CHADS2 and CHA2DS2-VASc scoring systems for predicting atrial fibrillation following cardiac valve surgery

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.

The CHA2DS2-VASC Score Predicts Mortality in Patients Undergoing Coronary Angiography

BACKGROUND

The CHA2DS2-VASC score is used to predict the risk of thromboembolic complications in patients with atrial fibrillation (AF). We hypothesized that the CHA2DS2-VASC score can be used to predict mortality in patients undergoing coronary angiography.

METHODS AND RESULTS

This was a prospective study of 990 patients undergoing coronary angiography. The median follow-up was 2294 days. The patients were categorized into two groups according to their CHA2DS2-VASC score: group I had scores <4 and group II had scores ≥4 (527 (53.2%) and 463 (46.8%), respectively). A Kaplan-Meier analysis demonstrated a significant association between the CHA2DS2-VASC score and mortality (69/527 (13.1%) vs. 179/463 (38.7%) for group I vs. group II, respectively, p < 0.0001). The association remained significant in patients with and without AF, reduced and preserved LVEF, normal and reduced kidney function, and with and without ACS (p < 0.009 to p < 0.0001 for all). In the Cox regression model, which combined the CHA2DS2-VASC score, the presence of AF, LVEF, anemia, and renal insufficiency, an elevated CHA2DS2-VASC score of ≥4 was independently associated with higher mortality (HR 2.12, CI 1.29-3.25, p = 0.001).

CONCLUSIONS

The CHA2DS2VASC score is a simple and reliable mortality predictor in patients undergoing coronary angiography and should be used for the initial screening for such patients.

Left atrial functional measurements' utility in predicting long-term risk of atrial fibrillation after isolated CABG

BACKGROUND

Atrial fibrillation (AF) is the most common cardiac arrhythmia following coronary artery bypass grafting (CABG). We hypothesized that measures of left atrial (LA) function would be useful in predicting AF in patients undergoing CABG.

METHODS AND RESULTS

In the study, 611 patients were included after CABG. All patients had echocardiograms performed preoperatively and LA functional measurements were assessed. These measurements were LA maximum volume index (LAVmax), LA minimum volume index (LAVmin) and LA emptying fraction (LAEF). The endpoint was AF occurring >14 days after surgery. During the follow-up period of a median of 3.7 years, 52 (9%) developed AF. The mean age was 67 years, 84% were male and the average left ventricle ejection fraction was 50%. Patients who developed AF had a lower CCS class and lower LAEF (40 vs. 45%), otherwise no clinical differences were observed between outcome groups. No functional LA measurements were significant predictors of AF in the whole CABG population. However, in patients with normal-sized LA (n = 532, events: 49), both LAEF and LAVmin were univariable predictors of AF. When the functional measurements were adjusted for the CHADS₂ score, both LAVmin (HR = 1.07 [1.01-1.13], p = .014) and LAEF (HR: 1.02 [1.00-1.03], p = .023), remained significant predictors.

CONCLUSION

No echocardiographic measurements were significant predictors of AF after CABG. In patients with a normal LA size, LAVmin as well as LAEF were significant predictors of AF.

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.

The Prediction Model of Medical Expenditure Appling Machine Learning Algorithm in CABG Patients

Most patients face expensive healthcare management after coronary artery bypass grafting (CABG) surgery, which brings a substantial financial burden to the government. The National Health Insurance Research Database (NHIRD) is a complete database containing over 99% of individuals' medical information in Taiwan. Our research used the latest data that selected patients who accepted their first CABG surgery between January 2014 and December 2017 (n = 12,945) to predict which factors will affect medical expenses, and built the prediction model using different machine learning algorithms. After analysis, our result showed that the surgical expenditure (X4) and 1-year medical expenditure before the CABG operation (X14), and the number of hemodialysis (X15), were the key factors affecting the 1-year medical expenses of CABG patients after discharge. Furthermore, the XGBoost and SVR methods are both the best predictive models. Thus, our research suggests enhancing the healthcare management for patients with kidney-related diseases to avoid costly complications. We provide helpful information for medical management, which may decrease health insurance burdens in the future.

Machine-Learning Techniques for Feature Selection and Prediction of Mortality in Elderly CABG Patients

Coronary artery bypass surgery grafting (CABG) is a commonly efficient treatment for coronary artery disease patients. Even if we know the underlying disease, and advancing age is related to survival, there is no research using the one year before surgery and operation-associated factors as predicting elements. This research used different machine-learning methods to select the features and predict older adults' survival (more than 65 years old). This nationwide population-based cohort study used the National Health Insurance Research Database (NHIRD), the largest and most complete dataset in Taiwan. We extracted the data of older patients who had received their first CABG surgery criteria between January 2008 and December 2009 (n = 3728), and we used five different machine-learning methods to select the features and predict survival rates. The results show that, without variable selection, XGBoost had the best predictive ability. Upon selecting XGBoost and adding the CHA2DS score, acute pancreatitis, and acute kidney failure for further predictive analysis, MARS had the best prediction performance, and it only needed 10 variables. This study's advantages are that it is innovative and useful for clinical decision making, and machine learning could achieve better prediction with fewer variables. If we could predict patients' survival risk before a CABG operation, early prevention and disease management would be possible.

Long-term outcomes of postoperative atrial fibrillation following non cardiac surgery: A systematic review and metanalysis

BACKGROUND

New-onset atrial fibrillation (AF) in non-cardiac postoperative setting is common and is associated with a high risk of in-hospital mortality and morbidity. The long-term risks of stroke, mortality and AF recurrence rate in patients with postoperative AF (POAF) are unclear.

METHODS

We performed a systematic literature review in electronic databases from inception to March 5th, 2020 of studies reporting the incidence of stroke, mortality and AF recurrence in patients with POAF. We confined our analysis to studies with a cohort of at least 150 patients with POAF and with a median follow-up of 12 months as a minimum. Odds Ratios (OR) were pooled using a random-effects model.

RESULTS

Qualitative analysis included 8 studies (7 observational cohort studies and 1 randomized controlled trial) enrolling 3,718,587 patients. Six studies underwent metanalysis comprising 17,684 postoperative patients with POAF and 2,169,248 postoperative patients without POAF. The development of POAF conferred a four-fold increased risk of stroke in the long-term [OR 4.05; 95% confidence interval (CI) 2.91-5.62]. Mortality in the two studies reporting long-term data was higher in patients with POAF compared to those without POAF (OR 3.59; CI 95% 2.84-4.53). Data about recurrence were too heterogeneous to undergo metanalysis.

CONCLUSIONS

POAF is associated with a greater risk of stroke and mortality over the long-term period. Studies focusing on AF recurrence are needed to address the perception of POAF as a benign transient entity. The increased mortality risk following POAF should encourage systematic detection and prevention of this arrhythmia.

Development and Validation of A Simple Clinical Risk Prediction Model for New-Onset Postoperative Atrial Fibrillation After Cardiac Surgery: Nopaf Score

Introduction

Postoperative atrial fibrillation (POAFib) occurs in 20 to 40% of patients following cardiac surgery, and is associated with an increased perioperative morbidity and mortality. We aimed to develop and validate a simple clinical risk model for the prediction of POAFib after cardiac surgery.

Methods

An analytical single center retrospective cohort study was conducted, including consecutive patients undergoing cardiac surgery between 2004 and 2017 with POAFib. To create the predictive risk score, a logistic regression model was performed using a random sample of 75% of the population. Coefficients of the model were then converted to a numerical risk score, and three groups were defined: low risk (≤1 point), intermediate risk (2-5 points) and high risk (≥6 points). The score was validated using the remaining 25% of the patients. Discrimination was evaluated through the area under the curve (AUC) ROC, and calibration using the Hosmer-Lemeshow (HL) test, calibration plots, and ratio of expected and observed events (E/O).

Results

Six thousand five hundred nine patients underwent cardiac surgery: 52% coronary artery bypass grafting (CABG), 20% valve surgery, 14% combined (CABG and valve surgery) and 12% other. New-onset AF occurred in 1222 patients (18.77%). In the multivariate analysis, age, use of cardiopulmonary bypass pump, severe reduction in left ventricular ejection fraction (LVEF), chronic renal disease and heart failure were independent risk factors for POAFib, while the use of statins was a protective factor. The NOPAF score was calculated by adding points for each independent risk predictor. In the derivation cohort, the AUC was 0.71 (CI95% 0.69-0.72), and in the validation cohort the model also showed good discrimination (AUC 0.67 IC 0.64-0.70) and excellent calibration (HL P = 0.24). The E/O ratio was 1 (CI 95%: 0.89-1.12). According to the risk category, POAFib occurred in 5% of low; 11% of intermediate and 27.7% of high risk patients in the derivation cohort (P <0.001), and 5.7%; 12.6%; and 23.6% in the validation cohort respectively (P <0.001).

Conclusion

From a large hospitalized population, we developed and validated a simple risk score named NOPAF, based on clinical variables that accurately stratifies the risk of POAFib. This score may help to identify high-risk patients prior to cardiac surgery, in order to strengthen postoperative atrial fibrillation prophylaxis.

RNAs and Gene Expression Predicting Postoperative Atrial Fibrillation in Cardiac Surgery Patients Undergoing Coronary Artery Bypass Grafting

Postoperative atrial fibrillation (POAF) is linked with increased morbidity, mortality rate and financial liability. About 20–50% of patients experience POAF after coronary artery bypass graft (CABG) surgery. Numerous review articles and meta-analyses have investigated links between patient clinical risk factors, demographic conditions, and pre-, peri- and post-operative biomarkers to forecast POAF incidence in CABG patients. This narrative review, for the first time, summarize the role of micro-RNAs, circular-RNAs and other gene expressions that have shown experimental evidence to accurately predict the POAF incidence in cardiac surgery patients after CABG. We envisage that identifying specific genomic markers for predicting POAF might be a significant step for the prevention and effective management of this type of post-operative complication and may provide critical perspective into arrhythmogenic substrate responsible for POAF.

Causes and characteristics associated with early and late readmission after open-heart valve surgery

OBJECTIVES

The objectives of the study were to describe the causes of readmission from discharge to 30 days and from day 31 to 180 after discharge and to investigate the characteristics associated with overall and cause-specific readmissions after open-heart valve surgery.

METHODS

A single-center, retrospective cohort of 980 patients undergoing open-heart valve surgery from 2013 to 2016. Time to the first readmission was analyzed using univariable and multivariable Cox proportional hazard models. Results are reported as hazard ratios (HR) with 95% confidence intervals (CI).

RESULTS

In total, 366 patients (37%) experienced unplanned cardiac readmission within 180 days after discharge. Within 30 days after discharge, the most frequent causes of readmission were pericardial/pleural effusions (n = 87), infections (n = 50), and atrial fibrillation/flutter (n = 45). Accordingly, infections (n = 32) were the most common cause from day 31 to 180. No powerful predictors of overall cardiac readmission were identified, but several characteristics were associated with cause-specific readmissions: age ≤65 years (HR: 1.85; CI: 1.18-2.88), male gender (HR: 1.85; CI: 1.11-3.09), high alcohol intake (HR: 1.99; CI: 1.22-3.24) and mitral valve procedures (HR: 1.86; CI: 1.11-3.10) were associated with readmissions due to effusions. Ischemic heart disease with a prior percutaneous coronary intervention (HR: 2.94; CI: 1.53-5.63), mitral valve procedures (HR: 2.10; CI: 1.23-3.59), and postoperative atrial fibrillation/flutter (HR: 1.71; CI: 1.03-2.85) were associated with atrial fibrillation/flutter readmissions.

CONCLUSION

Predicting overall readmissions after open-heart valve surgery is difficult as causes of readmissions vary and different causes are associated with different characteristics. Future studies should target reducing cause-specific readmissions.

Perioperative Biomarkers Predicting Postoperative Atrial Fibrillation Risk After Coronary Artery Bypass Grafting: A Narrative Review

Postoperative atrial fibrillation (POAF) after cardiac surgery remains a highly prevalent and costly condition that negatively impacts patient quality of life and survival. Numerous retrospective studies, meta-analysis, and review papers have been reported identifying POAF risk based on patients' risk factors and clinical biomarkers. In this narrative review, the authors report significant variations among selected pre- and perioperative biomarkers used to predict POAF incidence in patients without a history of atrial fibrillation (AF). POAF prediction based on B-type natriuretic peptide, N-terminal pro B-type natriuretic peptide, C-reactive protein, interleukin-6, creatinine, and plasminogen activator inhibitor-1 differs significantly among different studies, thereby limiting their clinical utility to predict POAF risk with high accuracy. Conversely, soluble vascular endothelial cells adhesion molecule-1, soluble CD40 ligand, Galectin-3, and aldosterone show promise for better POAF prediction. However, the current datasets for these selected biomarkers are not of sufficient size to validate the broad clinical application specifically for patients with no prior history of AF.

The CHA2DS2-VASc score for predicting atrial fibrillation in patients presenting with ST elevation myocardial infarction: prospective observational study

BACKGROUND

Atrial fibrillation (AF) is the most common form of supraventricular arrhythmia following ST-elevation myocardial infarction (STEMI). The CHA2DS2-VASc and CHADS2 scores are used to estimate thromboembolic risk in cases of AF. Their usefulness in predicting the development of AF in patients presenting STEMI is unknown.

OBJECTIVE

To evaluate the predictive value of the CHADS2 and CHA2DS2-VASc scores in patients with AF following STEMI.

DESIGN AND SETTING

This prospective cohort study on 696 patients with STEMI was conducted at a tertiary-level cardiology clinic in a public university hospital.

METHODS

Models including clinical and laboratory parameters were constructed to test the predictive value of CHADS2 and CHA2DS2-VASc scores. Patients were divided into two groups: with and without AF. Predictors of AF were determined using multivariate regression analysis.

RESULTS

In the patients with AF, CHADS2 and CHA2DS2-VASc scores were significantly higher than in those without AF (for both P < 0.001). Factors associated with AF in multivariate analyses included CHA2DS2-VASc score (odds ratio, OR: 1.48; 95% confidence interval, CI: 1.25-1.75; P < 0.001), peak creatine kinase-myocardial binding (OR: 1.002; 95% CI: 1.00-1.003; P = 0.0024), duration of the coronary intensive care unit stay (OR: 1.69; 95% CI: 1.24-12.30; P = 0.001) and no use of renin-angiotensin system blockers (OR: 2.16; 95% CI: 1.14-4.10; P = 0.0017). Receiver operating characteristic curve analyses showed that CHA2DS2-VASc scores were significant predictors for new-onset AF (C-statistic: 0.698; 95% CI: 0.631-0.765; P < 0.001).

CONCLUSION

CHADS2 and CHA2DS2-VASc scores predicted new AF in patients presenting STEMI.

New-Onset Atrial Fibrillation in Adult Patients After Cardiac Surgery

Purpose of Review

An overview of recent literature regarding pathophysiology, risk factors, prophylaxis, and treatment of new-onset atrial fibrillation (AF) in post-cardiac surgical patients.

Recent Findings

AF is the most frequent adverse event after cardiac surgery with significant associated morbidity, mortality, and financial cost. Its causes are multifactorial, and models to stratify patients into risk categories are progressing but a consistent, evidence-based system has not yet been developed. Pharmacologic and surgical interventions to prevent and treat this complication have been an area of ongoing research and recent societal guidelines reflect this.

Summary

Inconsistencies remain surrounding how to best identify higher-risk AF patients, which interventions should be used to prevent and treat AF, and which patient groups should receive these interventions. The evidence for these available strategies and their place in contemporary guidelines are summarized.

Postoperative atrial fibrillation is associated with higher scores on predictive indices

OBJECTIVE

To compare the performance of the CHADS VASc, POAF, and HATCH scoring systems to predict new-onset atrial fibrillation after cardiac surgery.

METHODS

We conducted a single-center cohort study, performing a retrospective analysis of prospectively collected data. The study included consecutive patients undergoing cardiac surgery between January 2010 and December 2016. The primary outcome was the development of new-onset postoperative atrial fibrillation during hospitalization.

RESULTS

A total of 3113 patients underwent cardiac surgery during the study period: coronary artery bypass graft surgery (45%), valve replacement (24%), combined procedure (revascularization-valve surgery) (15%), and other procedures (16%). Twenty-one percent (n = 654) presented postoperative atrial fibrillation. Median scores in patients with postoperative atrial fibrillation were significantly higher (P < .001). The CHAD2DS2-VASc score demonstrated greater discriminative ability to predict the event (C-statistic, 0.77; 95% confidence interval [CI], 0.75-0.79) versus the POAF score and the HATCH score (C-statistic, 0.71; 95% CI, 0.69-0.73 and C-statistic, 0.70; 95% CI, 0.67-0.72, respectively). All 3 scores presented good calibration according to the Hosmer-Lemeshow test univariate and multivariable analysis demonstrated that the 3 scores were independent predictors of postoperative atrial fibrillation: CHA2DS2-VASc score odds ratio 1.87 (95% CI, 1.64-2.13), POAF score odds ratio 1.18 (95% CI, 1.01-1.36), and HATCH score odds ratio 1.62 (95% CI, 1.37-1.92).

CONCLUSIONS

The POAF, CHA2DS2-VASc, and HATCH scoring systems showed good discrimination and calibration to predict postoperative atrial fibrillation in patients undergoing cardiac surgery. Among them, the CHA2DS2-Vasc score presented the best discriminative ability for postoperative atrial fibrillation and has the advantage of being easy to calculate.

Association Between CHADS2 Score and the Development of Interatrial Block

Interatrial block (IAB) is associated with a multitude of medical conditions. The aim of this retrospective study was to investigate whether CHADS₂ (congestive heart failure, hypertension, age ≥ 75 years, diabetes mellitus, prior stroke) score is positively associated with the development of IAB. A total of 1072 patients (men, 555; women, 517; mean age, 61 ± 14 years) were included in the study. P-wave duration was measured manually using a caliper. IAB was defined as a P-wave duration of ≥ 120 ms on a 12-lead electrocardiogram. CHADS₂ scores were calculated retrospectively. Among the 1072 patients, the prevalence of IAB was 36.1% (387/1072). In multivariate analysis, increased CHADS₂ score (odds ratio [OR], 1.810; 95% confidence interval [CI], 1.577-2.077; P < 0.001), coronary artery disease (OR, 1.536; 95% CI, 1.065-2.216; P = 0.022), and increased left atrial diameter (OR, 1.039; 95% CI, 1.008-1.071; P = 0.013) were independently associated with IAB. The percentages of patients with IAB among those with a CHADS₂ score of 0, 1, 2, 3, 4, 5, and 6 were 20.6%, 33.0%, 45.0%, 55.9%, 61.9%, 77.8%, and 100%, respectively (P < 0.001). There was a greater percentage of patients with a CHADS₂ score of ≥ 2 with IAB compared with a CHADS₂ score of < 2 (26.5% vsrsus 52.0%; P < 0.001). In receiver operating curve (ROC) analysis, CHADS₂ score (area under the curve, 0.670; 95% CI, 0.636-0.704; P < 0.001) was predictive of IAB. In conclusion, CHADS₂ score was significantly associated with the development of IAB in this study population.

Performance and validation of a simplified postoperative atrial fibrillation risk score

BACKGROUND

Postoperative atrial fibrillation (POAF) occurs in 20-40% patients who received isolated coronary artery cardiac bypass surgery (CABG). Several POAF risk prediction models have been developed, but none of them is widely adopted in practice. Our objective was to derive and validate a simple scoring system to estimate POAF risk after isolated CABG, using easily available clinical information.

METHODS

Medical records of 1,000 consecutive patients undergoing isolated CABG were reviewed. The data of first 700 patients were used for model derivation and data of the remaining 300 patients were used for model validation. Discrimination and calibration of the newly developed model were assessed.

RESULTS

POAF incidence in both the derivation and validation cohorts was 27.3%. Age ≥65, history of hypertension, heart failure, and myocardial infarction were independently associated with POAF risk. Risk scores were calculated by summing weighting points for each independent predictor. The score ≥3 was associated with high POAF incidence (41.1% in the derivation cohort and 44.3% in the validation cohort). The positive and negative POAF predictive value was 41.1% and 78.5%, respectively, in the derivation cohort, and 44.3% and 80.8%, respectively, in the validation cohort, when the cut-point score ≥3 was used. The Hosmer-Lemeshow goodness-of-fit test P-values were 0.917 and 0.894 in the derivation cohort and validation cohort, respectively.

CONCLUSIONS

This POAF risk following isolated CABG can be predicted with simple patient characteristic during the preoperative period. Patients with high risk scores (≥3) may constitute a target population for POAF prevention and prolonged postoperative surveillance.

The Frequency and Risk Factors for Ischemic Stroke in Myotonic Dystrophy Type 1 Patients

INTRODUCTION

Patients with myotonic dystrophy type 1 have several cardiac abnormalities, especially myocardial conduction disorders. Few studies have investigated cerebral infarction. We investigated the frequency of both symptomatic and asymptomatic ischemic strokes in patients with myotonic dystrophy type 1.

METHODS

Patients who were diagnosed with myotonic dystrophy type 1 using genetic testing or clinical examinations at Asahikawa Medical Center were included. We retrospectively reviewed their medical history, neuroradiological imaging, electrocardiograms, and treatment. Their CHADS2 and CHA2DS2-VASc scores were calculated.

RESULT

A total of 108 patients were diagnosed with myotonic dystrophy type 1. Magnetic resonance imaging was performed in 72 and 1 patient whose results were not available was excluded. Among these, 2 patients had atrial flutter and 3 had atrial fibrillation. Regarding the CHADS2 score, 11 patients scored more than 2. Regarding the CHA2DS2-VASc score, 22 patients scored more than 2. Ischemic strokes were found in 9 patients with 1 having an atrial flutter and 4 having atrial fibrillation. All patients with stroke had CHADS2 and CHA2DS2-VASc scores higher than 2. There were significant differences between the 2 groups in atrial fibrillation (P < .001), CHADS2 score (P < .001), and CHA2DS2-VASc score (P < .001).

CONCLUSIONS

Ischemic stroke in patients with myotonic dystrophy type 1 is associated with atrial fibrillation. The CHADS2 score seems to be useful for the management of patients with myotonic dystrophy type 1. Repeated electrocardiograms are necessary for managing these patients.

CHADS2 and CHA2DS2-VASc Scores Predict the Risk of Ischemic Stroke Outcome in Patients with Interatrial Block without Atrial Fibrillation

Aim: To evaluate the role of CHADS₂ and CHA₂DS₂-VASc scores in predicting the risk of ischemic stroke or transient ischemic attack (TIA) outcomes in patients with interatrial block (IAB) without a history of atrial fibrillation (AF).

Methods: A retrospective study was conducted, including 1,046 non-anticoagulated inpatients (612 males, 434 females; mean age: 63 ± 10 years) with IAB and without AF. IAB was defined as P-wave duration > 120 ms using a 12-lead electrocardiogram. CHADS₂ and CHA₂DS₂-VASc scores were retrospectively calculated. The primary outcomes evaluated were ischemic stroke or TIA.

Results: During the mean follow-up period of 4.9 ± 0.7 years, 55 (5.3%) patients had an ischemic stroke or TIA. Receiver operating characteristic (ROC) curve analysis showed that the CHADS₂ score [area under the curve (AUC), 0.638; 95% confidence interval (CI), 0.562–0.715; P = 0.001] and the CHA₂DS₂-VASc score (AUC, 0.671; 95% CI, 0.599–0.744; P <0.001) were predictive of ischemic strokes or TIA. Cut-off point analysis showed that a CHADS₂ score ≥ 3 (sensitivity = 0.455 and specificity = 0.747) and a CHA₂DS₂-VASc score ≥ 4 (sensitivity = 0.564 and specificity = 0.700) provided the highest predictive value for ischemic stroke or TIA. The multivariate Cox regression analysis showed that CHADS₂ [hazard ratio (HR), 1.442; 95% CI, 1.171–1.774; P = 0.001] and CHA₂DS₂-VASc (HR, 1.420; 95% CI, 1.203–1.677; P <0.001) scores were independently associated with ischemic stroke or TIA following adjustment for smoking, left atrial diameter, antiplatelet agents, angiotensin inhibitors, and statins.

Conclusions: CHADS₂ and CHA₂DS₂-VASc scores may be predictors of risk of ischemic stroke or TIA in patients with IAB without AF.