BACKGROUND AND PURPOSE: The purpose of this study was to determine the accuracy and optimal timing of physician prognostication in patients with subarachnoid hemorrhage, a prototypical neurological disease characterized by variable outcomes and frequent disability. METHODS: From October 2009 to April 2010, treating neurologists at a tertiary care academic medical center made daily predictions of the modified Rankin Scale at 6 months for consecutive patients with subarachnoid hemorrhage. Actual functional outcomes at 6 months were determined by phone interview and dichotomized into good (modified Rankin Scale 0-2) and poor (modified Rankin Scale 3-6) outcomes. Descriptive statistics were used to assess the accuracy of prognostications. Multiple logistic regression and generalized estimating equations were used to assess changes in prognostication accuracy over time and the relationship between prognostication accuracy and clinical factors. RESULTS: Physicians made 648 prognostications for 66 patients. Overall accuracy ranged from 78% to 88%. Among patients predicted to have a good outcome, 81% (95% CI, 71%-92%) actually had a good outcome, whereas 88% (95% CI, 77%-99%) of patients predicted to do poorly had poor outcomes. No significant trends were seen in prognostication accuracy over time during the hospital course (P=0.72). Increasing age, infection, mechanical ventilation, hydrocephalus, and seizures all significantly worsened physician accuracy. CONCLUSIONS: Neurologists were generally but not perfectly accurate in their prognostications of functional outcomes. The accuracy of prognoses did not correlate with the hospital day on which they were made but was affected by clinical factors that can cloud the neurological examination.
BACKGROUND AND PURPOSE: The purpose of this study was to determine the accuracy and optimal timing of physician prognostication in patients with subarachnoid hemorrhage, a prototypical neurological disease characterized by variable outcomes and frequent disability. METHODS: From October 2009 to April 2010, treating neurologists at a tertiary care academic medical center made daily predictions of the modified Rankin Scale at 6 months for consecutive patients with subarachnoid hemorrhage. Actual functional outcomes at 6 months were determined by phone interview and dichotomized into good (modified Rankin Scale 0-2) and poor (modified Rankin Scale 3-6) outcomes. Descriptive statistics were used to assess the accuracy of prognostications. Multiple logistic regression and generalized estimating equations were used to assess changes in prognostication accuracy over time and the relationship between prognostication accuracy and clinical factors. RESULTS: Physicians made 648 prognostications for 66 patients. Overall accuracy ranged from 78% to 88%. Among patients predicted to have a good outcome, 81% (95% CI, 71%-92%) actually had a good outcome, whereas 88% (95% CI, 77%-99%) of patients predicted to do poorly had poor outcomes. No significant trends were seen in prognostication accuracy over time during the hospital course (P=0.72). Increasing age, infection, mechanical ventilation, hydrocephalus, and seizures all significantly worsened physician accuracy. CONCLUSIONS: Neurologists were generally but not perfectly accurate in their prognostications of functional outcomes. The accuracy of prognoses did not correlate with the hospital day on which they were made but was affected by clinical factors that can cloud the neurological examination.
Authors: Pavel Atanasov; Andreas Diamantaras; Amanda MacPherson; Esther Vinarov; Daniel M Benjamin; Ian Shrier; Friedemann Paul; Ulrich Dirnagl; Jonathan Kimmelman Journal: Neurology Date: 2020-06-16 Impact factor: 9.910
Authors: Elan L Guterman; Hooman Kamel; Carmil Azran; Maulik P Shah; J Claude Hemphill; Wade S Smith; Babak B Navi Journal: Neurocrit Care Date: 2014-08 Impact factor: 3.210
Authors: Gustavo Saposnik; Robert Cote; Muhammad Mamdani; Stavroula Raptis; Kevin E Thorpe; Jiming Fang; Donald A Redelmeier; Larry B Goldstein Journal: Neurology Date: 2013-06-28 Impact factor: 9.910
Authors: David Y Hwang; Cameron A Dell; Mary J Sparks; Tiffany D Watson; Carl D Langefeld; Mary E Comeau; Jonathan Rosand; Thomas W K Battey; Sebastian Koch; Mario L Perez; Michael L James; Jessica McFarlin; Jennifer L Osborne; Daniel Woo; Steven J Kittner; Kevin N Sheth Journal: Neurology Date: 2015-12-16 Impact factor: 9.910
Authors: Marjolein Geurts; Floor A S de Kort; Paul L M de Kort; Julia H van Tuijl; L Jaap Kappelle; H Bart van der Worp Journal: PLoS One Date: 2017-09-29 Impact factor: 3.240