Preoperative Plasma Aldosterone Levels and Postoperative Atrial Fibrillation Occurrence Following Cardiac Surgery: A Review of Literature and Design of the ALDO-POAF Study (ALDOsterone for Prediction of Post-Operative Atrial Fibrillation)

Chequel, Mathieu; Ollitrault, Pierre; Saloux, Éric; Parienti, Jean‐Jacques; Fischer, Marc-Olivier; Desgué, Julien; Allouche, Stéphane; Milliez, Paul; Alexandre, Jonas

doi:10.2174/1574884711666160714162128

Cited by 14 publications

(4 citation statements)

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“…The medical community has extensively discussed the importance of predicting and rapidly detecting NOAF. Numerous alternative strategies have been proposed for NOAF prediction, including assessing DNA methylation levels [ 27 ], measuring plasma aldosterone concentrations [ 28 ], and exploring immune-associated biomarkers [ 29 ]. While these methods indicate potential for NOAF prediction, further investigations through prospective clinical trials are essential.…”

Section: Discussionmentioning

confidence: 99%

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

Glaser,

Marino,

Stubnya

et al. 2024

J Anesth

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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.

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Section: Discussionmentioning

confidence: 99%

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

Glaser,

Marino,

Stubnya

et al. 2024

J Anesth

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show abstract

“…In recent literature, PR-interval and QRS duration were found as useful for predicting POAF 16. According to the ALDO-POAF study, preoperative plasma aldosterone and galectin-3 levels could be helpful for prevention of POAF 17. Also, Gungor et al demonstrated that progression of AF after CABG surgery can be predicted by preoperative poor coronary circulation and POAF may be encountered more frequent in patients with increased postoperative resistin level 18 19.…”

Section: Discussionmentioning

confidence: 99%

A New Predictor of Atrial Fibrillation after Coronary Artery Bypass Graft Surgery: Hatch Score

Selvi

Güngör

Zencir

et al. 2018

Journal of Investigative Medicine

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The aim of this study was to investigate the association between HATCH score and atrial fibrillation (AF) after coronary artery bypass graft (CABG) surgery. 369 patients (103 patients with AF and 266 patients without AF) undergoing isolated CABG surgery were analyzed. Complete medical records were retrospectively collected to investigate HATCH score. The median age of patients with AF was significantly higher than the median age of non-AF group (60.8±10.0 years vs 67.8±9.5 years, P<0.001). HATCH score was significantly higher in patients who developed AF after CABG surgery than the non-AF group (P=0.017). Multivariate logistic regression analysis showed that HATCH score (OR 1.334; 95% CI 1.022 to 1.741, P=0.034) was an independent predictor of AF after CABG surgery. Receiver operating characteristic curve analysis showed that the cut-off point of HATCH score related to predict AF was >1 (two or more), with a sensitivity of 42% and specificity of 70%. Patients with elevated preoperative HATCH score may have higher risk for AF after CABG surgery.

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“…Previous studies have shown that demographic factors [ 3 ], comorbidity and perioperative medication [ 26 – 28 ], cardiac assessment [ 29 ], and oncological characteristics [ 17 ] were associated with the incidence of POAF. Therefore, in the multivariable analysis of POAF, covariates included age (< 60 and ≥ 60 years), sex, body mass index (BMI < 25 kg/m 2 and ≥ 25 kg/m 2 ), cancer stage (0, I, and II), diabetes mellitus (DM), hypertension (HTN), type of incision (Ivor Lewis, McKeown, and transhiatal), preoperative heart rate (HR) (by quartiles), preoperative left ventricular ejection fraction (LVEF) (by quartiles), β-blocker use, diuretics use, and neoadjuvant therapy.…”

Section: Methodsmentioning

confidence: 99%

The role of surgery type in postoperative atrial fibrillation and in-hospital mortality in esophageal cancer patients with preserved left ventricular ejection fraction

et al. 2020

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Background Postoperative atrial fibrillation (POAF) is one of the most common complications of esophagectomy, which may extend the inpatient hospital stay. Minimally invasive esophagectomy (MIE) has been increasingly used in clinical practice; however, its POAF risk and short-term mortality remain unclear. This study aimed to examine the POAF risk and in-hospital mortality rate between patients receiving MIE and open esophagectomy (OE). Methods Esophageal cancer patients who underwent MIE or OE from a retrospective cohort study were evaluated. A multivariate logistic regression model was built to assess the associations between esophagectomy (MIE vs. OE) and various outcomes (POAF, in-hospital mortality). Covariates included age, sex, body mass index, neoadjuvant therapy, tumor stage, surgery incision type, comorbidities, cardia conditions, peri-operative medication, and complications. Results Of the 484 patients with esophageal cancer, 63 received MIE. A total of 53 patients developed POAF. Compared to patients receiving OE, MIE patients had 81% reduced odds of POAF (adjusted odds ratio [aOR] 0.185, 95% CI 0.039–0.887, P = 0.035). No statistically significant association was found for in-hospital mortality (aOR 0.709, 95% CI 0.114–4.409, P = 0.712). Conclusions MIE is associated with a lower risk of POAF, compared to traditional surgery. No significant short-term survival benefit was found for MIE.

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Preoperative Plasma Aldosterone Levels and Postoperative Atrial Fibrillation Occurrence Following Cardiac Surgery: A Review of Literature and Design of the ALDO-POAF Study (ALDOsterone for Prediction of Post-Operative Atrial Fibrillation)

Cited by 14 publications

References 0 publications

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

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

A New Predictor of Atrial Fibrillation after Coronary Artery Bypass Graft Surgery: Hatch Score

The role of surgery type in postoperative atrial fibrillation and in-hospital mortality in esophageal cancer patients with preserved left ventricular ejection fraction

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