Factors influencing massive blood loss for neuromuscular scoliosis (NMS) patients.Despite advances in surgical and anesthetic techniques, scoliosis surgery is still associated with intraoperative massive blood loss, which can result in postoperative mortality and morbidity. The aim of this study was to assess the incidence, influencing factors, and prognostic impact of intraoperative massive blood loss in adolescents with NMS.A retrospective review of adolescents who underwent posterior spinal instrumentation and fusion for NMS was performed. Perioperative variables and data were recorded. Massive blood loss was defined as an estimated blood loss that exceeds 30% of total blood volume.We obtained data for 114 patients, of whom 63 (55%) had intraoperative massive blood loss. Compared with those without, patients with massive blood loss were more likely to be older, have lower body mass indexes (BMIs), larger Cobb angles, more fused levels, more osteotomy procedures, and prolonged duration of operation. Logistic regression analysis identified the number of fused levels to be more than 12 (P = 0.003, odds ratio = 6.614, 95% confidence interval [CI]: 1.891–23.131), BMI lower than 16.8 kg/m2 (P = 0.025, odds ratio = 3.293, 95% CI: 1.159–9.357), age greater than 15 years (P = 0.014, odds ratio = 3.505, 95% CI: 1.259–9.761), and duration of operation longer than 4.4 hours (P = 0.016, odds ratio = 3.746, 95% CI: 1.428–9.822) as influencing factors. Patients with massive blood loss are associated with more intraoperative colloids infusion and blood transfusions (red blood cell and fresh frozen plasma), as well as postoperative drainage volume.In adolescents with NMS who underwent posterior spinal instrumentation and fusion operations, intraoperative massive blood loss is common. The number of fused levels, BMI, age, and duration of operation are factors influencing intraoperative massive blood loss.
Serum PLGF level was lower in women who subsequently developed severe PE early in the second trimester, suggesting its role in prediction of PE.
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