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Background: To investigate the doctor shopping trend of patients with rotator cuff tear (RCT) before undergoing surgery and the relevance of the results to the public. Methods: A survey was conducted of 326 patients from 10 hospitals (male, 176; female, 150) who underwent arthroscopic rotator cuff repair (ARCR) for symptomatic RCT between September 2019 and February 2020. A questionnaire was used to obtain data regarding the type of medical care service, medical institutions visited before surgery, number of treatments received, and cost of treatment. Results: A total of 326 patients (87%) received treatment at least once at another medical institution before visiting the hospital where the surgery was performed. Patients visited an average of 9.4 health providers or physicians for shoulder pain before visiting the hospital where surgery was performed. Among the 326 patients, 148 (45%) visited more than two medical institutions and spent an average of 641,983 Korean won (KRW; $466, 50,000-5,000,000 KRW) before surgery. Medical expenses before surgery were proportional to the number of medical institutions visited (P=0.002), symptom duration (P=0.002), and initial visual analog scale (VAS) pain score (P=0.007) but were not associated with gender, age, VAS pain score immediately before surgery, or RCT size. Conclusions: Medical expense before ARCR was associated with the severity of preoperative pain and duration of symptoms. After onset of shoulder symptoms, patients should visit as soon as possible a hospital that has surgeons who specialize in shoulder repair to prevent unnecessary medical expense and proper treatment.
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Background: The morphology of the suprascapular notch (SSN) and the ossification of the superior transverse suprascapular ligament (STSL) are risk factors for injury of the suprascapular nerve (SN) during arthroscopic shoulder procedures. The purpose of the current study was to compare preoperative clinical and radiologic characteristics between patients with and without STSL ossification and to evaluate SSN morphology in patients who underwent arthroscopic rotator cuff repair using a 3-dimensional (3D) reconstructed model. Methods: Patients who underwent arthroscopic rotator cuff repair and were given a computed tomography (CT) scan from March 2018 to August 2019 were included in this study. Patients were divided into 2 groups: those without STSL ossification (group I) and those with STSL ossification (group II). Tear size of the rotator cuff and fatty infiltration of rotator cuff muscles were assessed in preoperative magnetic resonance imaging. The morphology of the SSN was classified following Rengachary's classification. The transverse and vertical diameters of the SSN and the distances from anatomical landmarks to the STSL were measured. All measurements were completed using a 3D CT reconstructed scapula model. Results: A total of 200 patients were included in this study. One hundred seventy-eight patients (89.0%) without STSL ossification were included in group I, and 22 patients (11.0%) with STSL ossification were included in group II. Group II showed a significantly advanced age (61.0 ± 7.4 vs. 71.0 ± 7.3 years, p < 0.001) and a shorter transverse diameter of SSN (10.7 ± 3.1 mm vs. 6.1 ± 3.7 mm, p < 0.001) than group I. In the logistic regression analysis, age was an independent prognostic factor for STSL ossification (odds ratio, 1.201; 95% confidence interval, 1.112-1.296; p < 0.001). Patients in type VI showed significantly shorter transverse diameters than other types (p < 0.001). The patient with type I showed a significantly shorter distance from the articular surface of the glenoid to the SSN than those with other types (p < 0.001). Conclusions: In the 3D morphological analysis, age was the independent factor associated with STSL ossification in patients who underwent arthroscopic rotator cuff repair. Type VI showed significantly shorter transverse diameters than other types. Type I showed a significantly shorter distance from the articular surface of the glenoid to the SSN than other types.
Subject(s)
Arthroscopy , Imaging, Three-Dimensional , Rotator Cuff Injuries , Tomography, X-Ray Computed , Humans , Arthroscopy/methods , Female , Male , Middle Aged , Rotator Cuff Injuries/surgery , Rotator Cuff Injuries/diagnostic imaging , Aged , Retrospective Studies , Ossification, Heterotopic/diagnostic imaging , Ossification, Heterotopic/surgery , Rotator Cuff/surgery , Rotator Cuff/diagnostic imaging , Scapula/diagnostic imaging , Scapula/surgery , Ligaments, Articular/surgery , Ligaments, Articular/diagnostic imaging , AdultABSTRACT
Artificial intelligence (AI) has rapidly transformed various aspects of life, and the launch of the chatbot "ChatGPT" by OpenAI in November 2022 has garnered significant attention and user appreciation. ChatGPT utilizes natural language processing based on a "generative pre-trained transfer" (GPT) model, specifically the transformer architecture, to generate human-like responses to a wide range of questions and topics. Equipped with approximately 57 billion words and 175 billion parameters from online data, ChatGPT has potential applications in medicine and orthopedics. One of its key strengths is its personalized, easy-to-understand, and adaptive response, which allows it to learn continuously through user interaction. This article discusses how AI, especially ChatGPT, presents numerous opportunities in orthopedics, ranging from preoperative planning and surgical techniques to patient education and medical support. Although ChatGPT's user-friendly responses and adaptive capabilities are laudable, its limitations, including biased responses and ethical concerns, necessitate its cautious and responsible use. Surgeons and healthcare providers should leverage the strengths of the ChatGPT while recognizing its current limitations and verifying critical information through independent research and expert opinions. As AI technology continues to evolve, ChatGPT may become a valuable tool in orthopedic education and patient care, leading to improved outcomes and efficiency in healthcare delivery. The integration of AI into orthopedics offers substantial benefits but requires careful consideration and continuous improvement.
Subject(s)
Artificial Intelligence , Orthopedic Procedures , Humans , Natural Language Processing , Patient CareABSTRACT
BACKGROUND: This study aimed to identify plasma and urinary cytokines as potential biomarkers for severe knee osteoarthritis (OA). It also investigated associations between these cytokines and cartilage markers, as well as their connections with synovial fluid (SF) markers. METHODS: Samples of plasma, urine, and SF were obtained from patients (n = 40) undergoing total knee arthroplasty (TKA) or unicompartmental knee arthroplasty (UKA) due to severe knee OA. Control samples of plasma and urine were collected from non-OA individuals (n = 15). We used a Luminex immunoassay for the simultaneous measurement of 19 cytokines, MMP-1, and MMP-3 levels. COMP, CTX-II, and hyaluronan (HA) levels were quantified using enzyme-linked immunosorbent assay (ELISA) kits. Receiver operating characteristic (ROC) curves were utilized to analyze each biomarker's performance. Correlations among these biomarkers were evaluated via Spearman's correlation. RESULTS: The levels of plasma (p)CCL11, pCXCL16, pIL-8, pIL-15, pHA, urinary (u)CCL2, uCCL11, uCCL19, uCXCL16, uIL-1ß, uIL-6, uIL-8, uIL-12p70, uIL-15, uIL-33, uMMP-3, uHA, uCTX-II, and uCOMP were significantly elevated in individuals with severe knee OA. Notably, specific correlations were observed between the plasma/urine biomarkers and SF biomarkers: pCCL11 with sfHA (r = 0.56) and sfTNF-α (r = 0.58), pIL-15 with sfCCL19 (r = 0.43) and sfCCL20 (r = 0.44), and uCCL19 with sfCCL11 (r = 0.45) and sfIL-33 (r = 0.51). Positive correlations were also observed between uCCL11 and its corresponding sfCCL11(r = 0.49), as well as between sfCCL11 and other cytokines, namely sfCCL4, sfCCL19, sfCCL20, sfIL-33, and sfTNF-α (r = 0.46-0.63). CONCLUSION: This study provides an extensive profile of systemic inflammatory mediators in plasma of knee OA and identified four inflammatory markers (pCCL11, pIL-15, uCCL11, and uCCL19) reflecting joint inflammation.
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Hypoxia-inducible factor-1α (HIF-1α) is a major transcriptional factor, which plays an important role in cellular reprogramming processes under hypoxic conditions, which facilitate solid tumors' progression. HIF-1α is directly involved in the regulation of the angiogenesis, metabolic reprogramming, and extracellular matrix remodeling of the tumor microenvironment. Therefore, an in-depth study on the role of HIF-1α in solid tumor malignancies is required to develop novel anti-cancer therapeutics. HIF-1α also plays a critical role in regulating growth factors, such as the vascular endothelial growth factor, fibroblast growth factor, and platelet-derived growth factor, in a network manner. Additionally, it plays a significant role in tumor progression and chemotherapy resistance by regulating a variety of angiogenic factors, including angiopoietin 1 and angiopoietin 2, matrix metalloproteinase, and erythropoietin, along with energy pathways. Therefore, this review attempts to provide comprehensive insight into the role of HIF-1α in the energy and angiogenesis pathways of solid tumors.
Subject(s)
Signal Transduction , Vascular Endothelial Growth Factor A , Humans , Vascular Endothelial Growth Factor A/metabolism , Cell Line, Tumor , Transcription Factors , Vascular Endothelial Growth Factors , Hypoxia-Inducible Factor 1, alpha Subunit/metabolism , Neovascularization, Pathologic/pathologyABSTRACT
Tendinopathy is a debilitating condition marked by degenerative changes in the tendons. Its complex pathophysiology involves intrinsic, extrinsic, and physiological factors. While its intrinsic and extrinsic factors have been extensively studied, the role of physiological factors, such as hypoxia and oxidative stress, remains largely unexplored. This review article delves into the contribution of hypoxia-associated genes and oxidative-stress-related factors to tendon degeneration, offering insights into potential therapeutic strategies. The unique aspect of this study lies in its pathway-based evidence, which sheds light on how these factors can be targeted to enhance overall tendon health.