Artificial Intelligence and Machine Learning in Cardiovascular Healthcare
ConclusionsAlthough there is an expanding body of literature on AI and ML in cardiovascular medicine, the future these fields will have in clinical practice remains to be paved. In particular, there is a promising role in providing automated imaging interpretation, automated data extraction and quality control, and clinical risk prediction although these techniques require further refinement and evaluation.
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CONCLUSIONS: This meta-analysis found cardiovascular factors to be the main causes for both 30-day and 1‑year rehospitalization. Heart failure represented the most common cardiovascular event at both short-term and mid-term follow-up. Several baseline characteristics and procedure-related factors were deemed unfavorable predictors of readmission. Importantly, transfemoral access and female gender were associated with a lower risk of readmission. PMID: 31807789 [PubMed - as supplied by publisher]
CONCLUSIONS: CMV infection was not associated with impaired long-term prognosis after HT. PMID: 31806387 [PubMed - as supplied by publisher]
Authors: Leebeek FWG, Muslem R Abstract Chronic heart failure (HF) is a growing health problem, and it is associated with high morbidity and mortality. Left ventricular assist devices (LVADs) are nowadays an important treatment option for patients with end-stage HF not only as a bridging tool to heart transplantation but also, as a permanent therapy for end-stage HF (destination therapy). The use of LVAD is associated with a high risk for bleeding complications and thromboembolic events, including pump thrombosis and ischemic stroke. Bleeding is the most frequent complication, occurring in 30% to 60% of patients, b...
This study provides a potential therapeutic target for VA in HF.
Conclusions: Our study suggests that greater attention to the experience and interpersonal relationships of dyads has the potential for improving HF self-management and facilitating patient-centered care.
Conclusions: Thirst in patients with HF was related to a higher dose of loop diuretics and fluid restriction. Healthcare providers should realize that it is important to assess thirst regularly and reconsider the need of a fluid restriction and the amount of loop diuretics in case of thirst.
Conclusions The older patient with HF should be carefully assessed for nonadherence. The development of interventions that are patient specific, target medications with the greatest potential for nonadherence, and use easy-to-access resources may promote decisions for medication adherence. More research is needed to develop interventions that promote decisions for medication adherence.
Conclusions Findings from this study suggest that SBML is a natural fit for the high-risk tasks needed to save VAD self-care. The 7 unique training-related themes derived from the qualitative data informed the design and development of a VAD SBML self-care curriculum.
ConclusionsSpontaneous reperfusion prior to pPCI in STEMI was associated with a lower risk of adverse clinical events. These exploratory data from a targeted discovery proteomics platform identifies novel proteins across diverse, yet complementary, pathobiological axes that show promise in providing mechanistic insights into spontaneous reperfusion in STEMI.Condensed abstractSpontaneous reperfusion has been established with improved STEMI outcomes, yet its pathobiology is unclear and appears to involve diverse physiological processes. Using a 91-biomarker high-throughput proteomics platform, we studied 683 STEMI patients i...