Managed Care after Acute Myocardial Infarction (MC-AMI) improves prognosis in AMI survivors with pre-existing heart failure: A propensity score matching analysis of Polish nationwide program of comprehensive post-MI care.

BACKGROUND: Despite improvement in acute myocardial infarction (AMI) treatment, post-discharge mortality remains high. The outcomes are supposed to be even worse in patients with post-MI heart failure (HF), as only a half of patients with newly diagnosed HF survive four years. AIMS: The study aimed to analyze whether managed care after acute myocardial infarction (MC-AMI) is associated with better survival in AMI survivors with a pre-existing diagnosis of HF. RESULTS: The study included 7228 patients with a pre-existing diagnosis of HF who survived the hospitalization for AMI in Poland between November 2017 and December 2020, of whom 2268 (31.4%) were referred for the MC-AMI program. The median follow-up was 1.5 (0.7-2.3) years. In the unmatched analysis, patients without MC-AMI had more than twice higher 12-month mortality (21.8% vs. 9.9%; P <0.01) than MC-AMI participants. The difference remained significant after propensity score matching (16,8% vs. 10.0%; P <0.01). In multivariable analysis, participation in MC-AMI was an independent factor of 12-month survival. MC-AMI participants had a lower stroke rate (1.5% vs. 3.0%; P <0.01) and fewer hospital admissions due to HF (22.9% vs. 27.6%; P <0.01). CONCLUSIONS: After propensity score matching, participation in MC-AMI was associated with lower rates of stroke, HF hospitalizations, and all-cause mortality in the 12-month follow-up and was an independent factor of 12-month survival in AMI survivors with pre-existing HF.

The Value of Activated Ion Electron Transfer Dissociation for High-Throughput Top-Down Characterization of Intact Proteins.

High-throughput top-down proteomic experiments directly identify proteoforms in complex mixtures, making high quality tandem mass spectra necessary to deeply characterize proteins with many sources of variation. Collision-based dissociation methods offer expedient data acquisition but often fail to extensively fragment proteoforms for thorough analysis. Electron-driven dissociation methods are a popular alternative approach, especially for precursor ions with high charge density. Combining infrared photoactivation concurrent with electron transfer dissociation (ETD) reactions, i.e., activated ion ETD (AI-ETD), can significantly improve ETD characterization of intact proteins, but benefits of AI-ETD have yet to be quantified in high-throughput top-down proteomics. Here, we report the first application of AI-ETD to LC-MS/MS characterization of intact proteins (<20 kDa), highlighting improved proteoform identification the method offers over higher energy-collisional dissociation (HCD), standard ETD, and ETD followed by supplemental HCD activation (EThcD). We identified 935 proteoforms from 295 proteins from human colorectal cancer cell line HCT116 using AI-ETD compared to 1014 proteoforms, 915 proteoforms, and 871 proteoforms with HCD, ETD, and EThcD, respectively. Importantly, AI-ETD outperformed each of the three other methods in MS/MS success rates and spectral quality metrics (e.g., sequence coverage achieved and proteoform characterization scores). In all, this four-method analysis offers the most extensive comparisons to date and demonstrates that AI-ETD both increases identifications over other ETD methods and improves proteoform characterization via higher sequence coverage, positioning it as a premier method for high-throughput top-down proteomics.