Publications by authors named "D H Chou"

Study Design: Systematic Review.

Objectives: Formalized terminology for pain experienced by spine cancer patients is lacking. The common descriptors of spine cancer pain as mechanical or non-mechanical is not exhaustive.

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Study Design: Systematic review.

Objective: In patients with extradural metastatic spine disease, we sought to systematically review the outcomes and complications of patients with intermediate Spinal Instability Neoplastic Score (SINS) lesions undergoing radiation therapy, percutaneous interventions, minimally invasive surgeries, or open spinal surgeries.

Methods: Following PRISMA guidelines for systematic reviews, MEDLINE, EMBASE, Web of Science, the Cochrane Database of Systematic Reviews and the Cochrane Center Register of Controlled Trials were queried for studies that reported on SINS intermediate patients who underwent: 1) radiotherapy, 2) percutaneous intervention, 3) minimally invasive, or 4) open surgery.

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Objective: Cervical spondylotic myelopathy (CSM) shows varying levels of improvement after surgical treatment. While some patients improve soon after surgery, others may take months to years to show any signs of improvement. The goal of this study was to evaluate postoperative improvement, patient-reported outcomes, and patient satisfaction up to 2 years after surgical treatment for CSM, which will help optimize the current treatment strategies and effectively manage patient expectations.

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Objective: The goal of this study was to compare the impact of using a lower thoracic (LT) versus upper lumbar (UL) level as the upper instrumented vertebra (UIV) on clinical and radiographic outcomes following minimally invasive surgery for adult spinal deformity.

Methods: A multicenter retrospective study design was used. Inclusion criteria were age ≥ 18 years, and one of the following: coronal Cobb angle > 20°, sagittal vertical axis > 50 mm, pelvic tilt > 20°, pelvic incidence-lumbar lordosis mismatch > 10°.

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Purpose: Information retrieval (IR) and risk assessment (RA) from multi-modality imaging and pathology reports are critical to prostate cancer (PC) treatment. This study aims to evaluate the performance of four general-purpose large language model (LLMs) in IR and RA tasks.

Materials And Methods: We conducted a study using simulated text reports from computed tomography, magnetic resonance imaging, bone scans, and biopsy pathology on stage IV PC patients.

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