Dataset Information

Development and Validation of a Novel Score for Predicting Paroxysmal Atrial Fibrillation in Acute Ischemic Stroke.

ABSTRACT: Atrial fibrillation (AF)-whether paroxysmal or sustained-increases the risk of stroke. We developed and validated a risk score for identifying patients at risk of paroxysmal atrial fibrillation (pAF) after acute ischemic stroke (AIS). A total of 6033 patients with AIS who received 24 h Holter monitoring were identified in the Chang Gung Research Database. Among the identified patients, 5290 with pAF and without AF were included in the multivariable logistic regression analysis to develop the pAF prediction model. The ABCD-SD score (Age, Systolic Blood pressure, Coronary artery disease, Dyslipidemia, and Standard Deviation of heart rate) comprises age (+2 points for every 10 years), systolic blood pressure (-1 point for every 20 mmHg), coronary artery disease (+2 points), dyslipidemia (-2 points), and standard deviation of heart rate (+2 points for every 3 beats per minute). Overall, 5.2% (274/5290) of patients had pAF. The pAF risk ranged from 0.8% (ABCD-SD score ≤ 7) to 18.3% (ABCD-SD score ≥ 15). The model achieved an area under the receiver operating characteristic curve (AUROCC) of 0.767 in the model development group. The ABCD-SD score could aid clinicians in identifying patients with AIS at risk of pAF for advanced cardiac monitoring.

SUBMITTER: Lee JD

PROVIDER: S-EPMC9223581 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Development and Validation of a Novel Score for Predicting Paroxysmal Atrial Fibrillation in Acute Ischemic Stroke.

Lee Jiann-Der JD Kuo Ya-Wen YW Lee Chuan-Pin CP Huang Yen-Chu YC Lee Meng M Lee Tsong-Hai TH

International journal of environmental research and public health 20220614 12

Atrial fibrillation (AF)-whether paroxysmal or sustained-increases the risk of stroke. We developed and validated a risk score for identifying patients at risk of paroxysmal atrial fibrillation (pAF) after acute ischemic stroke (AIS). A total of 6033 patients with AIS who received 24 h Holter monitoring were identified in the Chang Gung Research Database. Among the identified patients, 5290 with pAF and without AF were included in the multivariable logistic regression analysis to develop the pAF ...[more]

PMID: 35742524

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Project description:BackgroundAtrial fibrillation detected after stroke (AFDAS) is associated with an increased risk of ischemic stroke (IS) recurrence and death. Early diagnosis can help identify strategies for secondary prevention and improve prognosis. However, there are no validated predictive tools to assess the population at risk for AFDAS. Therefore, this study aimed to develop and validate a predictive model for assessing the incidence of AFDAS after acute ischemic stroke (AIS).MethodsThis study was a multicenter retrospective study. We collected clinical data from 5332 patients with AIS at two hospitals between 2014.01 and 2021.12 and divided the development and validation of clinical prediction models into a training cohort (n = 3173) and a validation cohort (n = 2159). Characteristic variables were selected from the training cohort using the least absolute shrinkage and selection operator (LASSO) algorithm and multivariable logistic regression analysis. A nomogram model was developed, and its performance was evaluated regarding calibration, discrimination, and clinical utility.ResultsWe found the best subset of risk factors based on clinical characteristics and laboratory variables, including age, congestive heart failure (CHF), previous AIS/transient ischemia attack (TIA), national institutes of health stroke scale (NIHSS) score, C-reactive protein (CRP), and B-type natriuretic peptide (BNP). A predictive model was developed. The model showed good calibration and discrimination, with calibration values of Hosmer-Lemeshow χ2 = 4.813, P = 0.732 and Hosmer-Lemeshow χ2 = 4.248, P = 0.834 in the training and validation cohorts, respectively. The area under the ROC curve (AUC) was 0.815, 95% CI (0.777-0.853) and 0.808, 95% CI (0.770-0.847). The inclusion of neuroimaging variables significantly improved the performance of the integrated model in both the training cohort (AUC. 0.846 (0.811-0.882) vs. 0.815 (0.777-0.853), P = 0.001) and the validation cohort (AUC: 0.841 (0.804-0.877) vs. 0.808 (0.770-0.847), P = 0.001). The decision curves showed that the integrated model added more net benefit in predicting the incidence of AFDAS.ConclusionPredictive models based on clinical characteristics, laboratory variables, and neuroimaging variables showed good calibration and high net clinical benefit, informing clinical decision-making in diagnosing and treating patients with AFDAS.

Project description:BackgroundThere is currently no validated risk prediction model for recurrent events among patients with acute ischemic stroke (AIS) and atrial fibrillation (AF). Considering that the application of conventional risk scores has contextual limitations, new strategies are needed to develop such a model. Here, we set out to develop and validate a comprehensive risk prediction model for stroke recurrence in AIS patients with AF.MethodsAIS patients with AF were collected from multicenter registries in South Korea and Japan. A developmental dataset was constructed with 5648 registered cases from both countries for the period 2011‒2014. An external validation dataset was also created, consisting of Korean AIS subjects with AF registered between 2015 and 2018. Event outcomes were collected during 1 year after the index stroke. A multivariable prediction model was developed using the Fine-Gray subdistribution hazard model with non-stroke mortality as a competing risk. The model incorporated 21 clinical variables and was further validated, calibrated, and revised using the external validation dataset.ResultsThe developmental dataset consisted of 4483 Korean and 1165 Japanese patients (mean age, 74.3 ± 10.2 years; male 53%); 338 patients (6%) had recurrent stroke and 903 (16%) died. The clinical profiles of the external validation set (n = 3668) were comparable to those of the developmental dataset. The c-statistics of the final model was 0.68 (95% confidence interval, 0.66 ‒0.71). The developed prediction model did not show better discriminative ability for predicting stroke recurrence than the conventional risk prediction tools (CHADS2, CHA2DS2-VASc, and ATRIA).ConclusionsNeither conventional risk stratification tools nor our newly developed comprehensive prediction model using available clinical factors seemed to be suitable for identifying patients at high risk of recurrent ischemic stroke among AIS patients with AF in this modern direct oral anticoagulant era. Detailed individual information, including imaging, may be warranted to build a more robust and precise risk prediction model for stroke survivors with AF.

Project description:BackgroundDetection of atrial fibrillation after ischemic stroke is challenging due to its paroxysmal nature. We aimed to assess predictors of paroxysmal atrial fibrillation using non-invasive surface ECG and transthoracic echocardiography to select candidates for atrial fibrillation screening.MethodsIschemic stroke patients without documented atrial fibrillation (n = 110, 67 ± 10 years, 40 female) and a control group of age- and gender-matched patients with history of paroxysmal atrial fibrillation prior to stroke (n = 55, 67 ± 10 years, 19 female) comprised the study sample. Using non-invasive ECG monitoring for three weeks, short episodes of paroxysmal atrial fibrillation were detected in 24 of 110 patients (22 %). The standard 12-lead ECG with sinus rhythm at stroke onset was digitally processed and analyzed. Transthoracic echocardiography data were reviewed for these patients.ResultsAtrial fibrillation history was independently associated with P terminal force in lead V 1 > 40 mm*ms (OR 4.04 95 % CI 1.34-12.14, p = 0.013) and left atrial volume index (OR 1.08 95 % CI 1.03-1.13, p = 0.002; for LAVI > 40 mL/m2 OR 6.40 95 % CL 1.47-27.91, p = 0.013). Among patients without atrial fibrillation history, no ECG characteristics were predictive of atrial fibrillation detected after stroke. Left atrial volume index remained an independent predictor of atrial fibrillation detected after stroke (OR 1.09 95 % CI 1.02-1.16, p = 0.017). A cutoff of <40 mL/m2 had an 84 % negative predictive value for ruling out atrial fibrillation on ambulatory monitoring with a sensitivity of 50 % and a specificity of 86 %.ConclusionIn a post hoc analysis, left atrial dilatation assessed by left atrial volume index independently predicted atrial fibrillation after stroke in patients without prior atrial fibrillation history, while the other clinical or ECG markers were not predictive of atrial fibrillation detected early after ischemic stroke.Trial registrationThis study is a post hoc analysis from the prospective case-control study registered in December 2011, ClinicalTrials.gov ID: NCT01325545 .

Project description:AimsIt is unclear whether early cardiac rhythm control is beneficial in patients with acute ischemic stroke and paroxysmal atrial fibrillation (PAF). We sought to investigate whether PAF self-termination and in-hospital sinus rhythm (SR) restoration is associated with improved outcome in ischemic stroke patients with PAF, compared to those with sustained atrial fibrillation (AF).MethodsConsecutive patients with first-ever acute stroke and confirmed PAF during hospitalization were followed for up to 10 years after the index stroke or until death. We investigated the association of in-hospital self-terminated PAF and PAF conversion to SR compared to sustained AF with 10-year all-cause mortality, stroke recurrence, and major adverse cardiovascular events (MACE). Cox regression analysis was performed to identify independent predictors of each outcome.ResultsAmong 297 ischemic stroke patients with in-hospital PAF detection, PAF was self-terminated in 87 (29.3%) patients, while 143 (48.1%) patients received antiarrhythmic medication in order to achieve PAF conversion to SR. During a median (Interquartile range, IQR) period of 28 (4-68) months, among patients with self-terminated PAF there were 13.5 deaths, 3.6 stroke recurrences, and 5.3 MACE per 100 patient-year while in patients who underwent medical PAF conversion there were 11.7 deaths, 4.6 stroke recurrences, and 5.8 MACE per 100 patient-year. Patients with sustained AF experienced 23.8 deaths, 8.7 stroke recurrences, and 13.9 MACE per 100 patient-years. In multivariable analysis, compared to patients with sustained AF, PAF self-termination was associated with significantly lower 10 years-risk of death (adjusted hazards ratio (adjHR): HR: 0.63, 95% Confidence interval: 0.40-0.96), stroke recurrence (adjHR: HR: 0.41, 95% CI: 0.19-0.91), and MACE (adjHR: 0.43, 95% CI: 0.23-0.81), while PAF medical conversion to SR was associated with lower 10 years-risk of death (adjHR: 0.65, 95% CI: 0.44-0.97) and MACE (adjHR: 0.56, 95% CI: 0.33-0.95).DiscussionThis study showed that in-hospital PAF self-termination was associated with lower risk of 10-year mortality, stroke recurrence, and MACE, potentially attributed to the lower burden of AF, whereas in-hospital PAF conversion to SR was associated with lower risk of 10-year mortality and MACE.ConclusionEarly restoration of sinus rhythm is associated with improved survival and MACE in patients with acute ischemic stroke and PAF.

Project description:Importance:Atrial fibrillation is a potent risk factor for stroke, but whether the burden of atrial fibrillation in patients with paroxysmal atrial fibrillation independently influences the risk of thromboembolism remains controversial. Objective:To determine if the burden of atrial fibrillation characterized using noninvasive, continuous ambulatory monitoring is associated with the risk of ischemic stroke or arterial thromboembolism in adults with paroxysmal atrial fibrillation. Design, Setting, and Participants:This retrospective cohort study conducted from October 2011 and October 2016 at 2 large integrated health care delivery systems used an extended continuous cardiac monitoring system to identify adults who were found to have paroxysmal atrial fibrillation on 14-day continuous ambulatory electrocardiographic monitoring. Exposures:The burden of atrial fibrillation was defined as the percentage of analyzable wear time in atrial fibrillation or flutter during the up to 14-day monitoring period. Main Outcomes and Measures:Ischemic stroke and other arterial thromboembolic events occurring while patients were not taking anticoagulation were identified through November 2016 using electronic medical records and were validated by manual review. We evaluated the association of the burden of atrial fibrillation with thromboembolism while not taking anticoagulation after adjusting for the Anticoagulation and Risk Factors in Atrial Fibrillation (ATRIA) or CHA2DS2-VASc stroke risk scores. Results:Among 1965 adults with paroxysmal atrial fibrillation, the mean (SD) age was 69 (11.8) years, 880 (45%) were women, 496 (25%) were persons of color, the median ATRIA stroke risk score was 4 (interquartile range [IQR], 2-7), and the median CHA2DS2-VASc score was 3 (IQR, 1-4). The median burden of atrial fibrillation was 4.4% (IQR ,1.1%-17.23%). Patients with a higher burden of atrial fibrillation were less likely to be women or of Hispanic ethnicity, but had more prior cardioversion attempts compared with those who had a lower burden. After adjusting for either ATRIA or CHA2DS2-VASc stroke risk scores, the highest tertile of atrial fibrillation burden (≥11.4%) was associated with a more than 3-fold higher adjusted rate of thromboembolism while not taking anticoagulants (adjusted hazard ratios, 3.13 [95% CI, 1.50-6.56] and 3.16 [95% CI, 1.51-6.62], respectively) compared with the combined lower 2 tertiles of atrial fibrillation burden. Results were consistent across demographic and clinical subgroups. Conclusions and Relevance:A greater burden of atrial fibrillation is associated with a higher risk of ischemic stroke independent of known stroke risk factors in adults with paroxysmal atrial fibrillation.

Dataset Information

Development and Validation of a Novel Score for Predicting Paroxysmal Atrial Fibrillation in Acute Ischemic Stroke.

Publications

Development and Validation of a Novel Score for Predicting Paroxysmal Atrial Fibrillation in Acute Ischemic Stroke.

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