Atrial fibrillation and paroxysmal atrial fibrillation detection in patients with acute ischemic stroke

A Simplified Risk Score to Predict In-Hospital Newly-Diagnosed Atrial Fibrillation in Acute Ischemic Stroke Patients

Purpose

Atrial fibrillation (AF) is a significant cause of stroke, and newly diagnosed AF (NDAF) is typically detected in the early period of stroke onset. We aimed to identify the factors associated with in-hospital NDAF in acute ischemic stroke patients and developed a simplified clinical prediction model.

Methods

Patients with cryptogenic stroke aged 18 years or older who were admitted between January 2017 and December 2021 were recruited. NDAF was determined by inpatient cardiac telemetry. Univariable and multivariable regression analyses were used to evaluate the factors associated with in-hospital NDAF. The predictive model was developed using regression coefficients.

Results

The study enrolled 244 eligible participants, of which 52 NDAFs were documented (21.31%), and the median time to detection was two days (1-3.5). After multivariable regression analysis, parameters significantly associated with in-hospital NDAF were elderly (>75 years) (adjusted Odds ratio, 2.99; 95% confident interval, 1.51-5.91; P = 0.002), female sex (2.08; 1.04-4.14; P = 0.04), higher admission national institute of health stroke scale (1.04; 1.00-1.09; P = 0.05), and presence of hyperdense middle cerebral artery sign (2.33; 1.13-4.79; P = 0.02). The area under the receiver operating characteristic curve resulted in 0.74 (95% CI 0.65-0.80), and the cut-point of 2 showed 87% sensitivity and 42% specificity.

Conclusion

The validated and simplified risk scores for predicting in-hospital NDAF primarily rely on simplified parameters and high sensitivity. It might be used as a screening tool for in-hospital NDAF in stroke patients who initially presumed cryptogenic stroke.

Evaluation of electrocardiographic P wave parameters in predicting long-term atrial fibrillation in patients with acute ischemic stroke

BACKGROUND

Electrocardiographic parameters, such as P wave peak time (PWPT), P wave duration (PWD), and P wave amplitude in lead DI, have been utilized to assess left atrial anomalies linked to the development of atrial fibrillation (AF) in different cohort settings.

OBJECTIVE

To compare electrocardiographic parameters, such as P waves, in predicting long-term AF risk in acute ischemic stroke cases.

METHODS

The data of 231 consecutive acute ischemic stroke cases were retrospectively collected. Two independent cardiologists interpreted the electrocardiography recordings for PWPT, PWD, and P wave amplitude in lead DI. The median follow-up study period was 16 (interquartile range [IQR]: 11-24) months.

RESULTS

In total, AF was detected in 43 (18.6%) cases. All studied P wave parameters were found to be statistically significant in cases with AF. Based on multivariable logistic regression analysis, dementia, left atrium volume index, PWD (razão de chances [RC]: 1.11; 95% confidence interval [CI]: 1.058-1.184; p = 0.003), PWPT in lead DII (RC: 1.030; 95%CI: 1.010-1.050; p = 0.003), and advanced interatrial block morphology were independent predictors of long-term AF. P wave duration had the highest area under the curve value, sensitivity, and specificity for long-term AF in such cases compared with the other P wave parameters.

CONCLUSIONS

Our head-to-head comparison of well-known P wave parameters demonstrated that PWD might be the most useful P wave parameter for long-term AF in acute ischemic stroke cases.

A nomogram for predicting atrial fibrillation detected after acute ischemic stroke

Background

Atrial 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).

Methods

This 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.

Results

We 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.

Conclusion

Predictive 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.

Risk of New-Diagnosed Atrial Fibrillation After Transient Ischemic Attack

Background

Transient ischemic attack (TIA) provides a unique opportunity to optimize secondary preventive treatments to avoid subsequent ischemic stroke (SIS). Although atrial fibrillation (AF) is the leading cause of cardioembolism in IS and anticoagulation prevents stroke recurrence (SR), limited data exists about the risk of new-diagnosed AF (NDAF) after TIA and the consequences of the diagnostic delay. The aim of our study was to determine this risk in a cohort of TIA patients with long-term follow-up.

Methods

We carried out a prospective cohort study of 723 consecutive TIA patients from January 2006 to June 2010. Median follow-up was 6.5 (5.0-9.6) years. In a subgroup of 204 (28.2%) consecutive patients, a panel of biomarkers was assessed during the first 24 h of the onset of symptoms. Multivariate analyses were performed to find out the associated factors of NDAF. Kaplan-Meier analysis was also performed to analyzed risk of SIS.

Results

NDAF was indentified in 116 (16.0%) patients: 42 (36.2%) during admission, 18 (15.5%) within first year, 29 (25%) between one and five years and 27 (23.3%) beyond 5 years. NDAF was associated with sex (female) [hazard ratio (HR) 1.61 (95% CI, 1.07- 2.41)], age [[HR 1.05 (95% CI, 1.03-1.07)], previous ischemic heart disease (IHD) [HR 1.84, (95% CI 1.15-2.97)] and cortical DWI pattern [HR 2.81 (95% CI, 1.87-4.21)]. In the Kaplan-Meier analysis, NT-proBNP ≥ 218.2 pg/ml (log-rank test P < 0.001) was associated with significant risk of NDAF during the first 5 years of follow-up. Patients with NDAF after admission and before 5 years of follow-up had the highest risk of SIS (P = 0.002).

Conclusion

The risk of NDAF after TIA is clinically relevant. We identified clinical and neuroimaging factors of NDAF. In addition, NT-proBNP was related to NDAF. Our results can be used to evaluate the benefit of long-term cardiac monitoring in selected patients.

Atrial fibrillation prevalence and risk profile from novel community-based screening in Thailand: A prospective multi-centre study

BACKGROUND

In Thailand, almost one-quarter of strokes are related to atrial fibrillation (AF), and many could be prevented if AF were diagnosed and treated prior to the stroke. Therefore, we tested a novel strategy to screen large numbers of community residents using village health volunteers and primary care nurses.

METHODS

Local primary care nurses and village health volunteers in Phetchaburi and Lopburi provinces, Thailand were trained to perform AF screening using a blood pressure device with AF algorithm (Microlife A200 AFib). 10% of residents aged ≥ 65 years were randomly selected for screening during home-visits. Participants with possible AF were given follow-up appointments for further testing, including 12-lead ECG and echocardiogram.

RESULTS

Over two-months, 9.7% (13,864/143,478) of the target population were screened: mean age 73.2 ± 6.4 years, 32.4% male. The estimated AF prevalence (detected by Microlife A200 AFib) was 2.8% (95% CI, 2.6-3.1%) for age ≥ 65 years (i.e. 393/13,864 participants). Prevalence increased with age from 1.9% (65-69 years) to 5.0% (≥85 years) (p < 0.001). Only 58% (226/393) of participants with suspected AF attended the follow-up appointment (1-3 months after initial screen): mean CHA2DS2-VASc score 3.2 ± 1.2; 86.3% (195/226) had Class-1 oral anticoagulation recommendation, and 33% (75/226) had AF on 12-lead ECG.

CONCLUSIONS

In Thailand, large-scale AF screening in the community is feasible using trained volunteer health workers, allowing screening of large numbers in a short time-period. Further investigation of this strategy is warranted, ensuring mechanisms to obtain a timely rhythm strip or 12-lead ECG locally, and a designated pathway to treatment.

Screening strategies for atrial fibrillation: a systematic review and cost-effectiveness analysis

Background

Atrial fibrillation (AF) is a common cardiac arrhythmia that increases the risk of thromboembolic events. Anticoagulation therapy to prevent AF-related stroke has been shown to be cost-effective. A national screening programme for AF may prevent AF-related events, but would involve a substantial investment of NHS resources.

Objectives

To conduct a systematic review of the diagnostic test accuracy (DTA) of screening tests for AF, update a systematic review of comparative studies evaluating screening strategies for AF, develop an economic model to compare the cost-effectiveness of different screening strategies and review observational studies of AF screening to provide inputs to the model.

Design

Systematic review, meta-analysis and cost-effectiveness analysis.

Setting

Primary care.

Participants

Adults.

Intervention

Screening strategies, defined by screening test, age at initial and final screens, screening interval and format of screening {systematic opportunistic screening [individuals offered screening if they consult with their general practitioner (GP)] or systematic population screening (when all eligible individuals are invited to screening)}.

Main outcome measures

Sensitivity, specificity and diagnostic odds ratios; the odds ratio of detecting new AF cases compared with no screening; and the mean incremental net benefit compared with no screening.

Review methods

Two reviewers screened the search results, extracted data and assessed the risk of bias. A DTA meta-analysis was perfomed, and a decision tree and Markov model was used to evaluate the cost-effectiveness of the screening strategies.

Results

Diagnostic test accuracy depended on the screening test and how it was interpreted. In general, the screening tests identified in our review had high sensitivity (> 0.9). Systematic population and systematic opportunistic screening strategies were found to be similarly effective, with an estimated 170 individuals needed to be screened to detect one additional AF case compared with no screening. Systematic opportunistic screening was more likely to be cost-effective than systematic population screening, as long as the uptake of opportunistic screening observed in randomised controlled trials translates to practice. Modified blood pressure monitors, photoplethysmography or nurse pulse palpation were more likely to be cost-effective than other screening tests. A screening strategy with an initial screening age of 65 years and repeated screens every 5 years until age 80 years was likely to be cost-effective, provided that compliance with treatment does not decline with increasing age.

Conclusions

A national screening programme for AF is likely to represent a cost-effective use of resources. Systematic opportunistic screening is more likely to be cost-effective than systematic population screening. Nurse pulse palpation or modified blood pressure monitors would be appropriate screening tests, with confirmation by diagnostic 12-lead electrocardiography interpreted by a trained GP, with referral to a specialist in the case of an unclear diagnosis. Implementation strategies to operationalise uptake of systematic opportunistic screening in primary care should accompany any screening recommendations.

Limitations

Many inputs for the economic model relied on a single trial [the Screening for Atrial Fibrillation in the Elderly (SAFE) study] and DTA results were based on a few studies at high risk of bias/of low applicability.

Future work

Comparative studies measuring long-term outcomes of screening strategies and DTA studies for new, emerging technologies and to replicate the results for photoplethysmography and GP interpretation of 12-lead electrocardiography in a screening population.

Study registration

This study is registered as PROSPERO CRD42014013739.

Funding

The National Institute for Health Research Health Technology Assessment programme.

Identification of Atrial Fibrillation by Quantitative Analyses of Fingertip Photoplethysmogram

Atrial fibrillation (AF) detection is crucial for stroke prevention. We investigated the potential of quantitative analyses of photoplethysmogram (PPG) waveforms to identify AF. Continuous electrocardiogram (EKG) and fingertip PPG were recorded simultaneously in acute stroke patients (n = 666) admitted to an intensive care unit. Each EKG was visually labeled as AF (n = 150, 22.5%) or non-AF. Linear and nonlinear features from the pulse interval (PIN) and peak amplitude (AMP) of PPG waveforms were extracted from the first 1, 2, and 10 min of data. Logistic regression analysis revealed six independent PPG features feasibly identifying AF rhythm, including three PIN-related (mean, mean of standard deviation, and sample entropy), and three AMP-related features (mean of the root mean square of the successive differences, sample entropy, and turning point ratio) (all p < 0.01). The performance of the PPG analytic program comprising all 6 features that were extracted from the 2-min data was better than that from the 1-min data (area under the receiver operating characteristic curve was 0.972 (95% confidence interval 0.951–0.989) vs. 0.949 (0.929–0.970), p < 0.001 and was comparable to that from the 10-min data [0.973 (0.953–0.993)] for AF identification. In summary, our study established the optimal PPG analytic program in reliably identifying AF rhythm.

Optimal Duration of Monitoring for Atrial Fibrillation in Cryptogenic Stroke: A Nonsystematic Review

Atrial fibrillation (AF) is the most common form of cardiac arrhythmias and an independent risk factor for stroke. Despite major advances in monitoring strategies, clinicians tend to miss the diagnoses of AF and especially paroxysmal AF due mainly to its asymptomatic presentation and the rather limited duration dedicated for monitoring for AF after a stroke, which is 24 hours as per the current recommended guidelines. Hence, determining the optimal duration of monitoring for paroxysmal atrial fibrillation after acute ischemic stroke remains a matter of debate. Multiple trials were published in regard to this matter using both invasive and noninvasive monitoring strategies for different monitoring periods. The data provided by these trials showcase strong evidence suggesting a longer monitoring strategy beyond 24 hours is associated with higher detection rates of AF, with the higher percentage of patients detected consequently receiving proper secondary stroke prevention with anticoagulation and thus justifying the cost-effectiveness of such measures. Overall, we thus conclude that increasing the monitoring duration for AF after a cryptogenic stroke to at least 72 hours will indeed enhance the detection rates, but the cost-effectiveness of this monitoring strategy compared to longer monitoring durations is yet to be established.

Detection of occult atrial fibrillation in patients with embolic stroke of uncertain source: a work in progress

Atrial fibrillation accounts for a substantial proportion of ischemic strokes of known etiology and may be responsible for an additional subset of the 25–40% of strokes of unknown cause (so-called cryptogenic). Oral anticoagulation is significantly more effective than antiplatelet therapy in the secondary prevention of atrial fibrillation-related strokes, providing justification for developing more sensitive approaches to detecting occult paroxysms of atrial fibrillation. In this article, we summarize the current state of knowledge regarding the value of in-hospital and out-patient monitoring for detecting atrial fibrillation in the context of cryptogenic stroke. We review the evidence for and against screening with standard Holter monitors, external loop recorders, the newer real-time continuous attended cardiac monitoring systems, cardiac implantable electronic devices, and insertable loop recorders. We review key questions regarding prolonged cardiac arrhythmia monitoring, including the relationship between duration of the atrial fibrillation episode and risk of thromboembolism, frequency of monitoring and its impact on the diagnostic yield in detecting occult or subclinical atrial fibrillation, and the temporal proximity of device-detected atrial fibrillation to stroke events. We conclude by proposing avenues for further research.

Hospital mortality from atrial fibrillation associated with ischemic stroke: a national data report

PURPOSE

To study factors associated with poor outcomes in acute ischemic stroke patients with atrial fibrillation (AF) by using a national database.

MATERIALS AND METHODS

This study was a retrospective analytical study by retrieving data from the Thailand national database system for universal coverage (UC) health insurance system. All adult patients aged over 18 years who were admitted with acute ischemic stroke during the fiscal years 2004-2012 by the appropriate ICD codes were searched. Eligible patients with AF were categorized as alive or dead during hospital stay. The mortality rate and factors associated with in-hospital mortality were studied.

RESULTS

There were 522,699 patients diagnosed as acute stroke; 277,291 patients (53.1%) had acute ischemic stroke. Of those with ischemic stroke, 25,319 patients (9.1%) had AF. The mortality rates of acute ischemic stroke with AF were 14.1% and without AF were 6.2%, (p < 0.001). Significant factors associated with mortality in acute stroke patients with AF by multivariate logistic regression were female gender (adjusted odds ratio; AOR 1.28), co-morbid diseases such as diabetes (AOR 1.28), hypertension (AOR 1.26), rt-PA treatment (AOR 0.55), and stroke complications, such as pneumonia (AOR 2.60), septicemia (AOR 6.50), or gastrointestinal bleeding (AOR 2.16).

CONCLUSIONS

At the national level, AF caused a higher mortality rate in acute ischemic stroke than in non-AF patients. Gender, co-morbid diseases, rt-PA treatment, and stroke complications were associated with mortality in acute ischemic stroke with AF.