A retrospective cohort study on the association between early coagulation disorder and short-term all-cause mortality of critically ill patients with congestive heart failure.

Conventional imaging methods such as magnetic resonance imaging, computed tomography and digital subtraction angiography have limited temporospatial resolutions and shortcomings like invasive angiography, potential allergy to contrast agents, and image deformation, that restrict their application in highresolution visualization of the structure of microvessels. In this study, through comparing synchrotron radiation (SR) absorption-contrast imaging to absorption phase-contrast imaging, it was found that SR-based phase-contrast imaging could provide more detailed ultra-high-pixel images of microvascular networks than absorption phase-contrast imaging. Simultaneously, SR-based phasecontrast imaging was used to perform high-quality, multi-dimensional and multi-scale imaging of rat brain angioarchitecture. With the aid of image postprocessing, high-pixel-size two-dimensional virtual slices can be obtained without sectioning. The distribution of blood supply is in accordance with the results of traditional tissue staining. Three-dimensional anatomical maps of cerebral angioarchitecture can also be acquired. Functional partitions of regions of interest are reproduced in the reconstructed rat cerebral vascular networks. Imaging analysis of the same sample can also be displayed simultaneously in two-and three-dimensional views, which provides abundant anatomical information together with parenchyma and vessels. In conclusion, SR-based phase-contrast imaging holds great promise for visualizing microstructure of microvascular networks in two-and three-dimensional perspectives during the development of neurovascular diseases.

BackgroundCardiac arrest (CA) can activate blood coagulation. This study aimed to explore the potential prognostic value of prothrombin time–international normalized ratio (INR) in post-CA patients.MethodsThe clinical data of eligible subjects diagnosed with CA was extracted from the MIMIC-IV database as the training cohort. Restricted cubic spline (RCS), Kaplan–Meier (K-M) survival curve, and Cox regression analyses were conducted to elucidate the association between the INR and all-cause mortality of post-CA patients. Subgroup analysis, propensity score matching (PSM), and inverse probability of treatment (IPTW) were also conducted to improve stability and reliability. Data of the validation cohort were collected from the eICU database, and logistic-regression analyses were performed to verify the findings of the training cohort.ResultsA total of 1,324 subjects were included in the training cohort. A linear correlation existed between INR and the risk of all-cause death of post-CA patients, as shown in RCS analysis, with a hazard ratio (HR) >1 when INR exceeded 1.2. K-M survival curve preliminarily indicated that subjects with INR ≥ 1.2 presented lower survival rate and shorter survival time, and the high level of INR was independently associated with 30-day, 90-day, 1-year, and in-hospital mortalities, with multivariate-adjusted HR of 1.44 (1.20, 1.73), 1.46 (1.23, 1.74), 1.44 (1.23, 1.69), and 1.37 (1.14, 1.64), respectively. These findings were consistent and robust across the subgroup analysis, PSM and IPTW analyses, and validation cohort.ConclusionsWe systematically and comprehensively demonstrated that elevated INR was associated with increased short- and long-term all-cause mortality of post-CA patients. Therefore, elevated INR may be a promising biomarker with prognosis significance.

Background Systemic immune-inflammation index (SII) is a novel inflammatory-related biomarker, and we aim to explore whether it can predict the poor prognosis of patients with aortic stenosis (AS). Methods The detailed data of patients with AS were extracted from the MIMIC-IV database. Restricted cubic spline (RCS) and COX regression analyses were used to reveal the potential association between SII and all-cause mortalities. Propensity score matching (PSM), inverse probability of treatment weighting (IPTW), and subgroup analyses were conducted to validate our findings. Receiver operating characteristic (ROC) analysis was performed to assess the performance of SII prognostic model. Results 839 patients were included in the study cohort. RCS analysis elucidated that the death risk of patients was gradually elevated with the increase of SII. Multivariate-adjusted 30-day (HR: 2.130; 95% CI: 1.167–3.885), 90-day (HR:1.644; 95% CI: 1.059–2.552) and 1-year (HR: 1.634; 95% CI: 1.136–2.350) all-cause mortalities were significantly higher in patients with high SII, which remained robust after PSM, IPTW, and subgroup analyses. The area under the ROC curve of SII (AUC: 0.727; 95% CI: 0.683–0.771) was superior to that of SOFA (AUC: 0.577; 95% CI: 0.525–0.629) and SAPSII (AUC: 0.681; 95% CI: 0.638–0.724) scores. Conclusion For patients with AS, SII was an independent predictor of elevated short-and long-term all-cause mortalities, with good predictive capability.