scholarly journals Risk Score for Prediction of 10-Year Atrial Fibrillation: A Community-Based Study

2018 ◽  
Vol 118 (09) ◽  
pp. 1556-1563 ◽  
Author(s):  
Doron Aronson ◽  
Varda Shalev ◽  
Rachel Katz ◽  
Gabriel Chodick ◽  
Diab Mutlak
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Risk Score ◽  
Proportional Hazards Model ◽  
Validation Cohort ◽  
Cox Proportional Hazards Model ◽  
Net Benefit ◽  
Derivation Cohort ◽  
Risk Equation ◽  
History Of

Purpose We used a large real-world data from community settings to develop and validate a 10-year risk score for new-onset atrial fibrillation (AF) and calculate its net benefit performance. Methods Multivariable Cox proportional hazards model was used to estimate effects of risk factors in the derivation cohort (n = 96,778) and to derive a risk equation. Measures of calibration and discrimination were calculated in the validation cohort (n = 48,404). Results Cumulative AF incidence rates for both the derivation and validation cohorts were 5.8% at 10 years. The final models included the following variables: age, sex, body mass index, history of treated hypertension, systolic blood pressure ≥ 160 mm Hg, chronic lung disease, history of myocardial infarction, history of peripheral arterial disease, heart failure and history of an inflammatory disease. There was a 27-fold difference (1.0% vs. 27.2%) in AF risk between the lowest (–1) and the highest (9) sum score. The c-statistic was 0.743 (95% confidence interval [CI], 0.737–0.749) for the derivation cohort and 0.749 (95% CI, 0.741–0.759) in the validation cohort. The risk equation was well calibrated, with predicted risks closely matching observed risks. Decision curve analysis displayed consistent positive net benefit of using the AF risk score for decision thresholds between 1 and 25% 10-year AF risk. Conclusion We provide a simple score for the prediction of 10-year risk for AF. The score can be used to select patients at highest risk for treatments of modifiable risk factors, monitoring for sub-clinical AF detection or for clinical trials of primary prevention of AF.

scholarly journals The Admit-AF risk score: a clinical risk score for predicting hospital admissions in patients with atrial fibrillation

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
P Meyre ◽  
S Aeschbacher ◽  
S Blum ◽  
M Coslovsky ◽  
J.H Beer ◽  
...  
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
High Risk ◽  
Risk Score ◽  
Hospital Admissions ◽  
Validation Cohort ◽  
Funding Source ◽  
Prediction Tool ◽  
Derivation Cohort

Abstract Background Patients with atrial fibrillation (AF) have a high risk of hospital admissions, but there is no validated prediction tool to identify those at highest risk. Purpose To develop and externally validate a risk score for all-cause hospital admissions in patients with AF. Methods We used a prospective cohort of 2387 patients with established AF as derivation cohort. Independent risk factors were selected from a broad range of variables using the least absolute shrinkage and selection operator (LASSO) method fit to a Cox regression model. The developed risk score was externally validated in a separate prospective, multicenter cohort of 1300 AF patients. Results In the derivation cohort, 891 patients (37.3%) were admitted to the hospital over a median follow-up 2.0 years. In the validation cohort, hospital admissions occurred in 719 patients (55.3%) during a median follow-up 1.9 years. The most important predictors for admission were age (75–79 years: adjusted hazard ratio [aHR], 1.33; 95% confidence interval [95% CI], 1.00–1.77; 80–84 years: aHR, 1.51; 95% CI, 1.12–2.03; ≥85 years: aHR, 1.88; 95% CI, 1.35–2.61), prior pulmonary vein isolation (aHR, 0.74; 95% CI, 0.60–0.90), hypertension (aHR, 1.16; 95% CI, 0.99–1.36), diabetes (aHR, 1.38; 95% CI, 1.17–1.62), coronary heart disease (aHR, 1.18; 95% CI, 1.02–1.37), prior stroke/TIA (aHR, 1.28; 95% CI, 1.10–1.50), heart failure (aHR, 1.21; 95% CI, 1.04–1.41), peripheral artery disease (aHR, 1.31; 95% CI, 1.06–1.63), cancer (aHR, 1.33; 95% CI, 1.13–1.57), renal failure (aHR, 1.18, 95% CI, 1.01–1.38), and previous falls (aHR, 1.44; 95% CI, 1.16–1.78). A risk score with these variables was well calibrated, and achieved a C-index of 0.64 in the derivation and 0.59 in the validation cohort. Conclusions Multiple risk factors were associated with hospital admissions in AF patients. This prediction tool selects high-risk patients who may benefit from preventive interventions. The Admit-AF risk score Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): The Swiss National Science Foundation (Grant numbers 33CS30_1148474 and 33CS30_177520), the Foundation for Cardiovascular Research Basel and the University of Basel

Abstract 17048: Dederivation and Validation of a Simple Heart Risk Score in 608,544 Thai Adults: HCUR Study

Circulation ◽  
2018 ◽  
Vol 138 (Suppl_1) ◽  
Author(s):  
Parinya Chamnan ◽  
Weera Mahawanakul ◽  
Prasert Boongird ◽  
Wannee Nitiyanant ◽  
Wichai Aekplakorn ◽  
...  
Keyword(s):  
General Population ◽  
Risk Score ◽  
Retrospective Cohort ◽  
Validation Cohort ◽  
Information Criteria ◽  
Global Model ◽  
Derivation Cohort ◽  
Risk Equation ◽  
Risk Algorithm ◽  
Incident Cases

Introduction: Most heart risk prediction equations were developed in Western populations. These risk scores are likely to perform less well in Asian populations, who have different background risk. Hypothesis: This study aimed to develop and validate a new risk algorithm for estimating 5-year risk of developing coronary heart disease (CHD) in a large retrospective cohort of Thai general population. Methods: This retrospective cohort was derived from the linkage of 2006 health checks data with diagnostic information from electronic health records of 608,544 men and women aged 20 years and above residing in Ubon Ratchathani. It was randomly and evenly divided into the derivation and validation cohorts. An outcome of interest was first recorded diagnosis of CHD over a period of 6 years between January 2006 and December 2012. A Cox proportional hazards model was used to estimate effects of risk factors on CHD risk and to derive a risk equation in the derivation cohort. Measures of discrimination, global model fits and calibration were calculated in the validation cohort. Results: The derivation cohort comprised of 304,272 individuals, who contributed 1,757,369 person-years of follow-up and 1,272 incident cases of CHD, while the validation cohort comprised of 304,272 individuals (1,757,312 person-years), with 1,290 incident cases of stroke. The risk equation was 0.0580 x Age (years) + 0.5739 x Sex (Male=1) + 0.3850 x Hypertension (present=1) + 0.7080 x Diabetes (present=1) + 0.0386 x Body mass index (kg/m 2 ) + 0.2117 x Central obesity (present=1) - 0.1389 (if exercise 1-2 days/week) or -0.3975 (if exercise 3-5 days/week) or - 0.5598 (if exercise >5 days/week). The stroke risk equation had a reasonably good discriminatory ability in the validation cohort with the area under the receiver operating characteristic curve of 0.790 (95%CI 0.779-0.801). The risk equation had good global model fit as measured by Bayesian information criteria. The Gronnesby and Borgan test showed good calibration, with chi-square statistic of 809.45 (p<0.001). Conclusions: This simple heart risk score is the first risk algorithm to estimate the 5-year risk of CHD in a Thai general population. The risk score does not need laboratory tests and can therefore be used in clinical settings and by the public.

Abstract 17617: History of Bleeding and Outcomes with Apixaban versus Warfarin in Patients with Atrial Fibrillation in the ARISTOTLE Trial

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Raffaele De Caterina ◽  
Ulrika Andersson ◽  
John H Alexander ◽  
M.Cecilia Bahit ◽  
Patrick J Commerford ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Body Weight ◽  
Major Bleeding ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Channel Blockers ◽  
Chads2 Score ◽  
History Of

Background: History of bleeding is important in decisions for anticoagulation. We analyzed outcomes in relation to history of bleeding and randomized treatments in patients with atrial fibrillation (AF) in the ARISTOTLE trial. Methods: The on-treatment safety population included 18,140 patients receiving ≥1 dose of study drug, apixaban 5 mg bd (2.5 mg bd if 2 of the following: age >80 yrs; body weight <60 kg; or creatinine >133 μmol/L) or warfarin aiming for INR 2.0-3.0 (median TTR 66%), for a median of 1.8 yrs. Adjudicated outcomes in relation to randomization and history of bleeding were analyzed using a Cox proportional hazards model. Efficacy endpoints were analyzed in the intention-to-treat population. Results: A history of bleeding was reported in 3033 patients (16.7%), who more often were male (68% vs 64%, p <0.0005); with a history of prior stroke/TIA/systemic embolism (23% vs 19%, p <0.0001); diabetes (27% vs 24%, p=0.0010); higher CHADS2 score (CHADS2 >3: 35% vs 29%), age (mean [SD] 71 [9] vs 69 [10], p <0001) and body weight (86 [21] vs 84 [21], p <0.0001); lower creatinine clearance (77 [33] vs 80 [33], p=0.0007) and mean systolic blood pressure (131 [17] vs 132 [16], p=0.0027). Calcium channel blockers, statins, non-steroidal anti-inflammatory drugs and proton pump inhibitors were used more often in patients with vs without a history of bleeding. Major bleeding was the only outcome event occurring more frequently in patients with vs without a history of bleeding, HR 1.7 (95% CI 1.4-2.3) with apixaban and 1.5 (1.2-1.0) with warfarin. Primary efficacy and safety outcomes in relation to randomization, see Table. Conclusions: In patients with AF, a history of bleeding was associated with several risk factors for stroke and bleeding and, accordingly, a higher bleeding risk during anticoagulation. Benefits with apixaban vs warfarin as to stroke, mortality and major bleeding, are however consistent irrespective of bleeding history.

Derivation and Validation of a Prediction Tool for Venous Thromboembolism: A VERITY Registry Study.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 697-697 ◽  
Author(s):  
Roopen Arya ◽  
Shankaranarayana Paneesha ◽  
Aidan McManus ◽  
Nick Parsons ◽  
Nicholas Scriven ◽  
...  
Keyword(s):  
Risk Factors ◽  
Venous Thromboembolism ◽  
Risk Score ◽  
Validation Cohort ◽  
Accurate Estimation ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Derivation Cohort ◽  
Hormonal Factor ◽  
Electronic Alerts

Abstract Accurate estimation of risk for venous thromboembolism (VTE) may help clinicians assess prophylaxis needs. Only empirical algorithms and risk scores have been described; an empirical risk score (‘Kucher’) based on 8 VTE risk factors (cancer, prior VTE, hypercoagulability, surgery, age>75 yrs, BMI>29, bed rest, hormonal factor) using electronic alerts improved hospitalized patient outcome (NEJM2005;352:969–77). We wished to develop a multivariate regression model for VTE risk, based on Kucher, and validate its performance. The initial derivation cohort consisted of patients enrolled in ‘VERITY’, a multicentre VTE treatment registry for whom the endpoint of VTE and all 8 risk factors were known. Initial univariate analysis (n=5928; 32.4% with diagnosis of VTE) suggested VTE risk was not accounted for by the 8 factors; an additional 3 were added (leg paralysis, smoking, IV drug use [IVD]). The final derivation cohort was 5241 patients (32.0% with VTE) with complete risk data. The validation cohort (n=915) was derived from a database of 928 consecutively enrolled patients at a single DVT clinic. Model parameters were estimated using the statistical package ‘R’ using a stepwise selection procedure to choose the optimal number of main effects and pair-wise interactions. This showed that advanced age (estimated odds ratio [OR]=2.8, p<0.001); inpatient (OR=3.0, p<0.001); surgery (OR=3.1, p<0.001); prior VTE (OR=2.9, p<0.001); leg paralysis (OR=3.8, p<0.001); cancer (OR=5.3, p<0.001); IVD (OR=14.3, p<0.001); smoking (OR=1.2, p=0.009); and thrombophilia (OR=2.8; p<0.001) increased the risk of VTE. Obesity (OR=0.7; p<0.001) increased the VTE risk only in patients with a hormonal factor (OR=2.0, p=0.007). Backward stepwise regression showed prior VTE as the most important factor followed by cancer, IVD, surgery, inpatient, age, leg paralysis, hormonal factor, obesity, thrombophilia and smoking. Expressing the parameter estimates in terms of probabilities defines a risk score model for VTE. Using the model, the receiver operating characteristic (ROC) curve (see figure) area under the curve (AUC) was estimated as 0.720 (95% CI, 0.705–0.735) for the model (dashed line), indicating a good diagnostic test significantly better (p<0.001) than Kucher (AUC=0.617, 95% CI, 0.599–0.634)(solid line). For the validation cohort, AUC was estimated as 0.678 (95% CI, 0.635–0.721) for the model, which was not significantly different from AUC for the full dataset used for model development, and was 0.587 (95% CI, 0.542–0.632) for Kucher. This model to predict individual patient risk of VTE may contribute to decision making regarding prophylaxis in clinical practice. Figure Figure

scholarly journals Risk factors for heart failure with preserved or reduced ejection fraction among Medicare beneficiaries: Applications of competing risks analysis and gradient boosted model

2019 ◽  
Author(s):  
Moa P. Lee ◽  
Robert J. Glynn ◽  
Sebastian Schneeweiss ◽  
Kueiyu Joshua Lin ◽  
Elisabetta Patorno ◽  
...  
Keyword(s):  
Risk Factors ◽  
Heart Failure ◽  
Atrial Fibrillation ◽  
Ejection Fraction ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
List Type ◽  
Close Monitoring ◽  
Reduced Ejection Fraction

AbstractBackgroundThe differential impact of various demographic characteristics and comorbid conditions on development of heart failure (HF) with preserved (pEF) and reduced ejection fraction (rEF) is not well studied among the elderly.Methods and ResultsUsing Medicare claims data linked to electronic health records, we conducted an observational cohort study of individuals ≥ 65 years of age without HF. A Cox proportional hazards model accounting for competing risk of HFrEF and HFpEF incidence was constructed. A gradient boosted model (GBM) assessed the relative influence (RI) of each predictor in development of HFrEF and HFpEF. Among 138,388 included individuals, 9,701 developed HF (IR= 20.9 per 1,000 person-year). Males were more likely to develop HFrEF than HFpEF (HR = 2.07, 95% CI: 1.81-2.37 vs. 1.11, 95% CI: 1.02-1.20, P for heterogeneity < 0.01). Atrial fibrillation and pulmonary hypertension had stronger associations with the risk of HFpEF (HR = 2.02, 95% CI: 1.80-2.26 and 1.66, 95% CI: 1.23-2.22) while cardiomyopathy and myocardial infarction were more strongly associated with HFrEF (HR = 4.37, 95% CI: 3.21-5.97 and 1.94, 95% CI: 1.23-3.07). Age was the strongest predictor across all HF subtypes with RI from GBM >35%. Atrial fibrillation was the most influential comorbidity for development of HFpEF (RI = 8.4%) while cardiomyopathy was most influential for HFrEF (RI = 20.7%).ConclusionsThese findings of heterogeneous relationships between several important risk factors and heart failure types underline the potential differences in the etiology of HFpEF and HFrEF.Key QuestionsWhat is already known about this subject?Previous epidemiologic studies describe the differences in risk factors involved in developing heart failure with preserved (HFpEF) and reduced ejection fraction (HFrEF), however, there has been no large study in an elderly population.What does this study add?This study provides further insights into the heterogeneous impact of various clinical characteristics on the risk of developing HFpEF and HFrEF in a population of elderly individuals.Employing an advanced machine learning technique allows assessing the relative importance of each risk factor on development of HFpEF and HFrEF.How might this impact on clinical practice?Our findings provide further insights into the potential differences in the etiology of HFpEF and HFrEF, which are critical in prioritizing populations for close monitoring and targeting prevention efforts.

scholarly journals Cumulative incidence, risk factors, and management of atrial fibrillation in patients receiving ibrutinib

2017 ◽  
Vol 1 (20) ◽  
pp. 1739-1748 ◽  
Author(s):  
Tracy E. Wiczer ◽  
Lauren B. Levine ◽  
Jessica Brumbaugh ◽  
Jessica Coggins ◽  
Qiuhong Zhao ◽  
...  
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Clinical Trial ◽  
Risk Score ◽  
Cumulative Incidence ◽  
Hematologic Malignancies ◽  
Key Points ◽  
Incidence Risk ◽  
History Of

Key Points Ibrutinib increases the incidence of AF in patients with hematologic malignancies treated on or off a clinical trial. Patients with a history of AF and those with a high FHS-AF risk score are at highest risk for developing AF while on ibrutinib.

P3794MOODS: a novel risk score to identify patients with atrial fibrillation and sleep apnoea

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
K Kadhim ◽  
A Elliott ◽  
M Middeldorp ◽  
J Hendriks ◽  
C Gallagher ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Risk Score ◽  
Clinical Characteristics ◽  
Validation Cohort ◽  
Multivariate Logistic Regression Analysis ◽  
Positive Likelihood Ratio ◽  
Resource Utilisation ◽  
Operating Characteristics ◽  
Derivation Cohort ◽  
Sleep Studies

Abstract Background Sleep-disordered breathing (SDB) is an important risk factor for developing atrial fibrillation (AF), and treatment of concomitant SDB can improve AF rhythm outcomes. Diagnosis of SDB requires sleep studies which can pose a significant time and resource burden. We sought to develop a prediction score based on clinical characteristics that can help identify AF patients who require further assessment for SDB. Methods Prospectively-collected data for 442 consecutive patients treated for AF from 2009 to 2017 were analysed. All patients were considered candidates for rhythm-control and therefore referred for sleep studies. The diagnosis of SDB was confirmed using in-lab polysomnography and classified using the apnoea-hypopnoea-index (AHI), with cut-offs of ≥15/hr and ≥30/hr indicating moderate-to-severe and severe SDB respectively. Patients treated up to 2015 formed the derivation cohort (n=311) and the remainder (n=113) formed the validation cohort. Multivariate logistic regression analysis was used to identify clinical variables predictive of moderate-to-severe SDB. A risk score model was developed based on regression coefficients and tested using receiver-operating-characteristics analyses on the validation cohort. Results Overall, mean age was 60±11 years, mean body mass index (BMI) was 30±5 kg/m2 and 69% were men. The prevalence of moderate-to-severe SDB was 33.7%. There were no significant differences in baseline characteristics between the derivation and validation cohorts. Male gender (score=1), overweight (BMI: 25–29 kg/m2, score=2), obesity (BMI≥30 kg/m2, score=3), diabetes (score=1), and stroke (score=2) were significantly independently predictive of moderate-to-severe SDB and formulated the score. The score performed well to predict moderate-to-severe SDB with a C-statistic of 0.73 (95% CI: 0.67–0.79, P<0.001) in the derivation cohort, and 0.67 (95% CI: 0.57–0.77, P<0.001) in the validation cohort. As a rule-out test, a score of ≤3 had a negative predictive value of 77% for moderate-to-severe SDB (91% for severe SDB). A score of ≥4 had an intermediate positive likelihood ratio (PLR) of 2 for moderate-to-severe SDB (2.2 for severe SDB), while a score of ≥5 had a high PLR of 6.5 and 6.8 for moderate-to-severe SDB and severe SDB respectively. Sensitivity and specificity table Conclusion A novel risk score comprising clinical characteristics can identify patients with AF likely to benefit from further assessment for SDB. Application of this model may aid optimise resource utilisation and facilitate timely patient care.

scholarly journals Contrast-Enhanced Ultrasound in the Differential Diagnosis and Risk Stratification of ACR TI-RADS Category 4 and 5 Thyroid Nodules With Non-Hypovascular

2021 ◽  
Vol 11 ◽  
Author(s):  
Yanfang Wang ◽  
Tiantian Dong ◽  
Fang Nie ◽  
Guojuan Wang ◽  
Ting Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Differential Diagnosis ◽  
Risk Stratification ◽  
Risk Score ◽  
Thyroid Nodules ◽  
Validation Cohort ◽  
Contrast Enhanced Ultrasound ◽  
Derivation Cohort ◽  
Contrast Enhanced ◽  
Independent Risk Factors

ObjectiveThis study aims to investigate the value of contrast-enhanced ultrasound (CEUS) in the differential diagnosis and risk stratification of ACR TI-RADS category 4 and 5 thyroid nodules with non-hypovascular.MethodsFrom January 2016 to December 2019 in our hospital, 217 ACR TI-RADS category 4 and 5 nodules with non-hypovascular in 210 consecutive patients were included for a derivation cohort. With surgery and/or fine-needle aspiration (FNA) as a reference, conventional ultrasound (US) features and CEUS features were analyzed. Multivariate logistic regression analysis was used to screen the independent risk factors and establish a risk predictive model. Between January 2020 and March 2021, a second cohort of 100 consecutive patients with 101 nodules were included for an external validation cohort. The model was converted into a simplified risk score and was validated in the validation cohort. The area under the receiver operating characteristic curves (AUC) were used to assess the models’ diagnostic performance.ResultsMicro-calcification, irregular margin, earlier wash-out, centripetal enhancement, and absence of ring enhancement were independent risk factors and strongly discriminated malignancy in the derivation cohort (AUC = 0.921, 95% CI 0.876–0.953) and the validation cohort (0.900, 0.824–0.951). There was no significant difference (P = 0.3282) between the conventional US and CEUS in differentiating malignant non-hypovascular thyroid nodules, but a combination of them (the predictive model) had better performance than the single method (all P &lt;0.05), with a sensitivity of 87.0%, specificity of 86.2%, and accuracy of 86.6% in the derivation cohort. The risk score based on the independent risk factors divided non-hypovascular thyroid nodules into low-suspicious (0–3 points; malignancy risk &lt;50%) and high-suspicious (4–7 points; malignancy risk ≥ 50%), the latter with nodule ≥10mm was recommended for FNA. The risk score showed a good ability of risk stratification in the validation cohort. Comparing ACR TI-RADS in screening suitable non-hypovascular nodules for FNA, the risk score could avoid 30.8% benign nodules for FNA.ConclusionsCEUS is helpful in combination with conventional US in differentiating ACR TI-RADS category 4 and 5 nodules with non-hypovascular. The risk score in this study has the potential to improve the diagnosis and risk stratification of non-hypovascular thyroid nodules.

scholarly journals A Pre-Interventional Scale to Predict in situ Atherosclerotic Thrombosis in Acute Vertebrobasilar Artery Occlusion Patients

2021 ◽  
Vol 12 ◽  
Author(s):  
Mingming Zha ◽  
Min Wu ◽  
Xianjun Huang ◽  
Xiaohao Zhang ◽  
Kangmo Huang ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Validation Cohort ◽  
Artery Occlusion ◽  
Serum Glucose ◽  
Derivation Cohort ◽  
Vertebrobasilar Artery ◽  
Lemeshow Test ◽  
History Of ◽  
Vertebrobasilar Artery Occlusion

Background and Purpose: Determining the occlusion mechanism before endovascular treatment (EVT) is of great significance for acute large vessel occlusion patients. We aimed to develop and validate a simple pre-EVT scale with readily available variables for predicting in situ atherosclerotic thrombosis (ISAT) in acute vertebrobasilar artery occlusion (VBAO) patients.Materials and Methods: Consecutive patients were retrieved from Nanjing Stroke Registry Program between January 2014 and December 2019 as a derivation cohort. Anonymous data of consecutive patients between January 2014 and December 2019 were collected from another comprehensive stroke center as an external validation cohort. Demographics, medical histories, and clinical characteristics were collected. ISAT was defined according to the following criteria: (a) detection of moderate to severe (≥50%) stenosis or stenosis with significant distal flow impairment at the occluded segment when successful reperfusion was achieved; (b) transient visualization of eccentric plaque contour or a recurrent re-occlusion tendency when reperfusion was unsuccessful. Logistic regression was taken to develop a predictive scale. The performance of the scale was assessed by area under the receiver operating characteristic curve (AUC) and Hosmer–Lemeshow test.Results: ISAT was observed in 41 of 95 (43.2%) patients included in the derivation cohort. The ISAT predictive scale consisted of three pre-interventional predictors, including the history of hypertension, atrial fibrillation rhythm, and baseline serum glucose level ≥7.55 mmol/L. The model depicted acceptable calibration (Hosmer–Lemeshow test, P = 0.554) and good discrimination (AUC, 0.853; 95% confidence interval, 0.775–0.930). The optimal cutoff value of the ISAT scale was 1 point with 95.1% sensitivity, 64.8% specificity, and 77.9% accuracy. In the validation cohort, the discrimination ability was still promising with an AUC value of 0.800 (0.682–0.918).Conclusion: The three-item scale comprised of the history of hypertension, atrial fibrillation rhythm, and dichotomous serum glucose level had a promising predictive value for ISAT before EVT in acute VBAO patients.

scholarly journals A Prediction Model with Lifestyle in Addition to Previously Known Risk Factors Improves Its Predictive Ability for Cardiovascular Death

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Masatoshi Nishimoto ◽  
Miho Tagawa ◽  
Masaru Matsui ◽  
Masahiro Eriguchi ◽  
Ken-ichi Samejima ◽  
...  
Keyword(s):  
Risk Factors ◽  
Prediction Model ◽  
Proportional Hazards Model ◽  
Predictive Ability ◽  
Cardiovascular Death ◽  
Lifestyle Factors ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Derivation Cohort ◽  
Kaplan Meier

Abstract This longitudinal cohort study aimed to create a novel prediction model for cardiovascular death with lifestyle factors. Subjects aged 40–74 years in the Japanese nationwide Specific Health Checkup Database in 2008 were included. Subjects were randomly assigned to the derivation and validation cohorts by a 2:1 ratio. Points for the prediction model were determined using regression coefficients that were derived from the Cox proportional hazards model in the derivation cohort. Models 1 and 2 were developed using known risk factors and known factors with lifestyle factors, respectively. The models were validated by comparing Kaplan-Meier curves between the derivation and validation cohorts, and by calibration plots in the validation cohort. Among 295,297 subjects, data for 120,823 were available. There were 310 cardiovascular deaths during a mean follow-up of 3.6 years. Model 1 included known risk factors. In model 2, weight gain, exercise habit, gait speed, and drinking alcohol were additionally included as protective factors. Kaplan-Meier curves matched better between the derivation and validation cohorts in model 2, and model 2 was better calibrated. In conclusion, our prediction model with lifestyle factors improved the predictive ability for cardiovascular death.

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