Presurgical Optimization and Surgical Management of Extreme Adolescent Idiopathic Scoliosis: A Case Report.

We present the case of an 18-year-old Asian male patient with extreme adolescent idiopathic scoliosis (AIS) exceeding 180 degrees, who remained untreated for eight years following his initial diagnosis due to socioeconomic barriers and limited access to healthcare. At presentation, the patient measured 165 cm in height and weighed only 40 kg (BMI 14.7). He exhibited severe spinal deformity, compromised pulmonary function (forced vital capacity (FVC) at 65% of the predicted value), chronic pain (rated 5-7/10), and progressive functional decline that had led to withdrawal from traditional schooling. A multidisciplinary team implemented a presurgical optimization protocol incorporating halo-gravity traction, spinal manipulation, therapeutic exercises, respiratory rehabilitation, and nutritional intervention, all tailored through patient-specific 3D-printed spinal modeling. After eight weeks, the patient demonstrated remarkable improvements: a 2-cm height increase, 4-kg weight gain, improved pulmonary function (FVC 78% of the predicted value), and reduced pain reduction (2-3/10). These gains enabled successful posterior spinal fusion from T2 to L4. Postoperatively, pulmonary function normalized to 82% of the predicted value, and the patient continues with rehabilitation focused on functional restoration and pain management. This case uniquely contributes to the literature by documenting quantifiable improvements achieved through multidisciplinary presurgical optimization in extreme deformity. It demonstrates effective integration of multidisciplinary spine care, provides rare insight into the natural history of untreated severe AIS, and offers a comprehensive model for transitional care from conservative management to surgical intervention. The successful outcome, despite significant barriers, underscores the importance of adaptive, multidisciplinary strategies in managing complex spinal deformities, particularly in resource-limited settings.