Blood culture bottles meet the operating room: enhancing the diagnostic accuracy of infectious spondylitis through open microsurgical biopsy and intraoperative inoculation.

Purpose: Infectious spondylitis is caused by hematogenous seeding or adjacent soft tissue infection. No study has provided evidence that incubating biopsy specimens in blood culture bottles could enhance detection rates, nor has any study compared this method with conventional culture techniques. We aimed to assess the diagnostic yield of open microsurgical biopsies for infectious spondylitis and the efficacy of various culture media in the presence and absence of pre-biopsy antibiotic therapy.

Dissatisfaction-considered waiting time prediction for outpatients with interpretable machine learning.

Long waiting time in outpatient departments is a crucial factor in patient dissatisfaction. We aim to analytically interpret the waiting times predicted by machine learning models and provide patients with an explanation of the expected waiting time. Here, underestimating waiting times can cause patient dissatisfaction, so preventing this in predictive models is necessary.

Hospitals' Adoption of Mobile-Based Personal Health Record Systems and Patients' Characteristics: A Cross-Sectional Study Analyzing National Healthcare Big Data.

Insufficient information exists on the associations between hospitals' adoption of mobile-based personal health record (mPHR) systems and patients' characteristics. This study explored the associations between patients' characteristics and hospitals' adoption of mPHR systems in Korea. This cross-sectional study used 316 hospitals with 100 or more beds as the unit of analysis.

Conversational Artificial Intelligence for Spinal Pain Questionnaire: Validation and User Satisfaction.

Objective: The purpose of our study is to develop a spoken dialogue system (SDS) for pain questionnaire in patients with spinal disease. We evaluate user satisfaction and validated the performance accuracy of the SDS in medical staff and patients.

Methods: The SDS was developed to investigate pain and related psychological issues in patients with spinal diseases based on the pain questionnaire protocol.

Development and Effectiveness of a Clinical Decision Support System for Pressure Ulcer Prevention Care Using Machine Learning: A Quasi-experimental Study.

This study was conducted to develop and evaluate the effectiveness of a clinical decision support system for pressure ulcer prevention on clinical (performance, visual discrimination ability, and decision-making ability) and cognitive (knowledge and attitude) workflow. After developing a clinical decision support system using machine learning, a quasi-experimental study was used. Data were collected between January and April 2020.

Machine learning-based survival rate prediction of Korean hepatocellular carcinoma patients using multi-center data.

Aim: To predict survival time of Korean hepatocellular carcinoma (HCC) patients using multi-center data as a foundation for the development of a predictive artificial intelligence model according to treatment methods based on machine learning.

Methods: Data of patients who underwent treatment for HCC from 2008 to 2015 was provided by Korean Liver Cancer Study Group and Korea Central Cancer Registry. A total of 10,742 patients with HCC were divided into two groups, with Group I (2920 patients) confirmed on biopsy and Group II (5562 patients) diagnosed as HCC according to HCC diagnostic criteria as outlined in Korean Liver Cancer Association guidelines.

Relationships between Nursing Students' Skill Mastery, Test Anxiety, Self-Efficacy, and Facial Expressions: A Preliminary Observational Study.

Test anxiety and self-efficacy significantly influence the mastery of nursing skills. Facial expression recognition tools are central components to recognising these elements. This study investigated the frequent facial expressions conveyed by nursing students and examined the relationships between nursing skill mastery, test anxiety, self-efficacy, and facial expressions in a test-taking situation.

Factors of quality of care and their association with smartphone based PHR adoption in South Korean hospitals.

Background: Healthcare organizations have begun to adopt personal health records (PHR) systems to engage patients, but little is known about factors associated with the adoption of PHR systems at an organizational level. The objective of this study is to investigate factors associated with healthcare organizations' adoption of PHR systems in South Korea.

Methods: The units of analysis were hospitals with more than 100 beds.

Predicting survival time of Korean hepatocellular carcinoma patients using the Cox proportional hazards model: a retrospective study based on big data analysis.

Aim: To predict survival time of Korean hepatocellular carcinoma (HCC) patients by analyzing big data using Cox proportional hazards model.

Methods: Big data of the patients who underwent treatment for HCC from 2008 to 2015, provided by Korea Central Cancer Registry, National Cancer Center, and Ministry of Health and Welfare, were analyzed. A total of 10 742 patients with HCC were divided into two groups, with Group I (3021 patients) confirmed on biopsy and Group II (5563 patients) diagnosed as HCC according to HCC diagnostic criteria as outlined in Korean Liver Cancer Association guidelines.

Successful Motor Evoked Potential Monitoring in Cervical Myelopathy : Related Factors and the Effect of Increased Stimulation Intensity.

Objective: Intraoperative neurophysiological monitoring (IONM) has been widely used during spine surgery to reduce or prevent neurologic deficits, however, its application to the surgical management for cervical myelopathy remains controversial. This study aimed to assess the success rate of IONM in patients with cervical myelopathy and to investigate the factors associated with successful baseline monitoring and the effect of increasing the stimulation intensity by focusing on motor evoked potentials (MEPs).

Methods: The data of 88 patients who underwent surgery for cervical myelopathy with IONM between January 2016 and June 2018 were retrospectively reviewed.

Analysis of Platforms and Functions of Mobile-Based Personal Health Record Systems.

Objectives: Little is known about the platforms and functionalities of mobile-based personal health record (PHR) applications. The objective of this study was to investigate these two features of PHR systems.

Methods: The unit of analysis was general hospitals with more than 100 beds.

Process Mining-Supported Emergency Room Process Performance Indicators.

Emergency room processes are often exposed to the risk of unexpected factors, and process management based on performance measurements is required due to its connectivity to the quality of care. Regarding this, there have been several attempts to propose a method to analyze the emergency room processes. This paper proposes a framework for process performance indicators utilized in emergency rooms.

Risk prediction models for the development of oral-mucosal pressure injuries in intubated patients in intensive care units: A prospective observational study.

Purpose: Oral-mucosal pressure injury (PI) is the most commonly encountered medical device-related PIs. This study was performed to identify risk factors and construct a risk prediction model for oral-mucosal PI development in intubated patients in the intensive care unit.

Methods: The study design was prospective, observational with medical record review.

Prediction of early neurological deterioration in acute minor ischemic stroke by machine learning algorithms.

Objectives: A significant proportion of patients with acute minor stroke have unfavorable functional outcome due to early neurological deterioration (END). The purpose of this study was to evaluate the applicability of machine learning algorithms to predict END in patients with acute minor stroke.

Patients And Methods: We collected clinical and neuroimaging information from patients with acute minor stroke with NIHSS score of ≤ 3.

Internet of Things, Digital Biomarker, and Artificial Intelligence in Spine: Current and Future Perspectives.

Recent interest in medical artificial intelligence (AI) has increased with onset of the fourth industrial revolution. Real-time monitoring of patients is an important research area of medical AI. The medical AI is very closely related to the Internet of Things (IoT), a core element of the fourth industrial revolution.

Application of Deep Learning System into the Development of Communication Device for Quadriplegic Patient.

Objective: In general, quadriplegic patients use their voices to call the caregiver. However, severe quadriplegic patients are in a state of tracheostomy, and cannot generate a voice. These patients require other communication tools to call caregivers.

Computer-based clinical coding activity analysis for neurosurgical terms.

Background: It is not possible to measure how much activity is required to understand and code a medical data. We introduce an assessment method in clinical coding, and applied this method to neurosurgical terms.

Methods: Coding activity consists of two stages.

Hounsfield Units on Lumbar Computed Tomography for Predicting Regional Bone Mineral Density.

Objective: Bone mineral density (BMD) is a very important factor in spinal fusion surgery using instrumentation. Our aim was to investigate the utility of Hounsfield units (HU) obtained from preoperative lumbar computed tomography (CT) to predict osteoporosis coupling with data of quantitative computed tomography (QCT) and dual X-ray absorptiometry (DEXA).

Methods: We reviewed 180 patients that underwent both QCT and lumbar CT for spine surgery.

The Usefulness of a Wearable Device in Daily Physical Activity Monitoring for the Hospitalized Patients Undergoing Lumbar Surgery.

Objective: Functional outcomes have traditionally been evaluated and compared using subjective surveys, such as visual analog scores (VAS), the Oswestry disability index (ODI), and Short Form-36 (SF-36), to assess symptoms and quality of life. However, these surveys are limited by their subjective natures and inherent bias caused by differences in patient perceptions of symptoms. The Fitbit Charge® (Fitbit Inc.

Machine Learning Model to Predict Osteoporotic Spine with Hounsfield Units on Lumbar Computed Tomography.

Objective: Bone mineral density (BMD) is an important consideration during fusion surgery. Although dual X-ray absorptiometry is considered as the gold standard for assessing BMD, quantitative computed tomography (QCT) provides more accurate data in spine osteoporosis. However, QCT has the disadvantage of additional radiation hazard and cost.

Symptomatic Pneumocephalus After Spinal Intradural-Extramedullary Tumor Surgery.

Objective: Durotomy is a necessary procedure for resection of spinal intradural-extramedullary (IDEM) tumor. The purpose of this study was to investigate the prevalence and clinical implications of pneumocephalus after spinal IDEM tumor surgery and also the association between pneumocephalus and postoperative headache.

Methods: This prospective study was conducted in a cohort of 20 patients who were diagnosed with a spinal IDEM tumor and underwent surgical resection.

Virtual Preoperative Simulation for Excision of Spinal Tumors: Surgeon Processing of Medical Computer-Assisted Design Software.

As medical computer-aided design (CAD) has improved, virtual 3-dimensional medical images have been gaining more easily without any special practice. These images can be applied to various clinical fields. This article illustrates virtual preoperative simulation for excision of spinal tumors using medical CAD software.

Spontaneous Epidural Hematoma Associated with Venous Phlebolith in Cervical Spine and Possible Pathogenesis.

Although the etiology of spontaneous spinal epidural hematoma (SSEH) is unclear, SSEH is known to be associated with anticoagulants, coagulopathy, vascular malformation, hypertension, and pregnancy. However, no report has been issued on the relation between SSEH and venous phlebolith. Here, the authors present an extremely rare case of SSEH associated with phlebolith in the cervical spine and suggest a possible pathogenesis.

Cervical Pedicle Screw Placement Using Medial Funnel Technique.

Objective: Cervical pedicle screw (CPS) placement is very challenging due to high risk of neurovascular complications. We devised a new technique (medial funnel technique) to improve the accuracy and feasibility of CPS placement.

Methods: We reviewed 28 consecutive patients undergoing CPS instrumentation using the medial funnel technique.

Delayed Epidural Mucin Collection after Surgery for Spinal Metastatic Pancreatic Adenocarcinoma.

A rare case of delayed large epidural mucin collection causing neurologic deficit after surgery for metastatic pancreatic cancer is reported. A 65-year-old man presented with intractable upper-thoracic back pain radiating to the chest and gait disturbance. He had a history of subtotal pancreatectomy due to intraductal papillary mucinous neoplasm (IPMN) of the pancreas and concurrent chemotherapy.