Establishment of Scoring to Predict Severe Complication After Pyogenic Spondylodiscitis Surgery.

Study Design: Retrospective cohort study using prospective database.

Objective: This study aimed to establish a risk-scoring system for predicting severe complications after pyogenic spondylodiscitis surgery.

Summary Of Background Data: Pyogenic spondylodiscitis surgery can cause severe complications.

Number of teeth and incidence of hip fracture in older adults aged ≥75 years: the OHSAKA study.

Background: Several studies reported an association between the number of teeth and the incidence of hip fractures in observational studies, mainly in middle-aged adults. This retrospective cohort study aimed to clarify the association between the number of teeth and the incidence of hip fractures.

Methods: In this retrospective cohort study, a total of 256,772 participants aged 75 years or older who underwent public dental checkups in Japan were evaluated.

rhBMP-2-loaded hydroxyapatite/beta-tricalcium phosphate microsphere/hydrogel composite promotes bone regeneration in a novel rat femoral nonunion model.

Background: Nonunion following fracture treatment remains a significant clinical challenge, adversely affecting the patient's quality of life and imposing a substantial economic burden. The emergence of bone morphogenetic protein 2 (BMP-2) for bone regeneration represents a promising avenue, albeit limited by side effects such as inflammatory reactions primarily due to suboptimal drug delivery systems. This study focuses on NOVOSIS putty (NP), a novel biomaterial designed for the sustained release of BMP-2, aiming to mitigate these limitations and enhance bone healing.

Multimodal Deep Learning-based Radiomics Approach for Predicting Surgical Outcomes in Patients with Cervical Ossification of the Posterior Longitudinal Ligament.

Study Design: A retrospective analysis.

Objective: This research sought to develop a predictive model for surgical outcomes in patients with cervical ossification of the posterior longitudinal ligament (OPLL) using deep learning and machine learning (ML) techniques.

Summary Of Background Data: Determining surgical outcomes assists surgeons in communicating prognosis to patients and setting their expectations.

Appropriate pelvic obliquity measurement method in Lenke type 5C adolescent idiopathic scoliosis: a preliminary study.

Background: Although pelvic obliquity (PO) is a risk factor for postoperative coronal decompensation in corrective surgery in adolescent idiopathic scoliosis (AIS), especially Lenke 5C, methods of measuring PO are controversial. This study aimed to establish an appropriate measurement method using multiplanar reconstructed computed tomography (MPR-CT) images instead of standing posteroanterior (PA) whole-spine radiographs to evaluate PO in patients with Lenke 5C AIS.

Methods: This study was a retrospective cross-sectional study.

A Comparison Between GPT-3.5, GPT-4, and GPT-4V: Can the Large Language Model (ChatGPT) Pass the Japanese Board of Orthopaedic Surgery Examination?

Introduction Recently, large-scale language models, such as ChatGPT (OpenAI, San Francisco, CA), have evolved. These models are designed to think and act like humans and possess a broad range of specialized knowledge. GPT-3.

Automated entry of paper-based patient-reported outcomes: Applying deep learning to the Japanese orthopaedic association back pain evaluation questionnaire.

Background: Health-related patient-reported outcomes (HR-PROs) are crucial for assessing the quality of life among individuals experiencing low back pain. However, manual data entry from paper forms, while convenient for patients, imposes a considerable tallying burden on collectors. In this study, we developed a deep learning (DL) model capable of automatically reading these paper forms.

Development of patient-reported outcome for adult spinal deformity: validation study.

Adult spinal deformity (ASD) is a complex condition that combines scoliosis, kyphosis, pain, and postoperative range of motion limitation. The lack of a scale that can successfully capture this complex condition is a clinical challenge. We aimed to develop a disease-specific scale for ASD.

Risk Factor Analysis of Surgery-related Complications in Primary Thoracic Spine Surgery for Degenerative Diseases and Characteristics of the Patients Also Undergoing Surgery on the Cervical and/or Lumbar Spine.

Study Design: A retrospective cohort study using prospectively collected data.

Objective: This study primarily aimed to investigate the risk factors for surgery-related complications in primary thoracic spine surgery for degenerative diseases using a surgeon-maintained database. The secondary purpose was to elucidate the characteristics of surgically treated thoracic myelopathy that also required cervical and/or lumbar spine surgery in the study period.

Bimodal artificial intelligence using TabNet for differentiating spinal cord tumors-Integration of patient background information and images.

We proposed a bimodal artificial intelligence that integrates patient information with images to diagnose spinal cord tumors. Our model combines TabNet, a state-of-the-art deep learning model for tabular data for patient information, and a convolutional neural network for images. As training data, we collected 259 spinal tumor patients (158 for schwannoma and 101 for meningioma).

Review of Basic Research about Ossification of the Spinal Ligaments Focusing on Animal Models.

Ossification of the posterior longitudinal ligament (OPLL) is a heterotopic ossification that may cause spinal cord compression. With the recent development of computed tomography (CT) imaging, it is known that patients with OPLL often have complications related to ossification of other spinal ligaments, and OPLL is now considered part of ossification of the spinal ligaments (OSL). OSL is known to be a multifactorial disease with associated genetic and environmental factors, but its pathophysiology has not been clearly elucidated.

Development of artificial intelligence for automated measurement of cervical lordosis on lateral radiographs.

Cervical sagittal alignment is an essential parameter for the evaluation of spine disorders. Manual measurement is time-consuming and burdensome to measurers. Artificial intelligence (AI) in the form of convolutional neural networks has begun to be used to measure x-rays.

Prostaglandin EP4 Selective Agonist AKDS001 Enhances New Bone Formation by Minimodeling in a Rat Heterotopic Xenograft Model of Human Bone.

To enhance bone regeneration, the use of bone morphogenetic protein (BMP)-2 is an attractive option. Unfortunately, the dose-dependent side effects prevent its widespread use. Therefore, a novel osteogenic agent using a different mechanism of action than BMP-2 is highly desirable.