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Effectiveness of amiodarone versus digitalis for heart rate control in critically ill patients with new-onset atrial fibrillation.

ABSTRACT: New-onset of atrial fibrillation (NOAF) in critically ill patients is the most common acute cardiac dysrhythmia, but evidence-based data regarding treatment strategies are scarce. In this retrospective monocentric study, we compared effectiveness of amiodarone versus digitalis for heart rate control in critically ill patients with new-onset of atrial fibrillation. We identified a total of 209 patients for the main analysis. Amiodarone as compared to digitalis was associated with a clinically relevant faster time to heart rate control < 110 bpm (2 h (IQR: 1 h to 6 h) versus 4 h (2 h to 12 h); p = 0.003) and longer durations of sinus rhythm during the first 24 h of treatment (6 h (IQR: 6 h to 22 h) versus 0 h (IQR: 0 h to 16 h); p < 0.001). However, more bradycardic episodes occurred in association with amiodarone than with digitalis (7.7% versus 3.4%; p = 0.019). Use of amiodarone was associated with an increase of noradrenalin infusion rate compared to digitalis (23.9% versus 12.0%; p = 0.019). Within the tertile of patients with the highest CRP measurements, amiodarone treated patients presented with a higher decrease in heart rate than digoxin treated patients. Clinical trials comparing different NOAF treatment strategies are much needed and should report on concomitant sympathetic activity and inflammatory status.

SUBMITTER: Gillmann HJ

PROVIDER: S-EPMC8854600 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Effectiveness of amiodarone versus digitalis for heart rate control in critically ill patients with new-onset atrial fibrillation.

Gillmann Hans-Joerg HJ Busche Philipp P Leffler Andreas A Stueber Thomas T

Scientific reports 20220217 1

New-onset of atrial fibrillation (NOAF) in critically ill patients is the most common acute cardiac dysrhythmia, but evidence-based data regarding treatment strategies are scarce. In this retrospective monocentric study, we compared effectiveness of amiodarone versus digitalis for heart rate control in critically ill patients with new-onset of atrial fibrillation. We identified a total of 209 patients for the main analysis. Amiodarone as compared to digitalis was associated with a clinically rel ...[more]

PMID: 35177703

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Project description:Objective: To describe the use of amiodarone in critically ill, septic shock patients experiencing new-onset atrial fibrillation (NOAF) during the acute resuscitative phase of septic shock. Methods: Single-center, retrospective review of adult medical or surgical intensive care unit (ICU) patients with septic shock and NOAF. All patients received amiodarone for NOAF during the acute resuscitative phase of septic shock. The cohort was analyzed via descriptive statistics. Associations between amiodarone exposure and clinical outcomes were analyzed via a Cox proportional-hazards model. An a priori defined sensitivity analysis of hospital survivors was also employed. Main Results: A total of 239 patients were included in the analysis. Patients had a median baseline Charlson Comorbidity Index of 4 (interquartile range [IQR]: 2-6) and were acutely ill with a median Acute Physiology and Chronic Health Evaluation II (APACHE II) score of 18 (IQR: 13-22) and an incidence of mechanical ventilation of 85%. In-hospital mortality was 56% with median ICU and hospital length of stay (LOS) of 9 and 15 days, respectively. Included patients received a median of 2760 (IQR: 1110-6415) mg of intravenous (IV) amiodarone during their ICU stay. Receipt of more than or equal to 2700 mg of amiodarone was identified as an independent factor associated with longer ICU LOS (hazard ratio [HR]: 1.30; 95% confidence interval [CI], 1.10-2.28). In a sensitivity analysis of hospital survivors (n = 105), receipt of more than or equal to 2700 mg of amiodarone remained independently associated with longer ICU LOS (HR: 1.64; 95% CI, 1.05-2.58). Conclusions: Exposure to more than or equal to 2700 mg of amiodarone in the setting of NOAF and septic shock is positively correlated with longer ICU LOS. Identifying opportunities to limit amiodarone exposure and address/resolve potential precipitating causes of NOAF in this clinical scenario may reduce the morbidity associated with septic shock.

Project description:ObjectivesNew-onset atrial fibrillation during critical illness is an independent risk factor for mortality. The ability to identify patients at high risk for new-onset atrial fibrillation is limited. We hypothesized that genetic susceptibility contributes to risk of new-onset atrial fibrillation in the ICU.DesignRetrospective sub-study of a prospective observational cohort study.SettingMedical and general surgical ICUs in a tertiary academic medical center.PatientsOne-thousand three-hundred sixty-nine critically ill patients admitted to the ICU for at least 2 days with no known history of atrial fibrillation who had DNA available for genotyping.InterventionsNone.Measurements and main resultsWe genotyped 21 single-nucleotide polymorphisms associated with atrial fibrillation in ambulatory studies using a Sequenom platform (San Diego, CA). We collected demographics, medical history, and development of new-onset atrial fibrillation during the first four days of ICU admission. New-onset atrial fibrillation occurred in 98 patients (7.2%) and was associated with age, male sex, coronary artery disease, and vasopressor use. Single-nucleotide polymorphisms associated with new-onset atrial fibrillation were rs3853445 (near PITX2, p = 0.0002), rs6838973 (near PITX2, p = 0.01), and rs12415501 (in NEURL, p = 0.03) on univariate testing. When controlling for clinical factors, rs3853445 (odds ratio, 0.47; 95% CI, 0.30-0.73; p = 0.001) and rs12415501 (odds ratio, 1.72; 95% CI, 1.27-2.59; p = 0.01) remained significantly associated with new-onset atrial fibrillation. The addition of genetic variables to clinical factors improved new-onset atrial fibrillation discrimination in a multivariable logistic regression model (C-statistic 0.82 vs 0.78; p = 0.0009).ConclusionsWe identified several single-nucleotide polymorphisms associated with new-onset atrial fibrillation in a large cohort of critically ill ICU patients, suggesting there is genetic susceptibility underlying this common clinical condition. This finding may provide new targets for future mechanistic studies and additional insight into the application of genomic information to identify patients at elevated risk for a common and important condition in the ICU.

Project description:Sepsis is defined by life-threatening organ dysfunction during infection and is the leading cause of death in hospitals. During sepsis, there is a high risk that new onset of atrial fibrillation (AF) can occur, which is associated with significant morbidity and mortality. Consequently, early prediction of AF during sepsis would allow testing of interventions in the intensive care unit (ICU) to prevent AF and its severe complications. In this paper, we present a novel automated AF prediction algorithm for critically ill sepsis patients using electrocardiogram (ECG) signals. From the heart rate signal collected from 5-min ECG, feature extraction is performed using the traditional time, frequency, and nonlinear domain methods. Moreover, variable frequency complex demodulation and tunable Q-factor wavelet-transform-based time-frequency methods are applied to extract novel features from the heart rate signal. Using a selected feature subset, several machine learning classifiers, including support vector machine (SVM) and random forest (RF), were trained using only the 2001 Computers in Cardiology data set. For testing the proposed method, 50 critically ill ICU subjects from the Medical Information Mart for Intensive Care (MIMIC) III database were used in this study. Using distinct and independent testing data from MIMIC III, the SVM achieved 80% sensitivity, 100% specificity, 90% accuracy, 100% positive predictive value, and 83.33% negative predictive value for predicting AF immediately prior to the onset of AF, while the RF achieved 88% AF prediction accuracy. When we analyzed how much in advance we can predict AF events in critically ill sepsis patients, the algorithm achieved 80% accuracy for predicting AF events 10 min early. Our algorithm outperformed a state-of-the-art method for predicting AF in ICU patients, further demonstrating the efficacy of our proposed method. The annotations of patients' AF transition information will be made publicly available for other investigators. Our algorithm to predict AF onset is applicable for any ECG modality including patch electrodes and wearables, including Holter, loop recorder, and implantable devices.

Project description:BackgroundNew-onset atrial fibrillation (AF) is the most common arrhythmia in critically ill patients. Although evidence base and expert consensus opinion for management have been summarised in several international guidelines, no specific considerations for critically ill patients have been included. We aimed to establish current practice of management of critically ill patients with new-onset AF.MethodsWe designed a short user-friendly online questionnaire. All members of the Intensive Care Society were invited via email containing a link to the questionnaire, which comprised 21 questions. The online survey was conducted between November 2016 and December 2016.ResultsThe response rate was 397/3152 (12.6%). The majority of respondents (81.1%) worked in mixed Intensive Care Units and were consultants (71.8%). Most respondents (39.5%) would start intervention on patients with fast new-onset AF and stable blood pressure at a heart rate between 120 and 139 beats/min. However, 34.8% of participants would treat all patients who developed new-onset fast AF. Amiodarone and beta-blockers (80.9% and 11.6% of answers) were the most commonly used anti-arrhythmics. A total of 63.8% of respondents do not regularly anti-coagulate critically ill patients with new-onset fast AF, while 30.8% anti-coagulate within 72 hours. A total of 68.0% of survey respondents do not routinely use stroke risk scores in critically ill patients with new-onset AF. A total of 85.4% of participants would consider taking part in a clinical trial investigating treatment of new-onset fast AF in the critically ill.DiscussionOur results suggest a considerable disparity between contemporary practice of management of new-onset AF in critical illness and treatment recommendations for the general patient population suffering from AF, particularly with regard to anti-arrhythmics and anti-coagulation used. Amongst intensivists, there is a substantial interest in research for management of new-onset AF in critically ill patients.

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Effectiveness of amiodarone versus digitalis for heart rate control in critically ill patients with new-onset atrial fibrillation.

Publications

Effectiveness of amiodarone versus digitalis for heart rate control in critically ill patients with new-onset atrial fibrillation.

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