BACKGROUND: Current guidelines suggest that patients with low likelihoods of survival may be excluded from intensive care. Patients with new or exacerbated congestive heart failure are frequently but not inevitably admitted to critical care units. OBJECTIVE: To assess how well physicians could predict the probability of survival for acutely ill patients with congestive heart failure, and in particular how well they could identify patients with small chances of survival. METHODS: This was a prospective cohort study done in the emergency departments of a university hospital, a Veterans Affairs medical center, and a community hospital. The study population was consecutive adults for whom new or exacerbated congestive heart failure, diagnosed clinically, was a major reason for the emergency department visit. Physicians caring for the study patients in the emergency departments recorded their judgments of the numeric probability that each patient would survive for 90 days and for 1 year. The patients vital status at 90 days and 1 year was ascertained by multiple means, including interview, chart review, and review of hospital and state databases. RESULTS: By calibration curve analysis, the physicians underestimated survival probability at both 90 days and 1 year, particularly for patients they judged to have the lowest probabilities of survival. Their predictions had modest discriminating ability (receiver operating characteristic curve areas, 0.66 [SE = 0.020] for 90 days; 0.63 [SE = 0.017] for 1 year). The physicians identified only 15 patients they judged to have a 90-day survival probability of 10% or less, whose survival rate was actually 33.3%. CONCLUSIONS: Physicians have great difficulty predicting survival for patients with acute congestive heart failure and cannot identify patients with poor chances of survival. Current triage guidelines that suggest patients with poor chances of survival may be excluded from critical care may be impractical or harmful.
BACKGROUND: Current guidelines suggest that patients with low likelihoods of survival may be excluded from intensive care. Patients with new or exacerbated congestive heart failure are frequently but not inevitably admitted to critical care units. OBJECTIVE: To assess how well physicians could predict the probability of survival for acutely ill patients with congestive heart failure, and in particular how well they could identify patients with small chances of survival. METHODS: This was a prospective cohort study done in the emergency departments of a university hospital, a Veterans Affairs medical center, and a community hospital. The study population was consecutive adults for whom new or exacerbated congestive heart failure, diagnosed clinically, was a major reason for the emergency department visit. Physicians caring for the study patients in the emergency departments recorded their judgments of the numeric probability that each patient would survive for 90 days and for 1 year. The patients vital status at 90 days and 1 year was ascertained by multiple means, including interview, chart review, and review of hospital and state databases. RESULTS: By calibration curve analysis, the physicians underestimated survival probability at both 90 days and 1 year, particularly for patients they judged to have the lowest probabilities of survival. Their predictions had modest discriminating ability (receiver operating characteristic curve areas, 0.66 [SE = 0.020] for 90 days; 0.63 [SE = 0.017] for 1 year). The physicians identified only 15 patients they judged to have a 90-day survival probability of 10% or less, whose survival rate was actually 33.3%. CONCLUSIONS: Physicians have great difficulty predicting survival for patients with acute congestive heart failure and cannot identify patients with poor chances of survival. Current triage guidelines that suggest patients with poor chances of survival may be excluded from critical care may be impractical or harmful.
Authors: Kyle Scarberry; Lee Ponsky; Edward Cherullo; William Larchian; Donald Bodner; Matthew Cooney; Rodney Ellis; Gregory Maclennan; Ben Johnson; William Tabayoyong; Robert Abouassaly Journal: Can Urol Assoc J Date: 2018-05-14 Impact factor: 1.862
Authors: Jennifer Franke; Lutz Frankenstein; Dieter Schellberg; Amer Bajrovic; Jan Sebastian Wolter; Philipp Ehlermann; Andreas O Doesch; Manfred Nelles; Hugo A Katus; Christian Zugck Journal: Clin Res Cardiol Date: 2011-07-16 Impact factor: 5.460
Authors: Nazima Allaudeen; Jeffrey L Schnipper; E John Orav; Robert M Wachter; Arpana R Vidyarthi Journal: J Gen Intern Med Date: 2011-03-12 Impact factor: 5.128
Authors: Sean P Collins; Christopher J Lindsell; Cathy A Jenkins; Frank E Harrell; Gregory J Fermann; Karen F Miller; Sue N Roll; Matthew I Sperling; David J Maron; Allen J Naftilan; John A McPherson; Neal L Weintraub; Douglas B Sawyer; Alan B Storrow Journal: Am Heart J Date: 2012-10-29 Impact factor: 4.749
Authors: Michael K Ong; Carol M Mangione; Patrick S Romano; Qiong Zhou; Andrew D Auerbach; Alein Chun; Bruce Davidson; Theodore G Ganiats; Sheldon Greenfield; Michael A Gropper; Shaista Malik; J Thomas Rosenthal; José J Escarce Journal: Circ Cardiovasc Qual Outcomes Date: 2009-10-13