Neuropathic pain markedly impairs quality of life and imposes a substantial socioeconomic burden, while available treatments often provide only partial relief and are limited by safety concerns. The Neuropathic Pain Special Interest Group of the International Association for the Study of Pain (NeuPSIG-IASP) first published pharmacologic recommendations in 2007, followed by a major update in 2015 and a new guideline in 2025. This narrative review specifically compares the 2015 and 2025 NeuPSIG-IASP guidelines, outlining key methodological changes and therapeutic shifts. The 2025 guideline is based on a larger, more rigorous meta-analysis, maintains α2δ-ligands (adds mirogabalin), serotonin-noradrenaline reuptake inhibitors, and tricyclic antidepressants as first-line drugs, downgrades tramadol into the opioid third-line group. It also introduces high-frequency motor-cortex repetitive transcranial magnetic stimulation as a weakly recommended third-line option and discusses implications for Korean clinical practice.

Purpose: Drainage fluid may serve as a biologically informative indicator of immune and infectious status during postsurgical recovery after trauma. However, microbiome shifts in drainage fluid associated with clinical resilience have not yet been characterized. This study aimed to investigate microbial dynamics in drainage fluid across the intensive care unit (ICU) and ward recovery phases in Korean trauma patients. Methods: A total of 25 drainage and 10 stool samples were collected from 10 trauma patients who underwent abdominal surgery at a regional trauma center. Microbial composition was analyzed using 16S ribosomal RNA amplicon sequencing.Alpha and beta diversity were compared between sample types and recovery stages. Linear mixed-effects models were used to identify recovery-associated taxa while adjusting for clinical variables, and predicted metabolic pathways were assessed using PICRUSt2. Results: Drainage fluid harbored distinct microbial communities independent of the intestinal microbiota. Shared taxa between drainage and stool increased significantly in patients with bowel injury, suggesting microbial translocation.Seven genera and 5 species showed significantly decreased abundance during the ward stage, with Modestobacter and Blastococcus tunisiensis demonstrating the highest discriminative ability between recovery stages (area under the curve = 0.721). Predicted metabolic pathways related to fatty acid degradation, amino acid degradation, and pro-inflammatory processes were more active during the ICU stage. Conclusion These findings provide preliminary evidence that drainage fluid microbiome profiles may reflect recovery dynamics following trauma, supporting its potential utility for microbiome-based monitoring and biomarker discovery in trauma surgery.

Behçet disease (BD) is a multisystem inflammatory disorder characterized by a chronic relapsing course. Because immunosuppressive therapy is the mainstay of BD treatment, its use in transplant recipients may attenuate typical clinical manifestations, thereby complicating diagnosis. We report a case of new-onset intestinal BD that developed in a 28-year-old man 3 years after deceased donor kidney transplantation, following an episode of cytomegalovirus colitis. The patient presented with recurrent abdominal pain, diarrhea, weight loss, and hematochezia. Colonoscopy revealed a deep, oval ulcer with well-demarcated, edematous, and nodular margins in the terminal ileum as well as healed scars near the ileocecal valve, findings consistent with intestinal BD.The patient’s symptoms improved after 2 weeks of therapy with colchicine, mesalazine, and mercaptopurine. This case highlights the rare, de novo development of intestinal BD years after kidney transplantation. Intestinal BD should be considered in transplant recipients presenting with unexplained abdominal pain or diarrhea.

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

Background: Prolonged length of hospital stay (LOS) is associated with an increased risk of hospital-acquired conditions and worse outcomes. We conducted a nationwide, multicenter, retrospective cohort study to determine whether prolonged hospitalization before developing sepsis has a negative impact on its prognosis. Methods: We analyzed data from 19 tertiary referral or university-affiliated hospitals between September 2019 and December 2020. Adult patients with confirmed sepsis during hospitalization were included. In-hospital mortality was the primary outcome. The patients were divided into two groups according to their LOS before the diagnosis of sepsis: early- (< 5 days) and late-onset groups (≥ 5 days). Conditional multivariable logistic regression for propensity score matched-pair analysis was employed to assess the association between lateonset sepsis and the primary outcome. Results: A total of 1,395 patients were included (median age, 68.0 years; women, 36.3%).The early- and late-onset sepsis groups comprised 668 (47.9%) and 727 (52.1%) patients.Propensity score-matched analysis showed an increased risk of in-hospital mortality in the late-onset group (adjusted odds ratio [aOR], 3.00; 95% confidence interval [CI], 1.69–5.34).The same trend was observed in the entire study population (aOR, 1.85; 95% CI, 1.37–2.50).When patients were divided into LOS quartile groups, an increasing trend of mortality risk was observed in the higher quartiles (Pfor trend < 0.001). Conclusion Extended LOS before developing sepsis is associated with higher in-hospital mortality. More careful management is required when sepsis occurs in patients hospitalized for ≥ 5 days.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Background/Aims: Drug-eluting balloons (DEBs) represent a novel therapeutic approach for patients with small coronary artery disease. However, further studies are needed to compare the clinical efficacy of DEBs versus drug-eluting stents (DESs). Methods: In total, 492 patients (age, 67.9 ± 11.0 years; 339 men) with small coronary artery lesions (diameter < 2.75 mm) were randomly assigned to group I (DEB) (n = 104; age, 67.2 ± 10.7 years; 83 men) and group II (DES) (n = 388; age, 68.0 ± 11.1 years; 254 men). For inverse probability of treatment weighting (IPTW) analysis, the study population was stratified into groups I (n = 269) and II (n = 280). We compared the incidences of major adverse cardiac events (MACE) between the two groups during 12 months of clinical follow-up. Results: Group I had shorter device lengths (22.4 ± 5.8 mm) compared with group II (27.4 ± 9.3 mm; p < 0.001). Additionally, devices in group I were smaller in diameter (2.4 ± 0.1 mm) compared with those in group II (2.6 ± 0.1 mm; p < 0.001). Left ventricular ejection fraction (LVEF) was lower in group I (53.8% ± 12.6%) than in group II (58.6% ± 11.9%; p < 0.001). After IPTW, no significant differences in LVEF were observed between groups I and II. During 12 months of follow-up, the incidence of total MACE did not differ between the two groups. Conclusions No significant differences were observed in clinical efficacy between DEB and DES for the treatment of small coronary artery disease. Therefore, DEB can be considered a viable alternative to DES in patients with small coronary artery disease.