Background: Rapid pathogen identification and antibiotic-susceptibility tests (ASTs) are important for treating bloodstream infections. We compared the performance of the QMAC-dRAST and BD Phoenix M50 direct AST (dPhoenix) systems using bacterial pellets prepared from positive blood culture broth and evaluated their impact on treatment modification. Methods: Direct AST results for 106 Enterobacterales isolates were retrospectively reviewed. Conventional broth microdilution was used to calculate categorical agreement (CA), very major error (VME), major error (ME), and minor error (mE). For isolates showing high VMEs in both methods, supplementary tests were performed. Clinical impact was evaluated by calculating the time required to obtain AST results (time-to-result) and observing changes in antibiotics prescribed after performing ASTs. Results: Both systems showed acceptable overall CA, VME, ME, and mE values (QMACdRAST: 93.6%, 1.6%, 0.9%, and 5.3%, respectively; dPhoenix: 93.1%, 0.9%, 0.6%, and 6.2%, respectively). Piperacillin–tazobactam showed high VMEs with QMAC-dRAST (4/20, 20.0%) and dPhoenix (3/20, 15.0%). Colony AST on 13 isolates revealed that QMACdRAST testing yielded lower minimal inhibitory concentrations (MICs) for piperacillin–tazobactam with three isolates, whereas dPhoenix testing yielded higher MICs with two isolates and lower MICs with two isolates. The average time-to-result was 20.8 hr and 30.1 hr for QMAC-dRAST and dPhoenix, respectively (P < 0.001). After AST, the number of optimal treatments increased from 43 (46.7%) to 72 (78.3%) (P < 0.001). Conclusions The QMAC-dRAST and dPhoenix systems provided reliable AST results with a short time-to-result. However, we recommend performing complementary tests, such as the disk diffusion test, for piperacillin–tazobactam.

Objective: This study aims to compare the incidence of active tuberculosis (TB) among Korean patients with rheumatoid arthritis (RA) initiating treatment with tumor necrosis factor inhibitors (TNFi) or tofacitinib. Methods: Using the Korean National Health Insurance database, we conducted a nationwide, retrospective cohort study of RA patients who started TNFi or tofacitinib therapy between 2015 and 2018. We calculated the incidence rates of active TB based on the treatment type and results from latent tuberculosis infection (LTBI) screening tests. A multivariable Cox proportional hazards model was employed to evaluate the risk of active TB in RA patients beginning TNFi or tofacitinib treatment. Results: Among 3,382 RA patients (596 on tofacitinib and 2,786 on TNFi), LTBI screening was predominantly conducted using the IGRA (interferon-gamma release assays) test. Of these patients, 624 (18.5%) with a positive LTBI test received prophylactic treatment. No cases of active TB occurred in tofacitinib users, while 32 cases were observed in TNFi users. The adjusted hazard ratio for active TB in LTBI-positive patients was 5.47 (95% confidence interval 2.74 to 10.92) compared to LTBI-negative patients.In subgroup analyses, TB incidence was significantly higher among individuals aged over 65 years. Conclusion Despite LTBI treatment, active TB remains prevalent among RA patients on TNFi therapy and in those with positive LTBI tests.

In forensic medicine, age estimation commonly involves assessing age-related changes in teeth and skeletal structures. Vertebral morphological alterations, such as osteophyte formation, serve as age indicators. Recent studies using deep-learning techniques, such as neural networks, for age estimation from radiographic images have been conducted, reporting significantly higher accuracy than previous studies. This study aimed to estimate age using neural network-based deep-learning techniques applied to computed tomography (CT) cross-sectional images of the spine and evaluate its feasibility. Postmortem CT scans of 214 cadavers with varying decomposition levels were used. Coronal and sagittal cross-sectional images penetrating the center of each vertebral body were extracted for the 11th and 12th thoracic vertebrae and the first to fifth lumbar vertebrae. Using these images, along with the chronological ages of deceased individuals, an age estimation model was developed through regression analysis in PyTorch, employing a convolutional neural networks architecture with five-fold cross-validation. The model achieved a mean absolute error of 5.385 years, root mean squared error of 7.029 years, and coefficient of determination of 0.793. Although the sample size was relatively small, the results suggested the potential applicability of vertebral imagingbased age estimation in the Korean population. Further research using a larger dataset may improve the accuracy and reliability of the model.

Objective: Although most gallbladder polyps are benign, some neoplastic polyps may be malignant or may serve as precursors to malignancy. Distinguishing neoplastic and non-neoplastic polyps using imaging examinations remains a major challenge.This meta-analysis aimed to identify the ultrasound (US) features that are significantly associated with neoplastic polyps. Materials and Methods: The MEDLINE, EMBASE, Cochrane, and KoreaMed databases were searched for articles published up to August 31, 2025. Bivariate random-effects models were used to calculate the meta-analytic pooled diagnostic odds ratios (DORs), sensitivities, and specificities, along with their 95% confidence intervals (CIs), for each US imaging feature in the diagnosis of neoplastic polyps. Results: Thirty studies evaluating 8,953 patients, including 1,216 (13.6%) patients with neoplastic polyps, were included.Among the nine evaluated US imaging features, namely, size ≥10 mm, sessile morphology, single polyp, coexisting gallstones, hypoechogenicity, heterogeneous echogenicity, gallbladder wall thickening (GBWT), absence of hyperechoic spot, and vascularity, eight were significantly associated with neoplastic polyps: size ≥10 mm (DOR: 6.23 [95% CI: 1.86– 20.90]), sessile morphology (DOR: 3.54 [1.93–5.97]), single polyp (DOR: 2.21 [1.76–2.74]), coexisting gallstones (DOR:1.86 [1.29–2.60]), hypoechogenicity (DOR: 3.55 [1.47–7.30]), GBWT (DOR: 9.38 [1.47–32.20]), absence of hyperechoic spots (DOR: 4.23 [2.46–6.83]), and vascularity (DOR: 9.72 [5.81–15.30]). Of these, size ≥10 mm demonstrated the highest pooled sensitivity (0.79 [95% CI: 0.68–0.87]), whereas hypoechogenicity showed the highest pooled specificity (0.93 [95% CI: 0.82–0.98]). Conclusion Eight US imaging features (size ≥10 mm, sessile morphology, single polyp, coexisting gallstones, hypoechogenicity, GBWT, absence of hyperechoic spots, and vascularity) were significantly associated with the presence of neoplastic polyps.These features may facilitate the management of gallbladder polyps.

Purpose: Neoadjuvant treatment (NAT) is now the standard for borderline resectable pancreatic cancer (RPC) and is being considered for RPC. Early recurrence after curative surgery in RPC is often seen as a treatment failure, prompting considerations for NAT. Our goal was to develop an artificial intelligence (AI)-based predictive model utilizing preoperatively available factors to forecast early recurrences of resected RPC. Methods: This study included 469 patients who underwent surgery for RPC between 2011 and 2019. Clinicopathologic and oncologic data were retrospectively reviewed. Preoperative variables, including laboratory data and imaging findings, were collected. Early recurrence was defined as recurrence occurring within a year after surgery. Deep neural networks were then used to select variables by assessing their importance. A new model predicting early recurrence of RPC was subsequently developed. Results: Of the patients evaluated, 199 (42.4%) experienced early recurrence. The predictive model included 14 preoperative variables: CA 19-9, preoperative pancreatitis, serum albumin, platelet count, lymphocyte count, the American Society of Anesthesiologists physical status classification, tumor size, monocyte count, age, body mass index, CRP, hemoglobin, WBC count, and CEA. The area under the curve for the model was 0.786 in the training set and 0.734 in the test set. Conclusion We developed an AI-based model to predict the early recurrence of RPC using preoperative parameters. By identifying patients at risk of early recurrence, optimal individualized treatments such as NAT can be considered. Future prospective studies are crucial to establish clear indications for NAT in RPC.

Purpose: The male predominance in the incidence of gastric cancer (GC) is established; however, sex differences in the prognosis of GC remain controversial. As such, this study analyzed the prognosis of patients with GC based on age and sex. Materials and Methods: Data from 14,739 patients diagnosed with GC at Seoul National University Bundang Hospital between 2003 and 2023 were analyzed. Baseline characteristics, histological types of GC, overall and GC-specific survival rates (age and stage stratification), and associated risk factors were analyzed. Results: Females were significantly younger (p < 0.001) and exhibited more gastric body cancers (p < 0.001) and tumors with diffuse-type or poorly differentiated histology (p < 0.001) than males. Females exhibited an advantage over males in terms of overall survival (p=0.004), but not in GC-specific survival. However, age stratification revealed significant sex differences, that females < 50 years of age exhibited survival disadvantages (p < 0.001); however, this trend was reversed with age, and females > 60 years exhibited survival advantages (p < 0.001) for both overall and GC-specific survival. This may be explained by the lower ratio of diffuse-type GC as females age. Furthermore, in the analysis according to stage, females with stage IV disease exhibited significant survival disadvantages, with significantly younger age and a higher proportion of diffuse-type GC which exhibits aggressive features, resulting in poorer survival than in males. Conclusion Age and stage stratification revealed significant differences in survival between the sexes, which can be helpful for public health strategies.

Purpose: This retrospective study evaluated the efficacy and safety of a weekly carfilzomib, cyclophosphamide, and dexamethasone (KCd) regimen in patients with relapsed or refractory multiple myeloma (RRMM) who had been previously treated with both bortezomib- and lenalidomide-containing regimens. Materials and Methods: We conducted a retrospective analysis of 33 patients with RRMM who received the KCd regimen between March 2020 and February 2024. All patients had prior exposure to both bortezomib and lenalidomide, and the majority (93.9%) were refractory to lenalidomide. Carfilzomib was administered once weekly at 70 mg/m2 (after a step-up dose), along with oral cyclophosphamide and dexamethasone. Treatment response was assessed according to the International Myeloma Working Group criteria, and survival outcomes were analyzed. Results: The overall response rate was 66.7%, including a complete response or better in 15.1% of patients and a very good partial response or better in 42.4%. With a median follow-up of 31.7 months, the median progression-free survival was 13.5 months (95% confidence interval, 11.47 to 15.53), while the median overall survival was not reached. The most common grade ≥ 3 adverse event was neutropenia (15.2%). Non-hematologic grade ≥ 3 toxicities were infrequent and manageable. Conclusion The weekly KCd regimen demonstrated encouraging efficacy and tolerability in a heavily pretreated RRMM population. These findings support its use as a feasible treatment option, particularly in patients refractory to lenalidomide.

Pharmacogenomic variations may significantly influence responses to commonly prescribed stroke medications. Despite accumulating evidence, genetic testing has not yet been widely integrated into stroke care. This review summarizes current evidence and provides practical guidance for clinical implementation. Pharmacogenomic studies and clinical guidelines related to antiplatelet agents, anticoagulants, and statins were reviewed, with particular emphasis on East Asian populations. Substantial evidence supports genotype-guided use of clopidogrel (CYP2C19), warfarin (CYP2C9, VKORC1, CYP4F2), and statins (SLCO1B1, ABCG2). For aspirin, PTGS1/2 and PEAR1 variants have been investigated; however, current data remain insufficient for clinical application. Regarding direct oral anticoagulants (DOACs), candidate genes such as ABCB1 and CES1 demonstrate pharmacokinetic associations, though robust clinical outcome data are lacking. Distinct allele frequencies in East Asians—such as higher prevalence of CYP2C19 and ABCG2 variants—underscore the need for population-specific strategies. Beyond single-gene approaches, polygenic risk scores, pharmacogenomic panels, and integration with multi-omics data and artificial intelligence represent promising directions for personalized therapy. Pharmacogenomic testing can enhance stroke pharmacotherapy, particularly in populations with high frequencies of actionable variants. Broader implementation requires rapid testing platforms, clinician education, tailored clinical guidelines, and real-world validation of aspirin, DOACs, and multi-gene approaches. Future research should expand population-specific studies and integrate pharmacogenomics within the broader framework of precision medicine to ensure equitable clinical benefit.