Management and Outcomes of Pediatric Lymphatic Malformations: A Systematic Review From the APSA Outcomes and Evidence-Based Practice Committee.

BACKGROUND: Significant variation in management strategies for lymphatic malformations (LMs) in children persists. The goal of this systematic review is to summarize outcomes for medical therapy, sclerotherapy, and surgery, and to provide evidence-based recommendations regarding the treatment. METHODS: Three questions regarding LM management were generated according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Publicly available databases were queried to identify articles published from January 1, 1990, to December 31, 2021. A consensus statement of recommendations was generated in response to each question. RESULTS: The initial search identified 9326 abstracts, each reviewed by two authors. A total of 600 abstracts met selection criteria for full manuscript review with 202 subsequently utilized for extraction of data. Medical therapy, such as sirolimus, can be used as an adjunct with percutaneous treatments or surgery, or for extensive LM. Sclerotherapy can achieve partial or complete response in over 90% of patients and is most effective for macrocystic lesions. Depending on the size, extent, and location of the malformation, surgery can be considered. CONCLUSION: Evidence supporting best practices for the safety and effectiveness of management for LMs is currently of moderate quality. Many patients benefit from multi-modal treatment determined by the extent and type of LM. A multidisciplinary approach is recommended to determine the optimal individualized treatment for each patient.

Presence of Microscopic Hematuria Does Not Predict Clinically Important Intra-Abdominal Injury in Children.

OBJECTIVE: Screening for blunt intra-abdominal injury in children often includes directed laboratory evaluation that guides need for computed tomography. We sought to evaluate the use of urinalysis in identifying patients with clinically important intraabdominal injury ( ci -IAI). METHODS: A retrospective chart review was performed for all patients less than 18 years who presented with blunt mechanisms at a level I trauma center between 2016 and 2019. Exclusion criteria included transfer from an outside facility, physical abuse, and death within thirty minutes of arrival. Demographics, physical exam findings, serum chemistries, urinalysis, and imaging were reviewed. Clinically important intraabdominal injury was defined as injury requiring ≥2 nights admission, blood transfusion, angiography with embolization, or therapeutic surgery. RESULTS: Two hundred forty patients were identified. One hundred sixty-five had a completed urinalysis. For all patients an abnormal chemistry panel and abnormal physical exam had a sensitivity of 88.9% and a negative predictive value of 99.3%. Nine patients had a ci -IAI. Patients with a ci -IAI were more likely to have abdominal pain, tenderness on exam, and elevated hepatic enzymes. When patients were stratified by the presence of an abnormal chemistry or physical exam with or without microscopic hematuria, urinalysis did not improve the ability to identify patients with a ci -IAI. In fact, presence of microscopic hematuria increased the rate of false positives by 12%. CONCLUSIONS: Microscopic hematuria was not a useful marker for ci -IAI and may lead to falsely assuming a more serious injury.

Derivation and Validation of a Machine Learning Algorithm for Predicting Venous Thromboembolism in Injured Children.

BACKGROUND: Venous thromboembolism (VTE) causes significant morbidity in pediatric trauma patients. We applied machine learning algorithms to the Trauma Quality Improvement Program (TQIP) database to develop and validate a risk prediction model for VTE in injured children. METHODS: Patients ≤18 years were identified from TQIP (2017-2019, n = 383,814). Those administered VTE prophylaxis ≤24 h and missing the outcome (VTE) were removed (n = 347,576). Feature selection identified 15 predictors: intubation, need for supplemental oxygen, spinal injury, pelvic fractures, multiple long bone fractures, major surgery (neurosurgery, thoracic, orthopedic, vascular), age, transfusion requirement, intracranial pressure monitor or external ventricular drain placement, and low Glasgow Coma Scale score. Data was split into training (n = 251,409) and testing (n = 118,175) subsets. Machine learning algorithms were trained, tested, and compared. RESULTS: Low-risk prediction: For the testing subset, all models outperformed the baseline rate of VTE (0.15%) with a predicted rate of 0.01-0.02% (p < 2.2e-16). 88.4-89.4% of patients were classified as low risk by the models. HIGH-RISK PREDICTION: All models outperformed baseline with a predicted rate of VTE ranging from 1.13 to 1.32% (p < 2.2e-16). The performance of the 3 models was not significantly different. CONCLUSION: We developed a predictive model that differentiates injured children for development of VTE with high discrimination and can guide prophylaxis use. LEVEL OF EVIDENCE: Prognostic, Level II. TYPE OF STUDY: Retrospective, Cross-sectional.

Adapting the IDEAL Framework and Recommendations for medical device evaluation: A modified Delphi survey.

INTRODUCTION: Current regulatory systems for medical device marketing approval lack adequate requirements for evidence of safety and efficacy. The Total Product Life Cycle (TPLC) concept, with clinical use and marketing expanding as evidence develops, has won support, but lacks a template to define evidence requirements at different stages. The IDEAL Framework & Recommendations, originally developed for new surgical procedures, might provide such a template, but may require modification. METHODS: We conducted a Delphi expert consensus exercise to determine how IDEAL might be modified to accommodate the needs of device regulation. 34 experts were invited to participate in 3 rounds of questioning, with feedback of the results of each round to participants before the next. RESULTS: 27 of 34 experts responded in at least one survey round. Experts agreed that, after appropriate modifications, IDEAL could form an evidence template for a TPLC-based regulatory system. Necessary modifications include a new Stage 0 should guide reporting of pre-clinical studies, expansion of registries to all stages, and omission of IDEAL stages 2 and 3 for "successor" devices under certain conditions. DISCUSSION: A standard approach to TPLC evaluation of medical devices does not currently exist. The IDEAL Framework, if modified appropriately, could fill such a void and improve the safety of new medical devices.