Use of levosimendan combined with Shenfu injection to treat acute heart failure patients with hypotension: a prospective randomized controlled single-blind study.

BACKGROUND: Levosimendan can improve clinical symptoms and the cardiorenal rescue success rate, and stabilize hemodynamic parameters in individuals suffering from acute decompensated heart failure. In addition, Shenfu injection (SFI) has been shown to protect the ischemic heart and enhance myocardial contractility. METHODS: For this randomized control single-blind study, 101 patients with acute decompensated heart failure (ADHF) were enrolled and randomly assigned to control levosimendan (n = 51) and levosimendan + SFI injection (n = 50) groups. Attending physicians were not blinded for which arm the patients were allocated. Blood pressure, heart rate, the electrocardiogram, respiratory rate, fluid intake and urine output were all recorded 2 h and 24 h after drug infusions had commenced, and the cardiac index (CI) was monitored by ultrasonic cardiac output monitors. RESULTS: Median blood pressure was markedly increased in the levosimendan + SFI group after 2 h and 24 h from the initiation of infusions compared to levosimendan administration alone. Brain natriuretic peptide (BNP) concentrations were reduced after administrations of levosimendan + SFI or solely levosimendan (both P < 0.001). Alterations in BNP concentrations were not different in the combination and control groups. No differences were found between the 2 groups in heart rate or severe hypotension, but blood pressure (systolic blood pressure, diastolic blood pressure) and hemodynamic parameters including CI, cardiac output and stroke volume index responded better in the levosimendan + SFI group compared to the monotherapy levosimendan group. CONCLUSIONS: Levosimendan + SFI was superior to treat ADHF patients compared to levosimendan monotherapy and produced significant improvements in hemodynamic parameters especially for ADHF patients with hypotension. Trail registration The study was prospectively registered at Chinese Clinical Trial Registry with registration number [ChiCTR2000039385] (10/25/2020).

Multi-set canonical correlation analysis for the fusion of concurrent single trial ERP and functional MRI.

Functional magnetic resonance imaging (fMRI) data and electroencephalography (EEG) data provide complementary spatio-temporal information about brain function. Methods to couple the relative strengths of these modalities usually involve two stages: first forming a feature set from each dataset based on one criterion followed by exploration of connections among the features using a second criterion. We propose a data fusion method for simultaneously acquired fMRI and EEG data that combines these steps using a single criterion for finding the cross-modality associations and performing source separation. Using multi-set canonical correlation analysis (M-CCA), we obtain a decomposition of the two modalities, into spatial maps for fMRI data and a corresponding temporal evolution for EEG data, based on trial-to-trial covariation across the two modalities. Additionally, the analysis is performed on data from a group of subjects in order to make group inferences about the covariation across modalities. Being multivariate, the proposed method facilitates the study of brain connectivity along with localization of brain function. M-CCA can be easily extended to incorporate different data types and additional modalities. We demonstrate the promise of the proposed method in finding covarying trial-to-trial amplitude modulations (AMs) in an auditory task involving implicit pattern learning. The results show approximately linear decreasing trends in AMs for both modalities and the corresponding spatial activations occur mainly in motor, frontal, temporal, inferior parietal, and orbito-frontal areas that are linked both to sensory function as well as learning and expectation--all of which match activations related to the presented paradigm.