The adoption of artificial intelligence (AI) in clinical practice is accelerating. Many physicians perceive effective AI use as requiring unfamiliar technical skills. This paper reexamines that assumption and proposes a reinterpretation of physicians' existing competencies for AI collaboration.Current concepts: Recent AI discourse has moved from prompt engineering toward the broader practice of context engineering. These concepts are not mutually exclusive: prompt engineering may be understood as one component of context engineering, which involves the deliberate collection, structuring, and integration of contextual information to improve AI output quality. In 2025, Gartner identified context engineering as a core AI competency. A 2026 Nature Medicine paper proposed context engineering as an emerging physician role across four axes: data, task, tool, and norm contexts. Whereas that paper framed this as a competency to develop, this paper argues that physicians have already been trained in all four axes. History taking structures subjective context; physical examination generates primary data inaccessible to AI; clinical reasoning defines task context; and guideline adherence with patient preferences constitutes norm context. Furthermore, patients increasingly bring AI-generated health conversation logs—a novel semi-structured context—to clinical encounters, expanding physicians’ context engineering scope with clinical and medicolegal implications.Discussion and conclusion: The challenge is less acquiring a novel technical skill than reframing existing competencies and adopting tools capable of handling rich clinical context. Future research should examine which forms of physician-supplied context most improve AI-assisted decisions and how patient-generated AI logs should be incorporated into clinical documentation.

Extravasation is the unintentional leakage of vesicant or irritant drugs, contrast media, or other infused fluids into surrounding tissue into the surrounding tissue. Extravasation causes injuries ranging from mild irritation to severe necrosis. Incidence ranges from 0.1%–6% in adults and up to 58% in neonates. This review summarizes evidence-based guidelines for diagnosis, management, and prevention.Current concepts: Risk factors include patient-related (fragile veins, older age, neonates, and patients with cancer), procedure- or device-related (inexperienced staff, multiple cannulation attempts, inappropriate catheter selection or fixation, and high infusion pressure), and drug- or product-related (vesicant drugs, high osmolarity or viscosity, and extreme pH) factors. Drugs are classified as vesicants, irritants, or nonvesicants. Diagnosis is primarily clinical, presenting with pain, swelling, and erythema. Differential diagnoses include flare reaction, venous irritation, and venous spasm. Immediate intervention is crucial: stop the infusion, leave the needle in situ for aspiration, then remove the cannula, mark the area, and notify a physician. Management includes elevating the limb, administering specific antidotes, and thermal therapy. Cold compresses are used for DNA-binding vesicants and contrast media, while warm compresses are indicated for non-DNA-binding vesicants. Each session should last 15–20 minutes every 4–6 hours for 24–48 hours.Discussion and conclusion: Surgical referral depends on clinical severity rather than volume alone. Prevention requires standardized protocols, appropriate device selection, and continuous staff training. Adherence to evidence-based guidelines significantly reduces the incidence of extravasation and associated morbidity.

Anesthesiology has evolved from a discipline focused primarily on ensuring intraoperative survival to one that promotes recovery, minimizes complications, and improves long-term outcomes. Drug choice is central to this shift, as it directly affects both immediate and long-term patient results. This review summarizes current evidence on anesthetic drug selection and its clinical implications.Current concepts: Enhanced recovery after surgery (ERAS) emphasizes opioid-sparing strategies and multimodal analgesia, with agents such as propofol, dexmedetomidine, and lidocaine supporting early mobilization and recovery. Sugammadex enables rapid and reliable reversal of neuromuscular blockade, reducing residual paralysis and associated respiratory complications. Remimazolam offers predictable recovery and hemodynamic stability, making it particularly valuable in older or high-risk patients. Beyond perioperative outcomes, precision anesthesia integrates factors such as frailty, sarcopenia, pharmacogenomics, and oncological considerations, suggesting that anesthetic management may influence long-term survival and quality of life.Discussion and conclusion: Anesthetic drug selection should be recognized as a key determinant of patient recovery and prognosis. Integrating ERAS principles, neuromuscular monitoring with sugammadex, and emerging agents such as remimazolam within a precision anesthesia framework can guide safer and more individualized clinical practice.

Remimazolam is a novel, ultra–short-acting benzodiazepine. Developed as a “soft drug,” it is rapidly metabolized by tissue esterases into an inactive metabolite. This metabolism enables fast onset, predictable offset, and straightforward reversibility with flumazenil, distinguishing it from non-benzodiazepine hypnotics.Current concepts: Pharmacokinetically, remimazolam exhibits high clearance, a small steady-state volume of distribution, and a short context-sensitive half-time, which help minimize accumulation during prolonged infusions. Pharmacodynamically, it produces dose-dependent sedation by modulating the GABAA receptor and demonstrates consistent concentration–response relationships. Clinically, randomized and observational studies support its efficacy in procedural sedation and general anesthesia. Remimazolam is associated with stable hemodynamics, reduced vasopressor requirements, and minimal respiratory compromise. Older adults and high-risk patients often experience favorable recovery profiles, and remimazolam shows promise in neurosurgery, where rapid neurological assessment is essential.Discussion and conclusion: Several challenges remain, presenting opportunities for innovation. Sporadic cases of reported anaphylaxis may involve remimazolam itself or the dextran-40 excipient, necessitate careful administration and warrant research into optimized infusion strategies. Reports of resedation after flumazenil antagonism underscore the need for extended recovery monitoring and highlight areas for clinical refinement. Limited pediatric data emphasize the importance of establishing standardized dosing regimens. Discrepancies between bispectral index values and actual hypnotic depth indicate the need to identify drug-specific electroencephalography (EEG) markers. Overall, remimazolam represents a promising alternative to conventional sedative-hypnotics, especially when hemodynamic stability and rapid, reversible hypnosis are priorities. Future studies should prioritize refining dosing strategies for special populations, validating EEG markers, and evaluating long-term cognitive outcomes and cost-effectiveness.

This review aims to provide an evidence-based overview of opioid-free analgesia (OFA) as an emerging strategy for perioperative pain management. Growing concerns regarding opioid-related adverse events, delayed recovery, and persistent postoperative opioid use have prompted a paradigm shift away from opioid-centered analgesia, transitioning first to opioid-sparing strategies and now toward the concept of opioid-free approaches. Drawing on recent meta-analyses and scoping reviews, this article critically evaluates the current strength of evidence supporting OFA and discusses key considerations for its implementation in clinical practice.Current Concepts: OFA combines non-opioid analgesic agents—including dexmedetomidine, ketamine, lidocaine, magnesium, acetaminophen, and nonsteroidal anti-inflammatory drugs—administered with or without regional analgesic techniques. Intraoperative OFA protocols have been shown to reduce the incidence of postoperative nausea and vomiting and to modestly alleviate early postoperative pain, without impairing hemodynamic stability or overall safety. After discharge, OFA provides analgesic efficacy comparable to opioid-based regimens while reducing the occurrence of opioid-related adverse effects. However, the magnitude of these benefits remains relatively modest, and existing clinical evidence is insufficient to support the routine adoption of OFA. Moreover, evidence supporting its effectiveness in the immediate postoperative period remains limited.Discussion and conclusion: OFA represents a promising yet still developing approach in perioperative care. The complete elimination of opioids should not supersede the fundamental goal of ensuring adequate analgesia and promoting functional recovery. Successful implementation requires individualized, procedure-specific protocols that integrate multimodal strategies and allow judicious opioid rescue when necessary. Additional high-quality randomized controlled trials are required to establish its clinical efficacy, cost-effectiveness, and safety.

Sugammadex, introduced in South Korea in 2013, has fundamentally changed the management of neuromuscular blockade. This review summarizes the pharmacology, clinical applications, and safety of sugammadex and analyzes its impact on anesthesia practice in South Korea over the past 12 years.Current concepts: Sugammadex is a modified γ-cyclodextrin that encapsulates rocuronium or vecuronium, enabling rapid reversal at any depth of neuromuscular blockade. Compared with neostigmine, it provides faster and more complete recovery, reduces postoperative residual paralysis, and avoids cholinergic side effects. International guidelines (American Society of Anesthesiologists 2023, European Society of Anaesthesiology and Intensive Care 2023) recommend quantitative neuromuscular monitoring and the preferential use of sugammadex. Experience in South Korea reflects these changes, with improvements in patient safety and expanded use in emergency situations and high-risk populations.Discussion and conclusion: Sugammadex is a paradigm-shifting drug that improves both routine and emergency anesthesia care. Although rare adverse events, such as anaphylaxis and severe bradycardia, require continued vigilance, its overall safety profile is favorable. In South Korea, insurance and policy constraints continue to affect utilization, but greater alignment with international guidelines is expected to broaden access. Future directions include research in infants and patients with renal failure, cost-effectiveness analyses, and further standardization of neuromuscular management.

Advances in surgical techniques, evolving patient demographics, and the expansion of perioperative care have fundamentally reshaped the objectives of modern anesthesia. Beyond maintaining intraoperative unconsciousness and physiological stability, anesthesia is now increasingly expected to influence postoperative recovery and long-term outcomes. This review examines how recent drug-centered innovations are transforming approaches to anesthesia, analgesia, and postoperative recovery and discusses their implications for the future direction of anesthetic practice.Current concepts: Modern anesthesia is delivered within a highly standardized, technology-driven environment that provides a high level of intraoperative safety. Nevertheless, substantial variability persists in postoperative recovery, neurocognitive outcomes, and complication rates, even among patients undergoing similar surgical procedures. Increasing evidence suggests that these differences are closely associated with the pharmacokinetic and pharmacodynamic properties of anesthetic agents. Accordingly, recent advances have emphasized reversibility, predictability, minimization of residual effects, and recovery-oriented pharmacology. Anesthetic agents with predictable recovery profiles, opioid-sparing multimodal analgesic strategies, and rapid neuromuscular blockade reversal exemplify this transition toward recovery-focused anesthesia management.Discussion and conclusion: Anesthetic strategies are evolving from depth-centered control toward the intentional design of recovery trajectories. Pain management is being restructured to reduce opioid-related adverse effects while promoting functional recovery through multimodal, non-opioid-based approaches. Concurrently, the emergence of reversibility as a core safety principle has reshaped anesthetic decision-making. The selection of anesthetic agents represents a central determinant of postoperative recovery, complications, and patient-centered outcomes. Anesthesia should no longer be viewed solely as a transient intraoperative intervention but rather as a deliberately designed, prognostically influential intervention grounded in strategic, evidence-based pharmacologic decision-making.

With a focus on novice researchers, it aims to clarify how artificial intelligence (AI) can support research design and may lower barriers to research participation while emphasizing the continuing importance of human judgment in study conception and interpretation.Current concepts: Traditional medical research training has emphasized methodological theory, statistical techniques, and mentor–mentee instruction. However, these approaches often present substantial challenges for novice researchers. Time constraints, limited access to data, and the need to learn unfamiliar methodologies further contribute to these difficulties. Recent advances in AI enable the rapid synthesis of large volumes of information and structured exploration of research questions. AI also facilitates the organization of study frameworks. These tools may help structure research designs that are less dependent on patient-level data. Examples include social media studies, narrative reviews, and qualitative analyses.Discussion and conclusion: AI has the potential to reshape research design education by functioning as a cognitive support tool. It can help novice researchers formulate meaningful questions, select appropriate study designs, and interpret findings. However, responsible use requires explicit attention to explainability, methodological rigor, and ethical standards. Significant limitations include AI’s dependence on available data, its inability to independently verify information, and the risk of generating misleading suggestions when prompts are poorly constructed. Clear guidance regarding the appropriate scope and limitations of AI-assisted research design is essential. When used appropriately, AI may broaden participation in medical research, enhance research literacy, and support the development of sustainable research skills among clinicians and medical trainees.

Large language models (LLMs) improve medical writing efficiency but introduce methodological, ethical, and legal risks. This review examines current evidence on the limitations of LLM-assisted medical writing and proposes principles for its responsible integration into biomedical research.Current concepts: LLMs are commonly used for draft generation, language editing, literature summarization, reference handling, statistical code generation, and manuscript structuring. Studies consistently report improved readability and reduced writing time, particularly among non-native English-speaking authors. However, recurrent challenges include factual hallucinations; fabricated or inaccurate citations; incomplete retrieval of recent literature due to training cutoffs; prompt-sensitive statistical errors; ambiguity regarding authorship and accountability; risks of unintended plagiarism; and concerns related to patient data privacy. These limitations arise from the probabilistic nature of LLMs and their lack of intrinsic fact-verification mechanisms or ethical reasoning.Discussion and conclusion: Risks associated with LLM use vary by manuscript stage and therefore require differentiated oversight. LLMs should be confined primarily to language refinement rather than fact generation, and literature-related outputs must be verified against primary sources, preferably using retrieval-augmented tools. Statistical analyses should remain under human control, with independent validation of all outputs. Ethical governance requires transparent disclosure of LLM use, clear assignment of human responsibility, and strict safeguards for sensitive data. A dual framework combining human-in-the-loop and human-on-the-loop oversight offers a pragmatic model for balancing efficiency with scientific rigor. When positioned as augmentative tools rather than autonomous agents, LLMs can be responsibly integrated into medical research without compromising integrity or reproducibility.