Strategies to Obtain and Deliver Blood Products Into Critically Injured Children: A Survey of Pediatric Trauma Society Members.

OBJECTIVES: Timely transfusion is associated with improved survival and a reduction in in-hospital morbidity. The benefits of early hemorrhagic shock recognition may be limited by barriers to accessing blood products and their timely administration. We examined how pediatric trauma programs obtain blood products, the types of rapid infusion models used, and the metrics tracked to improve transfusion process efficiency in their emergency department (ED). METHODS: We developed and distributed a self-report survey to members of the Pediatric Trauma Society. The survey consisted of 6 initial questions, including the respondent's role and institution, whether a blood storage refrigerator was present in their ED, the rapid infuser model used to transfuse critically injured children in their ED, if their program tracked 4 transfusion process metrics, and if a video recording system was present in the trauma bay. Based on these responses, additional questions were prompted with an option for a free-text response. RESULTS: We received 137 responses from 77 institutions. Most pediatric trauma programs have a blood storage refrigerator in the ED (n = 46, 59.7%) and use a Belmont rapid infuser to transfuse critically injured children (n = 45, 58.4%). The American College of Surgeons Level 1 designated trauma programs, or state-based equivalents, and "pediatric" trauma programs were more likely to have video recording systems for performance improvement review compared with lower designated trauma programs and "combined pediatric and adult" trauma programs, respectively. CONCLUSIONS: Strategies to improve the timely acquisition and infusion of blood products to critically injured children are underreported. This study examined the current practices that pediatric trauma programs use to transfuse critically injured children and may provide a resource for trauma programs to cite for transfusion-related quality improvement.

Factors Affecting Peripheral Intravenous Catheter Placement During Pediatric Trauma Resuscitation.

INTRODUCTION: Intravenous access is required for resuscitation of injured patients but may be delayed in children because of challenges associated with peripheral intravenous (PIV) catheter placement. Early identification of factors predisposing patients to difficult PIV placement can assist in deciding strategies for timely intravenous access. METHODS: We conducted a retrospective, video-based review of injured children and adolescents treated between April 2018 and May 2019. Patient demographic, physiological, injury, and resuscitation characteristics were obtained from the patient record, including age, race, weight, injury type, Injury Severity Score, initial systolic blood pressure, initial Glasgow Coma Score, intubation status, activation level, and presence of prearrival notification. Video review was used to determine the time to PIV placement, the number of attempts required, the purpose for additional access, and the reason for abandonment of PIV placement. Multivariable regressions were used to determine factors associated with successful placement. RESULTS: During the study period, 154 consented patients underwent attempts at PIV placement in the trauma bay. Placement was successful in 139 (90.3%) patients. Older patients (OR [odds ratio]: 0.9, 95% confidence interval [CI]: 0.9, 0.9) and patients who required the highest level activation response (OR: 0.0, 95% CI: 0.0, 0.3) were less likely to have an attempt at PIV placement abandoned. Children with nonblunt injuries (OR: 11.6, 95% CI: 1.3, 119.2) and pre-existing access (OR: 39.6, 95% CI: 7.0, 350.6) were more likely to have an attempt at PIV placement abandoned. Among patients with successful PIV placement, the time required for establishing PIV access was faster as age increased (-0.5 s, 95% CI: -1.1, -0.0). CONCLUSIONS: Younger age was associated with abandonment of PIV attempts and, when successful, increased time to placement. Strategies to improve successful PIV placement and alternate routes of access should be considered early to prevent treatment delays in younger children.

Comparative analysis of personal protective equipment nonadherence detection: computer vision versus human observers.

OBJECTIVES: Human monitoring of personal protective equipment (PPE) adherence among healthcare providers has several limitations, including the need for additional personnel during staff shortages and decreased vigilance during prolonged tasks. To address these challenges, we developed an automated computer vision system for monitoring PPE adherence in healthcare settings. We assessed the system performance against human observers detecting nonadherence in a video surveillance experiment. MATERIALS AND METHODS: The automated system was trained to detect 15 classes of eyewear, masks, gloves, and gowns using an object detector and tracker. To assess how the system performs compared to human observers in detecting nonadherence, we designed a video surveillance experiment under 2 conditions: variations in video durations (20, 40, and 60 seconds) and the number of individuals in the videos (3 versus 6). Twelve nurses participated as human observers. Performance was assessed based on the number of detections of nonadherence. RESULTS: Human observers detected fewer instances of nonadherence than the system (parameter estimate -0.3, 95% CI -0.4 to -0.2, P < .001). Human observers detected more nonadherence during longer video durations (parameter estimate 0.7, 95% CI 0.4-1.0, P < .001). The system achieved a sensitivity of 0.86, specificity of 1, and Matthew's correlation coefficient of 0.82 for detecting PPE nonadherence. DISCUSSION: An automated system simultaneously tracks multiple objects and individuals. The system performance is also independent of observation duration, an improvement over human monitoring. CONCLUSION: The automated system presents a potential solution for scalable monitoring of hospital-wide infection control practices and improving PPE usage in healthcare settings.

Factors associated with correction of personal protective equipment nonadherence in a multidisciplinary emergency department setting: A retrospective video review.

BACKGROUND: Despite local and national recommendations, health care provider adherence to personal protective equipment (PPE) varied during the COVID-19 pandemic. Previous studies have identified factors influencing initial PPE adherence but did not address factors influencing behaviors leading to correction after initial nonadherence. METHODS: We conducted a retrospective video review of 18 pediatric resuscitations involving aerosol-generating procedures from March 2020 to December 2022 to identify factors associated with nonadherence correction. We quantified adherent and nonadherent providers, instances of PPE nonadherence, and time to correction. We also analyzed correction behaviors, including provider actions and correction locations. RESULTS: Among 434 providers, 362 (83%) were nonadherent with at least 1 PPE. Only 186 of 1,832 instances of nonadherence were corrected, primarily upon room entry and during patient care. Correction time varied by PPE type and nonadherence level (incomplete vs absent). Most corrections were self-initiated, with few reminders from other providers. DISCUSSION: Potential barriers to correction include a lack of social pressure and external reminders. Solutions include optimizing PPE availability, providing real-time feedback, and educating on double gloving. CONCLUSIONS: Most providers were nonadherent to PPE requirements during high-risk infection transmission events. The low correction rate suggests challenges in promoting collective responsibility and maintaining protective behaviors during medical emergencies.

Development and Validation of a Bayesian Network Predicting Intubation Following Hospital Arrival Among Injured Children.

BACKGROUND: Inadequate airway management can contribute to preventable trauma deaths. Current machine learning tools for predicting intubation in trauma are limited to adult populations and include predictors not readily available at the time of patient arrival. We developed a Bayesian network to predict intubation in injured children and adolescents using observable data available upon or immediately after patient arrival. METHODS: We obtained patient demographic, injury, resuscitation, and transportation characteristics from trauma registries from four American College of Surgeons-verified level 1 pediatric trauma centers from January 2010 through December 2021. We trained and validated a Bayesian network to predict emergent intubation after pediatric injury. We evaluated model performance using the area under the receiver operating and calibration curves. RESULTS: The final model, TITAN (Timing of Intubation in Trauma Analysis Network), incorporated five factors: Glasgow Coma Scale, mechanism of injury, injury type (e.g., penetrating, blunt), systolic blood pressure, and age. The model achieved an area under the receiver operating characteristic curve of 0.83 (95% CI 0.80, 0.85) and had a calibration curve slope of 0.98 (95% CI 0.67, 1.29). TITAN had high specificity (98%), negative predictive value (97%), and accuracy (96%) at a binary probability threshold of 22.6%. CONCLUSION: The TITAN Bayesian network predicts the risk of intubation in pediatric trauma patients using five factors that are observable early in trauma resuscitation. Prospective validation of the model performance with patient outcomes is needed to assess real-life application benefits and risks. LEVEL OF EVIDENCE: Prognostic and Epidemiological, Level III.

Survival Bias in Pediatric Hemorrhagic Shock: Are We Misrepresenting the Data?

BACKGROUND: Studies of hemorrhage following pediatric injury often use the occurrence of transfusion as a surrogate definition for the clinical need for a transfusion. Using this approach, patients who are bleeding but die before receiving a transfusion are misclassified as not needing a transfusion. In this study, we aimed to evaluate the potential for this survival bias and to estimate its presence among a retrospective observational cohort of children and adolescents who died from injury. METHODS: We obtained patient, injury, and resuscitation characteristics from the 2017 to 2020 Trauma Quality Improvement Program database of children and adolescents (age < 18 years) who arrived with or without signs of life and died. We performed univariate analysis and a multivariable logistic regression to analyze the association between the time to death and the occurrence of transfusion within four hours after hospital arrival controlling for initial vital signs, injury type, body regions injured, and scene versus transfer status. RESULTS: We included 6,063 children who died from either a blunt or penetrating injury. We observed that children who died within 15 minutes had lower odds of receiving a transfusion (odds ratio [OR] = 0.1, 95% CI = 0.1, 0.2) compared to those who survived longer. We estimated that survival bias that occurs when using transfusion administration alone to define hemorrhagic shock may occur in up to 11% of all children who died following a blunt or penetrating injury but less than 1% of all children managed as trauma activations. CONCLUSION: Using the occurrence of transfusion alone may underestimate the number of children who die from uncontrolled hemorrhage early after injury. Additional variables than just transfusion administration are needed to more accurately identify the presence of hemorrhagic shock among injured children and adolescents. LEVEL OF EVIDENCE: Prognostic and Epidemiological, Level III.

Development and validation of a Bayesian network predicting neurosurgical intervention after injury in children and adolescents.

BACKGROUND: Timely surgical decompression improves functional outcomes and survival among children with traumatic brain injury and increased intracranial pressure. Previous scoring systems for identifying the need for surgical decompression after traumatic brain injury in children and adults have had several barriers to use. These barriers include the inability to generate a score with missing data, a requirement for radiographic imaging that may not be immediately available, and limited accuracy. To address these limitations, we developed a Bayesian network to predict the probability of neurosurgical intervention among injured children and adolescents (aged 1-18 years) using physical examination findings and injury characteristics observable at hospital arrival. METHODS: We obtained patient, injury, transportation, resuscitation, and procedure characteristics from the 2017 to 2019 Trauma Quality Improvement Project database. We trained and validated a Bayesian network to predict the probability of a neurosurgical intervention, defined as undergoing a craniotomy, craniectomy, or intracranial pressure monitor placement. We evaluated model performance using the area under the receiver operating characteristic and calibration curves. We evaluated the percentage of contribution of each input for predicting neurosurgical intervention using relative mutual information (RMI). RESULTS: The final model included four predictor variables, including the Glasgow Coma Scale score (RMI, 31.9%), pupillary response (RMI, 11.6%), mechanism of injury (RMI, 5.8%), and presence of prehospital cardiopulmonary resuscitation (RMI, 0.8%). The model achieved an area under the receiver operating characteristic curve of 0.90 (95% confidence interval [CI], 0.89-0.91) and had a calibration slope of 0.77 (95% CI, 0.29-1.26) with a y intercept of 0.05 (95% CI, -0.14 to 0.25). CONCLUSION: We developed a Bayesian network that predicts neurosurgical intervention for all injured children using four factors immediately available on arrival. Compared with a binary threshold model, this probabilistic model may allow clinicians to stratify management strategies based on risk. LEVEL OF EVIDENCE: Prognostic and Epidemiological; Level III.