The Impact of Silent Liver Disease on Hospital Length of Stay Following Isolated Coronary Artery Bypass Grafting Surgery
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SUBMITTER: Suffredini G
PROVIDER: S-EPMC11204604 | biostudies-literature | 2024 Jun
REPOSITORIES: biostudies-literature
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Project description:ObjectiveThis study aims to examine the impact of preoperative fibrinogen concentration on the short-term outcomes and hospital length of stay (LOS) of patients undergoing Coronary Artery Bypass Grafting (CABG).MethodsBetween January 2010 and June 2022, a retrospective analysis comprised 633 patients who sequentially received isolated, primary CABG. These patients were categorized into normal fibrinogen group (fibrinogen < 3.5 g/L) and high fibrinogen group (fibrinogen ≥ 3.5 g/L) according to preoperative fibrinogen concentration. The primary outcome was LOS. To correct for confounding and investigate the effect of preoperative fibrinogen concentration on the short-term outcomes and LOS, we employed propensity score matching (PSM). The correlation between fibriongen concentration and LOS in subgroups was examined using subgroup analysis.ResultsWe categorized 344 and 289 patients in the "normal fibrinogen group" and "high fibrinogen group", respectively. After PSM, compared to the normal fibrinogen group, the high fibrinogen group had a longer LOS [12.00 (9.00-15.00) vs. 13.00 (10.00-16.00), P = 0.028] and higher incidence of postoperative renal impairment [49 (22.1%) vs. 72 (32.4%), P = 0.014]. Cardiopulmonary bypass (CPB) or non-CPB CABG patients showed similar correlations between various fibrinogen concentrations and LOS, according to subgroup analyses.ConclusionsFibrinogen is an independent preoperative predictor of both the LOS and the postoperative renal impairment that occurs after CABG. Patients with high preoperative fibrinogen concentration had a higher incidence of postoperative renal impairment and a longer LOS, emphasizing the significance of preoperative fibrinogen management.
| S-EPMC10082530 | biostudies-literature
Project description:BackgroundPreoperative C-reactive protein (CRP) levels more than 10 mg/l have been shown to be associated with increased morbidity and mortality after cardiac surgery. We examine the value of preoperative CRP levels less than 10 mg/l for predicting long-term, all-cause mortality and hospital length of stay in surgical patients undergoing primary, nonemergent coronary artery bypass graft-only surgery.MethodsWe examined the association between preoperative CRP levels stratified into four categories (< 1, 1-3, 3-10, and > 10 mg/l), and 7-yr all-cause mortality and hospital length of stay in 914 prospectively enrolled primary, nonemergent coronary artery bypass graft-only surgical patients using a proportional hazards regression model.ResultsEighty-seven patients (9.5%) died during a mean follow-up period of 4.8 +/- 1.5 yr. After proportional hazards adjustment, the 3-10 and > 10 mg/l preoperative CRP groups were associated with long-term, all-cause mortality (hazards ratios [95% CI]: 2.50 [1.22-5.16], P = 0.01 and 2.66 [1.21-5.80], P = 0.02, respectively) and extended hospital length of stay (1.32 [1.07-1.63], P < 0.001 and 1.27 [1.02-1.62], P = 0.001, respectively).ConclusionWe demonstrate that preoperative CRP levels as low as 3 mg/l are associated with increased long-term mortality and extended hospital length of stay in relatively lower-acuity patients undergoing primary, nonemergent coronary artery bypass graft-only surgery. These important findings may allow for more objective risk stratification of patients who present for uncomplicated surgical coronary revascularization.
| S-EPMC3000538 | biostudies-literature
Project description:This SuperSeries is composed of the following subset Series: GSE12485: Changes in cardiac transcription profiles following off-pump coronary revascularization surgery GSE12486: Changes in cardiac transcription profiles following on-pump coronary artery bypass grafting Refer to individual Series
2010-07-07 | E-GEOD-12504 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below.
2010-06-22 | GSE12504 | GEO
Project description:ObjectiveTo develop and validate a predictive model utilizing machine-learning techniques for estimating the length of hospital stay among patients who underwent coronary artery bypass grafting.MethodsThree machine learning models (random forest, extreme gradient boosting and neural networks) and three traditional regression models (Poisson regression, linear regression, negative binomial regression) were trained in a dataset of 9,584 patients who underwent coronary artery bypass grafting between January 2017 and December 2021. The data were collected from hospital discharges from 133 centers in Brazil. Algorithms were ranked by calculating the root mean squared logarithmic error (RMSLE). The top performing algorithm was validated in a never-before-seen database of 2,627 patients. We also developed a model with the top ten variables to improve usability.ResultsThe random forest technique produced the model with the lowest error. The RMLSE was 0.412 (95%CI 0.405-0.419) on the training dataset and 0.454 (95%CI 0.441-0.468) on the validation dataset. Non-elective surgery, admission to a public hospital, heart failure, and age had the greatest impact on length of hospital stay.ConclusionsThe predictive model can be used to generate length of hospital stay indices that could be used as markers of efficiency and identify patients with the potential for prolonged hospitalization, helping the institution in managing beds, scheduling surgeries, and allocating resources.
| S-EPMC11578580 | biostudies-literature
Project description:BACKGROUND:To date, studies evaluating outcome improvements associated with participation in physician-led collaboratives have been limited by the absence of a contemporaneous control group. We examined post cardiac surgery pneumonia rates associated with participation in a statewide, quality improvement collaborative relative to a national physician reporting program. METHODS AND RESULTS:We evaluated 911 754 coronary artery bypass operations (July 1, 2011, to June 30, 2017) performed across 1198 hospitals participating in a voluntary national physician reporting program (Society of Thoracic Surgeons [STS]), including 33 that participated in a Michigan-based collaborative (MI-Collaborative). Unlike STS hospitals not participating in the MI-Collaborative (i.e., STSnonMI) that solely received blinded reports, MI-Collaborative hospitals received a multi-faceted intervention starting November 2012 (quarterly in-person meetings showcasing unblinded data, webinars, site visits). Eighteen of the MI-Collaborative hospitals received additional support to implement recommended pneumonia prevention practices ("MI-CollaborativePlus"), whereas 15 did not ("MI-CollaborativeOnly"). We evaluated rates of postoperative pneumonia, adjusting for patient mix and hospital effects. Baseline patient characteristics were qualitatively similar between groups and time. During the preintervention period (Q3/2011 through Q3/2012), there was no statistically significant difference in the adjusted odds of pneumonia for STS hospitals participating in the MI-Collaborative compared to the STS non-MI hospitals. However, during the intervention period (Q4/2012 through Q2/2017), there was a significant 2% reduction per quarter in the adjusted odds of pneumonia for MI-Collaborative hospitals (n=33) relative to the STS-nonMI hospitals. There was a significant 3% per quarter reduction in the adjusted odds of pneumonia for the MI-CollaborativeOnly (n=15) hospitals relative to the STS-nonMI hospitals. Over the course of the overall study period, the STS-nonMI hospitals had a 1.96% reduction in risk-adjusted pneumonia (pre- vs. intervention periods), which was less than the MI-Collaborative (3.23%, P=0.011). Over the same time period, the MI-CollaborativePlus (n=18) reduced adjusted pneumonia rates by 10.29%, P=0.001. CONCLUSIONS:Participation in a physician-led collaborative was associated with significant reductions in pneumonia relative to a national quality reporting program. Interventions including collaborative learning may yield superior outcomes relative to solely using physician feedback reporting. CLINICAL TRIAL REGISTRATION:URL: https://www.clinicaltrials.gov . Unique identifier: NCT02068716.
| S-EPMC6310019 | biostudies-literature
Project description:Background and purposeThe optimal operative strategy in patients with severe carotid artery disease undergoing coronary artery bypass grafting (CABG) is unknown. We sought to investigate the safety and efficacy of synchronous combined carotid endarterectomy and CABG as compared with isolated CABG.MethodsPatients with asymptomatic high-grade carotid artery stenosis ≥80% according to ECST (European Carotid Surgery Trial) ultrasound criteria (corresponding to ≥70% NASCET [North American Symptomatic Carotid Endarterectomy Trial]) who required CABG surgery were randomly assigned to synchronous carotid endarterectomy+CABG or isolated CABG. To avoid unbalanced prognostic factor distributions, randomization was stratified by center, age, sex, and modified Rankin Scale. The primary composite end point was the rate of stroke or death at 30 days.ResultsFrom 2010 to 2014, a total of 129 patients were enrolled at 17 centers in Germany and the Czech Republic. Because of withdrawal of funding after insufficient recruitment, enrolment was terminated early. At 30 days, the rate of any stroke or death in the intention-to-treat population was 12/65 (18.5%) in patients receiving synchronous carotid endarterectomy+CABG as compared with 6/62 (9.7%) in patients receiving isolated CABG (absolute risk reduction, 8.8%; 95% confidence interval, -3.2% to 20.8%; PWALD=0.12). Also for all secondary end points at 30 days and 1 year, there was no evidence for a significant treatment-group effect although patients undergoing isolated CABG tended to have better outcomes.ConclusionsAlthough our results cannot rule out a treatment-group effect because of lack of power, a superiority of the synchronous combined carotid endarterectomy+CABG approach seems unlikely. Five-year follow-up of patients is still ongoing.Clinical trial registrationURL: https://www.controlled-trials.com. Unique identifier: ISRCTN13486906.
| S-EPMC5610560 | biostudies-literature
Project description:Purpose Predictive analytics (PA) is a new trending approach in the field of healthcare that uses machine learning to build a prediction model using supervised learning algorithms. Isolated coronary artery bypass grafting (iCABG), an open-heart surgery, is commonly performed in the treatment of coronary heart disease. Aim The aim of this study was to develop and evaluate a model to predict postoperative length of stay (PLoS) for iCABG patients using supervised machine learning techniques, and to identify the features with the highest contribution to the model. Methods This is a retrospective study that uses historic data of adult patients who underwent isolated CABG (iCABG). After initial data pre-processing, data imputation using the kNN method was applied. The study used five prediction models using Naïve Bayes, Decision Tree, Random Forest, Logistic Regression and k Nearest Neighbor algorithms. Data imbalance was managed using the following widely used methods: oversampling, undersampling, “Both”, and random over-sampling examples (ROSE). The features selection process was conducted using the Boruta method. Two techniques were applied to examine the performance of the models, (70%, 30%) split and cross-validation, respectively. Models were evaluated by comparing their performance using AUC and other metrics. Results In the final dataset, six distinct features and 621 instances were used to develop the models. A total of 20 models were developed using R statistical software. The model generated using Random Forest with “Both” resampling method and cross-validation technique was deemed the best fit (AUC=0.81; F1 score=0.82; and recall=0.82). Attributes found to be highly predictive of PLoS were pulmonary artery systolic, age, height, EuroScore II, intra-aortic balloon pump used, and complications during operation. Conclusion This study demonstrates the significance and effectiveness of building a model that predicts PLoS for iCABG patients using patient specifications and pre-/intra-operative measures.
| S-EPMC7537993 | biostudies-literature
Project description:BackgroundGalectin-3 (Gal-3) is a well-established biomarker of adverse clinical outcomes, but its prognostic value for long-term survival after cardiac surgery is not well understood. Elevated levels of Gal-3 have been found to be remarkably associated with higher risk of death in both acute decompensated and chronic heart failure populations. Its prognostic value for long-term survival after cardiac surgery is not known.MethodsA sample of patients contributing to the Northern New England Cardiovascular Disease Study Group Cardiac Surgery Registry from 2004 to 2007 were enrolled in a prospective biomarker cohort (N = 1690). Preoperative Gal-3 levels were measured and categorized by quartile. We used Kaplan-Meier survival analysis and Cox regression models, adjusting for variables in The Society of Thoracic Surgeons Collaboration on the Comparative Effectiveness of Revascularization Strategy probability calculator to evaluate the association between elevated Gal-3 levels and survival to 6 years.ResultsPreoperative Gal-3 levels ranged from 1.72 to 28.89 ng/mL (mean, 8.96 ng/mL; median, 8.06 ng/mL; interquartile range, 5.42-11.08 ng/mL). Crude survival decreased by increasing quartile. After adjustment, serum levels of Gal-3 in the highest quartile of the cohort were associated with significantly decreased survival compared with the lowest quartile (hazard ratio [HR] 2.22; 95% confidence interval [CI], 1.40-3.54; P = .001). No decrease in survival was found for the middle quartiles (HR 1.36; 95% CI, 0.87-2.12; P = .177).ConclusionsA substantial association was found between elevated preoperative Gal-3 levels and risk of mortality after isolated coronary artery bypass grafting surgery. An assessment of the relationship between preoperative serum biomarkers and long-term survival can be used for risk stratification or estimating postsurgical prognosis.
| S-EPMC6917892 | biostudies-literature
Project description:BackgroundAlthough blood transfusions are common and have been associated with adverse sequelae after cardiac surgical procedures, few contemporaneous models exist to support clinical decision making. This study developed a preoperative clinical decision support tool to predict perioperative red blood cell transfusions in the setting of isolated coronary artery bypass grafting.MethodsWe performed a multicenter, observational study of 20,377 patients undergoing isolated coronary artery bypass grafting among patients at 39 hospitals participating in the Michigan Society of Thoracic and Cardiovascular Surgeons Quality Collaborative's PERFusion measures and outcomes (PERForm) registry between 2011 and 2015. Candidates' preoperative risk factors were identified based on previous work and clinical input. The study population was randomly divided into a 70% development sample and a 30% validation sample. A generalized linear mixed-effect model was developed to predict perioperative red blood cell transfusion. The model's performance was assessed for calibration and discrimination. Sensitivity analysis was performed to assess the robustness of the model in different clinical subgroups.ResultsTransfusions occurred in 36.8% of patients. The final regression model included 16 preoperative variables. The correlation between the observed and expected transfusions was 1.0. The risk prediction model discriminated well (receiver operator characteristic [ROC]development, 0.81; ROCvalidation, 0.82) and had satisfactory calibration (correlation between observed and expected rates was r = 1.00). The model performance was confirmed across medical centers and clinical subgroups.ConclusionsOur risk prediction model uses 16 readily obtainable preoperative variables. This model, which provides a patient-specific estimate of the need for transfusion, offers clinicians a guide for decision making and evaluating the effectiveness of blood management strategies.
| S-EPMC5968351 | biostudies-literature