Background: Patients undergoing left ventricular assist device (LVAD) implantation are at risk for death and postoperative adverse outcomes. Interhospital variability and concordance of quality metrics were assessed using the Society of Thoracic Surgeons Interagency Registry for Mechanically Assisted Circulatory Support (Intermacs).
Methods: A total of 22 173 patients underwent primary, durable LVAD implantation across 160 hospitals from 2012 to 2020, excluding hospitals performing <10 implant procedures. Observed and risk-adjusted operative mortality rates were calculated for each hospital. Outcomes included operative and 90-day mortality, a composite of adverse events (operative mortality, bleeding, stroke, device malfunction, renal dysfunction, respiratory failure), and secondarily failure to rescue. Rates are presented as median (interquartile range [IQR]). Hospital performance was evaluated using observed-to-expected (O/E) ratios for mortality and the composite outcome.
Results: Interhospital variability existed in observed (median, 7.2% [IQR, 5.1%-9.6%]) mortality. The rates of adverse events varied across hospitals: major bleeding, 15.6% (IQR, 11.4%-22.4%); stroke, 3.1% (IQR, 1.6%-4.7%); device malfunction, 2.4% (IQR, 0.8%-3.7%); respiratory failure, 10.5% (IQR, 4.6%-15.7%); and renal dysfunction, 6.4% (IQR, 3.2%-9.6%). The O/E ratio for operative mortality varied from 0.0 to 6.1, whereas the O/E ratio for the composite outcome varied from 0.28 to 1.99. Hospital operative mortality O/E ratios were more closely correlated with the 90-day mortality O/E ratio (r = 0.74) than with the composite O/E ratio (r = 0.12).
Conclusions: This study reported substantial interhospital variability in performance for hospitals implanting durable LVADs. These findings support the need to (1) report hospital-level performance (mortality, composite) and (2) undertake benchmarking activities to reduce unwarranted variability in outcomes.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035070 | PMC |
http://dx.doi.org/10.1016/j.athoracsur.2022.01.031 | DOI Listing |
Commun Biol
January 2025
Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
Single cell studies have transformed our understanding of cellular heterogeneity in disease but the need for fresh starting material can be an obstacle, especially in the context of international multicenter studies and archived tissue. We developed a protocol to obtain high-quality cells and nuclei from dissected human skeletal muscle archived in the preservative Allprotect® Tissue Reagent. After fluorescent imaging microscopy confirmed intact nuclei, we performed four protocol variations that compared sequencing metrics between cells and nuclei enriched by either filtering or flow cytometry sorting.
View Article and Find Full Text PDFBMC Musculoskelet Disord
January 2025
Division of Orthopaedic Surgery, Department of Surgery, McMaster University, Hamilton, ON, Canada.
Background: To summarize the statistical performance of machine learning in predicting revision, secondary knee injury, or reoperations following anterior cruciate ligament reconstruction (ACLR), and to provide a general overview of the statistical performance of these models.
Methods: Three online databases (PubMed, MEDLINE, EMBASE) were searched from database inception to February 6, 2024, to identify literature on the use of machine learning to predict revision, secondary knee injury (e.g.
Int J Obstet Anesth
December 2024
Department of Anesthesiology, 8700 Beverly Blvd #4209, Cedars-Sinai Medical Center, Los Angeles, CA 90064, United States. Electronic address:
Introduction: Over 90% of pregnant women and 76% expectant fathers search for pregnancy health information. We examined readability, accuracy and quality of answers to common obstetric anesthesia questions from the popular generative artificial intelligence (AI) chatbots ChatGPT and Bard.
Methods: Twenty questions for generative AI chatbots were derived from frequently asked questions based on professional society, hospital and consumer websites.
MAGMA
January 2025
Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital, Friedrich Schiller University Jena, Jena, Germany.
Objective: To establish an arterial spin labeling (ASL) protocol for rat livers that improves data reliability and reproducibility for perfusion quantification.
Methods: This study used respiratory-gated, single-slice, FAIR-based ASL imaging with multiple inversion times (TI) in rat livers. Quality assurance measures included: (1) introduction of mechanical ventilation to ensure consistent respiratory cycles by controlling the respiratory rate (45 bpm), tidal volume (10 ml/kg), and inspiration: expiration ratio (I:E ratio, 1:2), (2) optimization of the trigger window for consistent trigger points, and (3) use of fit residual map and coefficient of variance as metrics to assess data quality.
Sci Rep
January 2025
Hannover Centre for Optical Technologies (HOT), Leibniz University Hannover, Hannover, Germany.
Hyperspectral imaging (HSI) systems acquire images with spectral information over a wide range of wavelengths but are often affected by chromatic and other optical aberrations that degrade image quality. Deconvolution algorithms can improve the spatial resolution of HSI systems, yet retrieving the point spread function (PSF) is a crucial and challenging step. To address this challenge, we have developed a method for PSF estimation in HSI systems based on computed wavefronts.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!