RESUMEN
Heart failure remains the leading cause of death worldwide, creating a pressing need for better preclinical models of the human heart. Tissue engineering is crucial for basic science cardiac research; in vitro human cell culture eliminates the interspecies differences of animal models, while a more tissue-like 3D environment (e.g., with extracellular matrix and heterocellular coupling) simulates in vivo conditions to a greater extent than traditional two-dimensional culture on plastic Petri dishes. However, each model system requires specialized equipment, for example, custom-designed bioreactors and functional assessment devices. Additionally, these protocols are often complicated, labor-intensive, and plagued by the failure of the small, delicate tissues. This paper describes a process for generating a robust human engineered cardiac tissue (hECT) model system using induced pluripotent stem-cell-derived cardiomyocytes for the longitudinal measurement of tissue function. Six hECTs with linear strip geometry are cultured in parallel, with each hECT suspended from a pair of force-sensing polydimethylsiloxane (PDMS) posts attached to PDMS racks. Each post is capped with a black PDMS stable post tracker (SPoT), a new feature that improves the ease of use, throughput, tissue retention, and data quality. The shape allows for the reliable optical tracking of post deflections, yielding improved twitch force tracings with absolute active and passive tension. The cap geometry eliminates tissue failure due to hECTs slipping off the posts, and as they involve a second step after PDMS rack fabrication, the SPoTs can be added to existing PDMS post-based designs without major changes to the bioreactor fabrication process. The system is used to demonstrate the importance of measuring hECT function at physiological temperatures and shows stable tissue function during data acquisition. In summary, we describe a state-of-the-art model system that reproduces key physiological conditions to advance the biofidelity, efficiency, and rigor of engineered cardiac tissues for in vitro applications.
Asunto(s)
Células Madre Pluripotentes Inducidas , Ingeniería de Tejidos , Animales , Humanos , Ingeniería de Tejidos/métodos , Contracción Miocárdica , Miocitos Cardíacos , Reactores BiológicosRESUMEN
BACKGROUND: Complete revascularization (CR) of hemodynamically stable STEMI improves outcomes when compared to culprit-only PCI. However, the optimal timing for CR (CR during index PCI [iCR] versus staged PCI [sCR]) is unknown. sCR is defined as revascularization of non-culprit lesions not done during the index procedure (mean 31.5±24.6 days after STEMI). Our goal was to determine whether iCR was the superior strategy when compared to sCR. METHODS: A systematic review of Medline, Cochrane, and Embase was performed for RCTs reporting outcomes of stable STEMI patients who had undergone CR. Only RCTs with a clearly defined timing of CR, for the classification into iCR and sCR, and a follow-up of at least 12 months were included. Seven RCTs comprising 6647 patients (mean age:62.9±1.4 years, male sex:79.4%) met these criteria and were included. RESULTS: After a mean follow-up of 25.1±9.4 months, iCR was associated with a significant reduction in cardiovascular mortality (risk ratio [RR] 0.48, 95% confidence interval [CI] 0.26-0.90, p=0.02, relative risk reduction [RRR] 52%) and non-fatal reinfarctions (RR 0.42, 95% CI 0.25-0.70, p=0.001, RRR: 58%). sCR showed a significant reduction in non-fatal reinfarctions only (RR 0.68, 95% CI 0.54-0.85, p=0.0008, RRR: 32%). There was no difference in the safety outcome of contrast-induced nephropathy between groups. CONCLUSION: iCR of stable STEMI patients is associated with a significant reduction in cardiovascular death and a trend towards reduction in all-cause mortality. These benefits are not seen in sCR. Both strategies are associated with a reduction in non-fatal reinfarctions.
RESUMEN
BACKGROUND: Transcatheter mitral valve repair (TMVR) utilization has increased significantly in the United States over the last years. Yet, a risk-prediction tool for adverse events has not been developed. We aimed to generate a machine-learning-based algorithm to predict in-hospital mortality after TMVR. METHODS: Patients who underwent TMVR from 2012 through 2015 were identified using the National Inpatient Sample database. The study population was randomly divided into a training set (n = 636) and a testing set (n = 213). Prediction models for in-hospital mortality were obtained using five supervised machine-learning classifiers. RESULTS: A total of 849 TMVRs were analyzed in our study. The overall in-hospital mortality was 3.1%. A naïve Bayes (NB) model had the best discrimination for fifteen variables, with an area under the receiver-operating curve (AUC) of 0.83 (95% CI, 0.80-0.87), compared to 0.77 for logistic regression (95% CI, 0.58-0.95), 0.73 for an artificial neural network (95% CI, 0.55-0.91), and 0.67 for both a random forest and a support-vector machine (95% CI, 0.47-0.87). History of coronary artery disease, of chronic kidney disease, and smoking were the three most significant predictors of in-hospital mortality. CONCLUSIONS: We developed a robust machine-learning-derived model to predict in-hospital mortality in patients undergoing TMVR. This model is promising for decision-making and deserves further clinical validation.
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Insuficiencia de la Válvula Mitral , Válvula Mitral , Teorema de Bayes , Mortalidad Hospitalaria , Humanos , Aprendizaje Automático , Válvula Mitral/diagnóstico por imagen , Válvula Mitral/cirugía , Estados Unidos/epidemiologíaRESUMEN
Left ventricular (LV) thrombus in patients with reduced LV systolic function carries significant thromboembolic risk. Direct oral anticoagulants are an attractive alternative to warfarin for LV thrombus management. However, there are not enough data regarding the safety and efficacy of direct oral anticoagulants for the treatment of LV thrombus. (Level of Difficulty: Beginner.).