Characteristics, Prognosis, and Prediction Model of Heart Failure Patients in Intensive Care Units Based on Preserved, Mildly Reduced, and Reduced Ejection Fraction.

Background: Heart failure (HF) patients in intensive care units (ICUs) are rather poorly studied based on varying left ventricular ejection fraction (LVEF) classification. Characteristics and prognosis of patients in ICUs with HF with mildly reduced ejection fraction (HFmrEF), HF with reduced ejection fraction (HFrEF) and HF with preserved ejection fraction (HFpEF) require further clarification. Methods: Data involving clinical information and 4-year follow-up records of HF patients were extracted and integrated from the Medical Information Mart for Intensive Care III (MIMIC-III) database. Tests were carried out to identity differences among these three HF subtypes. Prognostic analyses were performed using Kaplan-Meier survival analysis and Cox proportional-hazards regression modeling. To develop a novel prediction nomogram, forward selection was used as the best-fit model. Prognostic heterogeneity of the subgroups prespecified by stratification factors in pairwise comparisons was presented using forest plots. Results: A total of 4150 patients were enrolled in this study. HFmrEF had the lowest all-cause mortality rate during the 4-year follow-up, which was significantly different from HFrEF and HFpEF (Log-Rank p < 0.001). The Cox proportional-hazards regression model also showed that a comparison of HFrEF versus HFmrEF indicated a hazard ratio (HR) of 0.76 (95% CI 0.61-0.94, p = 0.011) and HFrEF versus HFpEF indicated a HR 0.93 (95% CI 0.82-1.07, p = 0.307). Following a multivariable analysis, 13 factors were confirmed as independent. A new nomogram was established and quantified with a concordance index (C-index) of 0.70 (95% CI 0.67-0.73), and the internal validation indicated the accuracy of the model. Stratification factors such as a history of coronary artery bypass grafting (CABG) and comorbidity of chronic obstructive pulmonary disease (COPD) induced prognostic heterogeneity among the three subtypes. Conclusions: Clinical characteristics and prognosis significantly varied among the three subtypes of HF patients in ICUs, with HFmrEF patients achieving the best prognosis. The novel prediction model, tailored for this population, showed a satisfying prediction ability.

Acute kidney injury prediction model utility in premature myocardial infarction.

The incidence of premature myocardial infarction (PMI) has been rising and acute kidney injury (AKI) occurring in PMI patients severely impacts prognosis. This study aimed to develop and validate a prediction model for AKI specific to PMI patients. The MIMIC-Ⅲ-CV and MIMIC-Ⅳ databases were utilized for model derivation of PMI patients. Single-center data served for external validation. There were 571 and 182 AKI patients in the training set (n = 937) and external validation set (n = 292) cohorts, respectively. Finally, a 7-variable model consisting of: Sequential Organ Failure Assessment (SOFA) score, coronary artery bypass grafting (CABG), ICU stay time, loop diuretics, estimated glomerular filtration rate (eGFR) HCO3- and Albumin was developed, achieving an AUC of 0.85 (95% CI: 0.83-0.88) in the training set. External validation also confirmed model robustness. This model may assist clinicians in the early identification of patients at elevated risk for PMI. Further validation is warranted before clinical application.

Engineered Leukocyte Biomimetic Colorimetric Sensor Enables High-Efficient Detection of Tumor Cells Based on Bioorthogonal Chemistry.

Accurate detection of heterogeneous circulating tumor cells (CTCs) is critical as they can make tumor cells more aggressive, drug-resistant, and metastasizing. Although the leukocyte membrane coating strategy is promising in meeting the challenge of detecting heterogeneous CTCs due to its inherent antiadhesive properties, it is still limited by the reduction or loss of expression of known markers. Bioorthogonal glycol-metabolic engineering is expected to break down this barrier by feeding the cells with sugar derivatives with a unique functional group to establish artificial targets on the surface of tumor cells. Herein, an engineered leukocyte biomimetic colorimetric sensor was accordingly fabricated for high-efficient detection of heterogeneous CTCs. Compared with conventional leukocyte membrane coating, the sensor could covalently bound to the heterogeneous CTCs models fed with Ac4ManNAz in vitro through the synergy of bioorthogonal chemistry and metabolic glycoengineering, ignoring the phenotypic changes of heterogeneous CTCs. Meanwhile, a sandwich structure composed of leukocyte biomimetic layer/CTCs/MoS2 nanosheet was formed for visual detection of HeLa cells as low as 10 cells mL-1. Overall, this approach can overcome the dependence of conventional cell membrane biomimetic technology on specific cell phenotypes and provide a new viewpoint to highly efficiently detect heterogeneous CTCs.