BACKGROUND: A critical challenge for physicians facing patients presenting with signs and symptoms of acute heart failure (AHF) is how and where to best manage them. Currently, most patients evaluated for AHF are admitted to the hospital, yet not all warrant inpatient care. Up to 50% of admissions could be potentially avoided and many admitted patients could be discharged after a short period of observation and treatment. Methods for identifying patients that can be sent home early are lacking. Improving the physician's ability to identify and safely manage low-risk patients is essential to avoiding unnecessary use of hospital beds. METHODS: Two studies (STRATIFY and DECIDE) have been funded by the National Heart Lung and Blood Institute with the goal of developing prediction rules to facilitate early decision making in AHF. Using prospectively gathered evaluation and treatment data from the acute setting (STRATIFY) and early inpatient stay (DECIDE), rules will be generated to predict risk for death and serious complications. Subsequent studies will be designed to test the external validity, utility, generalizability and cost-effectiveness of these prediction rules in different acute care environments representing racially and socioeconomically diverse patient populations. RESULTS: A major innovation is prediction of 5-day as well as 30-day outcomes, overcoming the limitation that 30-day outcomes are highly dependent on unpredictable, post-visit patient and provider behavior. A novel aspect of the proposed project is the use of a comprehensive cardiology review to correctly assign post-treatment outcomes to the acute presentation. CONCLUSIONS: Finally, a rigorous analysis plan has been developed to construct the prediction rules that will maximally extract both the statistical and clinical properties of every data element. Upon completion of this study we will subsequently externally test the prediction rules in a heterogeneous patient cohort.
BACKGROUND: A critical challenge for physicians facing patients presenting with signs and symptoms of acute heart failure (AHF) is how and where to best manage them. Currently, most patients evaluated for AHF are admitted to the hospital, yet not all warrant inpatient care. Up to 50% of admissions could be potentially avoided and many admitted patients could be discharged after a short period of observation and treatment. Methods for identifying patients that can be sent home early are lacking. Improving the physician's ability to identify and safely manage low-risk patients is essential to avoiding unnecessary use of hospital beds. METHODS: Two studies (STRATIFY and DECIDE) have been funded by the National Heart Lung and Blood Institute with the goal of developing prediction rules to facilitate early decision making in AHF. Using prospectively gathered evaluation and treatment data from the acute setting (STRATIFY) and early inpatient stay (DECIDE), rules will be generated to predict risk for death and serious complications. Subsequent studies will be designed to test the external validity, utility, generalizability and cost-effectiveness of these prediction rules in different acute care environments representing racially and socioeconomically diverse patient populations. RESULTS: A major innovation is prediction of 5-day as well as 30-day outcomes, overcoming the limitation that 30-day outcomes are highly dependent on unpredictable, post-visit patient and provider behavior. A novel aspect of the proposed project is the use of a comprehensive cardiology review to correctly assign post-treatment outcomes to the acute presentation. CONCLUSIONS: Finally, a rigorous analysis plan has been developed to construct the prediction rules that will maximally extract both the statistical and clinical properties of every data element. Upon completion of this study we will subsequently externally test the prediction rules in a heterogeneous patient cohort.
Authors: Mariell Jessup; William T Abraham; Donald E Casey; Arthur M Feldman; Gary S Francis; Theodore G Ganiats; Marvin A Konstam; Donna M Mancini; Peter S Rahko; Marc A Silver; Lynne Warner Stevenson; Clyde W Yancy Journal: Circulation Date: 2009-03-26 Impact factor: 29.690
Authors: G Michael Felker; Jeffrey D Leimberger; Robert M Califf; Michael S Cuffe; Barry M Massie; Kirkwood F Adams; Mihai Gheorghiade; Christopher M O'Connor Journal: J Card Fail Date: 2004-12 Impact factor: 5.712
Authors: Douglas S Lee; Michael J Schull; David A Alter; Peter C Austin; Andreas Laupacis; Alice Chong; Jack V Tu; Thérèse A Stukel Journal: Circ Heart Fail Date: 2010-01-27 Impact factor: 8.790
Authors: Harriette G C Van Spall; Clare Atzema; Michael J Schull; Gary E Newton; Susanna Mak; Alice Chong; Jack V Tu; Thérèse A Stukel; Douglas S Lee Journal: PLoS One Date: 2011-08-10 Impact factor: 3.240
Authors: Alan B Storrow; Cathy A Jenkins; Wesley H Self; Pauline T Alexander; Tyler W Barrett; Jin H Han; Candace D McNaughton; Benjamin S Heavrin; Mihai Gheorghiade; Sean P Collins Journal: JACC Heart Fail Date: 2014-04-30 Impact factor: 12.035
Authors: Gregory J Fermann; Phillip D Levy; Peter Pang; Javed Butler; S Imran Ayaz; Douglas Char; Patrick Dunn; Cathy A Jenkins; Christy Kampe; Yosef Khan; Vijaya A Kumar; JoAnn Lindenfeld; Dandan Liu; Karen Miller; W Frank Peacock; Samaa Rizk; Chad Robichaux; Russell L Rothman; Jon Schrock; Adam Singer; Sarah A Sterling; Alan B Storrow; Cheryl Walsh; John Wilburn; Sean P Collins Journal: Circ Heart Fail Date: 2017-02 Impact factor: 8.790
Authors: Quinn S Wells; Deepak K Gupta; J Gustav Smith; Sean P Collins; Alan B Storrow; Jane Ferguson; Maya Landenhed Smith; Jill M Pulley; Sarah Collier; Xiaoming Wang; Dan M Roden; Robert E Gerszten; Thomas J Wang Journal: J Am Coll Cardiol Date: 2019-05-07 Impact factor: 24.094
Authors: Sean Collins; Alan B Storrow; Nancy M Albert; Javed Butler; Justin Ezekowitz; G Michael Felker; Gregory J Fermann; Gregg C Fonarow; Michael M Givertz; Brian Hiestand; Judd E Hollander; David E Lanfear; Phillip D Levy; Peter S Pang; W Frank Peacock; Douglas B Sawyer; John R Teerlink; Daniel J Lenihan Journal: J Card Fail Date: 2014-07-18 Impact factor: 5.712
Authors: Sean P Collins; Alan B Storrow; Phillip D Levy; Nancy Albert; Javed Butler; Justin A Ezekowitz; G Michael Felker; Gregory J Fermann; Gregg C Fonarow; Michael M Givertz; Brian Hiestand; Judd E Hollander; David E Lanfear; Peter S Pang; W Frank Peacock; Douglas B Sawyer; John R Teerlink; Daniel J Lenihan Journal: Acad Emerg Med Date: 2014-11-25 Impact factor: 3.451
Authors: Wesley H Self; Alan B Storrow; Oliver Hartmann; Tyler W Barrett; Gregory J Fermann; Alan S Maisel; Joachim Struck; Andreas Bergmann; Sean P Collins Journal: Am J Emerg Med Date: 2015-10-24 Impact factor: 2.469
Authors: Sean P Collins; Cathy A Jenkins; Frank E Harrell; Dandan Liu; Karen F Miller; Christopher J Lindsell; Allen J Naftilan; John A McPherson; David J Maron; Douglas B Sawyer; Neal L Weintraub; Gregory J Fermann; Susan K Roll; Matthew Sperling; Alan B Storrow Journal: JACC Heart Fail Date: 2015-10 Impact factor: 12.035