Gadoxetic acid–enhanced MRI had high interobserver variability and low diagnostic performance in the detection of microvascular invasion of hepatocellular carcinoma; therefore, caution is required ... Background Accurate identification of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) before treatment is critical for selecting a proper treatment strategy. Purpose To evaluate the ...

Background: Cardiac complications are associated with perioperative mortality, but perioperative adverse cardiac events (PACEs) that are associated with long‐term mortality have not been clearly defined. We identified PACE as a composite of myocardial infarction, coronary revascularization, congestive heart failure, arrhythmic attack, acute pulmonary embolism, cardiac arrest, or stroke during the 30‐day postoperative period and we compared mortality according to PACE occurrence. Methods and Results: From January 2011 to June 2019, a total of 203 787 consecutive adult patients underwent noncardiac surgery at our institution. After excluding those with 30‐day mortality, mortality during a 1‐year follow‐up was compared. Machine learning with the extreme gradient boosting algorithm was also used to evaluate whether PACE was associated with 1‐year mortality. After excluding 1203 patients with 30‐day mortality, 202 584 patients were divided into 7994 (3.9%) patients with PACE and 194 590 (96.1%) without PACE. After an adjustment, the mortality was higher in the PACE group (2.1% versus 7.7%; hazard ratio [HR], 1.90; 95% CI, 1.74–2.09; P <0.001). Results were similar for 7839 pairs of propensity‐score‐matched patients (4.9% versus 7.9%; HR, 1.64; 95% CI, 1.44–1.87; P <0.001). PACE was significantly associated with mortality in the extreme gradient boostingmodel. Conclusions: PACE as a composite outcome was associated with 1‐year mortality. Further studies are needed for PACE to be accepted as an end point in clinical studies of noncardiac surgery.

Tranilast has been used in allergic diseases because of its inhibitory effect on mast cells; it also has an anti-fibrotic effect in several diseases. Pentoxifylline (PTX), a methylxanthine derivative, is a potent anti-inflammatory drug that is known to manifest its effect through the inhibition of Th1 cytokine, but with an uncertain effect on Th2 cytokine. Seven-week-old female BALB/c mice were studied as a chronic asthma model. The mice were challenged with house dust mite (HDM) antigen for 7 weeks. Each group of mice was given an intraperitoneal injection of tranilast, PTX, or tranilast plus PTX before antigen administration. In this mouse model of chronic asthma, tranilast, and PTX each had an inhibitory effect on airway remodeling as well as on airway hyperresponsiveness (AHR) and airway inflammation. The improved events of these drugs were related with the inhibition of the Th2 cytokine IL-13 and TGF-β 1. Immunohistochemical analysis showed that decreases in the peribronchial trichrome stained area in each treatment group were associated with improvements in the peribronchial smooth muscle hyperplasia, collagen type I, and collagen type III deposition. These drugs could have potential beneficial effects on chronic asthma, especially with respect to airway remodeling.

Background: Prognostic considerations for non-predominant patterns are necessary because most lung adenocarcinomas (ADCs) have a mixed histologic pattern, and the spectrum of actual prognosis varies widely even among lung ADCs with the same most predominant pattern. We aimed to identify prognostic stratification by second most predominant pattern of lung ADC and to more accurately assess prognostic factors with CT imaging analysis, particularly enhancing non-predominant but high-grade pattern. Methods: In this prospective study, patients with early-stage lung ADC undergoing curative surgery underwent preoperative dual-energy CT (DECT) and positron emission tomography (PET)/CT. Histopathology of ADC, the most predominant and second most predominant histologic patterns, and preoperative imaging parameters were assessed and correlated with patient survival. Results: Among the 290 lung ADCs included in the study, 231 (79.7%) were mixed-pathologic pattern. When the most predominant histologic pattern was intermediate-grade, survival curves were significantly different among the three second most predominant subgroups (p = 0.004; low, lepidic; intermediate, acinar and papillary; high, micropapillary and solid). When the second most predominant pattern was high-grade, recurrence risk increased by 4.2-fold compared with the low-grade group (p = 0.005). To predict a non-predominant but high-grade pattern, the non-contrast CT value of tumor was meaningful with a lower HU value associated with the histologic combination of lower grade (low-grade as most predominant and intermediate-grade as second most predominant pattern, OR = 6.15, p = 0.005; intermediate-grade as most predominant and high-grade as second most predominant pattern, OR = 0.10, p = 0.033). SUVmax of the tumor was associated with the non-predominant but high-grade pattern, especially in the histologic combination of intermediate-high grade (OR = 1.14, p = 0.012). Conclusions: The second most predominant histologic pattern can stratify lung ADC patients according to prognosis. Thus, predicting the malignant potential and establishing treatment policies should not rely only on the most predominant pattern. Moreover, imaging parameters of non-contrast CT value and SUVmax could be useful in predicting a non-predominant but high-grade histologic pattern.

Background: Current severity scoring systems in intensive care units (ICUs) are complex and time-consuming, limiting their utility for rapid clinical decision-making. This study aimed to develop and validate simplified prediction models using readily available biomarkers for assessing in-hospital mortality risk. Methods: We analyzed 19,720 adult ICU patients in this retrospective study. Three prediction models were developed: a basic model using lactate-to-albumin ratio (LAR) and neutrophil percent-to-albumin ratio (NPAR) and two enhanced models incorporating mechanical ventilation and continuous renal replacement therapy. Model performance was evaluated against Sequential Organ Failure Assessment (SOFA) score and Acute Physiology and Chronic Health Evaluation (APACHE) II score using machine learning approaches and validated through comprehensive subgroup analyses. Results: Among individual biomarkers, SOFA score showed the highest discriminatory power (area under these curves [AUC] 0.931), followed by LAR (AUC 0.830), CAR (AUC 0.749), and NPAR (AUC 0.748). Our enhanced Model 3 demonstrated exceptional predictive performance (AUC 0.929), statistically comparable to SOFA (p = 0.052), and showed a trend toward superiority over APACHE II (AUC 0.900, p = 0.079). Model 2 performed comparably to APACHE II (AUC 0.913, p = 0.430), while Model 1, using only LAR and NPAR, achieved robust performance (AUC 0.898) despite its simplicity. Subgroup analyses across different ICU types demonstrated consistent performance of all three models, supporting their broad clinical applicability. Conclusions: This study introduces novel, simplified prediction models that rival traditional scoring systems in accuracy while offering significantly faster implementation. These findings represent a crucial step toward more efficient and practical risk assessment in critical care, potentially enabling earlier clinical interventions and improved patient outcomes.

We evaluated the optimal mean arterial pressure (MAP) for favorable neurological outcomes in patients who underwent extracorporeal cardiopulmonary resuscitation (ECPR). Adult patients who underwent ECPR were included. The average MAP was obtained during 6, 12, 24, 48, 72, and 96 h after cardiac arrest, respectively. Primary outcome was neurological status upon discharge, as assessed by the Cerebral Performance Categories (CPC) scale (range from 1 to 5). Overall, patients with favorable neurological outcomes (CPC 1 or 2) tended to have a higher average MAP than those with poor neurological outcomes. Six models were established based on ensemble algorithms for machine learning, multiple logistic regression and observation times. Patients with average MAP around 75 mmHg had the least probability of poor neurologic outcomes in all the models. However, those with average MAPs below 60 mmHg had a high probability of poor neurological outcomes. In addition, based on an increase in the average MAP, the risk of poor neurological outcomes tended to increase in patients with an average MAP above 75 mmHg. In this study, average MAPs were associated with neurological outcomes in patients who underwent ECPR. Especially, maintaining the survivor’s MAP at about 75 mmHg may be important for neurological recovery after ECPR.