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Biomarkers improve prediction of 30-day unplanned readmission or mortality after paediatric congenital heart surgery.

ABSTRACT: OBJECTIVE:To evaluate the association between novel pre- and post-operative biomarker levels and 30-day unplanned readmission or mortality after paediatric congenital heart surgery. METHODS:Children aged 18 years or younger undergoing congenital heart surgery (n = 162) at Johns Hopkins Hospital from 2010 to 2014 were enrolled in the prospective cohort. Collected novel pre- and post-operative biomarkers include soluble suppression of tumorgenicity 2, galectin-3, N-terminal prohormone of brain natriuretic peptide, and glial fibrillary acidic protein. A model based on clinical variables from the Society of Thoracic Surgery database was developed and evaluated against two augmented models. RESULTS:Unplanned readmission or mortality within 30 days of cardiac surgery occurred among 21 (13%) children. The clinical model augmented with pre-operative biomarkers demonstrated a statistically significant improvement over the clinical model alone with a receiver-operating characteristics curve of 0.754 (95% confidence interval: 0.65-0.86) compared to 0.617 (95% confidence interval: 0.47-0.76; p-value: 0.012). The clinical model augmented with pre- and post-operative biomarkers demonstrated a significant improvement over the clinical model alone, with a receiver-operating characteristics curve of 0.802 (95% confidence interval: 0.72-0.89; p-value: 0.003). CONCLUSIONS:Novel biomarkers add significant predictive value when assessing the likelihood of unplanned readmission or mortality after paediatric congenital heart surgery. Further exploration of the utility of these novel biomarkers during the pre- or post-operative period to identify early risk of mortality or readmission will aid in determining the clinical utility and application of these biomarkers into routine risk assessment.

SUBMITTER: Brown JR

PROVIDER: S-EPMC6711799 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Biomarkers improve prediction of 30-day unplanned readmission or mortality after paediatric congenital heart surgery.

Brown Jeremiah R JR Stabler Meagan E ME Parker Devin M DM Vricella Luca L Pasquali Sara S Leyenaar JoAnna K JK Bohm Andrew R AR MacKenzie Todd T Parikh Chirag C Jacobs Marshall L ML Jacobs Jeffrey P JP Everett Allen D AD

Cardiology in the young 20190710 8

<h4>Objective</h4>To evaluate the association between novel pre- and post-operative biomarker levels and 30-day unplanned readmission or mortality after paediatric congenital heart surgery.<h4>Methods</h4>Children aged 18 years or younger undergoing congenital heart surgery (n = 162) at Johns Hopkins Hospital from 2010 to 2014 were enrolled in the prospective cohort. Collected novel pre- and post-operative biomarkers include soluble suppression of tumorgenicity 2, galectin-3, N-terminal prohormo ...[more]

PMID: 31290383

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Project description:Unplanned hospital readmissions following surgical interventions are associated with adverse events and contribute to increasing health care costs. Despite numerous studies defining risk factors following lower extremity bypass surgery, evidence regarding readmission after endovascular interventions is limited. This study aimed to identify predictors of 30-day unplanned readmission following infrainguinal endovascular interventions.We identified all patients undergoing an infrainguinal endovascular intervention in the targeted vascular module of the American College of Surgeons National Surgical Quality Improvement Program between 2012 and 2014. Perioperative outcomes were stratified by symptom status (chronic limb-threatening ischemia [CLI] vs claudication). Patients who died during index admission and those who remained in the hospital after 30 days were excluded. Indications for unplanned readmission related to the index procedure were evaluated. Multivariable logistic regression was used to identify preoperative and in-hospital (during index admission) risk factors of 30-day unplanned readmission.There were 4449 patients who underwent infrainguinal endovascular intervention, of whom 2802 (63%) had CLI (66% tissue loss) and 1647 (37%) had claudication. The unplanned readmission rates for CLI and claudication patients were 16% (n = 447) and 6.5% (n = 107), respectively. Mortality after index admission was higher for readmitted patients compared with those not readmitted (CLI, 3.4% vs 0.7% [P < .001]; claudication, 2.8% vs 0.1% [P < .01]). Approximately 50% of all unplanned readmissions were related to the index procedure. Among CLI patients, the most common indication for readmission related to the index procedure was wound or infection related (42%), whereas patients with claudication were mainly readmitted for recurrent symptoms of peripheral vascular disease (28%). In patients with CLI, predictors of unplanned readmission included diabetes (odds ratio, 1.3; 95% confidence interval, 1.01-1.6), congestive heart failure (1.6; 1.1-2.5), renal insufficiency (1.7; 1.3-2.2), preoperative dialysis (1.4; 1.02-1.9), tibial angioplasty/stenting (1.3; 1.04-1.6), in-hospital bleeding (1.9; 1.04-3.5), in-hospital unplanned return to the operating room (1.9; 1.1-3.5), and discharge other than to home (1.5; 1.1-2.0). Risk factors for those with claudication were dependent functional status (3.5; 1.4-8.7), smoking (1.6; 1.02-2.5), diabetes (1.5; 1.01-2.3), preoperative dialysis (3.6; 1.6-8.3), procedure time exceeding 120 minutes (1.8; 1.1-2.7), in-hospital bleeding (2.9; 1.2-7.4), and in-hospital unplanned return to the operating room (3.4; 1.2-9.4).Unplanned readmission after endovascular treatment is relatively common, especially in patients with CLI, and is associated with substantially increased mortality. Awareness of these risk factors will help providers identify patients at high risk who may benefit from early surveillance, and prophylactic measures focused on decreasing postoperative complications may reduce the rate of readmission.

Project description:Readmission to hospital is a common occurrence due to adverse post-operative events. The primary objective of the present study was to examine the possible risk predictors for 30-day unplanned readmissions after the surgical treatment of gastric cancer. The secondary aim was to determine the clinical characteristics that are associated with readmission. Studies that reported the risk factors and clinical characteristics of patients with gastric cancer who had an unplanned 30-day post-operative readmission were identified systematically from PubMed, Cochrane Central Register of Controlled Trials, Web of Science and Embase databases, with a final search date of March 30, 2024. A systematic review and meta-analysis were then performed to estimate the risk predictors and relevant clinical characteristics for readmission. A total of 16,154 patients from 12 studies were included in the present study, with 1,736 patients who were readmitted and 14,418 patients who were not readmitted. A higher proportion of patients with an age ≥70 years, cardiovascular comorbidity, Nutritional Risk Screening (NRS) 2002 score ≥3, respiratory diseases, male sex, American Society of Anesthesiologists score ≥3, combined multi-organ resection, greater depth of invasion (T3-4/T1-2), discharge to home with provision of care services, neoadjuvant therapy, post-operative complications or a blood transfusion were found in the readmission group compared with that in the non-readmission group. A meta-analysis was also performed to calculate risk predictors using the results of multivariate regression analyses from the original literature. This identified cardiovascular comorbidity, NRS 2002 score ≥3, pancreatectomy and post-operative complications as risk predictors for 30-day unplanned readmission following surgery for gastric cancer. Therefore, it is recommended that extra attention and support should be given to patients with these high-risk predictors during the perioperative period.

Project description:Recent data shows that a neuromuscular block (NMB) induced by administration of high doses of rocuronium improves surgical conditions in certain procedures. However, there are limited data on the effect such practices on postoperative outcomes. We performed a retrospective analysis to compare unplanned 30-day readmissions in patients that received high-dose versus low-dose rocuronium administration during general anesthesia for laparoscopic retroperitoneal surgery. This retrospective cohort study was performed in the Netherlands in an academic hospital where routine high-dose rocuronium NMB has been practiced since July 2015. Charts of patients receiving anesthesia between January 2014 and December 2016 were searched for surgical cases receiving high-dose rocuronium and matched with respect to procedure, age, sex and ASA classification to patients receiving low-dose rocuronium. The primary post-operative outcome was unplanned 30-day readmission rate. There were 130 patients in each cohort. Patients in the high- and low-dose rocuronium cohorts received 217 ± 49 versus 37 ± 5 mg rocuronium, respectively. In the high-dose rocuronium group neuromuscular activity was consistently monitored; matched patients were unreliably monitored. All patients receiving high-dose rocuronium were reversed with sugammadex, while just 33% of matched patients were reversed with sugammadex and 20% with neostigmine; the remaining patients were not reversed. Unplanned 30-day readmission rate was significantly lower in the high-dose compared to the low-dose rocuronium cohort (3.8% vs. 12.7%; p = 0.03; odds ratio = 0.33, 95% C.I. 0.12-0.95). This small retrospective study demonstrates a lower incidence of unplanned readmissions within 30-days following laparoscopic retroperitoneal surgery with high-dose relaxant anesthesia and sugammadex reversal in comparison to low-dose relaxant anesthesia. Further prospective studies are needed in larger samples to corroborate our findings and additionally assess the pharmacoeconomics of high-dose relaxant anesthesia taking into account the benefits (reduced readmissions) and harm (cost of relaxants and reversal agents) of such practice.

Project description:BackgroundExisting readmission reduction solutions tend to focus on complementing inpatient care with enhanced care transition and postdischarge interventions. These solutions are initiated near or after discharge, when clinicians' impact on inpatient care is ending. Preventive intervention during hospitalization is an underexplored area that holds potential for reducing readmission risk. However, it is challenging to predict readmission risk at the early stage of hospitalization because few data are available.ObjectiveThe objective of this study was to build an early prediction model of unplanned 30-day hospital readmission using a large and diverse sample. We were also interested in identifying novel readmission risk factors and protective factors.MethodsWe extracted the medical records of 96,550 patients in 205 participating Cerner client hospitals across four US census regions in 2016 from the Health Facts database. The model was built with index admission data that can become available within 24 hours and data from previous encounters up to 1 year before the index admission. The candidate models were evaluated for performance, timeliness, and generalizability. Multivariate logistic regression analysis was used to identify readmission risk factors and protective factors.ResultsWe developed six candidate readmission models with different machine learning algorithms. The best performing model of extreme gradient boosting (XGBoost) achieved an area under the receiver operating characteristic curve of 0.753 on the development data set and 0.742 on the validation data set. By multivariate logistic regression analysis, we identified 14 risk factors and 2 protective factors of readmission that have never been reported.ConclusionsThe performance of our model is better than that of the most widely used models in US health care settings. This model can help clinicians identify readmission risk at the early stage of hospitalization so that they can pay extra attention during the care process of high-risk patients. The 14 novel risk factors and 2 novel protective factors can aid understanding of the factors associated with readmission.

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Biomarkers improve prediction of 30-day unplanned readmission or mortality after paediatric congenital heart surgery.

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Biomarkers improve prediction of 30-day unplanned readmission or mortality after paediatric congenital heart surgery.

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