Twice-daily rivaroxaban after percutaneous left atrial appendage closure for atrial fibrillation.

Background and aim: Rivaroxaban is an emerging oral anticoagulant for postoperative anticoagulation after percutaneous left atrial appendage closure (LAAC). Because a once-daily dosing regimen of rivaroxaban causes fluctuations in the drug plasma concentration, we studied the feasibility and safety of twice-daily rivaroxaban as a postoperative anticoagulation regimen for patients with atrial fibrillation (AF) undergoing LAAC. Methods: This study involved patients with AF who underwent LAAC and took rivaroxaban postoperatively. A total of 326 patients who received a standard total dose (15 or 20 mg) of rivaroxaban based on their creatinine clearance rate were divided into the twice-daily (BID) rivaroxaban group (n = 208) and once-daily (QD) rivaroxaban group (n = 118) according to their anticoagulation strategy. Transesophageal echocardiography was recommended at 3-6 months postoperatively to check for device-related thrombosis (DRT). Clinical outcomes were evaluated during postoperative anticoagulation. Results: The median CHA2DS2-VASc score (4 [3, 5] vs. 4 [3, 5], p = 0.28) and HAS-BLED score (2 [2, 3] vs. 2 [2, 3], p = 0.48) were not significantly different between the groups. During the anticoagulation period (4.1 ± 0.7 vs. 4.1 ± 0.9 months, p = 0.58), 148 (71.2%) patients in the BID group and 75 (63.6%) in the QD group underwent follow-up transesophageal echocardiography. There were no statistically significant differences between the two groups in terms of DRT (1.4% vs. 2.7%, p = 0.60), minor bleeding (8.2% vs. 11.0%, p = 0.39), thromboembolic events (1.0% vs. 0.8%, p = 1.00), major bleeding (0.5% vs. 0.8%, p = 1.00), or death. Conclusion: A short course of twice-daily rivaroxaban following LAAC is a feasible alternative regimen with a low rate of major bleeding events, DRT, and thromboembolic events for patients with AF.

Comparing safety and efficacy: MemoLefort versus watchman for left atrial appendage closure.

BACKGROUND: The MemoLefort is a new plug occluder for left atrial appendage closure (LAAC) in patients with atrial fibrillation (AF). This study compares the safety and efficacy of MemoLefort and the well-established Watchman occluder for LAAC. METHODS: Between January 2021 and September 2022, a cohort of 189 consecutive patients who underwent LAAC with MemoLefort or Watchman at The Second Affiliated Hospital of Wenzhou Medical University were included. Patients with MemoLefort or Watchman devices were compared in terms of the primary safety endpoints encompassing major periprocedural complications and major bleeding events at follow-up, the primary efficacy endpoint of all-cause stroke, systemic embolism and cardiovascular/unexplained death, and the combined hazard endpoint, a composite of all the above-mentioned hazards. RESULTS: Of the MemoLefort group (n = 83) and Watchman group (n = 106), the mean age, CHA2DS2-VASc score, and HAS-BLED score were 67.6 ± 9.2 vs. 69.0 ± 10.6 years, 3.9 ± 1.9 vs. 3.8 ± 1.9, and 1.6 ± 1.0 vs. 1.7 ± 1.2, respectively. After a median follow-up duration of 198 (99-329) vs. 334 (171-497) days, the primary endpoints of efficacy [2/49, 4.1% (MemoLefort) vs. 2/97, 2.1% (Watchman); hazard ratio (HR), 1.50; 95% confidence interval (CI), 0.20-11.08; P = 0.68] and safety (1/49, 2.0% vs. 5/97, 5.2%; HR, 0.26; 95% CI, 0.05-1.31; P = 0.19), as well as the combined hazard endpoint (3/49, 61% vs. 6/97, 6.2%; HR, 0.70; 95% CI, 0.18-2.58; P = 0.59) were similar between groups. CONCLUSIONS: In the short term, LAAC with MemoLefort provided similar efficacy, safety, and net clinical benefit in comparison to Watchman devices.

Nuclear magnetic resonance-based metabolomics and metabolic pathway networks from patient-matched esophageal carcinoma, adjacent noncancerous tissues and urine.

BACKGROUND: Several studies have demonstrated a correlation between esophageal cancer (EC) and perturbed urinary metabolomic profiles, but none has described the correlation between urine metabolite profiles and those of the tumor and adjacent esophageal mucosa in the same patient. AIM: To investigate how urinary metabolic phenotypes were linked to the changes in the biochemical landscape of esophageal tumors. METHODS: Nuclear magnetic resonance-based metabolomics were applied to esophageal tumor tissues and adjacent normal mucosal tissues alongside patient-matched urine samples. RESULTS: Analysis revealed that specific metabolite changes overlapped across both metrics, including glucose, glutamate, citrate, glycine, creatinine and taurine, indicating that the networks for metabolic pathway perturbations in EC, potentially involved in but not limited to disruption of fatty acid metabolism, glucose and glycolytic metabolism, tricarboxylic acid cycle and glutaminolysis. Additionally, changes in most urinary biomarkers correlated with changes in biomarker candidates in EC tissues, implying enhanced energy production for rapid cell proliferation. CONCLUSION: Overall, these associations provide evidence for distinct metabolic signatures and pathway disturbances between the tumor tissues and urine of EC patients, and changes in urinary metabolic signature could reflect reprogramming of the aforementioned metabolic pathways in EC tissues. Further investigation is needed to validate these initial findings using larger samples and to establish the underlying mechanism of EC progression.

1 H NMR-based metabolomics reveal overlapping discriminatory metabolites and metabolic pathway disturbances between colorectal tumor tissues and fecal samples.

Previous studies have compared fecal metabolites from healthy and colorectal cancer (CRC) patients to predict the pro-CRC signatures. However, the systemic mechanistic link between feces and colonic tissues of CRC patients is still limited. The current study was a paralleled investigation of colonic tumor tissues and their normal adjacent tissues alongside patient-matched feces by using 1 H nuclear magnetic resonance spectroscopy combined with pattern recognition to investigate how fecal metabolic phenotypes are linked to the changes in colorectal tumor profiles. A set of overlapping discriminatory metabolites across feces and tumor tissues of CRC were identified, including elevated levels of lactate, glutamate, alanine, succinate and reduced amounts of butyrate. These changes could indicate the networks for metabolic pathway perturbations in CRC potentially involved in the disruptions of glucose and glycolytic metabolism, TCA cycle, glutaminolysis, and short chain fatty acids metabolism. Furthermore, changes in fecal acetate were positively correlated with alterations of glucose and myo-inositol in colorectal tumor tissues, implying enhanced energy production for rapid cell proliferation. Compared to other fecal metabolites, acetate demonstrated the highest diagnostic performance for diagnosing CRC, with an AUC of 0.843 in the training set, and a good predictive ability in the validation set. Overall, these associations provide evidence of distinct metabolic signatures and metabolic pathway disturbances between the colonic tissues and feces within the same individual, and changes of fecal metabolic signature could reflect the CRC tissue microenvironment, highlighting the significance of the distinct fecal metabolic profiles as potential novel and noninvasive relevant indicators for CRC detection.

Diffusion Kurtosis at 3.0T as an in vivo Imaging Marker for Breast Cancer Characterization: Correlation With Prognostic Factors.

BACKGROUND: Diffusion-kurtosis imaging (DKI) has preliminarily shown promise as a relatively new MRI technique to provide useful information regarding breast lesions, but the diagnostic performance of DKI has not been fully evaluated. PURPOSE: To compare the diagnostic accuracy of DKI, diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE)-MRI) and proton MR spectroscopy (1 H-MRS) in differentiating malignant from benign breast lesions independently or jointly, and explore the correlation between DKI-derived parameters and prognostic factors. STUDY TYPE: Prospective. SUBJECTS: Seventy-one patients with breast lesions (50 malignant, 26 benign). SEQUENCE: DKI, DWI, DCE-MRI, and 1 H-MRS were performed at 3.0T. ASSESSMENT: Mean kurtosis (MK), mean diffusivity (MD), apparent diffusion coefficient (ADC), BI-RADS category, and choline peaks were analyzed by two experienced radiologists. STATISTICAL TESTS: Student's t-test was used for continuous variables; receiver operating characteristic (ROC) analysis for assessing the diagnostic accuracy of imaging parameters; Spearman or Pearson correlations for assessing the associations between imaging parameters and prognostic factors. RESULTS: MK exhibited higher area under the curves (AUCs) for differentiating malignant from benign lesions than did MD, ADC, DCE, and tCho (0.979 vs. 0.928, 0.911, 0.777, and 0.833, respectively, P < 0.05). MK showed a positive association with Ki-67 expression (r = 0.508) and histologic grades (r = 0.551), whereas MD and ADC were negatively correlated with Ki-67 expression (r = -0.416 and r = -0.458) and histologic grades (r = -0.411 and r = -0.319). Moreover, MK showed relatively higher AUCs compared with MD and ADC in detecting breast cancers with lymph nodal involvement, histologic grades, and Ki-67 expression. DATA CONCLUSION: MK has higher diagnostic accuracy compared with ADC, DCE, and tCho regarding detection of breast cancer. Moreover, DKI shows promise as a quantitative imaging technique for characterizing breast lesions, highlighting the potential utility of MK as a promising imaging marker for predicting tumor aggressiveness. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:845-856.

NMR-based metabolomic techniques identify potential urinary biomarkers for early colorectal cancer detection.

Better early detection methods are needed to improve the outcomes of patients with colorectal cancer (CRC). Proton nuclear magnetic resonance spectroscopy (1H-NMR), a potential non-invasive early tumor detection method, was used to profile urine metabolites from 55 CRC patients and 40 healthy controls (HCs). Pattern recognition through orthogonal partial least squares-discriminant analysis (OPLS-DA) was applied to 1H-NMR processed data. Model specificity was confirmed by comparison with esophageal cancers (EC, n=18). Unique metabolomic profiles distinguished all CRC stages from HC urine samples. A total of 16 potential biomarker metabolites were identified in stage I/II CRC, indicating amino acid metabolism, glycolysis, tricarboxylic acid (TCA) cycle, urea cycle, choline metabolism, and gut microflora metabolism pathway disruptions. Metabolite profiles from early stage CRC and EC patients were also clearly distinguishable, suggesting that upper and lower gastrointestinal cancers have different metabolomic profiles. Our study assessed important metabolomic variations in CRC patient urine samples, provided information complementary to that collected from other biofluid-based metabolomics analyses, and elucidated potential underlying metabolic mechanisms driving CRC. Our results support the utility of NMR-based urinary metabolomics fingerprinting in early diagnosis of CRC.

NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in patients with colorectal cancer.

Colorectal cancer (CRC) is a growing cause of mortality in developing countries, warranting investigation into its earlier detection for optimal disease management. A metabolomics based approach provides potential for noninvasive identification of biomarkers of colorectal carcinogenesis, as well as dissection of molecular pathways of pathophysiological conditions. Here, proton nuclear magnetic resonance spectroscopy (1HNMR) -based metabolomic approach was used to profile fecal metabolites of 68 CRC patients (stage I/II=20; stage III=25 and stage IV=23) and 32 healthy controls (HC). Pattern recognition through principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) was applied on 1H-NMR processed data for dimension reduction. OPLS-DA revealed that each stage of CRC could be clearly distinguished from HC based on their metabolomic profiles. Successive analyses identified distinct disturbances to fecal metabolites of CRC patients at various stages, compared with those in cancer free controls, including reduced levels of acetate, butyrate, propionate, glucose, glutamine, and elevated quantities of succinate, proline, alanine, dimethylglycine, valine, glutamate, leucine, isoleucine and lactate. These altered fecal metabolites potentially involved in the disruption of normal bacterial ecology, malabsorption of nutrients, increased glycolysis and glutaminolysis. Our findings revealed that the fecal metabolic profiles of healthy controls can be distinguished from CRC patients, even in the early stage (stage I/II), highlighting the potential utility of NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in CRC patients.