Priority Outcomes in Critically Ill Children: A Patient and Parent Perspective

BACKGROUND: Outcomes in pediatric critical care research are typically selected by the researcher. OBJECTIVES: (1) To identify outcomes prioritized by patients and their families following a critical illness and (2) to determine the overlap between patient-centered and researcher-selected study outcomes. METHODS: An exploratory descriptive qualitative study nested within a longitudinal cohort study conducted in 2 pediatric intensive care units (PICUs). Participants were purposively sampled from the primary cohort to ensure adequate demographic representation. Qualitative descriptive approaches based on naturalistic observation were used to collect data and analyze results. Data were coded by using the International Classification of Functioning, Disability, and Health Children and Youth (ICF-CY) framework. RESULTS: Twenty-one participants were interviewed a mean of 5.1 months after PICU discharge. Outcomes fell into 2 categories: patient-centered and family-centered. In the former, diagnosis, survival, and prognosis were key priorities during the acute critical illness. Once survival appears possible, functioning (physical, cognitive, and emotional), and factors that influence recovery (ie, rehabilitation, environment, and quality of life) are prioritized. Family-centered outcomes consisted of parents\u27 psychosocial functioning and experience of care. Patient-centered outcomes were covered well by the selected study measures of functioning, but not by the clinical outcome measures. CONCLUSION: Functioning and quality of life are key patient-centered outcomes during recovery from critical illness. These are not well captured by end points typically used in PICU studies. These results justify the importance of patient- and family-centered outcomes in PICU research and a need to determine how these outcomes can be comprehensively measured

Early mobilization in the critical care unit: A review of adult and pediatric literature.

Early mobilization of critically ill patients is beneficial, suggesting that it should be incorporated into daily clinical practice. Early passive, active, and combined progressive mobilizations can be safely initiated in intensive care units (ICUs). Adult patients receiving early mobilization have fewer ventilator-dependent days, shorter ICU and hospital stays, and better functional outcomes. Pediatric ICU data are limited, but recent studies also suggest that early mobilization is achievable without increasing patient risk. In this review, we provide a current and comprehensive appraisal of ICU mobilization techniques in both adult and pediatric critically ill patients. Contraindications and perceived barriers to early mobilization, including cost and health care provider views, are identified. Methods of overcoming barriers to early mobilization and enhancing sustainability of mobilization programs are discussed. Optimization of patient outcomes will require further studies on mobilization timing and intensity, particularly within specific ICU populations

Parental perspectives on the transfer process for critically ill children

Objective: To understand parental stressors and identify potential stress-mitigators during interfacility transfer of critically ill children. Methods: Descriptive qualitative multi-case study using semi-structured interviews. This study involved caregivers of patients admitted to the Paediatric Critical Care Unit at Children’s Hospital, London Health Sciences Centre transported from outlying hospitals. Study participants were recruited through purposeful sampling. Interviews were recorded, transcribed verbatim and manually de-identified. Coding was performed by two independent coders using a standard method of content analysis to identify common themes. Results: Themes were identified and reached saturation after twelve interviews were completed. Children were admitted primarily from Northwestern and Southwestern Ontario, at distances ranging from 36 to 1146 km. Sixty-seven percent were transported by ground and 33% were transported by air ambulance. We identified stressors (patient pain and discomfort on transport, separation anxiety, feeling of being uninvolved, general anxiety about transport, cost and logistics of return trip home, lack of support systems/loneliness and leaving other family members behind) and stress-mitigators (parental accompaniment, immediate access to the child at accepting facility, parental involvement in care/comfort, support systems – other families in hospital, support systems – staff, communication with the parents/caregivers and trust toward the transport team) associated with the transport process. Conclusions: The current study identified important parent perspectives regarding the transfer of critically ill children. We recommend that stakeholders at referral centres, transport services and accepting facilities examine their current standards regarding transport processes to ensure relevant mitigators are incorporated into their programs to improve the transport experience for critically ill children and their families

Clinical and Physiologic Factors Associated With Mode of Death in Pediatric Severe TBI

Aims and Objectives: Severe traumatic brain injury (sTBI) is the leading cause of death in children. Our aim was to determine the mode of death for children who died with sTBI in a Pediatric Critical Care Unit (PCCU) and evaluate factors associated with mortality. Methods: We performed a retrospective cohort study of all severely injured trauma patients (Injury Severity Score ≥ 12) with sTBI (Glasgow Coma Scale [GCS] ≤ 8 and Maximum Abbreviated Injury Scale ≥ 4) admitted to a Canadian PCCU (2000–2016). We analyzed mode of death, clinical factors, interventions, lab values within 24 h of admission (early) and pre-death (48 h prior to death), and reviewed meeting notes in patients who died in the PCCU. Results: Of 195 included patients with sTBI, 55 (28%) died in the PCCU. Of these, 31 (56%) had a physiologic death (neurologic determination of death or cardiac arrest), while 24 (44%) had withdrawal of life-sustaining therapies (WLST). Median (IQR) times to death were 35.2 (11.8, 86.4) hours in the physiologic group and 79.5 (17.6, 231.3) hours in the WLST group (p = 0.08). The physiologic group had higher partial thromboplastin time (PTT) within 24 h of admission (p = 0.04) and lower albumin prior to death (p = 0.04). Conclusions: Almost half of sTBI deaths in the PCCU were by WLST. There was a trend toward a longer time to death in these patients. We found few early and late (pre-death) factors associated with mode of death, namely higher PTT and lower albumin

Evaluation of Local Pediatric Out-of-Hospital Cardiac Arrest and Emergency Services Response

Background: Survival after pediatric out-of-hospital cardiac arrest is poor. Paramedic services provide critical interventions that impact survival outcomes. We aimed to describe local pediatric out-of-hospital cardiac arrest (POHCA) events and evaluate the impact of the paramedic service response to POHCA. Methods: The Canadian Resuscitation Outcomes Consortium and corresponding ambulance call records were used to evaluate deviations from best practice by paramedics for patients aged 1 day to \u3c18 years who had an atraumatic out-of-hospital cardiac arrest between 2012 and 2020 in Middlesex-London County. Deviations were any departure from protocol as defined by Middlesex-London Paramedic Services. Results: Fifty-one patients were included in this study. All POHCA events had at least one deviation, with a total of 188 deviations for the study cohort. Return of spontaneous circulation (ROSC) was achieved in 35.3% of patients and 5.8% survived to hospital discharge. All survivors developed a new, severe neurological impairment. Medication deviations were most common (n = 40, 21.3%) followed by process timing (n = 38, 20.2%), vascular access (n = 27, 14.4%), and airway (n = 27, 14.4%). A delay in vascular access was the most common deviation (n = 25, 49.0%). The median (IQR) time to epinephrine administration was 8.6 (5.90–10.95) min from paramedic arrival. Cardiac arrests occurring in public settings had more deviations than private settings (p = 0.04). ROSC was higher in events with a deviation in any circulation category (p = 0.03). Conclusion: Patient and arrest characteristics were similar to other POHCA studies. This cohort exhibited high rates of ROSC and bystander cardiopulmonary resuscitation but low survival to hospital discharge. The study was underpowered for its primary outcome of survival. The total deviations scored was low relative to the total number of tasks in a resuscitation. Epinephrine was frequently administered outside of the recommended timeframe, highlighting an important quality improvement opportunity

Pediatric severe traumatic brain injury mortality prediction determined with machine learning-based modeling

Introduction: Severe traumatic brain injury (sTBI) is a leading cause of mortality in children. As clinical prognostication is important in guiding optimal care and decision making, our goal was to create a highly discriminative sTBI outcome prediction model for mortality. Methods: Machine learning and advanced analytics were applied to the patient admission variables obtained from a comprehensive pediatric sTBI database. Demographic and clinical data, head CT imaging abnormalities and blood biochemical data from 196 children and adolescents admitted to a tertiary pediatric intensive care unit (PICU) with sTBI were integrated using feature ranking by way of a forest of randomized decision trees, and a model was generated from a reduced number of admission variables with maximal ability to discriminate outcome. Results: In total, 36 admission variables were analyzed using feature ranking with variable weighting to determine their predictive importance for mortality following sTBI. Reduction analysis utilizing Borata feature selection resulted in a parsimonious six-variable model with a mortality classification accuracy of 82%. The final admission variables that predicted mortality were: partial thromboplastin time (22%); motor Glasgow Coma Scale (21%); serum glucose (16%); fixed pupil(s) (16%); platelet count (13%) and creatinine (12%). Using only these six admission variables, a t-distributed stochastic nearest neighbor embedding algorithm plot demonstrated visual separation of sTBI patients that lived or died, with high mortality predictive ability of this model on the validation dataset (AUC = 0.90) which was confirmed with a conventional area-under-the-curve statistical approach on the total dataset (AUC = 0.91; P \u3c 0.001). Conclusions: Machine learning-based modeling identified the most clinically important prognostic factors resulting in a pragmatic, high performing prognostic tool for pediatric sTBI with excellent discriminative ability to predict mortality risk with 82% classification accuracy (AUC = 0.90). After external multicenter validation, our prognostic model might help to guide treatment decisions, aggressiveness of therapy and prepare family members and caregivers for timely end-of-life discussions and decision making. Level of evidence: III; Prognostic

Functional Recovery in Critically Ill Children, the WeeCover Multicenter Study

OBJECTIVES: To evaluate functional outcomes and evaluate predictors of an unfavorable functional outcome in children following a critical illness. DESIGN: Prospective observational longitudinal cohort study. SETTING: Two tertiary care, Canadian PICUs: McMaster Children\u27s Hospital and London Health Sciences. PATIENTS: Children 12 months to 17 years old, admitted to PICU for at least 48 hours with one or more organ dysfunction, were eligible. Patients not expected to survive, direct transfers from neonatal ICU and patients in whom long-term follow-up would not be able to be conducted, were excluded. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The primary endpoint was functional outcome up to 6 months post PICU discharge, measured using the Pediatric Evaluation of Disabilities Inventory Computer Adaptive Test. Secondary outcomes included predictors of unfavorable functional outcome, caregiver stress, health-related quality-of-life, and clinical outcomes such as mortality, length of stay, and PICU-acquired complications. One hundred eighty-two patients were enrolled; 78 children (43.6%) had functional limitations at baseline and 143 (81.5%) experienced functional deterioration following critical illness. Ninety-two (67.1%) demonstrated some functional recovery by 6 months. Higher baseline function and a neurologic insult at PICU admission were the most significant predictors of functional deterioration. Higher baseline function and increasing age were associated with slower functional recovery. Different factors affect the domains of functioning differently. Preexisting comorbidities and iatrogenic PICU-acquired morbidities were associated with persistent requirement for caregiver support (responsibility function) at 6 months. The degree of functional deterioration after critical illness was a significant predictor of increased hospital length of stay. CONCLUSIONS: This study provides new information regarding functional outcomes and the factors that influence meaningful aspects of functioning in critically ill children. Identifying patients at greatest risk and modifiable targets for improvement in PICU care guides us in developing strategies to improve functional outcomes and tailor to the rehabilitation needs of these patients and their families

Needs Assessment Survey Identifying Research Processes Which may be Improved by Automation or Artificial Intelligence: ICU Community Modeling and Artificial Intelligence to Improve Efficiency (ICU-Comma)

Background: Critical care research in Canada is conducted primarily in academically-affiliated intensive care units with established research infrastructure, including research coordinators (RCs). Recently, efforts have been made to engage community hospital ICUs in research albeit with barriers. Automation or artificial intelligence (AI) could aid the performance of routine research tasks. It is unclear which research study processes might be improved through AI automation. Methods: We conducted a cross-sectional survey of Canadian ICU research personnel. The survey contained items characterizing opinions regarding research processes that may be amenable to AI automation. We distributed the questionnaire via email distribution lists of 3 Canadian research societies. Open-ended questions were analyzed using a thematic content analysis approach. Results: A total of 49 survey responses were received (response rate: 8%). Tasks that respondents felt were time-consuming/tedious/tiresome included: screening for potentially eligible patients (74%), inputting data into case report forms (65%), and preparing internal tracking logs (53%). Tasks that respondents felt could be performed by AI automation included: screening for eligible patients (59%), inputting data into case report forms (55%), preparing internal tracking logs (51%), and randomizing patients into studies (45%). Open-ended questions identified enthusiasm for AI automation to improve information accuracy and efficiency while freeing up RCs to perform tasks that require human interaction. This enthusiasm was tempered by the need for proper AI education and oversight. Conclusions: There were balanced supportive (increased efficiency and re-allocation of tasks) and challenges (informational accuracy and oversight) with regards to AI automation in ICU research