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Non-steroidal anti-inflammatory drugs (NSAIDs) have been widely used in patients with respiratory infection, but their safety in coronavirus disease 19 (Covid-19) patients has not been fully investigated. We evaluated an association between NSAID use and outcomes of Covid-19. This study was a retrospective observational cohort study based on insurance benefit claims sent to the Health Insurance Review and Assessment Service of Korea by May 15, 2020. These claims comprised all Covid-19-tested cases and history of medical service use for the past 3 years in these patients. The primary outcome was all-cause mortality, and the secondary outcome was need for ventilator care. Among 7590 patients diagnosed with Covid-19, two distinct cohorts were generated based on NSAID or acetaminophen prescription within 2 weeks before Covid-19 diagnosis. A total of 398 patients was prescribed NSAIDs, and 2365 patients were prescribed acetaminophen. After propensity score matching, 397 pairs of data set were generated, and all-cause mortality of the NSAIDs group showed no significant difference compared with the acetaminophen group (4.0% vs. 3.0%; hazard ratio [HR], 1.33; 95% confidence interval [CI], 0.63–2.88; P  = 0.46). The rate of ventilator care also did not show significantly different results between the two groups (2.0% vs. 1.3%; HR, 1.60; 95% CI 0.53–5.30; P  = 0.42). Use of NSAIDs was not associated with mortality or ventilator care in Covid-19 patients. NSAIDs may be safely used to relieve symptoms in patients with suspicion of Covid-19.

Myocardial injury after non-cardiac surgery (MINS) is a well-known and relevant indicator of early postoperative mortality, but factors related to increased mortality in MINS patients are as yet unknown. The Charlson Comorbidity Index (CCI) is widely used to classify various comorbid conditions and underlying diseases. Our study aimed to determine the prognostic value of CCI with regard to mortality of patients with MINS. This study comprises 5633 patients who had MINS as diagnosed by a rise of postoperative cardiac troponin I above the normal range (≥ 0.04 ng/mL) from January 2010 to June 2019. Patients were divided into two groups according to median weighted CCI score: low CCI (≤ 2) and high CCI (> 2) groups. The primary outcome was 30-day mortality after surgery, and secondary outcomes were 1-year and overall mortalities. Of the 5633 patients, 3428 (60.9%) were in the low CCI group (1.21 ± 0.84) and 2205 (39.1%) were in the high CCI group (4.17 ± 1.82). After propensity score matching, mortality during the first 30 days after surgery was significantly greater in the high CCI group than the low CCI group (9.4% vs. 6.0%, respectively; hazard ratio 1.56, 95% confidence interval 1.23–1.98, p  < 0.001). A high CCI score was associated with increased 30-day mortality in patients with MINS, suggesting that the CCI may need to be considered when predicting outcomes of MINS patients.

Contradictory findings exist about association of angiotensin-converting enzyme inhibitor (ACEi) and angiotensin receptor blocker (ARB) with lung cancer development. This was a retrospective observational cohort study that used data from 7 hospitals in Korea, converted to the Observational Medical Outcomes Partnership Common Data Model. The primary outcome was occurrence of lung cancer. A total of 207,794 patients across the 7 databases was included in the final analysis; 33,230 (16%) were prescribed ACEi and 174,564 (84%) were prescribed ARB. Crude analysis adjusted for sex and age showed higher incidence of lung cancer in the ACEi group compared to the ARB group (hazard ratio [HR], 1.46; 95% confidence rate [CI], 1.08–1.97). After propensity-score matching, 30,445 pairs were generated, and there was no difference in incidence of lung cancer between the two groups (HR, 0.93; 95% CI, 0.64–1.35). Patients prescribed ACEi showed no difference in incidence of lung cancer development compared to those using ARB. This finding provides evidence on the association between ACEi and occurrence of lung cancer.

Background Postoperative delirium is a common complication that is distressing. This study aimed to demonstrate a prediction model for delirium. Methods Among 203,374undergoing non-cardiac surgery between January 2011 and June 2019 at Samsung Medical Center, 2,865 (1.4%) were diagnosed with postoperative delirium. After comparing performances of machine learning algorithms, we chose variables for a prediction model based on an extreme gradient boosting algorithm. Using the top five variables, we generated a prediction model for delirium and conducted an external validation. The Kaplan–Meier and Cox survival analyses were used to analyse the difference of delirium occurrence in patients classified as a prediction model. Results The top five variables selected for the postoperative delirium prediction model were age, operation duration, physical status classification, male sex, and surgical risk. An optimal probability threshold in this model was estimated to be 0.02. The area under the receiver operating characteristic (AUROC) curve was 0.870 with a 95% confidence interval of 0.855–0.885, and the sensitivity and specificity of the model were 0.76 and 0.84, respectively. In an external validation, the AUROC was 0.867 (0.845–0.877). In the survival analysis, delirium occurred more frequently in the group of patients predicted as delirium using an internal validation dataset ( p  < 0.001). Conclusion Based on machine learning techniques, we analyzed a prediction model of delirium in patients who underwent non-cardiac surgery. Screening for delirium based on the prediction model could improve postoperative care. The working model is provided online and is available for further verification among other populations. Trial registration KCT 0006363.

1-Palmitoyl-2-linoleoyl-3-acetyl-rac-glycerol (PLAG) is a synthetic monoacetyldiglyceride known for its immunomodulatory properties, including regulation of pathological neutrophil trafficking and modulation of antitumor immune responses. In this study, we evaluated the therapeutic potential of PLAG as an adjuvant to high-dose radiotherapy using murine tumor models. Combination treatment with PLAG and radiotherapy significantly delayed tumor growth in immunocompetent mice, whereas this therapeutic benefit was absent in immunodeficient hosts, indicating an immune-dependent mechanism. While PLAG selectively enhance CD8 + T-cell functional activation when combined with radiotherapy compared to radiotherapy alone, as evidenced by increased numbers of INF-γ + , Granzyme B + , and effector memory CD8 + T-cells. PLAG sustained tumor antigen-specific INF-γ secretion of splenocytes after radiotherapy, indicating prolonged systemic immune activation. Importantly, the amplified systemic immune response translated into a robust abscopal effect. In conclusion, these findings suggest that PLAG amplifies and sustains radiotherapy-induced antitumor immunity by increasing functional activation of CD8 + T-cells, and may serve as a promising immunomodulatory adjuvant to improve radiotherapy outcomes.

Myocardial injury after non-cardiac surgery (MINS) is strongly associated with postoperative outcomes. We developed a prediction model for MINS and have provided it online. Between January 2010 and June 2019, a total of 6811 patients underwent non-cardiac surgery with normal preoperative level of cardiac troponin (cTn). We used machine learning techniques with an extreme gradient boosting algorithm to evaluate the effects of variables on MINS development. We generated two prediction models based on the top 12 and 6 variables. MINS was observed in 1499 (22.0%) patients. The top 12 variables in descending order according to the effects on MINS are preoperative cTn level, intraoperative inotropic drug infusion, operation duration, emergency operation, operation type, age, high-risk surgery, body mass index, chronic kidney disease, coronary artery disease, intraoperative red blood cell transfusion, and current alcoholic use. The prediction models are available at https://sjshin.shinyapps.io/mins_occur_prediction/ . The estimated thresholds were 0.47 in 12-variable models and 0.53 in 6-variable models. The areas under the receiver operating characteristic curves are 0.78 (95% confidence interval [CI] 0.77–0.78) and 0.77 (95% CI 0.77–0.78), respectively, with an accuracy of 0.97 for both models. Using machine learning techniques, we demonstrated prediction models for MINS. These models require further verification in other populations.

The effect of renin-angiotensin-aldosterone system (RAAS) inhibitors in coronavirus disease 19 (Covid-19) patients has not been fully investigated. We evaluated the association between RAAS inhibitor use and outcomes of Covid-19. This study was a retrospective observational cohort study that used data based on insurance benefit claims sent to the Health Insurance Review and Assessment Service of Korea by May 15, 2020. These claims comprised all Covid-19 tested cases and the history of medical service use in these patients for the past five years. The primary outcome was all-cause mortality, and the rate of ventilator care was compared between the groups. From a total of 7,590 patients diagnosed with Covid-19, two distinct cohorts were generated based on RAAS inhibitors prescribed within 6 months before Covid-19 diagnosis. A total of 1,111 patients was prescribed RAAS inhibitors, and 794 patients were prescribed antihypertensive drugs, excluding RAAS inhibitors. In propensity-score matched analysis, 666 pairs of data set were generated, and all-cause mortality of the RAAS inhibitor group showed no significant difference compared with the non-RAAS inhibitor group (14.6% vs. 11.1%; hazard ratio [HR], 0.79; 95% confidence interval [CI], 0.54-1.15; p = 0.22). The rate of ventilator care was not significantly different between the two groups (4.4% vs. 4.1%; HR, 1.04; 95%CI, 0.60-1.79; p = 0.89). RAAS inhibitor treatment did not appear to increase the mortality of Covid-19 patients compared with other antihypertensive drugs, suggesting that they may be safely continued in Covid-19 patients.

Natural killer (NK) cells are considered a promising strategy for cancer treatment. Various methods for large-scale NK cell expansion have been developed, but they should guarantee that no viable cells are mixed with the expanded NK cells because most methods involve cancer cells or genetically modified cells as feeder cells. We used an anti-CD16 monoclonal antibody (mAb) and irradiated autologous peripheral blood mononuclear cells (PBMCs) (IrAPs) to provide a suitable environment (activating receptor-ligand interactions) for the NK cell expansion. This method more potently expanded NK cells, and the final product was composed of highly purified NK cells with lesser T-cell contamination. The expanded NK cells showed greater upregulation of various activation receptors, CD107a, and secreted larger amounts of interferon gamma. IrAPs expressed NKG2D ligands and CD48, and coengagement of CD16 with NKG2D and 2B4 caused potent NK cell activation and proliferation. The expanded NK cells were cytotoxic toward various cancer cells in vitro and in vivo . Moreover, irradiation or a chemotherapeutic drug further enhanced this antitumor effect. Therefore, we developed an effective in vitro culture method for large-scale expansion of highly purified cytotoxic NK cells with potent antitumor activity using IrAPs instead of cancer cell-based feeder cells.

Revised cardiac risk index (RCRI) is widely used for surgical patients without containing age as a risk factor. We investigated age older than 65 years with respect to low-to-moderate risk of RCRI. From January 2011 to June 2019, a total of 203,787 consecutive adult patients underwent non-cardiac surgery at our institution. After excluding high-risk patients defined as RCRI score > 2, we stratified the patients into four groups according to RCRI and age (A: age < 65 with RCRI < 2, [ n  = 148,288], B: age ≥ 65 with RCRI < 2, [ n  = 42,841], C: age < 65 with RCRI = 2, [ n  = 5,271], and D: age ≥ 65 with RCRI = 2, [ n  = 5,698]). Incidence of major cardiac complication defined as a composite of cardiac death, cardiac arrest and myocardial infarction was compared. After excluding 1,689 patients with high risk (defined as RCRI score > 2), 202,098 patients were enrolled. The incidence with 95% confidence interval of major cardiac complication for A, B, C, and D groups was 0.3% (0.2–0.3), 1.1% (1.0–1.2), 1.8% (1.6–1.8), and 3.1% (2.6–3.6), respectively. In a direct comparison between B and C groups, old patients with RCRI < 2 showed a significantly lower risk compared to younger patients with RCRI = 2 (odd ratio, 0.62; 95% confidence interval, 0.50–0.78; p  < 0.001). In non-cardiac surgery, the risk of age older than 65 years was shown to be comparable with low-to-moderate risk according to RCRI.

Introduction: Micro-computed tomography with nanoparticle contrast agents may be a suitable tool for monitoring the time course of the development and progression of tumors. Here, we suggest a practical and convenient experimental method for generating and longitudinally imaging murine liver cancer models. Methods: Liver cancer was induced in 6 experimental mice by injecting clustered regularly interspaced short palindromic repeats/clustered regularly interspaced short palindromic repeats-associated protein 9 plasmids causing mutations in genes expressed by hepatocytes. Nanoparticle agents are captured by Kupffer cells and detected by micro-computed tomography, thereby enabling longitudinal imaging. A total of 9 mice were used for the experiment. Six mice were injected with both plasmids and contrast, 2 injected with contrast alone, and one not injected with either agent. Micro-computed tomography images were acquired every 2- up to 14-weeks after cancer induction. Results: Liver cancer was first detected by micro-computed tomography at 8 weeks. The mean value of hepatic parenchymal attenuation remained almost unchanged over time, although the standard deviation of attenuation, reflecting heterogeneous contrast enhancement of the hepatic parenchyma, increased slowly over time in all mice. Histopathologically, heterogeneous distribution and aggregation of Kupffer cells was more prominent in the experimental group than in the control group. Heterogeneous enhancement of hepatic parenchyma, which could cause image quality deterioration and image misinterpretation, was observed and could be due to variation in Kupffer cells distribution. Conclusion: Micro-computed tomography with nanoparticle contrast is useful in evaluating the induction and characteristics of liver cancer, determining appropriate size of liver cancer for testing, and confirming therapeutic response.