Bedside tool for predicting the risk of postoperative atrial fibrillation after cardiac surgery: the POAF score

Machine learning in the prediction and detection of new-onset atrial fibrillation in ICU: a systematic review

Atrial fibrillation (AF) stands as the predominant arrhythmia observed in ICU patients. Nevertheless, the absence of a swift and precise method for prediction and detection poses a challenge. This study aims to provide a comprehensive literature review on the application of machine learning (ML) algorithms for predicting and detecting new-onset atrial fibrillation (NOAF) in ICU-treated patients. Following the PRISMA recommendations, this systematic review outlines ML models employed in the prediction and detection of NOAF in ICU patients and compares the ML-based approach with clinical-based methods. Inclusion criteria comprised randomized controlled trials (RCTs), observational studies, cohort studies, and case-control studies. A total of five articles published between November 2020 and April 2023 were identified and reviewed to extract the algorithms and performance metrics. Reviewed studies sourced 108,724 ICU admission records form databases, e.g., MIMIC. Eight prediction and detection methods were examined. Notably, CatBoost exhibited superior performance in NOAF prediction, while the support vector machine excelled in NOAF detection. Machine learning algorithms emerge as promising tools for predicting and detecting NOAF in ICU patients. The incorporation of these algorithms in clinical practice has the potential to enhance decision-making and the overall management of NOAF in ICU settings.

Prevention of Atrial Fibrillation After Cardiac Surgery: A Review of Literature and Comparison of Different Treatment Modalities

Atrial fibrillation is the most common arrhythmia to occur after cardiac surgery, with an incidence of 10% to 50%. It is associated with postoperative complications including increased risk of stroke, prolonged hospital stays and increased costs. Despite new insights into the mechanisms of atrial fibrillation, no specific etiologic factor has been identified as the sole perpetrator of the arrhythmia. Current evidence suggests that the pathophysiology of atrial fibrillation in general, as well as after cardiac surgery, is multifactorial. Studies have also shown that new-onset postoperative atrial fibrillation following cardiac surgery is associated with a higher risk of short-term and long-term mortality. Furthermore, it has been demonstrated that prophylactic medical therapy decreases the incidence of postoperative atrial fibrillation after cardiac surgery. Of note, the incidence of postoperative atrial fibrillation has not changed during the last decades despite the numerous preventive strategies and operative techniques proposed, although the perioperative and postoperative care of cardiac patients as such has improved.

Interventions to prevent postoperative atrial fibrillation in Dutch cardiothoracic centres: a survey study

INTRODUCTION

Postoperative atrial fibrillation (POAF) is a common phenomenon following cardiac surgery. In this study, we assessed current preventive strategies used by Dutch cardiothoracic centres, identified common views on this matter and related these to international guidelines.

METHODS

We developed an online questionnaire and sent it to all cardiothoracic surgery centres in the Netherlands. The questionnaire concerned the management of POAF and the use of pharmaceutical therapies (beta-blockers and calcium antagonists) and non-pharmaceutical methods (posterior left pericardiotomy, pericardial flushing and epicardial botulinum toxin type A injections). Usage of electrical cardioversions, anticoagulants and left atrial appendage closure were also enquired.

RESULTS

Of the 15 centres, 14 (93%) responded to the survey and 13 reported a POAF incidence, ranging from 20 to 30%. Of these 14 centres, 6 prescribed preoperative AF prophylaxis to their patients, of which non-sotalol beta-blockers were prescribed most commonly (57%). Postoperative medication was administered by all centres and included non-sotalol beta-blockers (38%), sotalol (24%), digoxin (14%), calcium antagonists (13%) and amiodarone (10%). Only 2 centres used posterior left pericardiotomy or pericardial flushing as surgical manoeuvres to prevent POAF. Moreover, respondents expressed the need for guidance on anticoagulant use.

CONCLUSION

Despite the use of various preventive strategies, the reported incidence of POAF was similar in Dutch cardiothoracic centres. This study highlights limited use of prophylactic amiodarone and colchicine, despite recommendations by numerous guidelines, and restricted implementation of surgical strategies to prevent POAF.

Scores predicting atrial fibrillation after mitral valve surgery: Do we need a more specific score?

Background

Atrial fibrillation after cardiac surgery (POAF) is associated with increased morbidity and mortality. Several scores were used to predict POAF, with variable results. Thus, this study assessed the performance of several scoring systems to predict POAF after mitral valve surgery. Additionally, we identified the risk factors for POAF in those patients.

Methods

This retrospective cohort included 1381 recruited from 2009 to 2021. The patients underwent mitral valve surgery, and POAF occurred in 233 (16.87%) patients. The performance of CHADS2, CHA2DS2-VASc, POAF, EuroSCORE II, and HATCH scores was evaluated.

Results

The median age was higher in patients who developed POAF (60 vs. 54 years; p < .001). CHA2-DS2-VASc, POAF, EuroSCORE II, and HATCH scores significantly predicted POAF, with areas under the curve of the receiver operator curve (AUCROC) of 0.56, 0.61, 0.58, and 0.54, respectively. We identified age > 58 years, body mass index > 28 kg/m2, creatinine clearance < 90 mL/min, reoperative surgery, and preoperative inotropic and intra-aortic balloon pump use as predictors of POAF. We constructed a score from these variables (PSCC-AF). A score > 2 significantly predicted POAF (p < .001). The AUCROC of this score was 0.67, which was significantly higher than the AUCROC of the POAF score (p = .009).

Conclusion

POAF after mitral valve surgery can be predicted based on preoperative patient characteristics. The new PSCC-AF score significantly predicted POAF after mitral valve surgery and can serve as a bedside diagnostic tool for POAF risk screening. Further studies are needed to validate the PSCC-AF-mitral score externally.

Postoperative atrial fibrillation (POAF) after cardiac surgery: clinical practice review

Postoperative atrial fibrillation (POAF) after cardiac surgery is associated with elevated morbidity and mortality. Although current prediction models have limited efficacy, several perioperative interventions can reduce patients' risk of POAF. These begin with preoperative medications, including beta-blockers and amiodarone. Moreover, patients should be screened for preexisting atrial fibrillation (AF) so that concomitant surgical ablation and left atrial appendage occlusion can be performed in appropriate candidates. Intraoperative interventions such as posterior pericardiectomy can reduce mediastinal fluid accumulation, which is a trigger for POAF. Furthermore, many preventive strategies for POAF are implemented in the immediate postoperative period. Initiating beta-blockers, amiodarone, or both is reasonable for most patients. Overdrive atrial pacing, colchicine, and steroids have been used by some, although the evidence base is less robust. For patients with POAF, rate-control and rhythm-control strategies have comparable outcomes. Decision-making regarding anticoagulation should recognize that the stroke risk associated with POAF appears to be lower than that for general nonvalvular AF. The evidence that oral anticoagulation reduces stroke risk is less clear for POAF patients than for patients with general nonvalvular AF. Given that POAF tends to be shorter-lived and is associated with greater bleeding risks in the perioperative period, decisions regarding anticoagulation should be individualized. Finally, wearable technology and machine learning algorithms for better predicting and managing POAF appear to be coming soon. These technologies and a comprehensive clinical program could meaningfully reduce the incidence of this common complication.

Sex-Specific Cardiometabolic Determinants of Postoperative Atrial Fibrillation After Cardiac Surgery

BACKGROUND

Cardiometabolic diseases increase the risk of postoperative atrial fibrillation (POAF), a complication leading to higher long-term risk of major cardiovascular events (MACE). It remains unknown whether the effect of these risk factors differs according to sex. We sought to evaluate the sex-specific predictors of POAF after coronary artery bypass grafting (CABG).

METHODS

In a prospective registry of patients undergoing isolated CABG, we compared predictors of POAF between sexes with logistic regression models. Because of high prevalence of abdominal obesity in women, > 80% having a waist circumference (WC) ≥ 88 cm, median WC values were used to define abdominal obesity (men ≥ 102 cm, women ≥ 100 cm).

RESULTS

This analysis included 6177 individuals (17% women). Mean age was 65.6 ± 8.9 years. POAF occurred in 32% of men and 28% of women (P < 0.05). Compared with men, women with POAF had similar WC; higher prevalence of hypertension and diabetes; lower high-density lipoprotein (HDL)-cholesterol; and higher glucose, triglyceride, low- density lipoprotein (LDL)-cholesterol, and C-reactive protein levels (all P < 0.05). After adjustment, age and abdominal obesity were associated with POAF in both sexes (P < 0.05). The interaction of WC with sex suggested a worse impact of WC on POAF risk among women (adjusted odds ratio [OR], 1.97; 95% confidence interval [CI], 1.48-2.62 vs in men 1.33; 95% CI, 1.17-1.50; P for interaction = 0.01).

CONCLUSIONS

Abdominal obesity is a major predictor of POAF in both sexes, with higher risk in women. These results emphasize the need for enhanced strategies to manage abdominal obesity and its cardiometabolic consequences in the general population and the potential to develop sex-specific preventive interventions to reduce risk of POAF.

Systemic immune-inflammation index for predicting postoperative atrial fibrillation following cardiac surgery: a meta-analysis

Background

Postoperative atrial fibrillation (POAF) is a frequent complication that may increase morbidity and mortality risk following cardiac surgery. The systemic immune-inflammation index (SII) is an emerging biomarker that provides an integrated measure of inflammation by incorporating neutrophil, lymphocyte, and platelet counts. Recent studies have reported associations between elevated SII and increased POAF risk; however, significant heterogeneity exists regarding its predictive efficacy. This meta-analysis aimed to assess SII's diagnostic efficacy for predicting POAF risk.

Methods

To synthesize existing evidence on the ability of perioperative SII for predicting POAF in patients undergoing cardiac surgery, a systematic review and meta-analysis was conducted. In August 2023, a comprehensive literature search was performed to identify relevant studies reporting SII cutoff values with corresponding sensitivity and specificity. The primary aim was to evaluate SII's diagnostic utility for predicting POAF, whereas secondary outcomes included the pooled incidence of POAF and the relationship between the SII and POAF.

Results

Eight studies published between 2021 and 2023 with 3,245 patients were included. Six studies involved coronary artery bypass grafting (CABG) surgery; one encompassed various cardiac procedures, and another focused solely on mitral valve surgery. The pooled incidence of POAF was 23.6% [95% confidence interval (CI), 18.7%-29.2%]. Elevated SII significantly increased the odds of POAF by 3.24-fold (odds ratio, 3.24; 95% CI, 1.6-6.55; p = 0.001). SII's pooled sensitivity and specificity for predicting POAF were 0.80 (95% CI, 0.68-0.89) and 0.53 (95% CI, 0.23-0.8), respectively. The SII had moderate predictive accuracy based on a hierarchical summary receiver operating characteristic (HSROC) area under the curve of 0.78 (95% CI, 0.74-0.81). Subgroup analyses, whether focusing on CABG alone or CABG with cardiopulmonary bypass (CPB), both indicated an area under the HSROC curve of 0.78 (95% CI, 0.74-0.81).

Conclusion

Elevated SII is significantly correlated with an increased POAF risk following cardiac surgery, highlighting its utility as a predictive biomarker. Considering its moderate diagnostic accuracy, further research is essential for clarifying SII's clinical effectiveness, either as an independent predictor or combined with other risk factors, for stratifying patients at high POAF risk.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/, identifier [CRD42023456128].

Prospective Study of Risk Factors for Postoperative Atrial Fibrillation After Cardiac Surgery

INTRODUCTION

To examine risk factors for new-onset postoperative atrial fibrillation (POAF) after cardiac surgery.

METHODS

Patients enrolled in the Cardiothoracic Surgical Trials Network multicenter, randomized trial of rate control versus rhythm control for POAF were included. Predictors of POAF were determined using multivariable logistic regression.

RESULTS

Among the 2104 patients who were enrolled preoperatively, 695 developed POAF (33.0%). Rates of POAF were 28.1% after isolated coronary artery bypass grafting (CABG), 33.7% after isolated valve repair or replacement, and 47.3% after CABG plus valve repair or replacement. Baseline characteristics associated with an increased risk of POAF identified on multivariable analysis included older age (odds ratio [OR] 1.57; 95% confidence interval [CI] 1.42-1.73, per 10 y), White race or non-Hispanic ethnicity (OR 1.52; CI: 1.11-2.07), history of heart failure (OR 1.55; CI: 1.16-2.08), and history of hypothyroidism (OR 1.42; CI 1.04-1.94). The type of cardiac procedure was associated with an increased risk of POAF with both isolated valve repair or replacement (OR 1.33, CI 1.08-1.64) and combined CABG plus valve repair or replacement (OR 1.64, CI 1.24-2.17) having increased risk of POAF compared to isolated CABG. No preoperative cardiac medication was associated with POAF.

CONCLUSIONS

In this prospective cohort of patients, older age, a history of hypothyroidism, a history of heart failure, and valve repair or replacement, with or without CABG, and White non-Hispanic race were associated with an increased risk of POAF.

Subacute postoperative atrial fibrillation after heart surgery: Incidence and predictive factors in cardiac rehabilitation

Background

Postoperative atrial fibrillation (POAF) is the most common arrhythmia following cardiac surgery (CS). It may occur between the 1st and the 4th postoperative day as acute POAF or between the 5th and the 30th as subacute (sPOAF). sPOAF is associated with higher thromboembolic risk, which consistently increase patients' morbidity. Neutrophil-to-lymphocyte ratio (NLR) is a low-cost inflammatory index proposed as possible POAF predictor. Identification of patients' risk categories might lead to improved postoperative outcomes.

Methods

The aim was to assess the incidence of sPOAF and to identify possible predictors in patients performing cardiovascular rehabilitation (CR) after CS. A single-center cohort study was performed on 737 post-surgical patients admitted to CR on sinus rhythm. Continuous monitoring with 12-lead ECG telemetry was performed. We evaluated the predictive role of anamnestic, clinical, and laboratory data, including baseline NLR.

Results

Subacute POAF was documented in 170 cases (23.1%). At the multivariate analysis, age (OR 1.03; p = .001), mitral valve surgery (OR 1.77; p = .012), acute POAF (OR 2.97; p < .001), and NLR at baseline (OR 1.13; p = .042) were found to be independent predictive factors of sPOAF following heart surgery.

Conclusions

sPOAF is common after CS. Age, mitral valve procedures, acute POAF, and preoperative NLR were proved to increase sPOAF occurrence in CR. NLR is an affordable and reliable parameter which might be used to qualify the risk of arrhythmias at CR admission. Identification of new predictors of postoperative atrial fibrillation may allow to improve patients' prognosis.

Risk Scores for Prediction of Postoperative Atrial Fibrillation After Cardiac Surgery: A Systematic Review and Meta-Analysis

Postoperative atrial fibrillation (POAF) is a common complication after cardiac surgery and is associated with poor clinical outcomes. The objective of this systematic review and meta-analysis was to assess the performance of risk scores to predict POAF in cardiac surgery patients. We searched MEDLINE, Embase, and Cochrane CENTRAL for studies that developed/evaluated a POAF risk prediction model. Pairs of reviewers independently screened studies and extracted data. We pooled area under the receiver operating curves (AUCs), sensitivity and specificity, and adjusted odds ratios from multivariable regression analyses using the generic inverse variance method and random effects models. Forty-three studies (n = 63,847) were included in the quantitative synthesis. Most scores were originally developed for other purposes but evaluated for predicting POAF. Pooled AUC revealed moderate POAF discrimination for the EuroSCORE II (AUC 0.59, 95% confidence interval [CI] 0.54 to 0.65), Society of Thoracic Surgeons (AUC 0.60, 95% CI 0.56 to 0.63), EuroSCORE (AUC 0.63, 95% CI 0.58 to 0.68), CHADS2 (AUC 0.66, 95% CI 0.57 to 0.75), POAF Score (AUC 0.66, 95% CI 0.63 to 0.68), HATCH (AUC 0.67, 95% CI 0.57 to 0.75), CHA2DS2-VASc (AUC 0.68, 95% CI 0.60 to 0.75) and SYNTAX scores (AUC 0.74, 95% CI 0.71 to 0.78). Pooled analyses at specific cutoffs of the CHA2DS2-VASc, CHADS2, HATCH, and POAF scores demonstrated moderate-to-high sensitivity (range 46% to 87%) and low-to-moderate specificity (range 31% to 70%) for POAF prediction. In conclusion, existing clinical risk scores offer at best moderate prediction for POAF after cardiac surgery. Better models are needed to guide POAF risk stratification in cardiac surgery patients.

New-onset postoperative atrial fibrillation after mitral valve surgery: Determinants and the effect on survival

Objective

Mitral valve surgery (MVS) carries substantial risk of postoperative atrial fibrillation (PAF). Identifying patients who benefit from prophylactic left atrial appendage amputation (LAAA) or maze is ill-defined. To guide such interventions, we determined preoperative predictors of PAF and investigated 3-year survival of patients with PAF.

Methods

We performed a retrospective analysis of patients undergoing isolated MVS (N = 670) between 2011 and 2021. Patients with preoperative atrial fibrillation, LAAA or pulmonary vein isolation were excluded. Patient characteristics were compared between those without PAF and those who developed transient or prolonged PAF. Predictors of any PAF and prolonged PAF were identified using multivariable regression analysis.

Results

In total, 504 patients without preoperative atrial fibrillation underwent isolated MVS. Of them, 303 patients (60.2%) developed PAF; 138 (27.3%) developed transient and 165 (32.7%) developed prolonged (beyond 30 days) PAF. Patients with PAF were older (65.7 vs 54.3 years, P < .001), with larger left atria (4.8 vs 4.3 cm, P < .001), greater prevalence of hypertension (60% vs 47.8%, P < .05), and were New York Heart Association class III/IV (36% vs 8.5%, P < .001). Independent predictors of PAF included left atria volume index (odds ratio [OR], 1.02; P < .003), older age (OR, 1.04; P < .001), heart failure (OR, 6.73; P < .001), and sternotomy (OR, 2.19; P < .002). Age, heart failure, and sternotomy were independent predictors of prolonged PAF. Patients with PAF had greater mortality at 3 years compared with those without PAF (5.3% vs 0.5%, P < .005). On multivariable analysis, PAF was associated with increased mortality (hazard ratio, 7.81; P < .046).

Conclusions

PAF is common after MVS and associated with late mortality. Older age, advanced heart failure, and sternotomy are associated with prolonged PAF. These factors may identify patients who would benefit from prophylactic LAAA or ablation during MVS.

Incidence, Risk Score Performance, and In-Hospital Outcomes of Postoperative Atrial Fibrillation After Cardiac Surgery

BACKGROUND

Postoperative atrial fibrillation (POAF) frequently complicates cardiac surgery. Predicting POAF can guide interventions to prevent its onset. This study assessed the incidence, risk factors, and related adverse outcomes of POAF after cardiac surgery.

METHODS

A cohort of 1,606 patients undergoing cardiac surgery at a tertiary referral center was analyzed. Postoperative AF was defined based on the Society of Thoracic Surgeons' criteria: AF/atrial flutter after operating room exit that either lasted longer than 1 hour or required medical or procedural intervention. Risk factors for POAF were evaluated, and the performance of established risk scores (POAF, HATCH, COM-AF, CHA2DS2-VASc, and Society of Thoracic Surgeons risk scores) in predicting POAF was assessed using discrimination (area under the receiver operator characteristics curve) analysis. The association of POAF with secondary outcomes, including length of hospital stay, ventilator time, and discharge to rehabilitation facilities, was evaluated using adjusted linear and logistic regression models.

RESULTS

The incidence of POAF was 32.2% (n = 517). Patients who developed POAF were older, had traditional cardiovascular risk factors and higher Society of Thoracic Surgeons risk scores, and often underwent valve surgery. The POAF risk score demonstrated the highest area under the receiver operator characteristics curve (0.65), but risk scores generally underperformed. Postoperative AF was associated with extended hospital stays, longer ventilator use, and higher likelihood of discharge to rehabilitation facilities (odds ratio, 2.30; 95% CI, 1.73-3.08).

CONCLUSION

This study observed a high incidence of POAF following cardiac surgery and its association with increased morbidity and resource utilization. Accurate POAF prediction remains elusive, emphasizing the need for better risk-prediction methods and tailored interventions to diminish the effect of POAF on patient outcomes.

Leveling Up: A Review of Machine Learning Models in the Cardiac ICU

Machine learning has emerged as a significant tool to augment the medical decision-making process. Studies have steadily accrued detailing algorithms and models designed using machine learning to predict and anticipate pathologic states. The cardiac intensive care unit is an area where anticipation is crucial in the division between life and death. In this paper, we aim to review important studies describing the utility of machine learning algorithms to describe the future of artificial intelligence in the cardiac intensive care unit, especially in regards to the prediction of successful ventilatory weaning, acute respiratory distress syndrome, arrhythmia, and acute kidney injury.

Development and validation of a diagnostic model based on left atrial diameter to predict postoperative atrial fibrillation after off-pump coronary artery bypass grafting

Background

This cohort study collected the clinical data of patients who underwent off-pump coronary artery bypass grafting (OPCABG) during hospitalization to observe the occurrence of postoperative atrial fibrillation (POAF), construct a POAF prediction model for CABG patients based on the left atrial diameter (LAD), and assist clinicians in making better medical decisions.

Methods

In this study, all patients who had no prior history of arrhythmia and who had received isolated OPCABG between May 1, 2021, and February 1, 2022, at Beijing Anzhen Hospital Affiliated to Capital Medical University (n=749) were reviewed. Depending on an optimal cutoff obtained from receiver operating characteristic (ROC) curve analysis, patients were separated into two groups: a group with POAF (n=188) and a group without POAF (n=561). The incidence of POAF was then compared. Prediction models were built, and nomograms were plotted was plotted. Model evaluation, including calibration curve and decision curve analysis, was performed.

Results

In all, 188 out of 749 (25.1%) patients who underwent cardiac surgery experienced POAF. Multifactorial logistic regression analysis showed that age ≥66 years, LAD ≥39 mm, and post-OPCABG atrial fibrillation (AF) were independently associated. The prognostic nomogram model showed good concordance index (C-index) scores. Decision curve analysis suggested the clinical benefit of the prediction models.

Conclusions

In this study, a prediction model for patients with POAF after OPCABG was assessed, which was shown to make more accurate predictions compared with the original risk prediction system. It may assist doctors to optimize management of patients with POAF.

Minimally Invasive Isolated Aortic Valve Replacement in a Potential TAVI Cohort of Patients Aged ≥ 75 Years: A Propensity-Matched Analysis

(1) Background and Objectives: Transcatheter aortic valve implantation is guideline-recommended from the age of 75. However, this European guideline recommendation is based on limited evidence, since no interaction between age and primary outcome has been found in guideline-stated references. This study aimed to compare the short-term outcomes of minimally invasive isolated aortic valve replacement in patients aged ≥ 75 with those of younger patients; (2) Patients and Methods: This retrospective cohort study included 1339 patients who underwent minimally invasive isolated aortic valve replacement at our facility between 2014 and 2022. This cohort was divided into two age-based groups: <75 and ≥75 years. Operative morbidity and mortality were compared between groups. Further analysis was performed using propensity score matching; (3) Results: After matching, 347 pairs of patients were included and analyzed. Despite the higher EuroSCORE II in the ≥75 group (2.2 ± 1.3% vs. 1.80 ± 1.34%, p ≤ 0.001), the 30-day mortality (1.4% vs. 1.2%; p = 0.90) and major adverse cardiac and cerebrovascular events, such as perioperative myocardial infarction (0.0% vs. 1.2%, p = 0.12) and stroke (1.4% vs. 2.6%, p = 0.06), were comparable between both treatment groups; (4) Conclusions: Minimally invasive aortic valve replacement is a safe treatment method for patients aged ≥ 75. Our results indicate that the unilateral cut-off of 75 years is not a limiting factor for performing minimally invasive aortic valve replacement.

Prediction of new onset postoperative atrial fibrillation using a simple Nomogram

BACKGROUND

New onset postoperative atrial fibrillation (POAF) is the most common complication of cardiac surgery, with an incidence ranging from 15 to 50%. This study aimed to develop a new nomogram to predict POAF using preoperative and intraoperative risk factors.

METHODS

We retrospectively analyzed the data of 2108 consecutive adult patients (> 18 years old) who underwent cardiac surgery at our medical institution. The types of surgery included isolated coronary artery bypass grafting, valve surgery, combined valve and coronary artery bypass grafting (CABG), or aortic surgery. Logistic regression or machine learning methods were applied to predict POAF incidence from a subset of 123 parameters. We also developed a simple nomogram based on the strength of the results and compared its predictive ability with that of the CHA2DS2-VASc and POAF scores currently used in clinical practice.

RESULTS

POAF was observed in 414 hospitalized patients. Logistic regression provided the highest area under the receiver operating characteristic curve (ROC) in the validation cohort. A simple bedside tool comprising three variables (age, left atrial diameter, and surgery type) was established, which had a discriminative ability with a ROC of 0.726 (95% CI 0.693-0.759) and 0.727 (95% CI 0.676-0.778) in derivation and validation subsets respectively. The calibration curve of the new model was relatively well-fit (p = 0.502).

CONCLUSIONS

Logistic regression performed better than machine learning in predicting POAF. We developed a nomogram that may assist clinicians in identifying individuals who are prone to POAF.

Atrial Fibrillation Occurring During Acute Hospitalization: A Scientific Statement From the American Heart Association

Acute atrial fibrillation is defined as atrial fibrillation detected in the setting of acute care or acute illness; atrial fibrillation may be detected or managed for the first time during acute hospitalization for another condition. Atrial fibrillation after cardiothoracic surgery is a distinct type of acute atrial fibrillation. Acute atrial fibrillation is associated with high risk of long-term atrial fibrillation recurrence, warranting clinical attention during acute hospitalization and over long-term follow-up. A framework of substrates and triggers can be useful for evaluating and managing acute atrial fibrillation. Acute management requires a multipronged approach with interdisciplinary care collaboration, tailoring treatments to the patient's underlying substrate and acute condition. Key components of acute management include identification and treatment of triggers, selection and implementation of rate/rhythm control, and management of anticoagulation. Acute rate or rhythm control strategy should be individualized with consideration of the patient's capacity to tolerate rapid rates or atrioventricular dyssynchrony, and the patient's ability to tolerate the risk of the therapeutic strategy. Given the high risks of atrial fibrillation recurrence in patients with acute atrial fibrillation, clinical follow-up and heart rhythm monitoring are warranted. Long-term management is guided by patient substrate, with implications for intensity of heart rhythm monitoring, anticoagulation, and considerations for rhythm management strategies. Overall management of acute atrial fibrillation addresses substrates and triggers. The 3As of acute management are acute triggers, atrial fibrillation rate/rhythm management, and anticoagulation. The 2As and 2Ms of long-term management include monitoring of heart rhythm and modification of lifestyle and risk factors, in addition to considerations for atrial fibrillation rate/rhythm management and anticoagulation. Several gaps in knowledge related to acute atrial fibrillation exist and warrant future research.

Imaging in atrial fibrillation: A way to assess atrial fibrosis and remodeling to assist decision-making

The 2020 ESC atrial fibrillation (AF) guidelines suggest the novel 4S-AF scheme for the characterization of AF. Imaging techniques could be helpful for this objective in everyday clinical practice, and information derived from these techniques reflects basic aspects of the pathophysiology of AF, which may facilitate treatment decision-making, and optimal management of AF patients. The aim of this review is to provide an overview of the mechanisms associated with atrial fibrosis and to describe imaging techniques that may help the management of AF patients in clinical practice. Transthoracic echocardiography is the most common procedure given its versatility, safety, and simplicity. Transesophageal echocardiography provides higher resolution exploration, and speckle tracking echocardiography can provide incremental functional and prognostic information over conventional echocardiographic parameters. In addition, LA deformation imaging, including LA strain and strain rate, are related to the extent of fibrosis. On the other hand, multidetector-row computed tomography and cardiac magnetic resonance provide higher resolution data and more accurate assessment of the dimensions, structure, and spatial relationships of the LA. Imaging is central when deciding on catheter ablation or cardioversion, and helps in selecting those patients who will really benefit from these procedures. Moreover, imaging enhances the understanding of the underlying mechanisms of atrial remodeling and might assists in refining the risk of stroke, which help to select the best medical therapies/interventions. In summary, evaluation of LA enlargement, LA remodeling and fibrosis with imaging techniques adds clinical and prognostic information and should be assessed as a part of routine comprehensive AF evaluation.

A prediction model for new-onset atrial fibrillation following coronary artery bypass graft surgery: A multicenter retrospective study

Objective

Developing and assessing a risk prediction model of postoperative atrial fibrillation (POAF) after coronary artery bypass grafting (CABG), and aims to provide a reference for the prediction and prevention.

Design

A retrospective case-control study.

Setting

Three major urban teaching and university hospitals and tertiary referral centers.

Participants

consecutive patients undergoing CABG.

Interventions

The study was retrospective and no interventions were administered to patients.

Measurements and main results

In the study, the overall new-onset POAF prevalence was approximately 28%. A prediction model for POAF with nine significant indicators was developed, and identified new predictors of POAF: left ventricular end diastolic diameter (LVEDD), intraoperative defibrillation, and intraoperative temporary pacing lead implantation. The model had good discrimination in both the derivation and validation cohorts, with the area under the receiver operating characteristic curves (AUCs) of 0.621 (95% CI = 0.602-0.640) and 0.616 (95% CI = 0.579-0.651), respectively, and showed good calibration. Compared with CHA₂DS₂-VASc, HATCH score, and the prediction model of POAF after CABG developed based on a small sample of clinical data from a single center in China, the model in this study had better discrimination.

Conclusion

We have developed and validated a new prediction model of POAF after CABG using multicenter data that can be used in the clinic for early identification of high-risk patients of POAF, and to help effectively prevent POAF in postoperative patients.

Myeloperoxidase in the pericardial fluid improves the performance of prediction rules for postoperative atrial fibrillation

OBJECTIVES

After surgery, inflammation is a prominent factor influencing postoperative atrial fibrillation. Myeloperoxidase is a major contributor to inflammatory responses after surgical tissue damage. We evaluated whether myeloperoxidase is associated with postoperative atrial fibrillation clinically and in an animal model.

METHODS

This prospective cohort study included patients undergoing isolated coronary artery bypass grafting. Myeloperoxidase concentrations in blood and pericardial fluid were determined at baseline and 6, 12, and 18 hours after coronary artery bypass grafting. Myeloperoxidase activity in blood, pericardial fluid, and atrium were also evaluated in a canine coronary artery bypass grafting model. Electrophysiologic, histologic, and immunohistochemistry analyses were performed to explore underlying mechanisms.

RESULTS

Postoperative atrial fibrillation occurred in 45 of 137 patients (32.8%). Patients with postoperative atrial fibrillation had significantly higher serum and pericardial myeloperoxidase levels. Individual clinical and surgical factors had moderate predictive value (area under the curve, 0.760) for postoperative atrial fibrillation. Discrimination improved remarkably when myeloperoxidase was combined with other parameters (area under the curve, 0.901). Pericardial myeloperoxidase at 6 hours postoperatively was the strongest independent predictor of postoperative atrial fibrillation (odds ratio, 19.215). The rate of postoperative atrial fibrillation increased exponentially across pericardial myeloperoxidase grades. Compared with controls, coronary artery bypass grafting-treated dogs showed higher atrial fibrillation vulnerability and maintenance, shorter atrial effective refractory period, attenuated connexin 43 expression, and increased myocardial and pericardial myeloperoxidase activity. Connexin 43 expression and atrial effective refractory period were strongly negatively correlated with myocardial and pericardial myeloperoxidase activity.

CONCLUSIONS

Myeloperoxidase is linked to postoperative atrial fibrillation, and the ability to predict postoperative atrial fibrillation was remarkably improved by adding pericardial myeloperoxidase. Myeloperoxidase-related atrial structural and electrical remodeling is a physiologic substrate for this arrhythmia.

Machine Learning Models of Postoperative Atrial Fibrillation Prediction After Cardiac Surgery

OBJECTIVES

This study aimed to use machine learning algorithms to build an efficient forecasting model of atrial fibrillation after cardiac surgery, and to compare the predictive performance of machine learning to traditional logistic regression.

DESIGN

A retrospective study.

SETTING

Second Affiliated Hospital of Zhejiang University School of Medicine.

PARTICIPANTS

The study comprised 1,400 patients who underwent valve and/or coronary artery bypass grafting surgery with cardiopulmonary bypass from September 1, 2013 to December 31, 2018.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Two machine learning approaches (gradient-boosting decision tree and support-vector machine) and logistic regression were used to build predictive models. The performance was compared by the area under the curve (AUC). The clinical practicability was assessed using decision curve analysis. Postoperative atrial fibrillation occurred in 519 patients (37.1%). The AUCs of the support-vector machine, logistic regression, and gradient boosting decision tree were 0.777 (95% CI: 0.772-0.781), 0.767 (95% CI: 0.762-0.772), and 0.765 (95% CI: 0.761-0.770), respectively. As decision curve analysis manifested, these models had achieved appropriate net benefit.

CONCLUSION

In the authors' study, the support-vector machine model was the best predictor; it may be an effective tool for predicting atrial fibrillation after cardiac surgery.

A Retrospective Study to Evaluate the Association Between the Glasgow Prognostic Score and Atrial Fibrillation, Stroke, and Mortality at 30 Days and at 1 Year After Coronary Artery Bypass Graft Surgery

BACKGROUND The Glasgow prognostic score (GPS) consists of a combination of serum C-reactive protein and albumin levels as indicators of systematic inflammatory response and nutritional status, respectively. The present retrospective study aimed to evaluate the association between the GPS and atrial fibrillation, stroke, and mortality at 30 days and 1 year after coronary artery bypass graft (CABG) surgery. MATERIAL AND METHODS Patients with chronic coronary syndromes who underwent CABG surgery between 2012 and 2019 in a single center were included. Preoperative GPS was calculated. Then, patients were grouped according to postoperative atrial fibrillation (POAF) development. Further, groups were formed to evaluate the relationship between GPS and 30-day and 1-year cardiovascular mortality as well as stroke development. RESULTS Patients who developed POAF had higher GPS, higher European System for Cardiac Operative Risk Evaluation (EuroSCORE II) score, advanced age, lower angiotensin converting enzyme inhibitor/angiotensin receptor blocker (ACEI/ARB) use, lower left ventricular ejection fraction, and were more likely to be female and to have a history of carotid artery disease (P<0.05, for all). Additionally, GPS, EuroSCORE II, advanced age, and lower left ventricular ejection fraction were detected as independent risk factors for POAF development. When adverse outcomes were assessed, cardiovascular mortality at 30 days or 1 year, and stroke development at 1 year, were more frequent in patients with POAF. Moreover, POAF development was found to be an independent risk factor for adverse outcomes. Also, GPS was established as an independent risk factor both for 30-day and 1-year cardiovascular mortality (P<0.0001 and P=0.001, respectively). CONCLUSIONS GPS is an easy-to-calculate score that has reasonable diagnostic accuracy in determining the risk of POAF and stroke as well as 30-day and 1-year cardiovascular mortality.

Post-operative atrial fibrillation after cardiac surgery: Challenges throughout the patient journey

Atrial fibrillation (AF) is the most common complication of cardiac surgery, occurring in up to half of patients. Post-operative AF (POAF) refers to new-onset AF in a patient without a history of AF that occurs within the first 4 weeks after cardiac surgery. POAF is associated with short-term mortality and morbidity, but its long-term significance is unclear. This article reviews existing evidence and research challenges for the management of POAF in patients who have had cardiac surgery. Specific challenges are discussed in four phases of care. Pre-operatively, clinicians need to be able to identify high-risk patients, and initiate prophylaxis to prevent POAF. In hospital, when POAF is detected, clinicians need to manage symptoms, stabilize hemodynamics and prevent increases in length of stay. In the month after discharge, the focus is on minimizing symptoms and preventing readmission. Some patients require short term oral anticoagulation for stroke prevention. Over the long term (2-3  months after surgery and beyond), clinicians need to identify which patients with POAF have paroxysmal or persistent AF and can benefit from evidence-based therapies for AF, including long-term oral anticoagulation.

Predicting atrial fibrillation after cardiac surgery: a scoping review of associated factors and systematic review of existing prediction models

INTRODUCTION

Postoperative atrial fibrillation (POAF) is common after cardiac surgery and associated with increased hospital length of stay, patient morbidity and mortality. We aimed to identify factors associated with POAF and evaluate the accuracy of available POAF prediction models.

METHODS

We screened articles from Ovid MEDLINE® and PubMed Central® (PMC) and included studies that evaluated risk factors associated with POAF or studies that designed or validated POAF prediction models. We only included studies in cardiac surgical patients with sample size n ⩾ 50 and a POAF outcome group ⩾20. We summarised factors that were associated with POAF and assessed prediction model performance by reviewing reported calibration and discriminative ability.

RESULTS

We reviewed 232 studies. Of these, 142 fulfilled the inclusion criteria. Age was frequently found to be associated with POAF, while most other variables showed contradictory findings, or were assessed in few studies. Overall, 15 studies specifically developed and/or validated 12 prediction models. Of these, all showed poor discrimination or absent calibration in predicting POAF in externally validated cohorts.

CONCLUSIONS

Except for age, reporting of factors associated with POAF is inconsistent and often contradictory. Prediction models have low discrimination, missing calibration statistics, are at risk of bias and show limited clinical applicability. This suggests the need for studies that prospectively collect AF relevant data in large cohorts and then proceed to validate findings in external data sets.

Association of LDL to HDL ratio with new-onset atrial fibrillation after on-pump coronary artery bypass graft surgery

OBJECTIVE

This study aims to analyze the association between preoperative LDL/HDL ratio and new-onset atrial fibrillation (AF) after on-pump coronary artery bypass grafting (on-pump CABG), evaluate the clinic value of preoperative LDL/HDL ratio to identify postoperative rhythm.

METHODS

A retrospective study of consecutive patients (n = 2052) who underwent on-pump CABG at TEDA International Cardiovascular Hospital (Tianjin, China), from June 1, 2020, to December 30, 2021, was conducted. The association between preoperative LDL/HDL and new-onset POAF was analyzed by Lowess curve and univariate logistic regression. The receiver operating characteristic curve (ROC) and area under the curve (AUC) were used to evaluate the identification capacity of preoperative LDL/HDL level for new-onset POAF.

RESULTS

In studied populations, the incidence of new-onset POAF was about 29.24%. The lowess curve showed that the association between preoperative LDL/HDL ratio and POAF after on-pump CABG was similar to a linear relationship. With the increasement of preoperative LDL/HDL ratio, the incidence of POAF increased simultaneously. ROC analysis showed that preoperative LDL/HDL ratio could identify postoperative arrhythmia after on-pump CABG (AUC = 0.569,95% CI = 0.529-0.608, P = 0.006) among female patients, the best preoperative LDL/HDL ratio cutoff of 2.11, which was considered a predictive factor of incident POAF, showed a sensitivity of 83.60% (95% CI = 0.775-0.886) and a specificity of 30.02% (95% CI = 0.257-0.346).

CONCLUSION

Preoperative LDL/HDL ratio is associated with new-onset POAF, but there is a difference in different sex. Preoperative LDL/HDL level can help to identify postoperative rhythm in females.

Circulating exosome-derived miR-122-5p is a novel biomarker for prediction of postoperative atrial fibrillation

Postoperative atrial fibrillation (POAF) is a frequent complication associated with increased periprocedural mortality and morbidity after cardiac surgery. Our study aimed to identify the difference in exosomal miRNA and further explore its role in the diagnosis of POAF. First, the differentially expressed miRNAs (DEMs) were obtained by high-throughput RNA sequencing. Second, the DEMs target genes were put into gene ontology (GO) and KEGG pathway analysis. Third, real-time quantification PCR (RT-qPCR) was used to verify the DEMs. Finally, we revealed 23 DEMs in POAF patients. Furthermore, analysis of gene function revealed that DEMs may affect atrial structure through many signaling pathways. We also found that miR-122-5p was up-regulated in POAF patients, but there are no significant changes in miR-191-5p, miR-181a-5p, miR-155-5p and miR-151a-5p. Our study revealed that exosomal miRNAs exert enormous potential in evaluating the severity or prognostic of POAF.

A novel predictive model for new-onset atrial fibrillation in patients after isolated cardiac valve surgery

Background

Postoperative atrial fibrillation (POAF) is a severe complication after cardiac surgery and is associated with an increased risk of ischemic stroke and mortality. The main aim of this study was to identify the independent predictors associated with POAF after isolated valve operation and to develop a risk prediction model.

Methods

This retrospective observational study involved patients without previous AF who underwent isolated valve surgery from November 2018 to October 2021. Patients were stratified into two groups according to the development of new-onset POAF. Baseline characteristics and perioperative data were collected from the two groups of patients. Univariate and multivariate logistic regression analyses were applied to identify independent risk factors for the occurrence of POAF, and the results of the multivariate analysis were used to create a predictive nomogram.

Results

A total of 422 patients were included in the study, of which 163 (38.6%) developed POAF. The Multivariate logistic regression analysis indicated that cardiac function (odds ratio [OR] = 2.881, 95% confidence interval [CI] = 1.595–5.206; P &lt; 0.001), Left atrial diameter index (OR = 1.071, 95%CI = 1.028–1.117; P = 0.001), Operative time (OR = 1.532, 95%CI = 1.095–2.141; P = 0.013), Neutrophil count (OR = 1.042, 95%CI = 1.006–1.08; P = 0.021) and the magnitude of fever (OR = 3.414, 95%CI = 2.454–4.751; P &lt; 0.001) were independent predictors of POAF. The above Variables were incorporated, and a nomogram was successfully constructed with a C-index of 0.810. The area under the receiver operating characteristic curve was 0.817.

Conclusion

Cardiac function, left atrial diameter index, operative time, neutrophil count, and fever were independent predictors of POAF in patients with isolated valve surgery. Establishing a nomogram model based on the above predictors helps predict the risk of POAF and may have potential clinical utility in preventive interventions.

Nomogram predicts atrial fibrillation after coronary artery bypass grafting

Objective

Using the nomogram to intuitively predict atrial fibrillation after coronary artery bypass grafting. Identify high-risk patients with atrial fibrillation and provide preoperative protective therapy.

Methods

A total of 397 patients that underwent coronary artery bypass grafting were consecutively enrolled. Independent predictors of patients were analyzed by multivariate logistic regression. Two nomograms were constructed to predict postoperative atrial fibrillation.

Results

The incidence of postoperative atrial fibrillation in this study was 29% (115/397). Multivariate Logistic showed that Age, Operative Time > 4 h, Left Atrial Diameter > 40 mm, Mean Arterial Pressure, Body Mass Index > 23 kg/m², Insulins, and Statins were independently associated with atrial fibrillation after isolated coronary artery bypass grafting. The nomogram of postoperative atrial fibrillation in patients was constructed using total predictor variables (AUC = 0.727, 95% CI 0.673–0.781). The model was internally validated (AUC = 0.701) by K-fold Cross-validation resampling (K = 5, Times = 400). To make an early intervention, the intraoperative information of the patients was excluded. Only 6 variables before surgery were used to establish the brief nomogram to predict postoperative atrial fibrillation (AUC = 0.707, 95% CI 0.651–0.764). The brief model was internally validated (AUC = 0.683) by resampling with K-fold Cross-validation resampling.

Conclusions

These two nomograms could be used to predict patients at high risk for atrial fibrillation after isolated coronary artery bypass grafting.

The conundrum of the complex relationship between acute kidney injury and cardiac arrhythmias

Acute kidney injury (AKI) is defined by a rapid increase in serum creatinine levels, reduced urine output, or both. Death may occur in 16%-49% of patients admitted to an intensive care unit with severe AKI. Complex arrhythmias are a potentially serious complication in AKI patients with pre-existing or AKI-induced heart damage and myocardial dysfunction, fluid overload, and especially electrolyte and acid-base disorders representing the pathogenetic mechanisms of arrhythmogenesis. Cardiac arrhythmias, in turn, increase the risk of poor renal outcomes, including AKI. Arrhythmic risk in AKI patients receiving kidney replacement treatment may be reduced by modifying dialysis/replacement fluid composition. The most common arrhythmia observed in AKI patients is atrial fibrillation. Severe hyperkalemia, sometimes combined with hypocalcemia, causes severe bradyarrhythmias in this clinical setting. Although the likelihood of life-threatening ventricular arrhythmias is reportedly low, the combination of cardiac ischemia and specific electrolyte or acid-base abnormalities may increase this risk, particularly in AKI patients who require kidney replacement treatment. The purpose of this review is to summarize the available epidemiological, pathophysiological, and prognostic evidence aiming to clarify the complex relationships between AKI and cardiac arrhythmias.

Postoperative Atrial Fibrillation Reduced by Intraoperative and Postoperative Cell Saver System in Coronary Artery Bypass Graft Surgery

OBJECTIVE

Postoperative atrial fibrillation is commonly seen after cardiac surgery. One of the contributing factors is mediastinal shed blood and inflammation. Cell salvage techniques can reduce allogenic blood transfusion and reduce inflammation. The aim of this study was to investigate the reduction of postoperative atrial fibrillation by using the cell-salvage system.

METHODS

Patients who underwent isolated coronary artery bypass graft surgery (n = 498) were analyzed retrospectively in 2 groups. Postoperative atrial fibrillation group (n = 75) and non-postoperative atrial fibrillation group (n = 423). Preoperative and postoperative demographic and clini- cal data were compared between the 2 groups, respectively. Postoperative atrial fibrillation and possible contributing factors were analyzed with multinomial logistic regression analysis.

RESULTS

In the postoperative atrial fibrillation group, the patients' age and European System for Cardiac Operative Risk Evaluation (Euroscore) were higher than in the non-postoperative atrial fibrillation group (P = .001 and P = .003, respectively). Postoperative intensive care unit stay and hospital stay were longer in the postoperative atrial fibrillation group than in the non-postoperative atrial fibrillation group (P = .001 and P = .046, respectively). There were no statistical differences in mortality between groups. The incidence of postoperative atrial fibrillation decreased with the use of cell saver system and low Euroscore.

CONCLUSION

The use of a cell salvage device intraoperatively and during the early postoperative period can decrease the incidence of postop- erative atrial fibrillation group.

Development of a Risk Prediction Model for New Episodes of Atrial Fibrillation in Medical-Surgical Critically Ill Patients Using the AmsterdamUMCdb

The occurrence of atrial fibrillation (AF) represents clinical deterioration in acutely unwell patients and leads to increased morbidity and mortality. Prediction of the development of AF allows early intervention. Using the AmsterdamUMCdb, clinically relevant variables from patients admitted in sinus rhythm were extracted over the full duration of the ICU stay or until the first recorded AF episode occurred. Multiple logistic regression was performed to identify risk factors for AF. Input variables were automatically selected by a sequential forward search algorithm using cross-validation. We developed three different models: For the overall cohort, for ventilated patients and non-ventilated patients. 16,144 out of 23,106 admissions met the inclusion criteria. 2,374 (12.8%) patients had at least one AF episode during their ICU stay. Univariate analysis revealed that a higher percentage of AF patients were older than 70 years (60% versus 32%) and died in ICU (23.1% versus 7.1%) compared to non-AF patients. Multivariate analysis revealed age to be the dominant risk factor for developing AF with doubling of age leading to a 10-fold increased risk. Our logistic regression models showed excellent performance with AUC.ROC &gt; 0.82 and &gt; 0.91 in ventilated and non-ventilated cohorts, respectively. Increasing age was the dominant risk factor for the development of AF in both ventilated and non-ventilated critically ill patients. In non-ventilated patients, risk for development of AF was significantly higher than in ventilated patients. Further research is warranted to identify the role of ventilatory settings on risk for AF in critical illness and to optimise predictive models.

Right ventricular diastolic function predicts clinical atrial fibrillation after coronary artery bypass graft

Background

Patients with moderate-severe left ventricular systolic dysfunction undergoing coronary artery bypass graft (CABG) surgery are at high risk of mortality and morbidity. Our aim is to evaluate the right ventricular (RV) diastolic function in these patients, and monitor its effects on postoperation outcomes.

Materials and Methods

In a cohort study, patients with moderate-severe left ventricular systolic dysfunction (ejection fraction ≤35%) who were candidate for CABG were included. Baseline transthoracic echocardiography (TTE) was performed, and RV diastolic function measures were obtained. After CABG, the length of intubation, inotrope dependency, hospital stay in intensive care unit and ward, in-hospital and after discharge mortality, postoperative atrial fibrillation (POAF) were evaluated in all patients.

Results

Sixty-seven patients were prospectively included in the study. The mean ± standard deviation age of our patients was 61.4 ± 9.3. There was no difference between grades of RV diastolic function and postoperative outcomes. However, we found significant difference between grades of RV diastolic function and onset of in hospital, and total POAF (P-value = 0.017). Multivariate analysis demonstrated that preoperative tricuspidEt/E't (ratio of peak early-diastolic flow rate across the tricuspid valve orifice to peak early-diastolic velocity at the lateral tricuspid annulus), left atrial volume and "high risk" Euroscore II were independent predictors for POAF during hospitalization and total POAF in patients with moderate to severely impaired left ventricular systolic function (P-values were 0.04, 0.003 and 0.001, respectively).

Conclusion

We believe that patients with increased tricuspid Et/E't are high risk for POAF; therefore, any risk score for POAF should include a comprehensive TTE including evaluation of RV diastolic function before surgery.

The Effect of Low Preoperative Ejection Fraction on Mortality After Cardiac Surgery in Indonesia

Background

Among cardiac surgery patients, low preoperative left ventricular ejection fraction (LVEF) is common and has been associated with poor outcomes. The objective of this study was to assess the association between LVEF and postoperative mortality in patients undergoing open-heart surgery in several hospitals in Indonesia.

Methods

We conducted a multicenter study with the retrospective design using data from patients undergoing open-heart surgery in 4 institutions in Indonesia. Data regarding LVEF and other potential risk factors were extracted from medical records and compiled in one datasheet. Statistical analyses were performed to assess if low LVEF was associated with postoperative mortality and identify other potential risk factors.

Results

A total of 4789 patients underwent cardiac surgery in participating centers during the study period. Of these, 189 subjects (3.9%) had poor preoperative LVEF. Poor LVEF was associated with postoperative mortality (adjusted OR 2.761, 95% CI 1.763–4.323, p < 0.001). Based on types of surgery, LVEF had a significant association with mortality only in CABG patients, while there was no such association in valve surgery and inconclusive in congenital surgery patients. Other significant independent predictors of in-hospital mortality included age more than 65 years old, non-elective surgery, the complexity of procedures, history of cardiac surgery, organ failure, CARE score ≥ 3, NYHA class ≥ III, and poor right ventricular function.

Conclusion

Patients with low preoperative LVEF undergoing open-heart surgery had a higher risk of postoperative mortality. Cardiac surgery can be performed with acceptable mortality rates. Accurate selection of patients, risk/benefit evaluation, and planning of surgical and anesthesiological management are mandatory to improve outcomes.

Role of fibroblast growth factor-23 (FGF-23) in the prediction of postoperative atrial fibrillation after coronary artery bypass surgery

Introduction

Fibroblast growth factor-23 (FGF-23) is a bone-derived hormone which had shown a significant association with the occurrence of atrial fibrillation (AF) in patients with chronic kidney disease. We hypothesized that FGF-23 could be a very useful predictive biomarker for atrial remodeling and in turn for postoperative atrial fibrillation (POAF) after coronary artery bypass grafting (CABG). We also looked at the correlation of cardiac remodeling in right atrial biopsy and its correlation with POAF and with the FGF-23 level.

Methods

This study was a single-center cross-sectional observational study. All the patients who were planned for CABG with no prior history of AF were included in the study. All the patients were tested for preoperative serum FGF-23 level. During CABG, biopsy specimen of the right atrial appendage was sent for histopathology evaluation. All patients were monitored for POAF until discharge from the hospital.

Results

This study involved 60 patients who underwent elective CABG. Multivariate analysis revealed a significant association between preoperative FGF-23 levels with the occurrence of POAF (p < 0.001). The area under the curve of FGF-23 was 0.894 with a sensitivity of 92.3% and specificity of 87.23%. The cut-off value for serum FGF-23 levels was found to be 6.50 ng/ml. Analysis of biopsy specimens revealed that the presence of hypertrophic myocytes had a significant association with the occurrence of POAF/POAE and with FGF-23.

Conclusion

Preoperative FGF-23 levels can predict the incidence of POAF in post-CABG patients. Histopathologically, the presence of hypertrophic myocytes correlated well with the occurrence of POAF.

Predictors of Mortality Following Aortic Valve Replacement in Aortic Stenosis Patients

Background: Understanding of the risk factors for the development of adverse outcomes after aortic valve replacement is necessary to develop timely preventive measures and to improve the results of surgical treatment. Methods: We analyzed patients with aortic stenosis (n = 742) who underwent surgical treatment in the period 2014−2020. The average age was 63 (57;69) years—men 58%, women 42%. Results: The hospital mortality rate was 3% (22 patients). The following statistically significant threshold values (cut-off points) were obtained in the ROC analysis: aortic cross-clamp time > 93 min AUC (CI) 0.676 (0.640−0.710), p = 0.010; cardiopulmonary bypass time > 144 min AUC (CI) 0.809 (0.778−0.837), p < 0.0001, hemoglobin before op <120 g/L. AUC (CI) 0.762 (0.728−0.793), p < 0.0001, hematocrit before op <39% AUC (CI) 0.755 (0.721−0.786), p < 0.001, end-diastolic dimension index >2.39 AUC (CI) 0.647 (0.607−0.686), p = 0.014, end-systolic dimension index > 1.68 AUC (CI) 0.657 (0.617−0.695), p = 0.009. Statistically significant independent predictors of hospital mortality were identified: BMI > 30 kg/m2 (OR 2.84; CI 1.15−7.01), ischemic heart disease (OR 3.65; CI 1.01−13.2), diabetes (OR 3.88; CI 1.38−10.9), frequent ventricular ectopy before operation (OR 9.78; CI 1.91−50.2), mitral valve repair (OR 4.47; CI 1.76−11.3), tricuspid valve repair (OR 3.06; CI 1.09−8.58), 3 and more procedures (OR 4.44; CI 1.67−11.8). Conclusions: The hospital mortality rate was 3%. The main indicators associated with the risk of death were: diabetes, overweight (body mass index more than 30 kg/m2), frequent ventricular ectopy before surgery, hemoglobin level below 120 g/L, hematocrit level below 39%, longer cardiopulmonary bypass time and aortic cross-clamp time, additional mitral and tricuspid valve interventions.

Clinical factors associated with arrhythmia and short-term prognosis following mitral valve repair: a retrospective cohort study

BACKGROUND

Postoperative arrhythmia (POA) is one of the common and serious postoperative complications. This retrospective study was conducted to investigate the clinical factors associated with POA and its short-term prognosis following mitral valve repair.

METHODS

A total of 618 patients receiving mitral valve repair between January 2015 and November 2020 in our hospital were included in this retrospective study, including 318 males and 300 females and aged 53.9±9.3 years. The patients were grouped into arrhythmia and non-arrhythmia groups and investigated for risk factors associated with the prognosis of POA using multivariate logistic regression based on their clinical data.

RESULTS

POA was observed in 314 (50.8%) patients and atrial fibrillation (AF) was the most frequent (43.3%) type of POA. Compared with non-arrhythmia patients, arrhythmia patients had significantly longer time to use vasoactive drug use, longer intensive care unit (ICU) stay and longer hospital stay. In addition, the incidence of postoperative heart failure was significantly higher (P<0.05). Logistic regression analysis showed that preoperative arrhythmia [odds ratio (OR) =9.17; 95% confident interval (CI): 4.49-18.10], postoperative pain (OR =4.70; 95% CI: 1.55-6.12) and postoperative hypoxemia (OR =3.25; 95% CI: 1.04-6.28) were independently associated with POA.

CONCLUSIONS

This study demonstrates that the incidence of arrhythmia is relatively high after mitral valve repair and is associated with preoperative arrhythmia, postoperative pain and postoperative hypoxemia.

Predicting New-Onset Postoperative Atrial Fibrillation Following Isolated Coronary Artery Bypass Grafting: Development and Validation of a Novel Nomogram

Objective

To select variables associated with new-onset postoperative atrial fibrillation (POAF) following isolated coronary artery bypass grafting (CABG) and develop a nomogram for risk prediction in a Chinese population.

Methods

The study retrospectively enrolled 4854 consecutive patients undergoing isolated CABG from February 2018 to September 2019, they were divided into derivation cohort and validation cohort with a 3:1 ratio according to the order of operation date. In the derivation cohort, significant variables were selected by use of the multivariate logistic backward stepwise regression analysis and a nomogram model was built on the strength of the results. The model performance was assessed in terms of discrimination and calibration. Besides, we compared the discriminative ability for POAF of the nomogram with established prediction models (CHA2DS2-VASc and HATCH scores) in the two cohorts.

Results

POAF occurred in 1025 (28.2%) out of 3641 patients in the derivation cohort, and in 337 (27.8%) out of 1213 patients in the validation cohort. A nomogram, composed of eight prognostic variables, namely age, sex, heart rate, hypertension, left ventricular ejection fraction (LVEF) <50%, left atrial diameter (LAD) > 40mm, estimated glomerular filtration rate (eGFR) level, and on-pump surgery, was constructed from the derivation cohort. The nomogram had substantial discriminative ability in derivation and validation cohorts with the area under the receiver operating characteristic curves (AUCs) of 0.661 (95% confidence interval, 0.642–0.681) and 0.665 (95% confidence interval, 0.631–0.699), respectively, and showed well-fitted calibration curves. Compared with CHA2DS2-VASc, HATCH and POAF scores, respectively, the nomogram had superior discrimination performance.

Conclusion

We constructed a novel nomogram with improved accuracy for predicting the risk of POAF following isolated CABG, which might help clinicians predict individual probability of POAF and achieve effective prophylaxis.

Prediction of Postcoronary Artery Bypass Grafting Atrial Fibrillation: POAFRiskScore Tool

BACKGROUND

 Atrial fibrillation (AF), a condition that might occur after a heart bypass procedure, has caused differing estimates of its occurrence and risk. The current study analyses the possible risk factors of post-coronary artery bypass grafting (post-CABG) AF (postoperative AF [POAF]) and presents a software for preoperative POAF risk prediction.

METHODS

 This retrospective research was performed on 1,667 patients who underwent CABG surgery using the hospital database. The associations between the variables of the patients and AF risk factors after CABG were examined using multivariable logistic regression (LR) after preprocessing the relevant data. The tool was designed to predict POAF risk using Shiny, an R package, to develop a web-based software.

RESULTS

 The overall proportion of post-CABG AF was 12.2%. According to the results of univariate tests, in terms of age (p < 0.001), blood urea nitrogen (p = 0.005), platelet (p < 0.001), triglyceride (p = 0.0026), presence of chronic obstructive pulmonary disease (COPD; p = 0.01), and presence of preoperative carotid artery stenosis (PCAS; p < 0.001), there were statistically significant differences between the POAF and non-POAF groups. Multivariable LR analysis disclosed the independent risk factors associated with POAF: PCAS (odds ratio [OR] = 2.360; p = 0.028), COPD (OR = 2.243; p = 0.015), body mass index (OR = 1.090; p = 0.006), age (OR = 1.054, p < 0.001), and platelet (OR = 0.994, p < 0.001).

CONCLUSION

 The experimental findings from the current research demonstrate that the suggested tool (POAFRiskScore v.1.0) can help clinicians predict POAF risk development in the preoperative period after validated on large sample(s) that can represent the related population(s). Simultaneously, since the updated versions of the proposed tool will be released periodically based on the increases in data dimensions with continuously added new samples and related factors, more robust predictions may be obtained in the subsequent stages of the current study in statistical and clinical terms.

Atrial Fibrillation after Lung Cancer Surgery: Prediction, Prevention and Anticoagulation Management

Simple Summary

Atrial fibrillation that occurs after surgery raises further questions with respect to spontaneous atrial fibrillation, being an event unquestionably related to the surgical act itself and always quite self-limiting. The purpose of this review is to present the knowledge gained so far, including the most recent findings, regarding this peculiar form of arrhythmia. Its prognostic impact and the possibility of predicting and preventing it were the subject of our analysis, as well as the similarities and differences with spontaneous atrial fibrillation in relation to anticoagulation. Where possible, the search for evidence has focused on studies involving lung cancer patients undergoing thoracic surgery, highlighting any differences with cardiac surgery.

Abstract

Atrial fibrillation (AF) is a common complication of the early postoperative period of various types of surgery, including that for lung cancer. Although induced by the homeostatic alterations related to surgery, there is evidence that it is not a mere stand-alone transitory event, but it represents a relevant complication of surgery, bearing considerable prognostic consequences. Different methods have therefore been explored to predict the occurrence of postoperative atrial fibrillation (POAF) and prevent it. In particular, the age among clinical factors, and N-terminal prohormone of brain natriuretic peptide (NT-proBNP), as a marker, have proven to be good predictors, and the use of beta-blockers or amiodarone in primary prevention seems to reduce its incidence significantly. There is growing evidence that POAF significantly increases the risk of stroke and global mortality in the long term; therefore, it should be managed in the same way as spontaneous atrial fibrillation. In this review, we will present the strongest evidence found so far and the most recent findings regarding the management of POAF, with a special focus on patients undergoing thoracic surgery for lung cancer.

Strain and strain rate echocardiographic imaging predict occurrence of atrial fibrillation in post-coronary artery bypass grafting patients

BACKGROUND

Atrial fibrillation (AF) occurs very frequently after coronary artery bypass grafting (CABG); it occurs in about 20-edictors can be used for the dedicatio40% of patients. It is associated with several adverse events. This study aimed to extrapolate a predictor for postoperative atrial fibrillation (POAF) occurrence which is reproducible and simple to be a part of routine echocardiography screening before CABG. This study included 89 patients scheduled for isolated coronary artery bypass surgery. History, clinical examination, and complete 2D echocardiography with LA speckle tracking analysis were done preoperatively. Patients were then followed up post-surgery for incidence of AF till discharge from the hospital. The patients were divided into 2 groups according to POAF occurrence.

RESULTS

Patients who developed postoperative AF had older age (P = 0.0032) and longer hospital stay (P = 0.021) and higher stroke incidence but statistically non-significant (14.3% vs 3.3%). The POAF patients showed less peak atrial longitudinal strain (PALS) value than non-POAF patients. The left atrial strain rate values showed a significant difference with the lower left atrial systolic strain rate and less negative (higher) early diastolic strain rate and late diastolic strain rate. After multivariate logistic regression analysis, the independent predictors for POAF were PALS (OR 0.770, 95% CI 0.627-0.946), late LA diastolic strain rate (LASRa) (OR 3.476, 95% CI 1.207-12.186), and age (OR 1.181, 95% CI 1.011-1.379).

CONCLUSION

Preoperative LA global strain assessed by 2D speckle tracking analysis could be helpful as a predictor for AF post-CABG surgery, and identification of these patients may reduce its morbidity and mortality. The study suggested PALS value less than 29.8 to be a predictor for the occurrence of POAF.

Atrial Fibrillation after Cardiac Surgery-To Infinity and Beyond!

No Abstract

Predicting atrial fibrillation after cardiac surgery using a simplified risk index

BACKGROUND

Postoperative atrial fibrillation (POAF) is a common complication after cardiac surgery and can lead to increased risk of postoperative adverse events. However, atrial fibrillation and postoperative adverse events are preventable. In this study, a risk index was developed to predict atrial fibrillation after cardiac surgery.

METHODS

A prospective cohort study of 405 patients who had undergone adult cardiac surgery from 2015 September to 2016 August at Heart Institute of HCMC and Cho Ray Hospital were obtained. In order to predict POAF, a logistic regression model was developed, and a risk score was derived and validated by bootstrap.

RESULTS

In our study, 98 patients developed POAF (24.2%). The risk score included three significant risk factors (age ≥ 60, left atrial diameter > 41 mm, Coronary Artery Bypass Graft with concomitant mitral valve replacement or repair) that were consistent with other reports. Each of these risk factors was assigned one point. The total risk score ranges from 0 to 3 (AUC = 0.69, 95% CI: 0.63-0.75) with the best cutoff point at 1. According to this scoring system, the incidences of POAF in patients associated with each score of 0, 1, 2, and 3 were 8.6%, 30.1%, 40.8%, and 58.3% respectively. Bootstrapping with 5000 samples confirmed the final model provided was consistent with predictions.

CONCLUSIONS

We developed and validated a simple risk score based on clinical variables that can be obtained before surgery in order to accurately predict the risk of POAF in patients undergoing cardiac surgery.

Biochemical predictors of postoperative atrial fibrillation following cardiac surgery

Background

New-onset postoperative atrial fibrillation (POAF) is common after cardiac surgery. Early identification of its risk factors during the preoperative period would help in reducing the associated morbidity, mortality, and healthcare costs.

Aim of the study

This study aimed to identify the predictors of POAF following open cardiac surgery, with emphasis on biochemical parameters.

Methods

A total of 1191 patients with no preoperative atrial fibrillation (AF) and undergoing open cardiac surgery for any reason were included in this retrospective study. Data on clinical and biochemical parameters, the occurrence of new-onset AF, and its clinical course were retrieved from the hospital database.

Results

During the early postoperative period 330 patients (27.7%) developed atrial fibrillation, at median third postoperative day (range 1–6 days) and 217 (65.8%) responded to treatment. Multivariate analysis identified the following as the significant independent predictors of any POAF: EF < 60% (Odds ratio (OR), 2.6), valvular intervention (OR, 2.4), liver failure (OR, 2.4), diabetes (OR, 1.6), low hematocrit (OR, 2.1), low thrombocyte (OR, 5.6), low LDL (OR, 1.6), high direct bilirubin (OR, 2.0), low GFR (OR, 1.6), and high CRP (OR, 2.0). Following parameters emerged as significant independent predictors of persistent AF: EF < 60% (OR, 1.9), diabetes (OR, 2.1), COPD (OR, 1.8), previous cardiac surgery (OR, 3.1), valvular intervention (OR, 2.4), low hematocrit (OR, 1.9), low LDL (OR, 2.1), high HbA1c (OR, 2.0), and high CRP (OR, 2.7).

Conclusions

Certain parameters assessed during preoperative physical and laboratory examinations have the potential to be used as markers of POAF.

Predictive Accuracy of a Polygenic Risk Score for Postoperative Atrial Fibrillation After Cardiac Surgery

BACKGROUND

Postoperative atrial fibrillation (PoAF) remains a significant risk factor for increased morbidity and mortality after cardiac surgery. The ability to accurately identify patients at risk through clinical risk factors is limited. There is growing evidence that polygenic risk contributes significantly to PoAF and incorporating measures of genetic risk could enhance prediction.

METHODS

A retrospective cohort study of 1047 patients of White European ancestry who underwent either coronary artery bypass grafting or valve surgery at a tertiary academic center and were free from a history or persistent preoperative atrial fibrillation. The primary outcome was defined as PoAF based on postoperative ECG reports, medical record documentation, and changes in medication. The exposure was a polygenic risk score (PRS) comprising 2746 single-nucleotide polymorphisms previously associated with atrial fibrillation risk. The prediction of PoAF risk was assessed using measures of model discrimination, calibration, and net reclassification improvement.

RESULTS

A total of 259 patients (24.7%) developed PoAF. The PRS was significantly associated with a higher risk for PoAF (odds ratio, 1.63 per SD increase in PRS [95% CI, 1.41-1.90]). Addition of PRS to patient- and procedure-related predictors of PoAF significantly increased the C statistic from 0.742 to 0.782 (change in C statistic, 0.040 [95% CI, 0.021-0.060]) while maintaining good calibration. The addition of the PRS to patient- and procedure-related predictors of PoAF improved model fit (likelihood ratio test, P=2.8×10^-15) and significantly improved measures of reclassification (net reclassification improvement, 0.158 [95% CI, 0.066-0.274]).

CONCLUSIONS

The PRS for PoAF was associated with improved discrimination, calibration, and risk reclassification compared with conventional clinical predictors suggesting that a PoAF PRS may enhance risk prediction of PoAF in patients undergoing coronary artery bypass grafting or valve surgery.

Importance of left atrial mechanical function as a predictor of atrial fibrillation risk following cardiac surgery

Postoperative atrial fibrillation (POAF) after cardiac surgery is a major health problem that is associated with a significant financial burden and increased early morbidity and mortality. We investigated the accuracy of new echocardiographic derived indices to predict patients at higher risk of developing POAF. 84 consecutive patients (age 57.9 ± 6.9, 32% female) hospitalized for isolated CABG underwent comprehensive echocardiographic evaluation before surgery. Left atrial (LA) function was quantified through the assessment of phasic LA volumes to calculate LATEF. Speckle tracking echocardiography STE was used to measure LA reservoir strain, conduit strain and booster strain. Patients who developed POAF had increased LA volumes and impaired LA functions assessed by both the volumetric phasic changes and STE. By univariable analysis, all LA function parameters significantly predicted POAF. Multivariate regression analysis showed that age (P = 0.03, OR 1.134, 95% CI 1.012-1.271) and LATEF (P = 0.001, OR 0.814, 95% CI 0.725-0.914) were strong independent factors for POAF with LATEF showing the highest predictive accuracy. After multivariable adjustment to include LA strain indices to the base model, LA contractile strain LACtS (23.93 ± 4.19 vs 37.0 ± 3.35, p < 0.001) was the best discriminated for the highest predictive accuracy (OR 0.429, 95% CI 0.26-0.708). The ROC Curve was calculated for the greatest performance for prediction of POAF (AUC LACtS: 0.992; LATEF: 0.899). Adding new left atrial mechanics parameters is a more sensitive, independent tool that provides an incremental predictive value to discriminate patients at more risk for POAF.