Pediatric Critical Care Medicine Fellowship Simulation Use Survey.

OBJECTIVES: Simulation-based education is used in the U.S. Pediatric Critical Care Medicine fellowship programs, yet the prevalence and types of simulation used is unknown. A survey was developed to determine the prevalence, the perceived importance, and barriers associated with simulation-based education in these programs. DESIGN: A 43-item survey instrument was sent to all 66 U.S. Accreditation Council for Graduate Medical Education-accredited Pediatric Critical Care Medicine fellowship programs during the summer of 2018. We defined simulation broadly as "any type of simulation that involved mannequins, task trainers, standardized actors, team training, etc." SETTING: An online survey was used to obtain information regarding simulation used in Pediatric Critical Care Medicine fellowship programs. SUBJECTS: All sixty-six U.S. Accreditation Council for Graduate Medical Education-accredited Pediatric Critical Care Medicine fellowship programs were sent a survey request. MEASUREMENTS AND MAIN RESULTS: Forty-four of the 66 U.S. Accreditation Council for Graduate Medical Education-accredited Pediatric Critical Care Medicine fellowship programs (67%) responded to the survey. Ninety-eight percent of responding programs (n = 43) use simulation-based education in their Pediatric Critical Care Medicine fellowship curriculum. Most programs (56%) have incorporated simulation training into their Pediatric Critical Care Medicine fellowship curriculum in the last 4-10 years (range, <1 to >15 yr, median 4-6 yr). A variety of principles, concepts, and programs were reported as used in their simulation programs. The most commonly reported barriers to Pediatric Critical Care Medicine fellowship simulation-based education were lack of funding (56%) and lack of faculty with simulation experience (56%). The majority of programs (64%; N = 28) think simulation-based education is absolutely necessary to Pediatric Critical Care Medicine fellowship training. CONCLUSIONS: Nearly, all responding U.S. Accreditation Council for Graduate Medical Education-accredited Pediatric Critical Care Medicine fellowship programs use simulation-based education to train Pediatric Critical Care Medicine fellows with the majority perceiving simulation as absolutely necessary to Pediatric Critical Care Medicine fellow training. The reported types of simulation used in fellow training varied, as did training theories and concepts in the simulation programs. More research is needed to understand how to optimize and perhaps standardize parts of Pediatric Critical Care Medicine fellowship simulation training to improve the impact and outcomes of such training.

Interleukin-27 is a novel candidate diagnostic biomarker for bacterial infection in critically ill children.

INTRODUCTION: Differentiating between sterile inflammation and bacterial infection in critically ill patients with fever and other signs of the systemic inflammatory response syndrome (SIRS) remains a clinical challenge. The objective of our study was to mine an existing genome-wide expression database for the discovery of candidate diagnostic biomarkers to predict the presence of bacterial infection in critically ill children. METHODS: Genome-wide expression data were compared between patients with SIRS having negative bacterial cultures (n = 21) and patients with sepsis having positive bacterial cultures (n = 60). Differentially expressed genes were subjected to a leave-one-out cross-validation (LOOCV) procedure to predict SIRS or sepsis classes. Serum concentrations of interleukin-27 (IL-27) and procalcitonin (PCT) were compared between 101 patients with SIRS and 130 patients with sepsis. All data represent the first 24 hours of meeting criteria for either SIRS or sepsis. RESULTS: Two hundred twenty one gene probes were differentially regulated between patients with SIRS and patients with sepsis. The LOOCV procedure correctly predicted 86% of the SIRS and sepsis classes, and Epstein-Barr virus-induced gene 3 (EBI3) had the highest predictive strength. Computer-assisted image analyses of gene-expression mosaics were able to predict infection with a specificity of 90% and a positive predictive value of 94%. Because EBI3 is a subunit of the heterodimeric cytokine, IL-27, we tested the ability of serum IL-27 protein concentrations to predict infection. At a cut-point value of ≥5 ng/ml, serum IL-27 protein concentrations predicted infection with a specificity and a positive predictive value of >90%, and the overall performance of IL-27 was generally better than that of PCT. A decision tree combining IL-27 and PCT improved overall predictive capacity compared with that of either biomarker alone. CONCLUSIONS: Genome-wide expression analysis has provided the foundation for the identification of IL-27 as a novel candidate diagnostic biomarker for predicting bacterial infection in critically ill children. Additional studies will be required to test further the diagnostic performance of IL-27. The microarray data reported in this article have been deposited in the Gene Expression Omnibus under accession number GSE4607.

The pediatric sepsis biomarker risk model.

INTRODUCTION: The intrinsic heterogeneity of clinical septic shock is a major challenge. For clinical trials, individual patient management, and quality improvement efforts, it is unclear which patients are least likely to survive and thus benefit from alternative treatment approaches. A robust risk stratification tool would greatly aid decision-making. The objective of our study was to derive and test a multi-biomarker-based risk model to predict outcome in pediatric septic shock. METHODS: Twelve candidate serum protein stratification biomarkers were identified from previous genome-wide expression profiling. To derive the risk stratification tool, biomarkers were measured in serum samples from 220 unselected children with septic shock, obtained during the first 24 hours of admission to the intensive care unit. Classification and Regression Tree (CART) analysis was used to generate a decision tree to predict 28-day all-cause mortality based on both biomarkers and clinical variables. The derived tree was subsequently tested in an independent cohort of 135 children with septic shock. RESULTS: The derived decision tree included five biomarkers. In the derivation cohort, sensitivity for mortality was 91% (95% CI 70 - 98), specificity was 86% (80 - 90), positive predictive value was 43% (29 - 58), and negative predictive value was 99% (95 - 100). When applied to the test cohort, sensitivity was 89% (64 - 98) and specificity was 64% (55 - 73). In an updated model including all 355 subjects in the combined derivation and test cohorts, sensitivity for mortality was 93% (79 - 98), specificity was 74% (69 - 79), positive predictive value was 32% (24 - 41), and negative predictive value was 99% (96 - 100). False positive subjects in the updated model had greater illness severity compared to the true negative subjects, as measured by persistence of organ failure, length of stay, and intensive care unit free days. CONCLUSIONS: The pediatric sepsis biomarker risk model (PERSEVERE; PEdiatRic SEpsis biomarkEr Risk modEl) reliably identifies children at risk of death and greater illness severity from pediatric septic shock. PERSEVERE has the potential to substantially enhance clinical decision making, to adjust for risk in clinical trials, and to serve as a septic shock-specific quality metric.

Extracorporeal membrane oxygenation promotes survival in children with trauma related respiratory failure.

Extracorporeal membrane oxygenation (ECMO), which is used for cardiopulmonary support in many non-trauma settings, may also be of use in pediatric patients with traumatic lung injury by allowing the lung to rest and heal. We have utilized ECMO to support three multitrauma pediatric patients with posttraumatic respiratory failure in the past 2 years. We sought to review our experience at a level 1 tertiary care children's hospital in this patient population. Our outcomes along with the limited number of pediatric trauma patients previously reported in the literature suggest that ECMO may be safely and effectively used to manage respiratory failure in this patient population.

Pediatric rapid response system innovations.

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

Association Between Rapid Response Algorithms and Clinical Outcomes of Hospitalized Children.

OBJECTIVES: To evaluate whether the implementation of clinical pathways, known as pediatric rapid response algorithms, within an existing rapid response system was associated with an improvement in clinical outcomes of hospitalized children. METHODS: We retrospectively identified patients admitted to the PICU as unplanned transfers from the general medical and surgical floors at a single, freestanding children's hospital between July 1, 2017, and January 31, 2020. We examined the impact of the algorithms on the rate of critical deterioration events. We used multivariable Poisson regression and an interrupted time series analysis to measure 2 possible types of change: an immediate implementation effect and an outcome trajectory over time. RESULTS: We identified 892 patients (median age: 4 [interquartile range: 1-12] years): 615 in the preimplementation group, and 277 in the postimplementation group. Algorithm implementation was not associated with an immediate change in the rate of critical deterioration events but was associated with a downward rate trajectory over time and a postimplementation trajectory that was significantly less than the preimplementation trajectory (trajectory difference of -0.28 events per 1000 non-ICU patient days per month; 95% confidence interval -0.40 to -0.16; P < .001). CONCLUSIONS: Algorithm implementation was associated with a decrease in the rate of critical deterioration events. Because of the study's observational nature, this association may have been driven by unmeasured confounding factors and the chosen implementation point. Nevertheless, the results are a promising start for future research into how clinical pathways within a rapid response system can improve care of hospitalized patients.

Correlation of intraocular pressure with intracranial pressure in children with severe head injuries.

OBJECTIVE: To determine whether there was a correlation between tonometric measurements of the intraocular pressure and transducer measurements of the intracranial pressure in the acute setting, and whether intraocular pressure can be used as a surrogate measure of intracranial pressure. Children with traumatic brain injuries commonly develop increased intracranial pressure requiring surgical placement of a pressure transducer to measure the intracranial pressure during the acute recovery period. The increased intracranial pressure may cause engorgement of the orbital compartments via dilation of the episcleral veins and manifest as increased intraocular pressure. DESIGN: Prospective study. SETTING: Tertiary academic pediatric intensive care unit. PATIENTS: Children admitted with severe traumatic brain injury. INTERVENTIONS: Tonometric intraocular pressure measurements. MEASUREMENTS AND MAIN RESULTS: We performed an Institutional Review Board-approved, prospective study on 36 children (age range, 2.9-15.1 yrs) with traumatic brain injuries, requiring intracranial pressure monitoring. A total of 274 intraocular pressure measurements were made after placement of the pressure transducer, and concordance between the sites of injury and measurement was documented. The average age of the patients was 8.3 yrs. The mean intraocular pressure, intracranial pressure difference was -0.5 +/- 0.68 cm H2O, and the variance was 29.88 (sd, 5.47). The 95% confidence interval was between -11.22 and 10.22. With concordance between the sites of measurement and injury, the mean IOP, intracranial pressure difference was -0.02 +/- 0.61 cm H2O (variance, 23.28; sd, 4.82; 95% confidence interval, - 9.47 to 9.42). Concordance reduced the variance of the intraocular pressure, intracranial pressure discrepancy by 20.3%. The Pearson intraocular pressure-intracranial pressure regression coefficient and the Krippendorff's alpha reliability estimate analyses indicated good agreement. The patient's age or Paco2 did not influence the intraocular pressure, intracranial pressure difference. Using 20 cm H2O as a normal intracranial pressure cutoff, the intraocular pressure had a specificity of 0.7 and sensitivity of 0.97; with concordance, the values improved to 0.78 and 0.96, respectively. CONCLUSIONS: Tonometry is a useful screening surrogate measure of intracranial pressure in children with traumatic brain injuries, but seems to lack the accuracy necessary for close management of intracranial pressure in the acute posttraumatic period.

The complete clinician model.

Historically, medical education has focused on acquiring knowledge of basic science and clinical medicine. Relationship management skills are an essential aspect of excellent clinicians that may have been overlooked in the educational curriculum and undervalued in practice. The complete clinician model is a theoretical model for clinician development that describes why knowledge acquisition and relationship management are both imperative skills to refine when progressing to be an excellent clinician. Four quadrants are described, with ideal progress going from the trainee quadrant to the golden quadrant, ultimately aiming for competence in both knowledge acquisition and relationship management. The pediatric resident milestones from the Accreditation Council for Graduate Medical Education were placed in the model to underscore the importance placed on both knowledge acquisition and relationship management skills. Relationship management training should be integrated into the medical curriculum. This model may be applicable to professional education in other health care disciplines.

Operationalizing Healthcare Simulation Psychological Safety: A Descriptive Analysis of an Intervention.

INTRODUCTION: Despite efforts to prepare a psychologically safe environment, simulation participants are occasionally psychologically distressed. Instructing simulation educators about participant psychological risks and having a participant psychological distress action plan available to simulation educators may assist them as they seek to keep all participants psychologically safe. METHODS: A Simulation Participant Psychological Safety Algorithm was designed to aid simulation educators as they debrief simulation participants perceived to have psychological distress and categorize these events as mild (level 1), moderate (level 2), or severe (level 3). A prebrief dedicated to creating a psychologically safe learning environment was held constant. The algorithm was used for 18 months in an active pediatric simulation program. Data collected included level of participant psychological distress as perceived and categorized by the simulation team using the algorithm, type of simulation that participants went through, who debriefed, and timing of when psychological distress was perceived to occur during the simulation session. The Kruskal-Wallis test was used to evaluate the relationship between events and simulation type, events and simulation educator team who debriefed, and timing of event during the simulation session. RESULTS: A total of 3900 participants went through 399 simulation sessions between August 1, 2014, and January 26, 2016. Thirty-four (<1%) simulation participants from 27 sessions (7%) were perceived to have an event. One participant was perceived to have a severe (level 3) psychological distress event. Events occurred more commonly in high-intensity simulations, with novice learners and with specific educator teams. Simulation type and simulation educator team were associated with occurrence of events (P < 0.001). There was no association between event timing and event level. CONCLUSIONS: Severe psychological distress as categorized by simulation personnel using the Simulation Participant Psychological Safety Algorithm is rare, with mild and moderate events being more common. The algorithm was used to teach simulation educators how to assist a participant who may be psychologically distressed and document perceived event severity.