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Introduction: Cardiogenic shock (CS) is a life-threatening condition and mechanical circulatory support (MCS) might exert a relevant impact on its clinical course. Among MCS devices, Impella is very promising. Yet, its usefulness is still debated. We performed a meta-analysis of all studies evaluating the clinical impact of Impella in CS.
Methods: All studies including patients with CS and treated with Impella were included. The primary endpoint was short-term mortality. Secondary endpoints were vascular access complications and major bleeding. Data synthesis was obtained using random-effects metanalysis.
Results: Thirty-three studies and 5204 patients were included. Short-term mortality was 47%. Meta-regression analysis showed that patients age (p = 0.01), higher support level (p = 0.004) and pre-PCI insertion (p < 0.001) were significant moderators for the primary endpoint. Vascular access complications were registered in 6.4% of cases, whereas age (p = 0.05) and diabetes (p = 0.007) were significant predictors. Major bleeding occurred in 16.4% of patients. Meta-analysis of the subgroup of studies comparing Impella to IABP showed no significant difference in short-term mortality (RR = 1.08, p = 0.45), while rates of vascular access complications (p < 0.001) or major bleeding (p < 0.001) were significantly higher with Impella. Subgroup and metaregression analyses showed that these results were influenced by lower adoption rates of higher degree of MCS support (p = 0.003), and by higher vascular complications rates (p = 0.014).
Conclusions: Our results suggest that the choice of adequate device size, careful patients selection and optimal timing of MCS initiation are key to clinical success with Impella in CS. Large prospective studies are mandatory to confirm these results deriving from retrospective studies.
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http://dx.doi.org/10.1016/j.ijcha.2022.101007 | DOI Listing |
Pediatr Cardiol
September 2025
Pediatric Cardiology Unit, University Hospital of Geneva, Geneva, Switzerland.
Anomalous origin of the left coronary artery from the pulmonary artery (ALCAPA) is a rare congenital anomaly. Its clinical course is typically severe in infancy, leading to left ventricular ischemia, cardiogenic shock, and high mortality without surgical intervention.We describe a rare case of a 3-year-old girl diagnosed with ALCAPA, showing extensive right-to-left collaterals, preserved left ventricular function, and minimal myocardial injury.
View Article and Find Full Text PDFUrol Case Rep
September 2025
Main Line Health, Division of Urology, Wynnewood, PA, USA.
Muscle-invasive bladder cancer (MIBC) with cardiac metastasis typically carries a very poor prognosis. A Black woman in her 70s developed high-grade urothelial carcinoma with squamous differentiation invading the bladder muscle. Despite chemotherapy, radiation, and nephrostomy, the disease progressed.
View Article and Find Full Text PDFCureus
August 2025
Emergency and Critical Care Center, Okinawa Prefectural Nanbu Medical Center and Children's Medical Center, Haebaru, JPN.
The indications for extracorporeal membrane oxygenation (ECMO) have broadened in clinical practice, and its use in circulatory failure caused by acute drug intoxication has become more frequent. We reviewed three cases of venoarterial (VA) ECMO use for intoxication at our hospital. Three cases (aged 60-69 years) developed refractory shock following intentional overdose, including calcium channel blockers.
View Article and Find Full Text PDFInt J Cardiol Heart Vasc
October 2025
Department of Cardiology, Haemostaseology and Medical Intensive Care, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Germany.
Front Artif Intell
August 2025
The First Clinical Medical School, Lanzhou University, Lanzhou, China.
Background: ST-elevation myocardial infarction (STEMI) poses a significant threat to global mortality and disability. Advances in percutaneous coronary intervention (PCI) have reduced in-hospital mortality, highlighting the importance of post-discharge management. Machine learning (ML) models have shown promise in predicting adverse clinical outcomes.
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