Osteoarthritis (OA) is the most common form of arthritis, and its prevalence is expected to further increase as our society ages.Despite many approaches to cure OA, no drugs are currently proven to modulate the progression of OA. Nowadays, new OA treatment options are holistically developed and one of the approaches of treatment option is botanical drugs. Some botanical drugs for OA have shown both therapeutic effect comparable to refined drugs in small studies and fewer side effects. Hence, there are various health functional foods which are known to relieve symptoms of OA. However, since there are many botanical products, clinicians are not familiar to the efficacy of each botanical product, making it challenging to use them appropriately in clinical practice. Here, we summarize the botanical products available for treating OA, including prescription botanical drugs and health functional foods available in Korea. Further studies and the purification of effective molecules from botanical products will be necessary in future.

Osteoarthritis is the most common form of chronic inflammatory arthritis, and its prevalence is steadily increasing owing to its association with aging. Therefore, understanding and implementing appropriate treatments for osteoarthritis in clinical practice is becoming increasingly important. Additionally, there is active research on a new approach for treating osteoarthritis: disease-modifying osteoarthritis drugs (DMOADs).Current Concepts: Several global osteoarthritis treatment guidelines exist; this article introduces the guidelines of the American College of Rheumatology and Osteoarthritis Research Society International, which are among the most widely recognized. A common theme across various guidelines is that exercise and weight loss are the primary recommended treatments. As for pharmacotherapy, the top recommendations include topical nonsteroidal anti-inflammatory drugs (NSAIDs) and oral NSAIDs. Although multiple classes of drugs such as DMOADs are being actively researched to slow the progression of osteoarthritis, no drug has yet been confirmed to be clinically effective or approved for use.Discussion and Conclusion: A deeper understanding of osteoarthritis treatment can help prevent malpractice and improve patient outcomes. While current treatments focus primarily on symptom management, the development of effective DMOADs holds promise for fundamentally altering the disease course and improving joint function and quality of life.

Osteoarthritis (OA) is the most prevalent chronic joint disorder that leads to pain, disability, and functional impairment. The OA prevalence among those aged ≥65 years in Korea was 30.2% between 2017 and 2021. Owing to a rapidly aging population, OA is becoming a significant public health and socioeconomic concern.Current Concepts: The onset of OA is characterized by cartilage injury, which affects the surrounding tissues and progresses to joint destruction. The pathophysiology varies across joints; hand OA is associated with genetic factors, whereas knee and hip OA are associated with mechanical stress. Nonsteroidal anti-inflammatory drugs are the primary treatment; however, considering their adverse effects and limited efficacy in halting disease progression, further research is warranted for more effective therapies. Natural medicines have been investigated; however, their clinical efficacy is inadequate.Discussion and Conclusion: Currently, no disease-modifying treatments are validated for OA. Animal models fail to reflect the slow progression and complexity of human OA; therefore, drug development remains challenging. In view of increasing healthcare costs and rapid population aging, further research and broader socioeconomic strategies are essential to manage the growing burden of OA.

Background/Aims: Hyperuricemia plays an essential role in the gout. Despite the clinical significance of hyperuricemia, a direct relationship between oral health and hyperuricemia has not been established. We aim to investigate the association between oral health and hyperuricemia. Methods: We selected 17,557 subjects from the Korea National Health and Nutrition Examination Survey database for the years 2016–2019. Oral health-related variables included the number of dental caries, regular tooth brushing, use of secondary oral products, and regular dental examinations. The odds ratio (OR) and 95% confidence intervals (CIs) for hyperuricemia were calculated using a multivariable-adjusted logistic regression model. Results: Oral health status with dental caries and oral health behaviors, including tooth brushing, secondary oral products, and regular dental examination, were significantly associated with hyperuricemia in all participants. The adjusted OR and 95% CIs for hyperuricemia comparing more than three dental caries with no dental caries were 1.28 (1.08–1.52). The adjusted OR and 95% CIs for hyperuricemia in regular tooth brushing, use of secondary oral products, and regular dental examination were 0.78 (0.67–0.91), 0.91 (0.83–1.00), and 0.86 (0.78–0.95), respectively. Notably, the association between oral health and hyperuricemia was more prominent in male subjects. In addition, when subjects were grouped by the oral health scoring system, the prevalence of hyperuricemia was lower in groups with better oral health scores. Conclusions We demonstrated that oral health status and behaviors are associated with hyperuricemia, particularly in males. Further studies are necessary to confirm the association between oral health and hyperuricemia.

Background: Chronic glucocorticoid exposure is associated with resistance to nondepolarizing neuromuscular blocking agents. Therefore, we hypothesized that sugammadex-induced recovery would occur more rapidly in subjects exposed to chronic dexamethasone compared to those who were not exposed. This study evaluated the sugammadex-induced recovery profile after neuromuscular blockade (NMB) in rats exposed to chronic dexamethasone. Methods: Sprague–Dawley rats were allocated to three groups (dexamethasone, control, and pair-fed group) for the in vivo study. The mice received daily intraperitoneal dexamethasone injections (500 μg/kg) or 0.9% saline for 15 days. To achieve complete NMB, 3.5 mg/kg rocuronium was administered on the sixteenth day. The recovery time to a train-of-four ratio ≥ 0.9 was measured to evaluate the complete recovery following the sugammadex injection. Results: Among the groups, no significant differences were observed in the recovery time to a train-of-four ratio ≥ 0.9 following sugammadex administration (P = 0.531). The time to the second twitch of the train-of-four recovery following rocuronium administration indicated that the duration of NMB was significantly shorter in Group D than that in Groups C and P (P = 0.001). Conclusions Chronic exposure to dexamethasone did not shorten the recovery time of sugammadex-induced NMB reversal. However, the findings of this study indicated that no adjustments to sugammadex dosage or route of administration is required, even in patients undergoing long-term steroid treatment.

Tables and figures are commonly adopted methods for presenting specific data or statistical analysis results. Figures can be used to display characteristics and distributions of data, allowing for intuitive understanding through visualization and thus making it easier to interpret the statistical results. To maximize the positive aspects of figure presentation and increase the accuracy of the content, in this article, the authors will describe how to choose an appropriate figure type and the necessary components to include. Additionally, this article includes examples of figures that are commonly used in research and their essential components using virtual data.

Sugammadex is a specific antagonist of aminosteroidal neuromuscular blocking agents with 1:1 binding to guest molecules. Sugammadex can also bind to other drugs having a steroid component in its chemical structure. In this in vivo experiment, we investigated the differences in the recovery of rocuronium-induced neuromuscular blockade using sugammadex pre-exposed with two different concentrations of hydrocortisone. Methods: The sciatic nerves and tibialis anterior muscles of 30 adult Sprague–Dawley rats were prepared for the experiment. The sciatic nerves were stimulated using a train-of-four (TOF) pattern with indirect supramaximal stimulation at 20 s intervals. After 15 min of stabilization, a 250 μg loading dose and 125 μg booster doses of rocuronium were serially administered until > 95% depression of the first twitch tension of TOF stimulation (T1) was confirmed. The study drugs were prepared by mixing sugamadex with the same volume of three different stock solutions (0.9% normal saline, 10 mg/ml hydrocortisone, and 100 mg/ ml hydrocortisone). The recovery of rats from neuromuscular blockade was monitored by assessing T1 and the TOF ratio (TOFR) simultaneously until T1 was recovered to > 95% and TOFR to > 0.9. Results: In the group injected with sugammadex premixed with a high concentration of hydrocortisone, statistically significant intergroup differences were observed in the recovery progression of T1 and TOFR (P < 0.050). Conclusions: When sugammadex was pre-exposed to a high dose of hydrocortisone only, recovery from neuromuscular blockade was delayed. Delayed recovery from neuromuscular blockade is not always plausible when sugammadex is pre-exposed to steroidal drugs.

Background: Conventional modality requires several days observation by Holter monitor to differentiate atrial fibril‑ lation (AF) between Paroxysmal atrial fibrillation (PAF) and Non-paroxysmal atrial fibrillation (Non-PAF). Rapid and practical differentiating approach is needed. Objective: To develop a machine learning model that observes 10-s of standard 12-lead electrocardiograph (ECG) for real-time classification of AF between PAF versus Non-PAF. Methods: In this multicenter, retrospective cohort study, the model training and cross-validation was performed on a dataset consisting of 741 patients enrolled from Severance Hospital, South Korea. For cross-institutional validation, the trained model was applied to an independent data set of 600 patients enrolled from Ewha University Hospital, South Korea. Lasso regression was applied to develop the model. Results: In the primary analysis, the Area Under the Receiver Operating Characteristic Curve (AUC) on the test set for the model that predicted AF subtype only using ECG was 0.72 (95% CI 0.65–0.80). In the secondary analysis, AUC only using baseline characteristics was 0.53 (95% CI 0.45–0.61), while the model that employed both baseline characteris‑ tics and ECG parameters was 0.72 (95% CI 0.65–0.80). Moreover, the model that incorporated baseline characteristics, ECG, and Echocardiographic parameters achieved an AUC of 0.76 (95% CI 0.678–0.855) on the test set. Conclusions Our machine learning model using ECG has potential for automatic differentiation of AF between PAF versus Non-PAF achieving high accuracy. The inclusion of  Echocardiographic parameters further increases model per‑ formance. Further studies are needed to clarify the next steps towards clinical translation of the proposed algorithm.

General medical journals such as the Korean Journal of Anesthesiology (KJA) receive numerous manuscripts every year. However, reviewers have noticed that the tables presented in various manuscripts have great diversity in their appearance, resulting in difficulties in the review and publication process. It might be due to the lack of clear written instructions regarding reporting of statistical results for authors. Therefore, the present article aims to briefly outline reporting methods for several table types, which are commonly used to present statistical results. We hope this article will serve as a guideline for reviewers as well as for authors, who wish to submit a manuscript to the KJA.

General medical journals such as the Korean Journal of Anesthesiology (KJA) receive numerous manuscripts every year. However, reviewers have noticed that the tables presented in various manuscripts have great diversity in their appearance, resulting in difficulties in the review and publication process. It might be due to the lack of clear written instructions regarding reporting of statistical results for authors. Therefore, the present article aims to briefly outline reporting methods for several table types, which are commonly used to present statistical results. We hope this article will serve as a guideline for reviewers as well as for authors, who wish to submit a manuscript to the KJA.