Elevated admission N-terminal pro-brain natriuretic peptide level predicts the development of atrial fibrillation in general surgical intensive care unit patients

Cardiac damage after polytrauma: the role of systematic transthoracic echocardiography - a pilot study

BACKGROUND

Heart injuries following polytrauma (PT) are identified as a predictor of poor outcome. The diagnostic algorithm of cardiac damage after trauma consists of the systemic measurement of cardiac damage markers, a 3-channel ECG and if there are any suspicious findings, the conduction of a transthoracic echocardiography (TTE). The aim of this study was to implement a systematic analysis of cardiac function using TTE in PT-patients.

METHODS

This study is a prospective non-randomized study, conducted in a German Level 1 Trauma Centre between January and July 2024. All polytraumatized patients with an ISS ≥ 16 were included immediately after entering the emergency department. Blood samples were withdrawn at 6 timepoints, at the Emergency room, 24 h, 48 h, three, five and ten days after admission to the hospital. Cardiac damage was measured by Troponin T (TnT) ECLIA, as well as NT-proBNP measurements. Entering the intensive care unit, transthoracic echocardiography was performed at two time points (day 1 and 2), by an experienced Cardiologist.

RESULTS

During the pilot phase, cardiac contusion was detected in 14.3% of patients, with significantly elevated TnT levels on arrival, after 24 (**p ≤ 0.01) and 48 h (*p ≤ 0.05) compared to patients without cardiac contusion. Echocardiographic findings revealed that 25% of all patients had wall motion abnormalities, and 20% showed relaxation disorders. Right ventricular function, measured by TAPSE (tricuspid annular plane systolic excursion), RVEDD (right ventricular end diastolic diameter) and sPAP (systolic pulmonary arterial pressure), was slightly impaired in trauma patients, while the left ventricular function (ejection fraction (EF) and left ventricular end diastolic diameter (LVEDD)) was preserved. We observed the increase of TnT and an increase of the heart failure marker NT-proBNP over the time. These biomarkers were associated with pre-existing cardiac risk factors, the ISS and changes in the right or left ventricular function. Mitral valve insufficiency (grade 1) was present in 50% and tricuspid valve (grade 1) insufficiency in 30%.

CONCLUSIONS

Taken together, we conducted for the first time of our knowledge, a systematic TTE analysis in PT-patients. We observed a slightly reduced right ventricular function, as well as mitral and tricuspid valve regurgitations in the patients.

Performance of an AI prediction tool for new-onset atrial fibrillation after coronary artery bypass grafting

Background

There is lack of tools to predict new-onset postoperative atrial fibrillation (NOAF) after coronary artery bypass grafting (CABG). We aimed to develop and validate a novel AI-based bedside tool that accurately predicts predict NOAF after CABG.

Methods

Data from 2994 patients who underwent CABG between March 2015 and July 2024 at two tertiary hospitals in China were retrospectively analyzed. 2486 patients from one hospital formed the derivation cohort, split 7:3 into training and test sets, while the 508 patients from a separate hospital formed the external validation cohort. A stacking model integrating 11 base learners was developed and evaluated using Accuracy, Precision, Recall, F1 score, and Area Under Curve (AUC). SHapley Additive exPlanations (SHAP) values were calculated and plotted to interpret the contributions of individual characteristics to the model's predictions.

Findings

Seventy-seven predictive characteristics were analyzed. The stacking model achieved superior performance with AUCs 0·931 and F1 scores 0·797 in the independent external validation, outperforming CHA2DS2-VASc, HATCH, and POAF scores (AUC 0·931 vs. 0·713, 0·708, and 0·667; p < 0·05). SHAP value indicate that the importance of predictive features for NOAF, in descending order, include: Brain natriuretic peptide, Left ventricular end-diastolic diameter, Ejection fraction, BMI, β-receptor blockers, Duration of surgery, Age, Neutrophil percentage-to-albumin ratio, Myocardial infarction, Left atrial diameter, Hypertension, and smoking status. Subsequently, we constructed an easy-to-use bedside clinical tool for NOAF risk assessment leveraging these characteristics.

Interpretation

The AI-based tool offers superior prediction of NOAF, outperforming three existing predictive tools. Future studies should further explore how various patient characteristics influence the timing of NOAF onset, whether early or late.

Funding

This work was funded by Lingnan Nightingale Nursing Research Institute of Guangdong Province, and Guangdong Nursing Society (GDHLYJYZ202401).

Predictors for sustained new-onset atrial fibrillation in critically ill patients: a retrospective observational study

PURPOSE

Although new-onset atrial fibrillation (AF) is frequently observed in the intensive care unit (ICU), the incidence and predictors for sustained new-onset AF have not been investigated, except for cardiac surgery patients. We have evaluated potential predictors for sustained new-onset AF in a mixed ICU.

METHODS

In this retrospective observational study, we screened non-cardiac surgery patients who were admitted to the ICU between January 2010 and December 2013 and had been hospitalized for > 24 h in the ICU. We collected information about heart rhythm 6 h after the onset of AF. We compared detailed patient characteristics between patients with sinus rhythm (SR) and those with sustained AF at 6 h after the onset of AF. Additionally, we applied variable selection using backward elimination based on Akaike's Information Criterion (AIC). Calibration was performed based on the Hosmer-Lemeshow test.

RESULTS

New-onset AF occurred in 151 of 1718 patients and 99 patients converted to SR at 6 h. Backward elimination identified predictors as follows (AIC = 175.3): CHADS2 score, elective surgery, infection on ICU admission, serum potassium > 4.0 mmol/L, male sex, mechanical ventilation, and diagnostic grouping. The model showed good calibration for sustenance of AF at 6 h after the onset using the Hosmer-Lemeshow Chi-square value of 4.36 (degrees of freedom = 4, p = 0.360) indicating a good fit.

CONCLUSIONS

These predictors might be useful in future interventional studies to identify patients who are likely to sustain new-onset AF.

Impact and treatment success of new-onset atrial fibrillation with rapid ventricular rate development in the surgical intensive care unit

BACKGROUND

Atrial fibrillation (AF) with rapid ventricular rate (RVR; heart rate >100) in noncardiac postoperative surgical patients is associated with poor outcomes. The objective of this study was to evaluate the practice patterns of AF management in a surgical intensive care unit to determine practices associated with rate and rhythm control and additional outcomes.

MATERIALS AND METHODS

Adult patients (≥18 y) admitted to the surgical intensive care unit (SICU) from June 2014 to June 2015 were retrospectively screened for the development of new-onset AF with RVR. Demographics, hospital course, evaluation and treatment of AF with RVR, and outcome were evaluated and analyzed.

RESULTS

Thousand seventy patients were admitted to the SICU during the study period; 33 met inclusion criteria (3.1%). Twenty-six patients (79%) had rate and rhythm control within 48 h of AF with RVR onset. β-Blockers were the most commonly used initial medication (67%) but were successful at rate and rhythm control in only 27% of patients (6/22). Amiodarone had the highest rate of success if used initially (5/6, 83%) and secondarily (11/13, 85%). Failure to control rate and rhythm was associated with a greater likelihood of comorbidities (100% versus 57%; P = 0.06).

CONCLUSIONS

New-onset AF with RVR in the noncardiac postoperative patient is associated with a high mortality (21%). Amiodarone is the most effective treatment for rate and rhythm control. Failure to establish rate and rhythm control was associated with cardiac comorbidities. These results will help to form future algorithms for the treatment of AF with RVR in the SICU.

Predictors of de novo atrial fibrillation in a non-cardiac intensive care unit

OBJECTIVE

To assess the predictors of de novo atrial fibrillation in patients in a non-cardiac intensive care unit.

METHODS

A total of 418 hospitalized patients were analyzed between January and September 2016 in a non-cardiac intensive care unit. Clinical characteristics, interventions, and biochemical markers were recorded during hospitalization. In-hospital mortality and length of hospital stay in the intensive care unit were also evaluated.

RESULTS

A total of 310 patients were included. The mean age of the patients was 61.0 ± 18.3 years, 49.4% were male, and 23.5% presented de novo atrial fibrillation. The multivariate model identified previous stroke (OR = 10.09; p = 0.016) and elevated levels of pro-B type natriuretic peptide (proBNP, OR = 1.28 for each 1,000pg/mL increment; p = 0.004) as independent predictors of de novo atrial fibrillation. Analysis of the proBNP receiver operating characteristic curve for prediction of de novo atrial fibrillation revealed an area under the curve of 0.816 (p < 0.001), with a sensitivity of 65.2% and a specificity of 82% for proBNP > 5,666pg/mL. There were no differences in mortality (p = 0.370), but the lengths of hospital stay (p = 0.002) and stay in the intensive care unit (p = 0.031) were higher in patients with de novo atrial fibrillation.

CONCLUSIONS

A history of previous stroke and elevated proBNP during hospitalization were independent predictors of de novo atrial fibrillation in the polyvalent intensive care unit. The proBNP is a useful and easy- and quick-access tool in the stratification of atrial fibrillation risk.