Attention to the fitting of the innovation to local practices, setting, organizational culture and end-user preferences can be achieved while maintaining the integrity of the innovation.

Clinical utility and acceptability of a whole-hospital, pro-active electronic paediatric early warning system (the DETECT study): A prospective e-survey of parents and health professionals

Background

Paediatric early warning systems (PEWS) are a means of tracking physiological state and alerting healthcare professionals about signs of deterioration, triggering a clinical review and/or escalation of care of children. A proactive end-to-end deterioration solution (the DETECT surveillance system) with an embedded e-PEWS that included sepsis screening was introduced across a tertiary children’s hospital. One component of the implementation programme was a sub-study to determine an understanding of the DETECT e-PEWS in terms of its clinical utility and its acceptability.

Aim

This study aimed to examine how parents and health professionals view and engage with the DETECT e-PEWS apps, with a particular focus on its clinical utility and its acceptability.

Method

A prospective, closed (tick box or sliding scale) and open (text based) question, e-survey of parents (n = 137) and health professionals (n = 151) with experience of DETECT e-PEWS. Data were collected between February 2020 and February 2021.

Results

Quantitative data were analysed using descriptive and inferential statistics and qualitative data with generic thematic analysis. Overall, both clinical utility and acceptability (across seven constructs) were high across both stakeholder groups although some challenges to utility (e.g., sensitivity of triggers within specific patient populations) and acceptability (e.g., burden related to having to carry extra technology) were identified.

Conclusion

Despite the multifaceted nature of the intervention and the complexity of implementation across a hospital, the system demonstrated clinical utility and acceptability across two key groups of stakeholders: parents and health professionals.

Escalation of care in children at high risk of clinical deterioration in a tertiary care children's hospital using the Bedside Pediatric Early Warning System

Background

Escalation and de-escalation are a routine part of high-quality care that should be matched with clinical needs. The aim of this study was to describe escalation of care in relation to the occurrence and timing of Pediatric Intensive Care Unit (PICU) admission in a cohort of pediatric inpatients with acute worsening of their clinical condition.

Methods

A monocentric, observational cohort study was performed from January to December 2018. Eligible patients were children: 1) admitted to one of the inpatient wards other than ICU; 2) under the age of 18 years at the time of admission; 3) with two or more Bedside-Paediatric-Early-Warning-System (BedsidePEWS) scores ≥ 7 recorded at a distance of at least one hour and for a period of 4 h during admission. The main outcome -the 24-h disposition – was defined as admission to PICU within 24-h of enrolment or staying in the inpatient ward. Escalation of care was measured using an eight-point scale—the Escalation Index (EI), developed by the authors. The EI was calculated every 6 h, starting from the moment the patient was considered eligible. Analyses used multivariate quantile and logistic regression models.

Results

The 228 episodes included 574 EI calculated scores. The 24-h disposition was the ward in 129 (57%) and the PICU in 99 (43%) episodes. Patients who were admitted to PICU within 24-h had higher top EI scores [median (IQR) 6 (5–7) vs 4 (3–5), p < 0.001]; higher initial BedsidePEWS scores [median (IQR) 10(8–13) vs. 9 (8–11), p = 0.02], were less likely to have a chronic disease [n = 62 (63%) vs. n = 127 (98%), p < 0.0001], and were rated by physicians as being at a higher risk of having a cardiac arrest (p = 0.01) than patients remaining on the ward. The EI increased over 24 h before urgent admission to PICU or cardiac arrest by 0.53 every 6-h interval (CI 0.37–0.70, p < 0.001), while it decreased by 0.25 every 6-h interval (CI -0.36–0.15, p < 0.001) in patients who stayed on the wards.

Conclusion

Escalation of care was related to temporal changes in severity of illness, patient background and environmental factors. The EI index can improve responses to evolving critical illness.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12887-022-03555-0.

Do paediatric early warning systems reduce mortality and critical deterioration events among children? A systematic review and meta-analysis

Aim

We conducted a systematic review and meta-analysis to answer the question: Does the implementation of Paediatric Early Warning Systems (PEWS) in the hospital setting reduce mortality, cardiopulmonary arrests, unplanned codes and critical deterioration events among children, as compared to usual care without PEWS?

Methods

We conducted a comprehensive search using Medline, EMBASE, Cochrane Central Register of Controlled Trials, Cumulative Index to Nursing and Allied Health Literature and Web of Science. We included studies published between January 2006 and April 2022 on children <18 years old performed in inpatient units and emergency departments, and compared patient populations with PEWS to those without PEWS. We excluded studies without a comparator, case control studies, systematic reviews, and studies published in non-English languages. We employed a random effects meta-analysis and synthesised the risk and rate ratios from individual studies. We used the Scottish Intercollegiate Guidelines Network (SIGN) to appraise the risk of bias.

Results

Among 911 articles screened, 15 were included for descriptive analysis. Fourteen of the 15 studies were pre- versus post-implementation studies and one was a multi-centre cluster randomised controlled trial (RCT). Among 10 studies (580,604 hospital admissions) analysed for mortality, we found an increased risk (pooled RR 1.18, 95% CI 1.01–1.38, p = 0.036) in the group without PEWS compared to the group with PEWS. The sensitivity analysis performed without the RCT (436,065 hospital admissions) showed a non-significant relationship (pooled RR 1.17, 95% CI 0.98–1.40, p = 0.087). Among four studies (168,544 hospital admissions) analysed for unplanned code events, there was an increased risk in the group without PEWS (pooled RR 1.73, 95%CI 1.01–2.96, p = 0.046) There were no differences in the rate of cardiopulmonary arrests or critical deterioration events between groups. Our findings were limited by potential confounders and imprecision among included studies.

Conclusions

Healthcare systems that implemented PEWS were associated with reduced mortality and code rates. We recognise that these gains vary depending on resource availability and efferent response systems.

PROSPERO registration: CRD42021269579.

Beyond objective measurements: Danish nurses' identification of hospitalized pediatric patients at risk of clinical deterioration - A qualitative study

PURPOSE

While the use of Pediatric Track and Trigger Tools as a standard to discriminate high level of urgency in pediatric care has received considerable attention, less focus has been given to other important factors such as nurses' clinical observations and judgement. The purpose of this study was to explore nurses' observational practice and focus on which non-measurable signs and symptoms nurses find important when identifying inpatient pediatric patients at risk of clinical deterioration.

DESIGN AND METHODS

This was an inductive qualitative study based on an interpretive description methodology. Data were obtained through participant observation of experienced nurses working in a Danish pediatric unit and focus group interviews with pediatric nurses. Field notes were taken, and focus group interviews were audio taped and transcribed. A thematic text condensation method was used to analyse data.

RESULTS

Findings revealed the following four main themes of non-measurable signs and symptoms that nurses find important when identifying children at risk of clinical deterioration: Colour and skin tone; sounds; movement patterns; behavioural signs.

CONCLUSIONS

This study suggest that pediatric patients show signs and symptoms that go beyond the objective measurements integrated in Pediatric Track and Trigger Tools and they should not be ignored as they are highly valuable to nurses who are responsible for observing inpatient pediatric patients at risk of clinical deterioration.

IMPLICATIONS

More empirical research on nurses' observational practice is recommended, especially research to identify the signs and symptoms - both measurable and non-measurable - that are significant to nurses at the bedside.

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.

Paediatric early warning systems: not a simple answer to a complex question

Paediatric early warning systems (PEWS) to reduce in-hospital mortality have been a laudable endeavour. Evaluation of their impact has rarely examined the internal validity of the components of PEWS in achieving desired outcomes. We highlight the assumptions made regarding the mode of action of PEWS and, as PEWS become more commonplace, this paper asks whether we really understand their function, process and outcome.

Risk factors for unplanned paediatric intensive care unit admission after anaesthesia—an international multicentre study

Objectives

Unplanned intensive care unit (ICU) admissions are associated with near-miss events, morbidity, and mortality. We describe the rate, resource utilization, and outcomes of paediatric patients urgently admitted directly to ICU post-anaesthesia compared to other sources of unplanned ICU admissions.

Methods

We performed a secondary analysis of data from specialist paediatric hospitals in 7 countries. Patients urgently admitted to the ICU post-anaesthesia were combined and matched with 1 to 3 unique controls from unplanned ICU admissions from other locations by age and hospital. Demographic, clinical, and outcome variables were compared using the Wilcoxon rank-sum test for continuous variables and chi-square or Fisher’s exact test for categorical variables. The effect of admission sources on binary outcomes was estimated using univariable conditional logistic regression models with stratification by matched set of anaesthesia and non-anaesthesia admission sources.

Results

Most admissions were &lt;1 year of age and for respiratory reasons. Admissions post-anaesthesia were shorter, occurred later in the day, and were more likely to be mechanically ventilated. Admissions post-anaesthesia were less likely to have had a previous ICU admission (4.8% compared to 11%, P=0.032) or PIM ‘high-risk diagnosis’ (9.5% versus 17.2%, P=0.035) but there was no difference in the number of subsequent ICU admissions. There was no difference in the PIM severity of illness score and no mortality difference between the groups.

Conclusions

Young children and respiratory indications dominated unplanned ICU admissions post-anaesthesia, which was more likely later in the day and with mechanical ventilation.

Development and External Validation of a Machine Learning Model for Prediction of Potential Transfer to the PICU

OBJECTIVES

Unrecognized clinical deterioration during illness requiring hospitalization is associated with high risk of mortality and long-term morbidity among children. Our objective was to develop and externally validate machine learning algorithms using electronic health records for identifying ICU transfer within 12 hours indicative of a child's condition.

DESIGN

Observational cohort study.

SETTING

Two urban, tertiary-care, academic hospitals (sites 1 and 2).

PATIENTS

Pediatric inpatients (age <18 yr).

INTERVENTIONS

None.

MEASUREMENT AND MAIN RESULTS

Our primary outcome was direct ward to ICU transfer. Using age, vital signs, and laboratory results, we derived logistic regression with regularization, restricted cubic spline regression, random forest, and gradient boosted machine learning models. Among 50,830 admissions at site 1 and 88,970 admissions at site 2, 1,993 (3.92%) and 2,317 (2.60%) experienced the primary outcome, respectively. Site 1 data were split longitudinally into derivation (2009-2017) and validation (2018-2019), whereas site 2 constituted the external test cohort. Across both sites, the gradient boosted machine was the most accurate model and outperformed a modified version of the Bedside Pediatric Early Warning Score that only used physiologic variables in terms of discrimination ( C -statistic site 1: 0.84 vs 0.71, p < 0.001; site 2: 0.80 vs 0.74, p < 0.001), sensitivity, specificity, and number needed to alert.

CONCLUSIONS

We developed and externally validated a novel machine learning model that identifies ICU transfers in hospitalized children more accurately than current tools. Our model enables early detection of children at risk for deterioration, thereby creating opportunities for intervention and improvement in outcomes.

Development and an initial validation of the Responses to Illness Severity Quantification (RISQ) score for severely malnourished children

Aim

To develop and perform an initial validation of a score to measure the severity of illness in hospitalised children with severe acute malnutrition (SAM).

Methods

A prospective study enrolled SAM children aged 6–59 months hospitalised in Borno State, Nigeria. Candidate items associated with inpatient mortality were combined and evaluated as candidate scores. Clinical and statistical methods were used to identify a preferred score.

Results

The 513 children enrolled had a mean age of 15.6 months of whom 48 (9%) died. Seven of the 10 evaluated items were significantly associated with mortality. Five different candidate scores were tested. The final score, Responses to Illness Severity Quantification (RISQ), included seven items: heart rate, respiratory rate, respiratory effort, oxygen saturation, oxygen delivery, temperature and level of consciousness. The mean RISQ score on admission was 2.6 in hospital survivors and 7.3 for children dying <48 h. RISQ scores <24 h before death had an area under the receiver operating characteristic curve (AUROC) of 0.93. The RISQ score performed similarly across differing clinical conditions with AUROCs 0.77–0.98 for all conditions except oedema.

Conclusion

The RISQ score can identify high‐risk malnourished children at and during hospital admission. Clinical application may help prioritise care and potentially improve survival.

Dynamic Bayesian network for predicting physiological changes, organ dysfunctions and mortality risk in critical trauma patients

BACKGROUND

Critical trauma patients are particularly prone to increased mortality risk; hence, an accurate prediction of their conditions enables early identification of patients' mortality status. Thus, we aimed to develop and validate a real-time prediction model for physiological changes, organ dysfunctions and mortality risk in critical trauma patients.

METHODS

We used Dynamic Bayesian Networks (DBNs) to model complicated relationships of physiological variables across time slices, accessing data of trauma patients from the Medical Information Mart for Intensive Care database (MIMIC-III) (n = 2915) and validated with patients' data from ICU admissions at the Changhai Hospital (ICU-CH) (n = 1909). The DBN model's evaluation included the predictive ability of physiological changes, organ dysfunctions and mortality risk.

RESULTS

Our DBN model included two static variables (age and sex) and 18 dynamic physiological variables. The differences in ratios between the real values and the 24- and 48-h predicted values of most physiological variables were within 5% in the two datasets. The accuracy of our DBN model for predicting renal, hepatic, cardiovascular and hematologic dysfunctions was more than 0.8.The calculated area under the curve (AUC) from receiver operating characteristic curves and 95% confidence interval for predicting the 24- and 48-h mortality risk were 0.977 (0.967-0.988) and 0.958 (0.945-0.971) in the MIMIC-III and 0.967 (0.947-0.987) and 0.946 (0.925-0.967) in ICU-CH.

CONCLUSIONS

A DBN is a promising method for predicting medical temporal data such as trauma patients' mortality risk, demonstrated by high AUC scores and validation by a real-life ICU scenario; thus, our DBN prediction model can be used as a real-time tool to predict physiological changes, organ dysfunctions and mortality risk during ICU admissions.

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.

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.