OBJECTIVES: To examine the prognostic value of prestroke disability in predicting inpatient mortality and length of hospital stay (LOS) independent of age, sex, and stroke type and severity. DESIGN: Retrospective analysis of prospectively collected stroke registers. SETTING: United Kingdom. PARTICIPANTS: Fourteen thousand four hundred thirty-seven individuals (52.9% female, mean age 75.4 ± 12.1) with stroke (82% ischemic) admitted to three university hospitals. MEASUREMENTS: Data were examined from three hospital registers: Aintree (2005-2010), Newcastle (2000-2005), and Norwich (1997-2010). Risk of inpatient death and prolonged hospital stay according to prestroke disability using the modified Rankin Score (mRs) were assessed using logistic regression adjusting for age, sex, and stroke subtype (ischemic vs hemorrhagic) and severity. RESULTS: Inpatient death was 20.8%. In fully adjusted models, higher prestroke mRs was associated with significantly greater risk of mortality (for mRs = 1, 2, 3, 4, and 5 vs mRs = 0: odds ratio (OR)=1.28, 95% confidence interval (CI)=1.09-1.50; OR = 1.50, 95% CI = 1.29-1.75; OR = 1.85, 95% CI = 1.60-2.13; OR = 2.56, 95% CI = 2.15-3.04; and OR = 4.48, 95% CI = 3.47-5.80, respectively). The relationship appeared to be linear, and each point increase in mRs equated to being approximately 5 years older. Although age and stroke type appear to be strong independent predictors of LOS, premorbid mRs also predicted longer LOS regardless of discharge status. The predictability of the model using these parameters was very good (receiver operating characteristic: 0.82 for death and 0.65-0.70 for LOS). CONCLUSION: Prestroke disability predicts inpatient death and LOS, independent of age, sex, and stroke type and severity. Whether this is related to mental or physical disability should be examined in future prospective studies.
OBJECTIVES: To examine the prognostic value of prestroke disability in predicting inpatient mortality and length of hospital stay (LOS) independent of age, sex, and stroke type and severity. DESIGN: Retrospective analysis of prospectively collected stroke registers. SETTING: United Kingdom. PARTICIPANTS: Fourteen thousand four hundred thirty-seven individuals (52.9% female, mean age 75.4 ± 12.1) with stroke (82% ischemic) admitted to three university hospitals. MEASUREMENTS: Data were examined from three hospital registers: Aintree (2005-2010), Newcastle (2000-2005), and Norwich (1997-2010). Risk of inpatient death and prolonged hospital stay according to prestroke disability using the modified Rankin Score (mRs) were assessed using logistic regression adjusting for age, sex, and stroke subtype (ischemic vs hemorrhagic) and severity. RESULTS: Inpatient death was 20.8%. In fully adjusted models, higher prestroke mRs was associated with significantly greater risk of mortality (for mRs = 1, 2, 3, 4, and 5 vs mRs = 0: odds ratio (OR)=1.28, 95% confidence interval (CI)=1.09-1.50; OR = 1.50, 95% CI = 1.29-1.75; OR = 1.85, 95% CI = 1.60-2.13; OR = 2.56, 95% CI = 2.15-3.04; and OR = 4.48, 95% CI = 3.47-5.80, respectively). The relationship appeared to be linear, and each point increase in mRs equated to being approximately 5 years older. Although age and stroke type appear to be strong independent predictors of LOS, premorbid mRs also predicted longer LOS regardless of discharge status. The predictability of the model using these parameters was very good (receiver operating characteristic: 0.82 for death and 0.65-0.70 for LOS). CONCLUSION:Prestroke disability predicts inpatient death and LOS, independent of age, sex, and stroke type and severity. Whether this is related to mental or physical disability should be examined in future prospective studies.
Authors: David Asuzu; Karin Nyström; Hardik Amin; Joseph Schindler; Charles Wira; David Greer; Nai Fang Chi; Janet Halliday; Kevin N Sheth Journal: Neurocrit Care Date: 2015-10 Impact factor: 3.210
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Authors: Christopher I Price; Victoria Rae; Jay Duckett; Ruth Wood; Joanne Gray; Peter McMeekin; Helen Rodgers; Karen Portas; Gary A Ford Journal: PLoS One Date: 2013-10-08 Impact factor: 3.240
Authors: Terence J Quinn; Martin Taylor-Rowan; Aishah Coyte; Allan B Clark; Stanley D Musgrave; Anthony K Metcalf; Diana J Day; Max O Bachmann; Elizabeth A Warburton; John F Potter; Phyo Kyaw Myint Journal: Front Neurol Date: 2017-06-13 Impact factor: 4.003
Authors: Alexander J George; Amelia K Boehme; James E Siegler; Dominique Monlezun; Bethena D Fowler; Amir Shaban; Karen C Albright; T Mark Beasley; Sheryl Martin-Schild Journal: ISRN Stroke Date: 2013-08-14