This Article Abstract Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Lai, S. M. Articles by Sobel, E. Search for Related Content PubMed PubMed Citation Articles by Lai, S. M. Articles by Sobel, E.

(Stroke. 1995;26:2011-2015.)
© 1995 American Heart Association, Inc.

Articles

Prognosis for Survival After an Initial Stroke

Sue Min Lai, PhD, MS, MBA; Milton Alter, MD, PhD; Gary Friday, MD Eugene Sobel, PhD

From the University of Kansas (Kansas City) (S.M.L.), the Medical College of Pennsylvania, Philadelphia, Pa (M.A., G.F.), and the University of Southern California, Los Angeles, Calif (E.S.).

	Abstract

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Background and Purpose We studied prognosis for survival after an initial stroke in 662 patients who survived at least 30 days after onset while taking into account age, sex, the number of neurological deficits from the initial stroke, stroke type, and five selected medical conditions: hypertension, myocardial infarction, cardiac arrhythmia, diabetes mellitus, and history of transient ischemic attacks.

Methods All patients were enrolled between July 1, 1987, and August 1, 1989, and were followed regularly at about 6-month intervals until death or the end of the study (mean of 24 months).

Results At 6 months, 90.8% of the 30-day stroke survivors were still alive. At 1, 2, 3, and 4 years, the cumulative survival rates were 86.9%, 78.7%, 73.2%, and 72.0%, respectively. Older age and the number of neurological deficits at onset of initial stroke increased risk of death. Compared with patients of the same age, sex, number of neurological deficits, and comorbidities, increased risk of death is present among those with myocardial infarction, cardiac arrhythmia, and diabetes mellitus. Hazard ratios were 1.7 (P=.006), 1.5 (P=.023), and 1.4 (P=.059), respectively. Hypertension and transient ischemic attacks were not significantly associated with increased mortality.

Conclusions This study clarifies prognosis for survival after an initial stroke by taking into account other confounding variables that could also contribute to risk of death.

Key Words: prognosis • risk factors • survival

	Introduction

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Stroke mortality has decreased significantly during the second half of this century. Investigators suggest that better control of hypertension accounts for much of this decrease,^{1 2 3 4 5} but age and sex as well as other medical disorders and their treatment^{6 7 8 9 10 11 12 13 14 15 16 17 18} may influence prognosis after a stroke. Therefore, an analysis of stroke mortality after taking age, sex, and various medical risk factors into account is warranted. In the present study, we selected hypertension, MI, cardiac arrhythmia, DM, and history of TIAs. To minimize the effect of the initial stroke itself on mortality, we studied only those who had survived at least 30 days after the initial stroke and were discharged alive after hospitalization.

	Subjects and Methods

Top Abstract Introduction Subjects and Methods Results Discussion References

 
The Lehigh Valley Recurrent Stroke cohort was used in this study. The Lehigh Valley is a region in northeastern Pennsylvania near New Jersey that is served by eight acute-care hospitals. Patients with stroke or TIA (or conditions inferred to be stroke or TIA) and admitted to any of the eight acute-care hospitals in the Lehigh Valley between July 1, 1987, and August 1, 1989, were identified by screening all admissions and hospital discharge summaries. Only patients with an initial stroke who were admitted to any of the eight acute-care hospitals within 1 month of onset were enrolled in the study. Approximately 4000 patients were screened. The reasons for excluding patients from the study have been reported previously.¹⁹ Patients with severe stroke who died quickly or could not give consent were not included in this cohort. The diagnosis of initial stroke was based on criteria similar to those of the Stroke Data Bank¹² and was verified clinically by two neurologists (G.F. and M.A.). At enrollment, the patient's medical status was determined by interview, examination, and review of medical records using standardized forms. These patients were followed up prospectively for up to 4 years (mean, 24 months). During the follow-up visits conducted first at 4 months and approximately at 6-month intervals thereafter, information was again systematically collected using the same standardized interview forms. Twelve-lead ECG was used to determine the cardiac rhythm and presence of an MI. There were 13 categories of arrhythmia noted at baseline, with the most common being atrial fibrillation/flutter (18% of patients) followed in decreasing order by ventricular and atrial premature contractions, sinus bradycardia, sinus tachycardia, first-degree atrioventricular block, pacemaker rhythm, and sinus arrhythmia. Other arrhythmias were noted in six patients.¹⁹ DM was determined by history and use of insulin or hypoglycemic agents. The patient was considered to be hypertensive if a patient, a surrogate, or the medical chart reported a history of hypertension. Blood pressure readings were also taken three times on the initial visit by the study nurse using a standardized method. Patients were also interviewed and examined to determine neurological status. When there was evidence of a new cerebrovascular event, the patient was examined by a neurologist (M.A. or G.F.) who determined level of consciousness, orientation, language, memory, cranial nerve status, motor, sensory status of lower or upper extremities, steadiness of lower and upper extremities, and gait. More details regarding the methods used in this study and the definitions of the five medical conditions studied have been published elsewhere.¹⁹

To ascertain death of study patients, obituaries were reviewed daily; if a death was missed in these notices, it was identified when an attempt was made to schedule the follow-up visit. The cause of death was determined from hospital records, telephone contacts with family members, and death certificates retrieved from the Bureau of Vital Statistics in Pennsylvania and New Jersey. When discrepancies in cause of death existed among these sources, the most plausible cause of death based on all of the available evidence was deemed correct, with priority given to hospital records.

A t test or ² was used when appropriate to determine significance of differences among variables compared. The effect on mortality of the five baseline medical conditions was similarly analyzed, listing each as normal or abnormal. For comorbidities, a survival-analysis technique was used, with survival time defined as the time from the date of stroke onset to date of death. For those who survived until the end of study, survival time was from date of stroke onset until the end of the study. Because occurrence of a second stroke was a study end point, patients who developed a second stroke were censored, as were those who moved away, were lost to follow-up, or refused further follow-up. The log rank statistic was used to test the statistical significance of differences in survival curves. Only a factor with a value of P<.1 from the univariate analysis was included in the multivariate analysis. The Cox proportional hazards model was used to identify the baseline risk factors associated with the mortality from any cause while taking into account demographic characteristics (age and sex) as covariates, number of neurological deficits from the initial stroke, stroke type, and the varying lengths of follow-up. The stroke types were categorized into the following three groups: thrombosis/embolus/nonspecific infarct, lacunar stroke, and intracerebral hemorrhage. The number of neurological deficits ranged from zero (ie, no deficit) to eight deficits. The eight deficits were for abnormalities of consciousness, orientation, language, memory, cranial nerve status, motor status, sensory status of lower or upper extremities, coordination of lower and upper extremities, and gait. The interactions between the risk factors were also examined.

	Results

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Of the 684 patients enrolled, 662 were discharged alive or survived at least 30 days after the initial stroke. These 662 patients constituted the study cohort, of which 51.4% were men and 97.2% were white. The men averaged 69.6±10.6 years in age, whereas women averaged 74.3±11.1 years in age. By the end of the study, 138 of the 662 patients had died, 81 had developed a second stroke, 23 had moved out of the study area, and 70 withdrew before the end of the study.

Demographic features and distribution of comorbidities among this cohort for each stroke type are shown in Table 1. All stroke types had a similar average age at enrollment. There were more men with lacunar stroke (58.6%) but more women with intracerebral hemorrhage (56.1%). Hypertension was most common in those with a lacunar stroke, DM was most common in those with lacune or cerebral thrombosis/embolus/nonspecific infarct, and TIA was most common in those with cerebral thrombosis/embolus/nonspecific infarct (but history of TIA was used as a criterion for diagnosing cerebral thrombosis). The distribution of number of deficits is also shown in Fig 1. Only 15 patients (0.02%) had no deficit. One hundred seventy-six patients (26.6%) had any of three deficits.

View this table: [in this window] [in a new window]   Table 1. Demographic Features and Medical Status at Enrollment Among Patients With an Initial Stroke (30-Day Survivors, n=662)

View larger version (36K): [in this window] [in a new window]   Figure 1. Bar graph shows distribution of number of deficits at baseline in patients with an initial stroke who survived 30 days (n=662).

The causes of death based on all available data sources were cardiac (n=53, 38.4%), the initial stroke (after 30 days, n=19, 13.8%), infection (n=19, 13.0%), metabolic (n=8, 5.8%), pulmonary (n=5, 3.6%), gastrointestinal hemorrhage (n=3, 2.2%), cancer (n=16, 11.6%), trauma (n=1, 0.7%), and unknown cause (n=14, 10.9%). Since only 9 patients with lacunes and 6 with intracerebral hemorrhage died during follow-up, the list of causes reflects essentially the causes of death among the 123 patients with a thrombosis, embolus, or nonspecific cerebral infarct.

The cumulative survival rates among patients who survived at least 30 days after an initial stroke was 90.8% at 6 months, 86.9% at 1 year, 78.7% at 2 years, 73.2% at 3 years, and 72.0% at the end of the fourth year. The three stroke types had a similar survival curve over time. Comparison of survival among patients who had a given medical condition at enrollment with those who did not showed significantly increased mortality for those with cardiac arrhythmia (P=.0001; Fig 2), MI (P=.0003; Fig 3), and DM (P=.02; Fig 4). However, patients with a history of hypertension at enrollment had no significantly increased mortality compared with those without hypertension (P=.99), and those with a history of TIA actually had a lower mortality than patients without a history of TIA, although the difference was not statistically significant (P=.4).

View larger version (14K): [in this window] [in a new window]   Figure 2. Graph shows Kaplan-Meier estimates of cumulative survival rates by cardiac arrhythmia (ARR) in patients with an initial stroke who survived 30 days (n=662).

View larger version (14K): [in this window] [in a new window]   Figure 3. Graph shows Kaplan-Meier estimates of cumulative survival rates by MI in patients with an initial stroke who survived 30 days (n=662).

View larger version (14K): [in this window] [in a new window]   Figure 4. Graph shows Kaplan-Meier estimates of cumulative survival rates by DM in patients with an initial stroke who survived 30 days (n=662).

A proportional hazards model analysis was also carried out to determine the effect of five selected medical conditions while taking into account age, sex, initial stroke type, the number of neurological deficits at baseline, and varying length of follow-up (Table 2). Older age, as expected, increased risk of death (P=.0001), whereas sex was not associated with higher risk of death. However, the patient's age and sex were both included in the model as covariates. A higher number of neurological deficits from the initial stroke also increased risk of death (P=.007). Patients diagnosed with MI on the baseline ECG had 1.7 times higher risk of death compared with patients of the same age and sex, number of neurological deficits, and comorbidities who did not have MI on the baseline ECG. The same type of analysis showed that patients with cardiac arrhythmia on the baseline ECG had a 1.5 times higher risk of death compared with patients of the same age, sex, number of neurological deficits, and comorbidities who did not have a cardiac arrhythmia on the baseline ECG. Patients with DM had 1.4 times higher risk of death compared with patients of the same sex, age, number of neurological deficits, and comorbidities who did not have DM. No significant risk-factor interactions on risk of death were observed among the factors studied. No significant increased mortality was found for those with hypertension or in those with history of TIA compared with those without these comorbidities, again controlling for the other potential confounders and covariates with the proportional hazards model.

View this table: [in this window] [in a new window]   Table 2. Proportional Hazards Model Estimates for Risk of Death

	Discussion

Top Abstract Introduction Subjects and Methods Results Discussion References

 
In this study, we showed that cardiac arrhythmia, MI, and DM but not hypertension or TIA were associated with increased risk of death after an initial stroke in patients who had survived at least 30 days or were discharged alive from the hospital. This stroke cohort had the advantage of including only patients whose stroke was verified both clinically and by CT as an initial stroke. The patients were followed up prospectively, and the medical data were collected systematically using standardized methods for all cases. Also, the analysis took into account age, sex, stroke type, and the number of neurological deficits from the initial stroke. In the more stringent Cox proportional hazards analysis, we showed an increased risk of death for MI and cardiac arrhythmia when controlling for demographic characteristics, the number of neurological deficits, and comorbidities. After controlling for other factors, DM had a statistically marginal significant effect (P=.059) on mortality. In this cohort, there were 41 patients who had intracerebral hemorrhage and survived at least 30 days. Had we excluded these 41 patients from the analysis, the hazard ratio of death for having MI would be identical; for cardiac arrhythmia it would be reduced from 1.5 to 1.4; and for DM it would remain the same.

In the Framingham study in the United States,⁸ stroke patients with coronary heart disease or congestive heart failure had a poorer prognosis for survival than patients with neither of these conditions. As in our study, the status of the heart in stroke patients was an important marker for survival prognosis after stroke. In the Rochester Epidemiology Project, Broderick et al¹⁴ identified the independent predictors of death to be prior MI (hazard ratio=2), atrial fibrillation present at onset of stroke (hazard ratio=1.7), congestive heart failure before the stroke, and an agexcongestive heart failure interaction. Anderson et al,⁹ working in Australia, also noted a poorer survival prognosis in patients with heart disease. There was a 6.5-fold increased mortality in his series for those with cardiac failure and a twofold increased mortality in those with atrial fibrillation at 1 year compared with those without these medical conditions. Olsson et al¹⁰ in Sweden investigated risk factors associated with mortality for stroke patients with diabetes. They reported that cardiac failure was a significant predictor of mortality after stroke. The authors did not find a poorer survival among those with atrial fibrillation or previous MI. In a Canadian study,^{6 7} after adjusting for heart failure, DM emerged as a significant predictor for mortality, but lack of association with increased mortality after stroke was reported for atrial fibrillation, MI, and hypertensive heart disease.

The differences in results among these various studies could well be due to methodological differences. For example, some studies of stroke mortality were retrospective or included patients with an initial as well as with a recurrent stroke.^{6 7 10 17 20} Risk factors may not have been assessed systematically, as it was in our study. Analyses may not have taken into account possible interactions among medical conditions, nor were stroke type and the number of neurological deficits taken into account.^{6 7 10} Our study addressed these possible sources of influence on mortality and attempted to adjust for them in the study design and data analysis.

The lack of association between hypertension and risk of death in the present study may seem counterintuitive. However, we know from other analyses²¹ that most patients in this stroke cohort had good or at least fair control of hypertension during follow-up. Therefore, presence of hypertension at enrollment by history does not necessarily imply a poor outcome measured as risk of death. Perhaps because hypertension was well controlled, risk of death in hypertensive patients was not appreciatively greater than in those who were nonhypertensive.

Diabetic control in these patients was good, as reflected by the HbA1c assay. Yet, DM was still associated with increased mortality. This implies that diabetic vasculopathy may be less reversible than hypertensive vascular changes.

The seemingly better prognosis for survival of patients with a history of TIA in this cohort as shown in the univariate analysis, if true, was unexpected. We considered two possible explanations: patients with TIA may have been more likely to be taking an antiplatelet-aggregating drug, such as aspirin, or an anticoagulant. Indeed, more than half of this cohort was taking one or the other of these drugs (or both at some time) after the stroke.²² This may have prevented not only stroke recurrence but also may have decreased risk of death, since risk of cardiac death is higher after stroke and aspirin has been shown to reduce death from cardiac causes. Alternatively, the vessel responsible for the TIA may have occluded with the initial stroke, and thereafter these patients may have had a risk of death no greater than those with no history of TIA. Indirectly supporting this notion is our observation that patients who developed TIA after the initial stroke were at higher risk of death than those who had no TIA after the initial stroke (Reference 22 and G.F. et al, unpublished data).

The data we have reported in this analysis assess the role of at least some common medical conditions in relation to risk of death after stroke and generally support work by others.^{8 9 10 11 14 15 17} Besides the five comorbidities that we studied, future studies could analyze other risk factors for stroke such as smoking, lipid level, exercise, body mass, and race in relation to prognosis for survival with use of a similar design. Such analyses could clarify even further the complex interplay of conditions that need to be considered in estimating prognosis for survival after stroke.

	Selected Abbreviations and Acronyms

 

DM = diabetes mellitus ECG = electrocardiogram, electrocardiography MI = myocardial infarction TIA = transient ischemic attack<\/.>

	Footnotes

 
Reprint requests to Sue Min Lai, PhD, MS, MBA, Department of Preventive Medicine, The University of Kansas Medical Center, 3901 Rainbow Blvd, Kansas City, KS 66160-7313. E-mail smlai@kumc.wpo.ukans.edu.

Received May 1, 1995; revision received June 22, 1995; accepted August 4, 1995.

	References

Top Abstract Introduction Subjects and Methods Results Discussion References

 
1. Matsumoto N, Whisnant JP, Kurland LT, Okazaki H. Natural history of stroke in Rochester, Minnesota, 1955 through 1969: an extension of a previous study, 1945 through 1954. Stroke.. 1973;4:20-29. [Abstract/Free Full Text]

2. Homer D, Whisnant JP, Schoenberg BS. Trends in the incidence rates of stroke in Rochester, Minnesota, since 1935. Arch Neurol.. 1987;22:245-251.

3. Whisnant JP. The decline of stroke. Stroke.. 1984;15:160-168. [Abstract/Free Full Text]

4. Hachinski V. Decreased incidence and mortality of stroke. Stroke.. 1984;15:376-378. [Abstract/Free Full Text]

5. Klag MJ, Whelton PK, Seidler AJ. Decline in US stroke mortality. Stroke.. 1989;20:14-21.[Abstract/Free Full Text]

6. Abu-Zeid HAH, Choi NW, Hsu PH, Maini KK. Prognostic factors in the survival of 1,484 stroke cases observed for 30 to 48 months, I: diagnostic types and descriptive variables. Arch Neurol.. 1978;35:121-125. [Abstract/Free Full Text]

7. Abu-Zeid HAH, Choi NW, Hsu PH, Maini KK. Prognostic factors in the survival of 1,484 stroke cases observed for 30 to 48 months, II: clinical variables and laboratory measurements. Arch Neurol.. 1978;35:213-218. [Abstract/Free Full Text]

8. Sacco RL, Wolf PA, Kannel WB, McNamara PM. Survival and recurrence following stroke. Stroke.. 1982;13:290-295. [Abstract/Free Full Text]

9. Anderson CS, Jamrozik KD, Broadhurst RJ, Stewart-Wynne EG. Predicting survival for 1 year among different subtypes of stroke: results from the Perth Community Stroke Study. Stroke. 1994;25:1935-1944. [Abstract]

10. Olsson T, Viitanen M, Asplund K, Eriksson S, Hagg E. Prognosis after stroke in diabetic patients: a controlled prospective study. Diabetologia.. 1990;33:244-249. [Medline] [Order article via Infotrieve]

11. Gray CS, French JM, Bates D, Cartlidge NEF, Venables GS, James OFW. Increasing age, diabetes mellitus and recovery from stroke. Postgrad Med J.. 1989;65:720-724. [Abstract/Free Full Text]

12. Kunitz SC, Gross CR, Heyman A, Kase CS, Mohr JP, Price TR, Wolf PA. The pilot stroke data bank: definition, design, and data. Stroke.. 1984;15:740-746. [Abstract/Free Full Text]

13. Chen Q, Ling R. A 1-4 year follow-up study of 306 cases of stroke. Stroke.. 1985;16:323-327. [Abstract/Free Full Text]

14. Broderick JP, Phillips SJ, O'Fallon WM, Frye RL, Whisnant JP. Relationship of cardiac disease to stroke occurrence, recurrence, and mortality. Stroke.. 1991;23:1250-1256. [Abstract/Free Full Text]

15. Sheikh K, Brennan PJ, Meade TW, Smith DS, Goldenberg E. Predictors of mortality and disability in stroke. J Epidemiol Community Health. 1983;37:70-74. [Abstract/Free Full Text]

16. Wade D, Skilbeck CE, Wood VA, Langton Hewer R. Long-term survival after stroke. Age Ageing.. 1984;13:76-82. [Abstract/Free Full Text]

17. Howard G, Walker MD, Becker C, Coull B, Feibel J, McLevoy K, Toole JF, Yatsu F. Community hospital-based stroke programs: North Carolina, Oregon, and New York, III: factors influencing survival after stroke: proportional hazards analysis of 4,219 patients. Stroke.. 1986;17:295-299.

18. Dennis M, Burn JPS, Sandercock PAG, Bamford JM, Wade DT, Warlow CP. Long-term survival after first-ever stroke: the Oxfordshire Community Stroke Project. Stroke.. 1993;24:796-800. [Abstract/Free Full Text]

19. Alter M, Friday G, Sobel E, Lai SM. The Lehigh Valley recurrent stroke study: description of design and methods. Neuroepidemiology.. 1993;12:241-248. [Medline] [Order article via Infotrieve]

20. Sobel E, Alter M, Davanipour Z, Friday G, McCoy R, Levitt LP, Isack T. Stroke in the Lehigh Valley: combined risk factors for recurrent ischemic stroke. Neurology.. 1989;39:669-672. [Abstract/Free Full Text]

21. Alter M, Friday G, Lai SM, O'Connell J, Sobel E. Hypertension and risk of stroke recurrence. Stroke.. 1994;25:1605-1610. [Abstract]

22. Cartlidge NEF, Whisnant JP, Elveback LR. Carotid and vertebral-basilar transient ischemic attacks: a community study, Rochester, MN. Mayo Clin Proc.. 1977;52:117-120.[Medline] [Order article via Infotrieve]

This article has been cited by other articles:

				M. H. Eckman, J. Rosand, S. M. Greenberg, and B. F. Gage Cost-Effectiveness of Using Pharmacogenetic Information in Warfarin Dosing for Patients With Nonvalvular Atrial Fibrillation Ann Intern Med, January 20, 2009; 150(2): 73 - 83. [Abstract] [Full Text] [PDF]

				M. H. Eckman, L. K.S. Wong, Y. O.Y. Soo, W. Lam, S. R. Yang, S. M. Greenberg, and J. Rosand Patient-Specific Decision-Making for Warfarin Therapy in Nonvalvular Atrial Fibrillation: How Will Screening With Genetics and Imaging Help? * Supplemental Appendix Stroke, December 1, 2008; 39(12): 3308 - 3315. [Abstract] [Full Text] [PDF]

				E. L. Air and B. M. Kissela Diabetes, the Metabolic Syndrome, and Ischemic Stroke: Epidemiology and possible mechanisms Diabetes Care, December 1, 2007; 30(12): 3131 - 3140. [Full Text] [PDF]

				B. Langhammer and J. K Stanghelle Bobath or Motor Relearning Programme? A follow-up one and four years post stroke Clinical Rehabilitation, July 1, 2003; 17(7): 731 - 734. [Abstract] [PDF]

				K. Fox Poststroke patients: implications for the cardiologist Eur. Heart J. Suppl., July 1, 2003; 5(suppl_E): E4 - E10. [Abstract] [PDF]

				M. H. Eckman, J. Rosand, K. A. Knudsen, D. E. Singer, and S. M. Greenberg Can Patients Be Anticoagulated After Intracerebral Hemorrhage?: A Decision Analysis Stroke, July 1, 2003; 34(7): 1710 - 1716. [Abstract] [Full Text] [PDF]

				S. Fuchs, E. Stabile, T. D. Kinnaird, G. S. Mintz, L. Gruberg, D. A. Canos, E. E. Pinnow, R. Kornowski, W. O. Suddath, L. F. Satler, et al. Stroke Complicating Percutaneous Coronary Interventions: Incidence, Predictors, and Prognostic Implications Circulation, July 2, 2002; 106(1): 86 - 91. [Abstract] [Full Text] [PDF]

				M. H. Eckman, S. K. Singh, J. K. Erban, and G. Kao Testing for Factor V Leiden in Patients with Pulmonary or Venous Thromboembolism: A Cost-Effectiveness Analysis Med Decis Making, April 1, 2002; 22(2): 108 - 124. [Abstract] [PDF]

				S.C. Lewis, M.S. Dennis, S.J. O'Rourke, and M. Sharpe Negative Attitudes Among Short-Term Stroke Survivors Predict Worse Long-Term Survival Stroke, July 1, 2001; 32(7): 1640 - 1645. [Abstract] [Full Text] [PDF]

				A. W. Andrews and R. W. Bohannon Discharge Function and Length of Stay for Patients with Stroke are Predicted by Lower Extremity Muscle Force on Admission to Rehabilitation Neurorehabil Neural Repair, March 1, 2001; 15(2): 93 - 97. [Abstract] [PDF]

				J. Carod-Artal, J. A. Egido, J. L. Gonzalez, and E. Varela de Seijas Quality of Life Among Stroke Survivors Evaluated 1 Year After Stroke : Experience of a Stroke Unit Stroke, December 1, 2000; 31(12): 2995 - 3000. [Abstract] [Full Text] [PDF]

				S.-L. Wang, W.-H. Pan, M.-C. Lee, S.-P. Cheng, and M.-C. Chang Predictors of Survival Among Elders Suffering Strokes in Taiwan : Observation From a Nationally Representative Sample Stroke, October 1, 2000; 31(10): 2354 - 2360. [Abstract] [Full Text] [PDF]

				J. C. Sharma, S. Fletcher, M. Vassallo, and I. Ross Cardiovascular disease and outcome of acute stroke: influence of pre-existing cardiac failure Eur J Heart Fail, June 1, 2000; 2(2): 145 - 150. [Abstract] [Full Text] [PDF]

				M. Prencipe, F. Culasso, M. Rasura, A. Anzini, M. Beccia, M. Cao, F. Giubilei, and C. Fieschi Long-term Prognosis After a Minor Stroke : 10-Year Mortality and Major Stroke Recurrence Rates in a Hospital-Based Cohort Stroke, January 1, 1998; 29(1): 126 - 132. [Abstract] [Full Text] [PDF]

				M. Alter, S.-M. Lai, G. Friday, V. Singh, V. M. Kumar, and E. Sobel Stroke Recurrence in Diabetics : Does Control of Blood Glucose Reduce Risk? Stroke, June 1, 1997; 28(6): 1153 - 1157. [Abstract] [Full Text]

This Article Abstract Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Lai, S. M. Articles by Sobel, E. Search for Related Content PubMed PubMed Citation Articles by Lai, S. M. Articles by Sobel, E.