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Background: Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is used increasingly to support patients who are in cardiogenic shock. Due to the risk of complications, prediction models may aid in identifying patients who would benefit most from VA-ECMO. One such model is the Survival After Veno-Arterial Extracorporeal Membrane Oxygenation (SAVE) score. Therefore, we wanted to validate the utility of the SAVE score in a contemporary cohort of adult patients.
Methods: Retrospective data were extracted from electronic health records of 120 patients with cardiogenic shock supported with VA-ECMO between 2011 and 2018. The SAVE score was calculated for each patient to predict survival to hospital discharge. We assessed the SAVE score calibration by comparing predicted vs observed survival at discharge. We assessed discrimination with the area under the receiver operating curve using logistic regression.
Results: A total of 45% of patients survived to hospital discharge. Survivors had a significantly higher mean SAVE score (-9.3 ± 4.1 in survivors vs -13.1 ± 4.4, respectively; = 0.001). SAVE score discrimination was adequate (c = 0.77; 95% confidence interval 0.69-0.86; < 0.001). SAVE score calibration was limited, as observed survival rates for risk classes II-V were higher in our cohort (II: 67% vs 58%; III: 78% vs 42%; IV: 61% vs 30%; and V: 29% vs 18%).
Conclusions: The SAVE score underestimates survival in a contemporary North American cohort of adult patients with cardiogenic shock. Its inaccurate performance could lead to denying ECMO support to patients deemed to be too high risk. Further studies are needed to validate additional predictive models for patients requiring VA-ECMO.
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http://dx.doi.org/10.1016/j.cjco.2020.09.011 | DOI Listing |
Cureus
August 2025
Department of Emergency and Critical Care Medicine, Hyogo Emergency Medical Center, Kobe, JPN.
Objective This study aimed to evaluate the influence of public assistance on patients with out-of-hospital cardiac arrest (OHCA) who received extracorporeal cardiopulmonary resuscitation (ECPR) in Japan. Methods We conducted a secondary analysis of data from the SAVE-J II study, a retrospective, multicenter registry study involving 36 participating institutions in Japan. Patients with cardiac arrest who received ECPR were divided into two groups, depending on whether or not they had received public assistance.
View Article and Find Full Text PDFAust J Rural Health
October 2025
Save Sight Institute, University of Sydney, Sydney, New South Wales, Australia.
Objective: To evaluate the effectiveness of the Griffith Ophthalmology Project in improving visual acuity and quality of life (QoL) among cataract surgery patients in regional New South Wales (NSW), Australia.
Design: Retrospective observational study.
Setting: Griffith Base Hospital's Department of Ophthalmology in the Western Murrumbidgee Local Health District (MLHD).
JACC Adv
August 2025
Division for Heart Disease and Stroke Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA. Electronic address:
Background: Fixed-dose combination (FDC) antihypertensives combine two or more agents. Compared with non-FDC antihypertensives of multiple classes (multi-pill therapy), combination-pill therapy using FDC antihypertensives may improve hypertension control. However, combination-pill therapy remains low.
View Article and Find Full Text PDFInsects
August 2025
Biological Sciences, Bishop's University, 2600 College Street, Sherbrooke, QC J1M 1Z7, Canada.
Ongoing changes in the distribution and abundance of several tick species of medical relevance in Canada have prompted the development of the eTick platform-an image-based crowd-sourcing public surveillance tool for Canada enabling rapid tick species identification by trained personnel, and public health guidance based on tick species and province of residence of the submitter. Considering that more than 100,000 images from over 73,500 identified records representing 25 tick species have been submitted to eTick since the public launch in 2018, a partial automation of the image processing workflow could save substantial human resources, especially as submission numbers have been steadily increasing since 2021. In this study, we evaluate an end-to-end artificial intelligence (AI) pipeline to support tick identification from eTick user-submitted images, characterized by heterogeneous quality and uncontrolled acquisition conditions.
View Article and Find Full Text PDF