Advanced Search

CN 34-1304/RISSN 1674-3679

Volume 24 Issue 4
Jun.  2020
Turn off MathJax
Article Contents
HUANG Jia-qi, ZHONG Li, ZHANG Zhi-hui, WU Na, WU Long, XIANG Ying, LI Cheng-ying, LI Ya-fei. Construction and comparative analysis of prognostic scoring system in patients with atrial fibrillation[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2020, 24(4): 473-479. doi: 10.16462/j.cnki.zhjbkz.2020.04.020
Citation: HUANG Jia-qi, ZHONG Li, ZHANG Zhi-hui, WU Na, WU Long, XIANG Ying, LI Cheng-ying, LI Ya-fei. Construction and comparative analysis of prognostic scoring system in patients with atrial fibrillation[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2020, 24(4): 473-479. doi: 10.16462/j.cnki.zhjbkz.2020.04.020

Construction and comparative analysis of prognostic scoring system in patients with atrial fibrillation

doi: 10.16462/j.cnki.zhjbkz.2020.04.020
Funds:  Project of Youth Science Foundation of National Natural Science Foundation of China(81502883)
More Information
  • Corresponding author: LI Ya-fei, E-mail:liyafei2008@hotmail.com
  • Received Date: 2019-09-14
  • Rev Recd Date: 2020-01-09
  • Publish Date: 2020-04-10
  •   Objective   To construct a score system for predicting the prognosis of atrial fibrillation(AF) in China, and to compare its predictive ability.   Methods   A total of 275 patients with new-onset AF were continuously enrolled in the study. The outcome events of follow-up included stroke and all-cause mortality. Prognostic-related epidemiological and clinical information were collected. The blood concentration of N-terminal B-type natriuretic peptide(NT-proBNP), high-sensitivity troponin T(hs-cTnT) and growth differentiation factor(GDF)-15 were detected. A Cox proportional hazards regression model was used to develop novel risk scoring system. C-statistics and calibration plots were used to estimate and compare the predictive ability of risk scores.   Results   Multivariate Cox regression analysis showed that history of diabetes, history of transient ischemic attack, history of stroke and plasma level of NT-proBNP were independently associated with the risk of stroke. Age, history of heart failure, plasma level of hs-cTnT and GDF-15 were independent risk factors of all-cause mortality. The C-statistic of the stroke-risk score was similar to that of the CHA2 DS2-VASc score and ABC(age, biomarker, clinical history)-stroke score; the C-statistic of the death-risk score was similar to that of ABC-death score and significantly higher than that of the CHA2 DS2-VASc score.   Conclusions   The stroke and death risk scoring system of atrial fibrillation patients constructed in this study showed a good predictive performance. The nomograms of these scoring systems are expected to be auxiliary tools for clinical decision-making.
  • loading
  • Chao TF, Liu CJ, Tuan TC, et al. Lifetime risks, projected numbers, and adverse outcomes in Asian patients with atrial fibrillation: areport from the Taiwan nationwide AF cohort study[J]. Chest, 2018, 153(2): 453-466. DOI: 10.1016/j.chest.2017.10.001.
    European Heart Rhythm Association, European Association for Cardio-Thoracic Surgery, Camm AJ, et al. Guidelines for the management of atrial fibrillation: the task force for the management of atrial fibrillation of the European society of cardiology(ESC)[J]. Eur Heart J, 2010, 31(19): 2369-2429. DOI: 10.1093/eurheartj/ehq278.
    Hart RG, Pearce LA, Aguilar MI. Meta-analysis: antithrombotic therapy to prevent stroke in patients who have nonvalvular atrial fibrillation[J]. Ann Intern Med, 2007, 146(12): 857-867. DOI: 10.7326/0003-4819-146-12-200706190-00007.
    The SPAF III writing committee for the stroke prevention in atrial fibrillation investigators. Patients with nonvalvular atrial fibrillation at low risk of stroke during treatment with aspirin: stroke prevention in atrial fibrillation III study[J]. JAMA, 1998, 279(16): 1273-1277. DOI: 10.1001/jama.279.16.1273.
    Gage BF, Waterman AD, Shannon W, et al. Validation of clinical classification schemes for predicting stroke: results from the national registry of atrial fibrillation[J]. JAMA, 2001, 285(22): 2864-2870. DOI: 10.1001/jama.285.22.2864.
    Lip GY, Nieuwlaat R, Pisters R, et al. Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation[J]. Chest, 2010, 137(2): 263-272. DOI: 10.1378/chest.09-1584.
    Kirchhof P, Benussi S, Kotecha D, et al. 2016 ESC guidelines for the management of atrial fibrillation developed in collaboration with EACTS[J]. Eur Heart J, 2016, 37(38): 2893-2962. DOI: 10.1093/eurheartj/ehw210.
    January CT, Wann LS, Alpert JS, et al. 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American college of cardiology/American heart association task force on practice guidelines and the heart rhythm society[J]. Circulation, 2014, 130(23): 199-267. DOI: 10.1161/cir.0000000000000041.
    Apiyasawat S, Tangcharoen T, Wisaratapong T, et al. CHA2DS2-VASc scores predict mortality after hospitalization for atrial fibrillation[J]. Int J Cardiol, 2015, 185: 293-296. DOI: 10.1016/j.ijcard.2015.03.180.
    Hijazi Z, Lindback J, Alexander JH, et al. The ABC(age, biomarkers, clinical history)stroke risk score: a biomarker-based risk score for predicting stroke in atrial fibrillation[J]. Eur Heart J, 2016, 37(20): 1582-1590. DOI: 10.1093/eurheartj/ehw054.
    Hijazi Z, Oldgren J, Lindback J, et al. A biomarker-based risk score to predict death in patients with atrial fibrillation: the ABC(age, biomarkers, clinical history)death risk score[J]. Eur Heart J, 2018, 39(6): 477-485. DOI: 10.1093/eurheartj/ehx584.
    Camp RL, Dolled-Filhart M, Rimm DL. X-tile: a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization[J]. Clin Cancer Res, 2004, 10(21): 7252-7259. DOI: 10.1158/1078-0432.ccr-04-0713.
    Kang L, Chen W, Petrick NA, et al. Comparing two correlated C indices with right-censored survival outcome: a one-shot nonparametric approach[J]. Stat Med, 2015, 34(4): 685-703. DOI: 10.1002/sim.6370.
    Pisters R, Lane DA, Nieuwlaat R, et al. A novel user-friendly score(HAS-BLED)to assess 1-year risk of major bleeding in patients with atrial fibrillation: the Euro Heart Survey[J]. Chest, 2010, 138(5): 1093-1100. DOI: 10.1378/chest.10-0134.
    Hijazi Z, Oldgren J, Siegbahn A, et al. Application of biomarkers for risk stratification in patients with atrial fibrillation[J]. Clin Chem, 2017, 63(1): 152-164. DOI: 10.1373/clinchem.2016.255182.
    Hijazi Z, Oldgren J, Andersson U, et al. Cardiac biomarkers are associated with an increased risk of stroke and death in patients with atrial fibrillation: a randomized evaluation of long-term anticoagulation therapy(RE-LY)substudy[J]. Circulation, 2012, 125(13): 1605-1616. DOI: 10.1161/circulationaha.111.038729.
    Wallentin L, Hijazi Z, Andersson U, et al. Growth differentiation factor 15, a marker of oxidative stress and inflammation, for risk assessment in patients with atrial fibrillation: insights from the apixaban for reduction in stroke and other thromboembolic events in atrial fibrillation(ARISTOTLE)trial[J]. Circulation, 2014, 130(21), 130: 1847-1858. DOI: 10.1161/circulationaha.114.011204.
    Agency for Healthcare Research and Quality(US). Stroke prevention in patients with atrial fibrillation: a systematic review update[R]. Rockville, MD, 2018.
    Proietti M, Farcomeni A, Romiti GF, et al. Association between clinical risk scores and mortality in atrial fibrillation: systematic review and network meta-regression of 669, 000 patients[J]. Eur J Prev Cardiol, 2018: 2047487318817662. DOI: 10.1177/2047487318817662.
    Fanola CL, Giugliano RP, Ruff CT, et al. A novel risk prediction score in atrial fibrillation for a net clinical outcome from the ENGAGE AF-TIMI 48 randomized clinical trial[J]. Eur Heart J, 2017, 38(12): 888-896. DOI: 10.1093/eurheartj/ehw565.
    Fox KAA, Lucas JE, Pieper KS, et al. Improved risk stratification of patients with atrial fibrillation: an integrated GARFIELD-AF tool for the prediction of mortality, stroke and bleed in patients with and without anticoagulation[J]. BMJ Open, 2017, 7(12): e017157. DOI: 10.1136/bmjopen-2017-017157.
    Balachandran VP, Gonen M, Smith JJ, et al. Nomograms in oncology: more than meets the eye[J]. Lancet Oncol, 2015, 16(4): e173-180. DOI: 10.1016/s1470-2045(14)71116-7.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(1)  / Tables(3)

    Article Metrics

    Article views (395) PDF downloads(28) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return