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    Pediatric Anesthesia

    Pediatric Anesthesia

    JournalISSN 1155-5645eISSN 1460-9592中科院 医学 4区

    年发文量

    研究主题

    论文(7638)

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    1Regional Anesthesia for Pediatric Penile Surgery in Contemporary Practice: A Prospective Observational Cohort Study
    Paolo Rufini, Silvia Cumbo, Martina Pagano, Matteo Lui, Cesare Greco, Emmanuele Mongelli,Denise Colosimo,Zaccaria Ricci
    2026
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    2Multidisciplinary Risk Assessment Outcomes Are Associated with 30‐day in Hospital Complications Following Pediatric Scoliosis Surgery: Evaluation of a Three‐Tiered Traffic‐Light Triage System at Great Ormond Street Children's Hospital
    Colette Neethling, Lois Williams,Marina George,Edel Broomfield, Steven Staffa,Stewart Tucker, Florian Moenkemeyer, Vasileios Patelis, Pascale Du Pre, Pratheeban Nambyiah

    ABSTRACT Background Scoliosis surgery is complex and associated with significant morbidity. Accurate risk assessment is essential for appropriate resource allocation and improved care. Risk factors for developing complications have been identified; however, structured frameworks to support preoperative assessment are limited. Great Ormond Street Hospital (GOSH) uses a three‐tier multidisciplinary team (MDT) traffic‐light system to triage patients based on well‐defined risk factors and expert clinical judgment. Aim We aimed to describe complications following scoliosis surgery at GOSH and evaluate the relationship between preoperative MDT traffic‐light assessment and outcomes such as complication rates, operative times, and length of stay. Method A retrospective hospital file review was conducted for all patients presenting to GOSH for primary scoliosis surgery between January 2019 and December 2023. Institutional approval was obtained, and the need for ethical approval was waived. Preoperative risk is quantified by the MDT using a three‐tier traffic‐light system categorizing patients as low (green), intermediate (amber), and high‐risk (red). Outcomes including 30‐day in‐hospital complications, operative time, and length of stay were analyzed in relation to preoperative MDT traffic‐light score. Results Of 350 eligible patients, 337 had a documented preoperative MDT traffic‐light assessment. Low‐risk patients comprised 43.6% ( n = 147/337), intermediate‐risk 49.3% ( n = 166/337), and high‐risk 7.1% ( n = 24/337). Major complications occurred in 2% ( n = 3/147) of low‐risk patients compared with 50% ( n = 12/24) of high‐risk patients, corresponding to an adjusted odds ratio of 11.4 ([95% CI 1.98–65.4], p = 0.006). High‐risk patients also had significantly longer operative times (381 min vs. 320 min, p < 0.001) and length of stay (12 days vs. 5 days, p < 0.001) when compared to low‐risk patients. Conclusion Patients classified as high‐risk by the MDT demonstrated an increased odds of developing major complications, longer operative time, and extended length of stay when compared to low‐risk patients. Similar structured tools, with local adaptations, may be valuable in other centers to support preoperative assessment, shared decision making, and guide resource allocation.

    2026
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    3Substance over Style—How to Make a Difference
    Britta S. von Ungern‐Sternberg,Aine Sommerfield
    2026
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    4Awareness and Clinical Practices of Turkish Anesthesiologists Regarding the Perioperative Management of Children with Autism Spectrum Disorder: A Cross‐Sectional Survey
    Zeynep Köksal,Suzan Öztürk Selçuk, Vildan Ergen
    2026
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    5Correlation of Neuron‐Specific Enolase and S100ß Protein Levels, Inflammatory Cytokines, and Neurological Injury in Children Undergoing Cardiopulmonary Bypass
    Mark Twite, Aris Sophocles, Zhaoxing Pan, Robert Friesen

    ABSTRACT Background The systemic inflammatory response syndrome to cardiopulmonary bypass (CPB) affects all organ systems including the brain. Perioperative brain injury in children with congenital heart disease is often clinically silent in the acute perioperative period and may not be detected until patients are older. The plasma biomarkers neuron‐specific enolase (NSE) and S100ß protein show potential for detecting neurological injury in the perioperative period. Objectives The three objectives of this study were to examine the correlation of NSE and S100ß protein levels with inflammatory cytokines, parameters of CPB, and the development of neurological injury in the intensive care unit following cardiac surgery in children. Methods 50 children undergoing cardiac surgery with CPB had blood samples drawn at three time points: after induction of anesthesia, 30 min post‐CPB, and 24 h post‐CPB. Blood samples were analyzed for NSE, S100ß, and the inflammatory cytokines IL‐6, IL‐8, and IL‐10. Data were collected on CPB durations and neurological injury diagnosed in the postoperative period. Results NSE and S100ß increased significantly following bypass and correlated with increases of IL‐6, IL‐8, and IL‐10. There was a significant positive correlation of NSE and S100ß with duration of CPB, and of S100ß with duration of aortic cross clamp. Three patients suffered neurological insult. These patients had greater levels of NSE during the post‐CPB period ( p = 0.02) and S100ß at 24 h post‐CPB ( p = 0.02) than patients without neurological deficits. Conclusion The positive correlation between NSE, S100ß, inflammatory cytokines, and neurological deficits suggests that the systemic inflammatory response to CPB may contribute to neurological injury and that NSE and S100ß may be useful tools to detect neurological injury following CPB.

    2026
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    高被引作者

    作者引用发文
    Brian J Anderson4507130
    Markus Weiss283180
    Britta S Von Ungern-Sternberg2255106
    Andrew Stewart Davidson209971
    Joseph Tobias185975
    Isabelle Murat183124
    Voepel-Lewis Terri178430
    N. S. Morton155754
    Isabelle Constant154616
    Thomas Engelhardt152959

    高产作者

    作者引用发文
    Brian J Anderson4507130
    Britta S Von Ungern-Sternberg2255106
    Markus Weiss283180
    Joseph Tobias185975
    Andrew Stewart Davidson209971
    Thomas Engelhardt152959
    N. S. Morton155754
    James F. Mayhew17047
    FuShan Xue26646
    Xu Liao27045

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