The prognosis of patients hospitalized with a first episode of heart failure, validation of two scores: PREDICE and AHEAD

References

• Ponikowski P, Voors AA, Anker SD, et al. 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J. 2016;37:2129–2200. doi:10.1093/eurheartj/ehw12827206819
   PubMed Web of Science ®Google Scholar
• Ceia F, Fonseca C, Mota T, et al. Prevalence of chronic heart failure in Southwestern Europe: the EPICA study. Eur J Heart Fail. 2002;4:531–539. doi:10.1016/s1388-9842(02)00034-x12167394
   PubMed Web of Science ®Google Scholar
• Van Riet EES, Hoes AW, Wagenaar KP, Limburg A, Landman MAJ, Rutten FH. Epidemiology of heart failure: the prevalence of heart failure and ventricular dysfunction in older adults over time. A systematic review. Eur J Heart Fail. 2016;18:242–252. doi:10.1002/ejhf.48326727047
   PubMed Web of Science ®Google Scholar
• Defunciones según la Causa de Muerte 2014. Instituto Nacional de Estadística. [Internet, Spanish]. Available from: http://www.ine.es/jaxi/Datos.htm?path=/t15/p417/a2014/l0/&file=01001.px. Accessed 151, 2019
   Google Scholar
• Harjola VP, Follath F, Nieminen MS, et al. Characteristics, outcomes, and predictors of mortality at 3 months and 1 year in patients hospitalized for acute heart failure. Eur J Heart Fail. 2010;12:239–248. doi:10.1093/eurjhf/hfq00220156940
   PubMed Web of Science ®Google Scholar
• Gómez de la Cámara A, Tapia PM, Rivas FJP, Rodríguez-Moñino AP. ¿Qué pretenden estimar los estudios de pronóstico? Revisión de la metodología en la investigación pronóstica. Med Clin (Barc). 2010;135:456–461. doi:10.1016/j.medcli.2009.03.02019520395
   PubMed Web of Science ®Google Scholar
• Moons KGM, Altman DG, Reitsma JB, et al. Transparent Reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med. 2015;162:W1–W73. doi:10.7326/M14-069825560730
   PubMed Web of Science ®Google Scholar
• Alba AC, Agoritsas T, Jankowski M, et al. Risk prediction models for mortality in ambulatory patients with heart failure: a systematic review. Circ Heart Fail. 2013;6:881–889. doi:10.1161/CIRCHEARTFAILURE.112.00004323888045
   PubMed Web of Science ®Google Scholar
• Ouwerkerk W, Voors AA, Zwinderman AH. Factors influencing the predictive power of models for predicting mortality and/or heart failure hospitalization in patients with heart failure. JACC Heart Fail. 2014;2:429–436. doi:10.1016/j.jchf.2014.04.00625194294
   PubMed Web of Science ®Google Scholar
• Stevenson LW, Davis RB. Model building as an educational hobby. Circ Heart Fail. 2016;9:pii: e003457. doi:10.1161/CIRCHEARTFAILURE.116.003457
   Web of Science ®Google Scholar
• Rahimi K, Bennett D, Conrad N, et al. Risk prediction in patients with heart failure: a systematic review and analysis. JACC Heart Fail. 2014;2:440–446. doi:10.1016/j.jchf.2014.04.00825194291
   PubMed Web of Science ®Google Scholar
• Gómez de la Cámara A, Guerra Vales JM, Tapia PM, et al. Role of biological and non biological factors in congestive heart failure mortality: PREDICE-SCORE: a clinical prediction rule. Cardiol J. 2012;19:578–585.23224919
   PubMed Web of Science ®Google Scholar
• Spinar J, Jarkovsky J, Spinarova L, et al. AHEAD score–long-term risk classification in acute heart failure. Int J Cardiol. 2016;202:21–26. doi:10.1016/j.ijcard.2015.08.18726386914
   PubMed Web of Science ®Google Scholar
• Levy WC, Anand IS. Heart failure risk prediction models: what have we learned? JACC Heart Fail. 2014;2:437–439. doi:10.1016/j.jchf.2014.05.00625194289
   PubMed Web of Science ®Google Scholar
• Altman DG, Royston P. What do we mean by validating a prognostic model? Stat Med. 2000;19:453–473.10694730
   PubMed Web of Science ®Google Scholar
• Debray TPA, Vergouwe Y, Koffijberg H, Nieboer D, Steyerberg EW, Moons KGM. A new framework to enhance the interpretation of external validation studies of clinical prediction models. J Clin Epidemiol. 2015;68:279–289. doi:10.1016/j.jclinepi.2014.06.01825179855
   PubMed Web of Science ®Google Scholar
• Steyerberg E Clinical prediction models: a practical approach to development, validation, and updating [Internet]. Springer Science & Business Media; 2008 [Internet] Available from: https://books.google.es/books?hl=es‎&id=kHGK58cLsMIC&oi=fnd&pg=PR2&dq=Clinical+Prediction+Models:+A+Practical+Approach+to+Development,+Validation,+and+Updating&ots=TMXdI0eLhi&sig=G1pavyIK0wWc141D3kZlQEERlNw. Accessed 151, 2019.
   Google Scholar
• Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of diet in renal disease study group. Ann Intern Med. 1999;130:461–470. doi:10.7326/0003-4819-130-6-199903160-0000210075613
   PubMed Web of Science ®Google Scholar
• Harrell F Regression modeling strategies: with applications to linear models, logistic and ordinal regression, and survival analysis. Springer; 2015 [Internet, Spanish] Available from: https://books.google.es/books?hl=es‎&id=94RgCgAAQBAJ&oi=fnd&pg=PR7&dq=Regression+Modeling+Strategies:+With+Applications+to+Linear+Models,+Logistic+Regression,+and+Survival+Analysis&ots=Zzq7Uo7S2m&sig=DuEFLtS8jUTOcoCwaI-oizMZZeI. Accessed 151, 2019.
   Google Scholar
• Núñez E, Steyerberg EW, Núñez J. Regression modeling strategies. Rev Esp Cardiol. 2011;64:501–507. doi:10.1016/j.recesp.2011.01.01921531065
   PubMed Web of Science ®Google Scholar
• Moons KGM, Kengne AP, Grobbee DE, et al. Risk prediction models: II. External validation, model updating, and impact assessment. Heart. 2012;98:691–698. doi:10.1136/heartjnl-2011-30124722397946
   PubMed Web of Science ®Google Scholar
• Altman DG, Vergouwe Y, Royston P, Moons KGM. Prognosis and prognostic research: validating a prognostic model. BMJ. 2009;338:b605. doi:10.1136/bmj.b90219477892
   PubMed Web of Science ®Google Scholar
• Steyerberg EW, Moons KGM, van der Windt DA, et al. Prognosis research strategy (PROGRESS) 3: prognostic model research. PLoS Med. 2013;10:e1001381. doi:10.1371/journal.pmed.100138123393430
   PubMed Web of Science ®Google Scholar
• Vergouwe Y, Steyerberg EW, Eijkemans MJC, Habbema JDF. Substantial effective sample sizes were required for external validation studies of predictive logistic regression models. J Clin Epidemiol. 2005;58:475–583. doi:10.1016/j.jclinepi.2004.06.01715845334
   PubMed Web of Science ®Google Scholar
• Collins GS, de Groot JA, Dutton S, et al. External validation of multivariable prediction models: a systematic review of methodological conduct and reporting. BMC Med Res Methodol. 2014;14:40. doi:10.1186/1471-2288-14-4024645774
   PubMed Web of Science ®Google Scholar
• Lazzarini V, Mentz RJ, Fiuzat M, Metra M, O’Connor CM. Heart failure in elderly patients: distinctive features and unresolved issues. Eur J Heart Fail. 2013;15:717–723. doi:10.1093/eurjhf/hft02823429975
   PubMed Web of Science ®Google Scholar
• Nielsen FE, Mard S. Single-living is associated with increased risk of long-term mortality among employed patients with acute myocardial infarction. Clin Epidemiol. 2010;2:91–98.20865108
   PubMedGoogle Scholar
• Holt-Lunstad J, Smith TB, Layton JB. Social relationships and mortality risk: a meta-analytic review Brayne C, editor PLoS Med. 2010;7:e1000316. doi:10.1371/journal.pmed.100031620668659
   PubMed Web of Science ®Google Scholar
• Rudski LG, Lai WW, Afilalo J, et al. Guidelines for the echocardiographic assessment of the right heart in adults: a report from the American society of echocardiography. J Am Soc Echocardiogr. 2010;23:685–713. doi:10.1016/j.echo.2010.05.01020620859
   PubMed Web of Science ®Google Scholar
• Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373–383.3558716
   PubMedGoogle Scholar
• Ely JW. Answering physicians’ clinical questions: obstacles and potential solutions. J Am Med Inform Assoc. 2004;12:217–224. doi:10.1197/jamia.M160815561792
   PubMed Web of Science ®Google Scholar
• Kawamoto K. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ. 2005;330:765–770. doi:10.1136/bmj.38398.500764.8F15767266
   PubMed Web of Science ®Google Scholar
• Levy WC, Mozaffarian D, Linker DT, et al. The Seattle heart failure model: prediction of survival in heart failure. Circulation. 2006;113:1424–1433. doi:10.1161/CIRCULATIONAHA.105.58410216534009
   PubMed Web of Science ®Google Scholar
• Cohen-Solal A, Laribi S, Ishihara S, et al. Prognostic markers of acute decompensated heart failure: the emerging roles of cardiac biomarkers and prognostic scores. Arch Cardiovasc Dis. 2015;108:64–74. doi:10.1016/j.acvd.2014.10.00225534886
   PubMed Web of Science ®Google Scholar
• Miralda GP, Soriano N, Brotons C, et al. Baseline characteristics and determinants of outcome in a patient population admitted for heart failure to a general hospital. Rev Esp Cardiol. 2002;55:571–578.12113715
   PubMed Web of Science ®Google Scholar
• Jondeau G, Arnoult F, Caligiuri G, et al. Practical management of heart failure with preserved ejection fraction. A modest proposal. Arch Cardiovasc Dis. 2013;106:345–348. doi:10.1016/j.acvd.2013.04.00523810131
   PubMed Web of Science ®Google Scholar
• Nutter AL, Tanawuttiwat T, Silver MA. Evaluation of 6 prognostic models used to calculate mortality rates in elderly heart failure patients with a fatal heart failure admission. Congest Heart Fail. 2010;16:196–201. doi:10.1111/j.1751-7133.2010.00180.x20887615
   PubMedGoogle Scholar