Peripheral arterial catheter securement and catheter survival in the pediatric intensive care unit.

BACKGROUND: Peripheral arterial catheters (PACs), and their associated complications, are common in the pediatric intensive care unit (PICU). Accidental catheter displacement and non-functional PACs are the most common complications, and this may be related to inadequate catheter securement. There is mixed guidance on the best way to secure PACs to prevent complications. The authors hypothesized that sutures would not be associated with a decreased risk of malfunction or accidental removal. METHODS: This was a single center retrospective cohort study at a quaternary-care PICU. PICU patients with a peripheral arterial catheter placed in the PICU from 7/2020 to 1/2023 were included. The primary outcome was unplanned PAC removal. A univariate and multivariate Cox proportional hazards regression analysis was performed, using patient weight, sedation, paralytic, and role of the proceduralist as covariates. The secondary outcome was survival probability. A log-rank test was used to compare survival curves. RESULTS: Of 761 PACs that met inclusion criteria in 437 unique patients, 599 were sutured (78.7%) and 162 were un-sutured (21.3%). In 257 cases (33.8%), the PAC had an unplanned removal. Among all PACs, the median duration of PAC placement was 5.3 days (IQR 2.1-10.5 days). There was an unplanned removal rate of 42.2% (68) in the un-sutured group and 31.4% (188) in the sutured group (p < 0.001). In multivariable analysis, sutured PACs were also associated with a lower rate of unplanned removal (hazard ratio, 0.59; 95% CI, 0.44-0.78). Use of continuous sedation was also associated with an increased risk of unplanned removal of PACs (hazard ratio, 1.54; 95% CI, 1.10-2.16). There was a 50% survival probability at 13.3 days for un-sutured PACs and 23.7 days for sutured PACs. CONCLUSIONS: Suturing is associated with fewer unplanned removals and longer catheter survival, compared to un-sutured PACs in pediatric patients.

Performance of Tools and Measures to Predict Fluid Responsiveness in Pediatric Shock and Critical Illness: A Systematic Review and Meta-Analysis.

OBJECTIVES: In this systematic review and meta-analysis we asked: Do predictors of fluid responsiveness in children perform comparably: 1) in the PICU as in non-PICU settings? 2) in shock states compared with nonshock states? Additionally, 3) is there an association between preload responsiveness and clinical response? DATA SOURCES: Ovid Medline, PubMed, and Embase databases were searched from inception through May 2022. STUDY SELECTION: Included studies reported physiological response to IV fluid administration in humans less than 18 years. Only studies reporting an area under the receiver operating characteristic curve (AUROC) were included for descriptive analysis. Only studies for which a se could be estimated were included for meta-analysis. DATA EXTRACTION: Title, abstract, full text screening, and extraction were completed by two authors (S.B.W., J.M.W.). Variables extracted included predictors ("tools") and outcome measures ("reference tests") of fluid responsiveness, demographic, and clinical variables. DATA SYNTHESIS: We identified 62 articles containing 204 AUROCs for 55 tools, primarily describing mechanically ventilated children in an operating room or PICU. Meta-analysis across all tools showed poor predictive performance (AUROC, 0.66; 95% CI, 0.63-0.69), although individual performance varied greatly (range, 0.49-0.87). After controlling for PICU setting and shock state, PICU setting was associated with decreased predictive performance (coefficient, -0.56; p = 0.0007), while shock state was associated with increased performance (0.54; p = 0.0006). Effect of PICU setting and shock state on each tool was not statistically significant but analysis was limited by sample size. The association between preload responsiveness and clinical response was rarely studied but results did not suggest an association. Ultrasound measurements were prone to inherent test review and incorporation biases. CONCLUSIONS: We suggest three opportunities for further research in fluid responsiveness in children: 1) assessing predictive performance of tools during resuscitation in shock states; 2) separating predictive tool from reference test when using ultrasound techniques; and 3) targeting decreasing time in a shock state, rather than just increase in preload.

The Pediatric Data Science and Analytics Subgroup of the Pediatric Acute Lung Injury and Sepsis Investigators Network: Use of Supervised Machine Learning Applications in Pediatric Critical Care Medicine Research.

OBJECTIVE: Perform a scoping review of supervised machine learning in pediatric critical care to identify published applications, methodologies, and implementation frequency to inform best practices for the development, validation, and reporting of predictive models in pediatric critical care. DESIGN: Scoping review and expert opinion. SETTING: We queried CINAHL Plus with Full Text (EBSCO), Cochrane Library (Wiley), Embase (Elsevier), Ovid Medline, and PubMed for articles published between 2000 and 2022 related to machine learning concepts and pediatric critical illness. Articles were excluded if the majority of patients were adults or neonates, if unsupervised machine learning was the primary methodology, or if information related to the development, validation, and/or implementation of the model was not reported. Article selection and data extraction were performed using dual review in the Covidence tool, with discrepancies resolved by consensus. SUBJECTS: Articles reporting on the development, validation, or implementation of supervised machine learning models in the field of pediatric critical care medicine. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 5075 identified studies, 141 articles were included. Studies were primarily (57%) performed at a single site. The majority took place in the United States (70%). Most were retrospective observational cohort studies. More than three-quarters of the articles were published between 2018 and 2022. The most common algorithms included logistic regression and random forest. Predicted events were most commonly death, transfer to ICU, and sepsis. Only 14% of articles reported external validation, and only a single model was implemented at publication. Reporting of validation methods, performance assessments, and implementation varied widely. Follow-up with authors suggests that implementation remains uncommon after model publication. CONCLUSIONS: Publication of supervised machine learning models to address clinical challenges in pediatric critical care medicine has increased dramatically in the last 5 years. While these approaches have the potential to benefit children with critical illness, the literature demonstrates incomplete reporting, absence of external validation, and infrequent clinical implementation.

Novel approaches to capturing and using continuous cardiorespiratory physiological data in hospitalized children.

Continuous cardiorespiratory physiological monitoring is a cornerstone of care in hospitalized children. The data generated by monitoring devices coupled with machine learning could transform the way we provide care. This scoping review summarizes existing evidence on novel approaches to continuous cardiorespiratory monitoring in hospitalized children. We aimed to identify opportunities for the development of monitoring technology and the use of machine learning to analyze continuous physiological data to improve the outcomes of hospitalized children. We included original research articles published on or after January 1, 2001, involving novel approaches to collect and use continuous cardiorespiratory physiological data in hospitalized children. OVID Medline, PubMed, and Embase databases were searched. We screened 2909 articles and performed full-text extraction of 105 articles. We identified 58 articles describing novel devices or approaches, which were generally small and single-center. In addition, we identified 47 articles that described the use of continuous physiological data in prediction models, but only 7 integrated multidimensional data (e.g., demographics, laboratory results). We identified three areas for development: (1) further validation of promising novel devices; (2) more studies of models integrating multidimensional data with continuous cardiorespiratory data; and (3) further dissemination, implementation, and validation of prediction models using continuous cardiorespiratory data. IMPACT: We performed a comprehensive scoping review of novel approaches to capture and use continuous cardiorespiratory physiological data for monitoring, diagnosis, providing care, and predicting events in hospitalized infants and children, from novel devices to machine learning-based prediction models. We identified three key areas for future development: (1) further validation of promising novel devices; (2) more studies of models integrating multidimensional data with continuous cardiorespiratory data; and (3) further dissemination, implementation, and validation of prediction models using cardiorespiratory data.

Integrating Focused Cardiac Ultrasound Into Pediatric Septic Shock Assessment.

OBJECTIVES: To assess focused cardiac ultrasound impact on clinician hemodynamic characterization of patients with suspected septic shock as well as expert-generated focused cardiac ultrasound algorithm performance. DESIGN: Retrospective, observational study. SETTING: Single-center, noncardiac PICU. PATIENTS: Less than 18 years old receiving focused cardiac ultrasound study within 72 hours of sepsis pathway initiation from January 2014 to December 2016. INTERVENTIONS: Hemodynamics of patients with suspected septic shock were characterized as fluid responsive, myocardial dysfunction, obstructive physiology, and/or reduced systemic vascular resistance by a bedside clinician before and immediately following focused cardiac ultrasound performance. The clinician's post-focused cardiac ultrasound hemodynamic assessments were compared with an expert-derived focused cardiac ultrasound algorithmic hemodynamic interpretation. Subsequent clinical management was assessed for alignment with focused cardiac ultrasound characterization and association with patient outcomes. MEASUREMENTS AND MAIN RESULTS: Seventy-one patients with suspected septic shock (median, 4.7 yr; interquartile range, 1.6-8.1) received clinician performed focused cardiac ultrasound study within 72 hours of sepsis pathway initiation (median, 2.1 hr; interquartile range, -1.5 to 11.8 hr). Two patients did not have pre-focused cardiac ultrasound and 23 patients did not have post-focused cardiac ultrasound hemodynamic characterization by clinicians resulting in exclusion from related analyses. Post-focused cardiac ultrasound clinician hemodynamic characterization differed from pre-focused cardiac ultrasound characterization in 67% of patients (31/46). There was substantial concordance between clinician's post-focused cardiac ultrasound and algorithm hemodynamic characterization (33/48; κ = 0.66; CI, 0.51-0.80). Fluid responsive (κ = 0.62; CI, 0.40-0.84), obstructive physiology (к = 0.87; CI, 0.64-1.00), and myocardial dysfunction (1.00; CI, 1.00-1.00) demonstrated substantial to perfect concordance. Management within 4 hours of focused cardiac ultrasound aligned with algorithm characterization in 53 of 71 patients (75%). Patients with aligned management were less likely to have a complicated course (14/52, 27%) compared with misaligned management (8/19, 42%; p = 0.25). CONCLUSIONS: Incorporation of focused cardiac ultrasound in the evaluation of patients with suspected septic shock frequently changed a clinician's characterization of hemodynamics. An expert-developed algorithm had substantial concordance with a clinician's post-focused cardiac ultrasound hemodynamic characterization. Management aligned with algorithm characterization may improve outcomes in children with suspected septic shock.

Clinical Signs to Categorize Shock and Target Vasoactive Medications in Warm Versus Cold Pediatric Septic Shock.

OBJECTIVES: Determine level of agreement among clinical signs of shock type, identify which signs clinicians prioritize to determine shock type and select vasoactive medications, and test the association of shock type-vasoactive mismatch with prolonged organ dysfunction or death (complicated course). DESIGN: Retrospective observational study. SETTING: Single large academic PICU. PATIENTS: Patients less than 18 years treated on a critical care sepsis pathway between 2012 and 2016. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Agreement among clinical signs (extremity temperature, capillary refill, pulse strength, pulse pressure, and diastolic blood pressure) was measured using Fleiss and Cohen's κ. Association of clinical signs with shock type and shock type-vasoactive mismatch (e.g., cold shock treated with vasopressor rather than inotrope) with complicated course was determined using multivariable logistic regression. Of 469 patients, clinicians determined 307 (65%) had warm and 162 (35%) had cold shock. Agreement across all clinical signs was low (κ, 0.25; 95% CI, 0.20-0.30), although agreement between extremity temperature, capillary refill, and pulse strength was better than with pulse pressure and diastolic blood pressure. Only extremity temperature (adjusted odds ratio, 26.6; 95% CI, 15.5-45.8), capillary refill (adjusted odds ratio, 15.7; 95% CI, 7.9-31.3), and pulse strength (adjusted odds ratio, 21.3; 95% CI, 8.6-52.7) were associated with clinician-documented shock type. Of the 86 patients initiated on vasoactive medications during the pathway, shock type was discordant from vasoactive medication (κ, 0.14; 95% CI, -0.03 to 0.31) and shock type-vasoactive mismatch was not associated with complicated course (adjusted odds ratio, 0.3; 95% CI, 0.1-1.02). CONCLUSIONS: Agreement was low among common clinical signs used to characterize shock type, with clinicians prioritizing extremity temperature, capillary refill, and pulse strength. Although clinician-assigned shock type was often discordant with vasoactive choice, shock type-vasoactive mismatch was not associated with complicated course. Categorizing shock based on clinical signs should be done cautiously.

Delayed intracranial hemorrhage after blunt trauma: are patients on preinjury anticoagulants and prescription antiplatelet agents at risk?

BACKGROUND: Trauma centers are more frequently evaluating patients who are receiving anticoagulant or prescription antiplatelet (ACAP) therapy at the time of injury. Because there are reports of delayed intracranial hemorrhage (ICH) after blunt trauma in this patient group, we evaluated patients receiving ACAP with a head computed tomography (CT) on admission (CT1) followed by a routine repeat head CT (CT2) in 6 hours. We hypothesized that among patients with no traumatic findings on CT1 and a normal or unchanged interval neurologic examination, the incidence of clinically significant delayed ICH would be zero. METHODS: We retrospectively reviewed adult blunt trauma patients admitted to our Level I trauma center from January 2006 to August 2009 who were receiving preinjury ACAP therapy. We reviewed medications, mechanism of injury, head CT results, and outcomes. Demographic data, injury severity scores, international normalized ratio, and neurologic examinations were recorded. We determined the incidence of delayed ICH on CT2 for patients with a negative CT1. RESULTS: Five hundred patients qualified for the protocol. Of these, 424 patients (85%) had a negative CT1. Among these patients, mean age was 75 years; 210 (50%) were male. Fall from standing was the most common mechanism of injury found in 357 patients (84%). Warfarin alone was taken in 68%, clopidogrel alone in 24%, and other agents in 2%. Six percent of patients were taking two agents. Mean international normalized ratio for patients on warfarin was 2.5. Among patients with a negative CT1, CT2 was obtained in 362 patients (85%) and was negative in 358 patients (99%). Four patients (1%) with a negative CT1 had a positive (n = 3) or equivocal (n = 1) CT2. All the changes on CT2 were minor and had either resolved or stabilized on third head CT. Of the four patients with positive or equivocal CT2, none had a change in neurologic examination; however, two had symptoms that could be attributed to head injury. Three were discharged home and one died of cardiac disease unrelated to head trauma. CONCLUSIONS: The incidence of delayed ICH in our study was 1%. However, none of the delayed findings were clinically significant. Among patients on ACAP therapy with a negative CT1 and a normal or unchanged neurologic examination, a routine CT2 is unnecessary. We recommend a period of observation to recognize those patients with symptoms that could be due to delayed ICH.

Resource commitment to improve outcomes and increase value at a level I trauma center.

BACKGROUND: Optimal care of trauma patients requires cost-effective organization and commitment of trauma center resources. We examined the impact of creating a dedicated trauma care unit (TCU) and adding advanced practice nurses on the quality and cost of care at an adult Level I trauma center. METHODS: Patient demographic and injury data, length of stay, complications, outcomes, and total direct cost of care were evaluated for four 1-year intervals in the recent history of our trauma center: Year A, a trauma team of in-house trauma surgeons and resident physicians; Year B, the addition of nurse practitioners to the trauma team 5 days/week; Year C, the creation of a dedicated TCU for all non intensive care unit trauma patients; and Year D, the addition of a permanent clinical nurse specialist and an increase in nurse practitioner coverage to 7 days/week. For each year, value was determined by calculating the median cost of a survivor and the median cost of a survivor with no complications. Significance was attributed to p<0.05. RESULTS: Patient volume increased from 1,927 in year A to 2,546 by year D. Over the period of study, there was an increase in blunt trauma (87.1-89.9%; p<0.05), median Injury Severity Score (5-6; p<0.05), and patients aged ≥65 years (11.4-19.8%; p<0.05). However, risk-adjusted mortality was unchanged. There was a decrease in patients with a complication (20.8-14.9%; p < 0.05), median intensive care unit length of stay (39.5-23.4 hours; p < 0.05), and median cost of care ($4,306-$3,698; p<0.05). Value increased: both the median costs of a survivor and of a survivor with no complications decreased from $4,259 to $3,658 (p<0.05) and from $3,898 to $3,317 (p<0.05), respectively. The median cost of a survivor with severe injury (Injury Severity Score ≥15) decreased from $17,651 to $12,285 (p<0.05). CONCLUSION: The addition of a dedicated TCU and advanced practice nurses improved the quality and reduced the cost of care, resulting in increased value at an adult Level I trauma center.