Lucrecia María Burgos, Andreina Gil Ramírez, Victoria Galizia Brito, Leonardo Seoane, Juan Francisco Furmento, Juan Espinoza, Mirta Diez, Mariano Benzadon, Daniel Navia
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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).</p><p><strong>Results: </strong>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).</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":15072,"journal":{"name":"Journal of atrial fibrillation","volume":"13 2","pages":"2249"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8691308/pdf/jafib-13-02249.pdf","citationCount":"2","resultStr":"{\"title\":\"Development and Validation of A Simple Clinical Risk Prediction Model for New-Onset Postoperative Atrial Fibrillation After Cardiac Surgery: Nopaf Score.\",\"authors\":\"Lucrecia María Burgos, Andreina Gil Ramírez, Victoria Galizia Brito, Leonardo Seoane, Juan Francisco Furmento, Juan Espinoza, Mirta Diez, Mariano Benzadon, Daniel Navia\",\"doi\":\"10.4022/jafib.2249\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>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.</p><p><strong>Methods: </strong>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).</p><p><strong>Results: </strong>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).</p><p><strong>Conclusion: </strong>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. 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引用次数: 2
摘要
术后心房颤动(POAFib)发生在心脏手术后患者的20%至40%,并与围手术期发病率和死亡率增加相关。我们的目的是建立和验证一个简单的临床风险模型来预测心脏手术后POAFib的发生。方法:采用分析性单中心回顾性队列研究,纳入2004年至2017年连续接受心脏手术的POAFib患者。为了创建预测风险评分,使用75%的随机样本进行逻辑回归模型。然后将模型系数转换为数值风险评分,定义低风险(≤1分)、中风险(2-5分)和高风险(≥6分)三组。使用剩余25%的患者验证评分。通过曲线下面积(AUC) ROC评估鉴别性,并使用Hosmer-Lemeshow (HL)检验、校准图和预期事件与观测事件之比(E/O)进行校准。结果:65009例患者接受心脏手术:冠状动脉旁路移植术(CABG)占52%,瓣膜手术占20%,CABG联合瓣膜手术占14%,其他手术占12%。新发房颤1222例(18.77%)。在多因素分析中,年龄、使用体外循环泵、左室射血分数(LVEF)严重降低、慢性肾脏疾病和心力衰竭是POAFib的独立危险因素,而他汀类药物的使用是一个保护因素。NOPAF评分通过对每个独立风险预测因子加分来计算。在衍生队列中,模型的AUC为0.71 (CI95%为0.69 ~ 0.72),在验证队列中,模型也具有良好的判别性(AUC 0.67, IC 0.64 ~ 0.70)和良好的校准性(HL P = 0.24)。E/O比值为1 (CI 95%: 0.89-1.12)。根据风险类别,POAFib发生率低5%;结论:从大量住院人群中,我们开发并验证了一种简单的风险评分,称为NOPAF,基于临床变量,准确地划分了POAFib的风险。该评分有助于在心脏手术前识别高危患者,以加强术后房颤预防。
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.