Background: The purpose of this study was to develop a specific postoperative score for intensive care unit (ICU) cardiac surgical patients for assessment of organ dysfunction and survival.
Methods: This prospective study consisted of all consecutive adult patients admitted after cardiac surgery to our ICU over a period of 3 years. Evaluation of variables was performed using the first year patients who stayed in the ICU for at least 24 hours. The reproducibility was then tested in two validation sets using all patients. Performance was assessed with the Hosmer-Lemeshow (chi2 statistics) goodness-of-fit test and receiver operating characteristic (ROC) curves and compared with the Acute Physiology and Chronic Health Evaluation (APACHE II) and Multiple Organ Dysfunction Score (MODS).
Results: A total of 3,230 patients were admitted to the ICU after cardiac surgery. Mean chi2 values for the new score were 5.8 (APACHE II, 11.3; MODS, 9.7) for the construction set, 7.2 (APACHE II, 8.0; MODS, 4.5) for the validation set I, and 5.9 for the validation set II. The mean area under the ROC curve was 0.91 (APACHE II, 0.86; MODS, 0.84) for the new score in the construction set, 0.88 (APACHE II, 0.84; MODS, 0.84) in the validation set I, and 0.92 in the validation set II.
Conclusions: Our new 10-variable risk index performs very well, with calibration and discrimination very high, better than general severity systems; and it is an appropriate tool for daily risk stratification in ICU cardiac surgery patients. Thus, it may serve as an "expert system" for diagnosing organ failure, decision making, resource evaluation, and predicting mortality among ICU cardiac surgical patients.
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http://dx.doi.org/10.1016/j.athoracsur.2004.10.017 | DOI Listing |
Ann Vasc Surg
January 2025
Division of Vascular Surgery, University of South Florida College of Medicine, Tampa, Florida, USA. Electronic address:
Objective: Frailty has become an increasingly recognized perioperative risk stratification tool. While frailty has been strongly correlated with worsening surgical outcomes, the individual determinants of frailty have rarely been investigated in the setting of aortic disease. The aim of this study was to examine the determinants of an 11-factor modified frailty index (mFI-11) on mortality and postoperative complications in patients undergoing endovascular aortic aneurysm repair (EVAR).
View Article and Find Full Text PDFAnn Vasc Surg
January 2025
Institute of Cardiac and Aortic Disorders, SRM Institutes for Medical Science (SIMS Hospitals), Chennai, India.
Background: Nonocclusive mesenteric ischemia (NOMI), a subtype of acute mesenteric ischemia, is primarily caused by mesenteric arterial vasoconstriction and decreased vascular resistance, leading to impaired intestinal perfusion.Commonly observed after cardiac surgery, NOMI affects older patients with cardiovascular or systemic diseases, accounting for 20-30% of acute mesenteric ischemia cases with a mortality rate of ∼50%. This review explores NOMI's pathophysiology, clinical implications in aortic dissection, and the unmet needs in diagnosis and management, emphasizing its prognostic significance.
View Article and Find Full Text PDFJ Crit Care
January 2025
Department of Emergency Medicine Center, the Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu 221002, China. Electronic address:
Objective: To assess the association of serum glycocalyx shedding components (Heparan sulfate, HS; Hyaluronic acid, HA; Syndecan-1, Sdc-1) with outcomes after CA.
Methods: Patients who were comatose for >24 h after CA in the intensive care unit (ICU) of the Affiliated Hospital of Xuzhou Medical University from 9/2021 to 04/2023 were enrolled. Serum samples were collected 24 h after CA to measure the concentrations of glycocalyx shedding components.
Pharmaceuticals (Basel)
January 2025
Department of Pharmacology, College of Pharmacy, Harbin Medical University, Harbin 150081, China.
Background/objectives: Septic cardiomyopathy (SCM) is a severe cardiac complication of sepsis, characterized by cardiac dysfunction with limited effective treatments. This study aimed to identify repurposable drugs for SCM by integrated multi-omics and network analyses.
Methods: We generated a mouse model of SCM induced by lipopolysaccharide (LPS) and then obtained comprehensive metabolic and genetic data from SCM mouse hearts using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and RNA sequencing (RNA-seq).
J Clin Med
January 2025
Clinical Trial and Biostatistics, Research and Innovation Unit, University Hospital of Ferrara, 44124 Ferrara, Italy.
A machine learning prognostic mortality scoring system was developed to address challenges in patient selection for clinical trials within the Intensive Care Unit (ICU) environment. The algorithm incorporates Red blood cell Distribution Width (RDW) data and other demographic characteristics to predict ICU mortality alongside existing ICU mortality scoring systems like Simplified Acute Physiology Score (SAPS). The developed algorithm, defined as a Mixed-effects logistic Random Forest for binary data (MixRFb), integrates a Random Forest (RF) classification with a mixed-effects model for binary outcomes, accounting for repeated measurement data.
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