DYSPHAGIA AND NUTRITIONAL STATUS FOLLOWING STROKE

By

MICHAEL A. CRARY

A THESIS PRESENTED TO THE GRADUATE SCHOOLOF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT

FOR THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2004

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ACKNOWLEDGMENTS

Many professionals contributed to the completion of this research effort. I would

like to thank the Shands Jacksonville clinical research team of Dr. Scott Silliman and

Leslie Page Miller. They have been the front line in this effort. My friend and colleague,

Dr. Giselle Carnaby Mann, has been central in educating me on the behavioral aspects of

clinical stroke research and extended my knowledge of statistical analysis and design

issues. My thesis committee has been flexible, informative, and extremely helpful. I am

grateful for the efforts of Drs. Peter Stacpoole, Nabih Asal, and Scott Silliman. Finally,

I thank Dean Robert Frank of the College of Public Health and Health Professions for

financial support to conduct this research.

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TABLE OF CONTENTS

page

ACKNOWLEDGMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii

ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi

LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

CHAPTER

1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Specific Aims . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1Glossary of Key Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2 REVIEW OF LITERATURE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Disability Among Stroke Survivors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5Dysphagia in Acute Stroke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5Nutritional Status in Acute Stroke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7Relationships Between Dysphagia and Nutritional Status . . . . . . . . . . . . . . . . . . . . . 9Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

3 METHODS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13Subjects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14Power Analysis and Sample Size Feasibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16Statistical Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

4 RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Timing of Assessments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18Patient Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19Correlation and Association Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23Predictors of Dysphagia or Poor Nutritional Status . . . . . . . . . . . . . . . . . . . . . . . . . 26

5 DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

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REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

BIOGRAPHICAL SKETCH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

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LIST OF TABLES

Table page

1-1 Glossary of key terms and procedures used in this study . . . . . . . . . . . . . . . . . . . . . 2

3-1 Dysphagia prevalence estimated at 60% . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

3-2 Malnutrition prevalence estimated at 20% . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

4-1 Time intervals between stroke onset, admission to hospital, admission tostroke unit, neuroradiologistic evaluations, and clinical outcome evaluations . . . 18

4-2 Descriptive data for continuous variables obtained from 55 acute ischemicstroke patients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

4-3 Descriptive data for ordinal and categorical variables obtained from 55 acuteischemic stroke patients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

4-4 Frequency of impairment of dysphagia, nutrition, and stroke severityvariables. Individual measures and cut off scores are identified withinparentheses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

4-5 Correlations among outcome measures for dysphagia, nutritional status, andstroke severity in 55 patients with acute ischemic stroke . . . . . . . . . . . . . . . . . . . . 23

4-6 Odds ratios (OR), 95% confidence intervals (CI), and chi-square (X2) resultsfor categorical variable comparisons with dysphagia (+/-). . . . . . . . . . . . . . . . . . . 24

4-7 Odds ratios (OR), 95% confidence intervals (CI), and chi-square (X2) resultsfor categorical variable comparisons with nutritional status (+/-) . . . . . . . . . . . . . 25

vi

ABSTRACT

Abstract of Thesis Presented to the Graduate Schoolof the University of Florida in Partial Fulfillment of the

Requirements for the Degree of Master of Science

DYSPHAGIA AND NUTRITIONAL STATUS FOLLOWING STROKE

By

Michael A. Crary

Chair: Peter W. StacpooleMajor Department: Clinical Investigation

Swallowing difficulties are prevalent following acute stroke with estimates

exceeding 50% of stroke patients. Nutritional deficits are less prevalent upon acute

hospital admission (16%-22%) but this problem appears to increase subsequent to stroke

with estimated prevalence approaching 50% upon admission to rehabilitation. An

association appears to exist between dysphagia and nutritional status, but this potential

association has not been carefully studied. The purpose of the present cross sectional

study was to examine potential associations between swallowing ability and nutritional

status in acute stroke patients upon admission to a dedicated, hospital-based stroke unit.

Potential relationships between these stroke sequelae and more traditional stroke severity

measures were evaluated. Patients with acute ischemic stroke were recruited sequentially

upon admission to the dedicated stroke unit of an academic medical center. Average age

of the study patients was 65.2 years with 49% male gender. Forty three percent (43%) of

patients were African American and 62% suffered first-ever stroke. Patients were

assessed with a clinical swallowing evaluation, a functional oral intake scale, the Mini

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Nutritional Assessment, BMI, percent body fat, NIHSS, modified Rankin Scale, and

modified Barthel Scale. On clinical examination, 50.9% of study patients demonstrated

dysphagia, and 23.6% were identified with poor nutrition. Just over 30% (30.9%) of the

cohort was obese upon admission. The majority of patients were eating by mouth, but

47.3% had some degree of limitation in this function. Clinical swallowing ability

correlated with stroke severity and with functional oral intake but not with measures of

nutritional status. Nutritional measures did not correlate with any of the swallowing or

stroke severity measures. It is possible that the clinical nutrition measures chosen for this

study may not be sensitive to rapid changes in nutritional status. To better address this

possibility, longer term follow up studies are being designed that will include blood

serum assessments of nutritional markers in addition to anthropomorphic and behavioral

measures. Ultimately, a better understanding of potential associations between dysphagia

and nutritional status following stroke will lead to improved care for the acute and

subacute stroke patient and improved long-term outcomes.

1

CHAPTER 1INTRODUCTION

Stroke is the leading cause of long-term disability in the United States. Dysphagia

(difficulty swallowing food or liquid) and poor nutritional status have been estimated to

impact between 16% to 60% of stroke survivors leading to increased morbidity and poor

long-term functional outcomes. The association between dysphagia and nutritional status

is unknown. The primary purpose for this cross-sectional study is to determine the

prevalence of dysphagia and poor nutritional status in acute ischemic stroke and to

identify potential associations between these outcome measures and more global stroke

severity indices. Given the suggested magnitude of swallowing and nutritional deficits in

acute stroke, and the potential for ongoing complications following discharge, it is

anticipated that this line of research will lead to improved clinical resource utilization and

development of clinical management strategies to enhance long-term functional outcome

for stroke survivors.

Specific Aims

The specific aims of this research are the following:

• To determine the prevalence of dysphagia and poor nutritional status in a cohort ofacute ischemic stroke patients from a single center dedicated stroke unit.

• To identify potential associations between dysphagia and nutritional status andbetween these outcomes and traditional measures of stroke severity in acuteischemic stroke patients.

• To identify important predictors of dysphagia and poor nutritional status in acuteischemic stroke patients.

2

Glossary of Key Terms

To facilitate clarity in this manuscript, Table 1-1 provides abbreviations and

operational definitions of key words and procedures used in completion of this research.

Table 1-1. Glossary of key terms and procedures used in this studyVariable Abbreviation DescriptionAge N/A Age in yearsGender N/A Male or FemaleRace N/A Caucasian, African-American, OtherMarital status N/A Living alone or with a spouse at the time of

strokePrior stroke N/A Patient did or did not have a history of a prior

stroke before the current eventDiabetes Mellitus N/A One of the following:

• Fasting plasma glucose > 126 mg/dL• 2-hour oral glucose tolerance test > 200

mg/dL• On medication for diabetes mellitus

Chronic hypertension Hypertension One of the following:• Systolic blood pressure > 140 or diastolic

blood pressure > 90 based on the mean of atleast two readings conducted on twodifferent days.

• History of treatment for chronichypertension.

Smoking N/A Patient is smoking or using smokeless tobaccoat the time of stroke or recently (within afew months) quit smoking or usingsmokeless tobacco.

Alchohol N/A Patient is identified as using excessive alcoholas documented in medical chart.

Coronary artery disease CAD One of the following:• History of angina• History of myocardial infarction• History of coronary artery intervention such

as CABG or angioplasty

Atrial fibrilation AFIB Atrial fibrillation identified upon clinicalexamination and documented in medicalchart

Table 1-1. Continued.

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Variable Abbreviation DescriptionHyperlipidemia N/A One of the following:

• Total cholesterol 200-239 mg/dL• LDL cholesterol 130-159• Taking a medication for hyperlipedemia

Stroke type (Bamford)

TACIPACILACIPOCI

One of the following as identified by Bamfordet al. 1991)• Total Anterior Circulation Infarct• Partial Anterior Circulation Infarct• Lacunar Infarct• Posterior Circulation Infarct

Intervention withthrombolysis

rTPA Whether or not patients were treated withrTPA.

National Institutes ofHealth stroke scale

NIHSS The total score on this clinical measure ofstroke severity

Modified Rankin scale mRS The scale score on this ordinal measure ofstroke disability

Modified Barthel index mBI The total score on this measure of functionalability

Mann assessment ofswallowing ability

MASA The total score on this clinical measure ofswallowing ability (dysphagia).

Functional oral intakescale

FOIS The scale score on this ordinal measure of oralintake of food and liquid

Mini nutritionalassessment

MNA The total score on this clinical assessment ofnutritional status

% body fat % Fat Percent body fat estimated by the 3-siteskinfold test

Body mass index BMI This nutritional reference is calculated by theratio of height to weight

Dysphagia N/A Difficulty ingesting food or liquid by mouth. Specifically, the result of oropharyngealdeficits including weakness orincoordination. Dysphagia has beenmeasured by various methods acrossstudies. In this study, dysphagia ismeasured by the MASA.

Table 1-1. Continued.

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Variable Abbreviation DescriptionPoor nutrition N/A A global term representing a current state of

under nutrition. Other studies have usedterms such as “under nutrition,”“malnutrition,” or “impaired nutritionalstatus.” Nutrition has been measuredvariably across studies. In this study, theMNA will be used to identify patients “atrisk for malnutrition” which will beconsidered as reflecting poor nutritionalstatus.

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CHAPTER 2REVIEW OF LITERATURE

Disability Among Stroke Survivors

Stroke is the leading cause of long-term disability in the United States with

estimates as high as 73% among stroke survivors (American Heart Association [AHA],

2004). According to statistics provided by the American Heart Association,

approximately 4.4 million stroke survivors are alive today, 15% to 30% of whom are

permanently disabled.

The American Stroke Association states that in 1999 direct and indirect costs of

stroke exceeded $51 billion. Over $30 billion was spent on hospital, nursing home,

physicians and other health care specialists fees, medication, and other medical durables.

The remaining $20 billion was a result of lost productivity, morbidity, and mortality.

Given the rapid aging of the United States population, it is expected that Medicare’s

financial burden will double in the next 75 years. Research identifying significant post

stroke problems, their persistence, and how to predict and more effectively treat these

problems will yield benefit to the burdened health care system by improved resource

utilization.

Dysphagia in Acute Stroke

Dysphagia is highly prevalent among acute stroke patients. Some estimates

suggest that nearly 65% of stroke survivors suffer some degree of impairment in the

ability to swallow (Mann, Hankey, & Cameron, 2000). This limitation in the ability to

6

ingest safely adequate amounts of food and liquid places the patient with acute stroke at

risk for poor nutrition and hydration and/or for complications such as aspirated related

pneumonia (Finestone, Foley, Woodbury, & Greene-Finestone, 2001; Mann, Hankey, &

Cameron, 1999). Dysphagia and related complications increase length of acute stay and

are associated with increased mortality, comorbidity, and increased health care costs

(Smithard et al., 1997). Furthermore, dysphagia is reported to persist and perhaps worsen

during the first month after stroke (Sala et al., 1998). Overt dysphagia is reported to have

a high rate of spontaneous resolution. However, a substantial number of stroke survivors

will demonstrate dysphagia characteristics well beyond the rehabilitation period; for

some patients this can be a permanent condition (Mann, Hankey, & Cameron, 1999;

Smithard et al., 1997). These persisting deficits impact physical and social functioning,

quality of life for both patients and caregivers, community re-entry opportunities, and

health care resource utilization.

One persistent problem in studies of dysphagia post stroke is the variability in

how dysphagia is diagnosed. Clinical investigators have relied on subjective measures

such as observations of coughing following liquid ingestion, global impressions, or level

of consciousness. The disparity among studies in the criteria for identifying patients with

dysphagia contributes to heterogeneity in dysphagic subjects both within and across

studies. An appropriate assessment tool to identify dysphagia in acute stroke should

represent a comprehensive examination of those factors known to relate to dysphagia in

this population. Furthermore, this tool should be validated in a population of acute stroke

patients and demonstrate strong reliability among raters. Finally, such a measure should

have the potential to grade severity of identified dysphagia. In the present study, a

clinical measure of dysphagia is employed that has demonstrated strong inter-rater

7

reliability, has been validated in a population of stroke patients, and provides a numerical

score reflecting the severity of dysphagia symptoms (Mann Assessment of Swallowing

Ability (MASA); Mann, 2002). A related measure, the Functional Oral Intake Scale

(FOIS; Crary, Carnaby (Mann), & Groher, 2004) is used to document functional

limitations in the oral ingestion of food and liquid secondary to the presence of

swallowing difficulties. Like the MASA, this tool has demonstrated strong inter-rater

reliability, been validated in a population of stroke patients, and has a numerical score

reflecting the degree of limitation in oral intake of food and liquid.

Nutritional Status in Acute Stroke

Poor nutritional status is prevalent among acute stroke patients upon admission

and may worsen during hospitalization. Upon admission, prevalence has been estimated

between 16% and 22%. This figure increases to 22% and 26% through discharge from

acute care (Axelsson, Asplund, Norberg, & Alafuzoff, 1988; Davalos et al., 1996;

Gariballa, Parker, Taub, & Castleden, 1998a). Nutritional decline appears to go beyond

acute care. The prevalence of poor nutritional status in stroke patients at admission to

rehabilitation has been reported to approximate 50% (Finestone, Greene-Finestone,

Wilson, & Teasell, 1995). At approximately 1 month post stroke, nutritional status

improves with continuing improvement up to 4 months follow up. Thus, one-quarter to

one-half of poststroke patients may demonstrate poor nutritional status from hospital

admission through acute rehabilitation. This deficit in nutritional status may be

preexisting to the stroke in some patients (Davis et al., 2004). Additionally, stroke may

serve as a trigger to a catabolic stress response that may initiate and/or further amplify

poor nutritional status (Chalea, Haymore, Schellinger, & Kang, 2004). Regardless of the

mechanism for this deterioration in nutritional status, impact of poor nutritional status on

8

recovery and long-term functional outcome becomes a significant issue. Various

outcome factors have been reported to be associated with poor nutritional status

including increased 3 month mortality (OR 1.13, 95% CI 1.01–1.27; Gariballa et al.,

1998), frequency of urinary or respiratory infection (50% versus 24%; p = .017) and

bedsores (17% versus 4%; p = .054: Davalos et al., 1996), length of stay in acute

rehabilitation (p < .01; Finestone et al., 1995), and functional outcome as measured by

general indices such as the Barthel Index (OR 3.5, 95% CI 1.2–10.2; Davalos et al.,

1996).

A remaining concern in studies of nutritional status (as in dysphagia) is which

nutritional measure is best suited to assess nutritional status. Studies of nutritional status

in stroke patients have utilized anthropomorphic measures such as skin fold or mid arm

muscle circumference (Davalos et al., 1996), biochemical measures such as serum

albumin levels (Davalos et al., 1996; Dziedzic, Slowik, Szczudlik, 2004), and/or

behavioral health surveys such as the Subjective Global Assessment (SGA; Davis et al.,

2004). In studies of stroke in elderly patients, an appropriate tool should be simple and

available to the widest range of patients to increase external validity of results. It should

also have demonstrated validity compared to other measures of nutrition and

demonstrated reliability across raters. Finally, it should be sensitive to change in

nutritional status over time. The present study employs a clinical measure of nutritional

status that has been validated on elderly, medically compromised populations (Mini

Nutritional Assessment (MNA); Vellas, Guigoz, Garry, & Albarede, 1994). It has high

sensitivity, specificity, and predictive value compared to blood serum and

anthropomorphic nutritional measures (Vellas et al., 2000). It has not, to date, been

employed in studying nutritional status following stroke. However, the MNA is similar

9

to the SGA, which has been used in recent research on nutritional status in acute stroke

patients (Davis et al., 2004). Thus, while no “gold standard” for nutritional assessment

exists (Gariballa, 2003), it is important for any tool utilized to estimate nutritional status

to be robust across clinical environments, have strong validity with other nutritional

measures, and adequate reliability across judges. The MNA meets these criteria. In this

study, MNA findings are compared to two more traditional nutritional measures; Body

Mass Index and percent body fat.

Relationships Between Dysphagia and Nutritional Status

Little research has been conducted on the potential relationships between

swallowing ability (dysphagia) and nutritional status in stroke patients. This is surprising

given the relatively high prevalence of these factors, their parallel clinical course post

stroke, and the overt, logical interaction between them. Davalos and colleagues (1996)

reported that nutritional parameters (midarm muscle circumference, triceps skinfold, or

low serum albumin) did not differ between stroke patients with and without swallowing

problems upon admission. One limitation of this study was the definition of dysphagia

among stroke patients. Patients who failed a water swallow test (cough within one

minute of ingesting 10ml of water) and patients who were unconscious both were

considered to demonstrate dysphagia. Likewise, preliminary results from the FOOD trial

(FOOD Trial Collaboration, 2003) indicate no differences in the percent of patients able

to swallow among undernourished (73%), normal nourished (77%), or overweight (73%)

stroke patients examined within the first seven days following stroke. These

investigators used clinician judgement based on multiple sources of information to

identify both poor nutritional status and dysphagia. Conversely, Finestone and colleagues

(1995) reported similar rates of malnutrition assessed with biochemical and

10

anthropomorphoric data (49%) and dysphagia assessed clinically (47%) among stroke

patients admitted to a rehabilitation service. Malnutrition and dysphagia as measured in

their study were significantly associated (p = .032) at the univariate level. Westergren,

Karlsson, Andersson, Ohlsson, and Hellberg (2001) reported that several “eating

variables” were predictive of nutritional status. Inspection of their data suggests that in

84% of patients “eating variables” suggested reduced oral intake secondary to poor

swallowing abilities. Eating variables suggestive of dysphagia in this study included but

were not limited to eats three-quarters or less of served food (60%), aberrant eating speed

(26%), difficulty manipulating food in the mouth (24%), and overt swallowing

difficulties (18%). Nonoral feeding routes (NG, PEG) also should be considered as

Finestone and colleagues (1995) have reported a significant association (p = .002)

between acute service tube feedings and malnutrition (defined by biochemical and

anthropomorphic data) in stroke patients admitted to a rehabilitation service. Davalos

and colleagues (1996) reported that malnutrition was more frequent (48.3%) in patients

with swallowing incapacity (nonoral feeding) than in those with normal swallowing

function (13.6%), but refer to the abovementioned limitation of their definition of

dysphagia. Though prior studies have implied overlap between dysphagia and nutritional

status it is obvious that relationships between dysphagia and nutritional status post stroke

remain unclear at this time. Despite the initial attempts described herein, potential

relationships between dysphagia and nutritional status, and the impact of combined

dysphagia and nutritional status on long term functional outcomes in stroke remain

poorly understood and warrant further study.

The importance of obtaining a better understanding of potential associations

between dysphagia and nutritional status is highlighted by a second consideration.

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Several published trials have suggested positive results from nutritional supplementation

in hospitalized adult patients; however, there is no agreement on the benefit of routine

supplementation or how it should be achieved (Potter Langhorne, & Roberts, 1998).

Provision of additional calories beyond oral or nonoral feeding regimens (e.g. nutritional

supplementation) has been shown to improve nutritional status and functional outcome in

elderly nursing home patients (Lauque et al., 2000), critically ill older inpatients

(Bourdel-Marchasson et al., 2000) and in certain surgical or respiratory conditions

(Akner & Cederholm, 2001). Specific to stroke, Gariballa, Parker, Taub, and Castleden

(1998b) reported that supplemental oral sip feeding improved energy and protein intake

in non-dysphagic stroke patients in a rehabilitation setting. More accurately, their data

suggest maintenance of nutritional markers rather than improvement in nutritional

markers. Follow up over a 12-week period indicated trends toward improved functional

outcome and lower morbidity and mortality, but no significant differences were obtained.

Thus, limited available data suggest that nutritional supplementation via oral sip feeding

may be successful in combating nutritional decline in the initial weeks post stroke. The

impact of this nutritional maintenance on functional outcome is unclear. Also, this single

limited trial of nutritional supplementation in stroke patients did not include patients with

any degree of dysphagia. Many patients with mild dysphagia may be appropriate

candidates for nutritional intervention. A better understanding of the association between

dysphagia and nutritional status in this population will facilitate improved and possibly

expanded patient selection for this form of intervention.

Summary

Studies using a variety of definitions of both dysphagia and poor nutritional

status, and disparate methods to measure these conditions consistently reveal that both

12

dysphagia and poor nutritional status occur frequently in the acute stroke patient. They

often coexist but the nature of their association remains vague. Both are related to

increased mortality and poorer functional outcomes in stroke patients. Both may impact

the type of postacute rehabilitation and interventions afforded to stroke patients and

influence health care resource utilization. Given the lack of information in this area and

the clinical importance of these factors, it is imperative that further research be

completed to identify potential associations between dysphagia and nutritional status in

acute ischemic stroke patients and factors that may impact resultant associations.

Important considerations for studying these factors are the clinical protocols employed to

measure each. Prior studies have varied greatly in the tools used to identify both

dysphagia and malnutrition. The present study proposes to utilize clinical tools that have

been developed and standardized in elderly populations including acute stroke in order to

offer a consistent framework for comparison. As an initial investigation, this study uses

a cross sectional design in an attempt to identify associations between dysphagia and

poor nutritional status and factors that may impact any obtained association in a

population of acute ischemic stroke patients.

13

CHAPTER 3METHODS

Design

This study follows a cross-sectional design in which dysphagia and nutritional

status were evaluated simultaneously in a sequential cohort of stroke patients admitted to

a dedicated stroke unit.

Subjects

Fifty-five (55) patients with acute ischemic stroke were recruited for this study.

This study focused on ischemic stroke as this is the most frequent form of stroke with

estimates up to 88% of all strokes (American Heart Association [AHA], 2004).

Sequential patients admitted to the inpatient stroke unit at Shands Hospital in

Jacksonville (Shands Jacksonville) who met the following inclusion-exclusion criteria

were recruited as the sample for this study.

• Ischemic stroke identified by neurological and radiological examination

• No prior history of oropharyngeal dysphagia by patient and/or caregiver report

• No previous head/neck surgery or trauma that may impact swallowing ability

• No other/concomitant neurological disorders (e.g., Parkinson’s disease) thatwould impact oropharyngeal swallowing ability. This exclusion does not includepost stroke deficits.

• Physician and patient/family agreement to participate

The geographic area of recruitment incorporated the greater Jacksonville, Florida,

metropolitan area and beyond. This reflects a population of over 1,100,000. In Duval

14

County, the home of Jacksonville, the population in 2003 was 817,480 with 51.5% of the

population being female, 27.8% being African American, and 10.5% being over 65 years

of age. Shands Jacksonville is the major stroke referral center in the city. This facility is

a tertiary care hospital with 720 beds. The hospital is a major teaching hospital affiliated

with the University of Florida School of Medicine. Over 600 stroke patients are admitted

to Shands Jacksonville on an annual basis. Stroke patients are treated in a state of the art

18 bed neuroscience specialty unit by a stroke team including neurologists,

neuroradiologists, specialized nurses, and rehabilitation specialists.

All subjects were initially identified by the treating stroke neurologist as

appropriate for inclusion in this study and subsequently approached by the speech

pathologist researcher who reviewed study procedures and obtained informed consent

from either the patient or the family. This study was reviewed and approved by the

Institutional Review Board on the Jacksonville campus.

Data Collection

All patients enrolled in this study received stroke-specific, dysphagia-specific,

and nutrition-specific evaluations. All evaluations were completed as soon as possible

following admission into the inpatient stroke unit. Stroke-specific evaluations were

completed by qualified stroke neurologists (Dr Silliman or his fellow). Dysphagia-

specific and nutrition-specific evaluations were completed by a licensed speech

pathologist trained in the specific assessment procedures used in this study. Information

on the timing of the admission process (days from stroke to hospital admission, hospital

admission to stroke unit admission) and study evaluations (CT/MRI scans, clinical

outcome measurement) was collected for each patient and averaged to describe the

timing of study procedures.

15

Stroke-Specific Evaluations

Stroke neurologists performed standard stroke evaluations at the time of

admission and during the acute hospital stay including:

• Brain and vascular imaging (CT and/or MRI) was used to identify the nature andlocation of pathology and stroke subtype. Stroke classification byclinical/anatomic location was completed according to the Oxfordshireclassification (Bamford, Sandercock, Dennis, Burn, & Warlow, 1991).

• Functional outcome was measured using the modified Rankin Scale (Hacke et al.,1998) and the modified Barthel Index (Collin, Wade, Davis, & Horne, 1988). Obtained scores were used except when these measures were dichotomized. Dichotomized cut-off scores were >3 for the modified Rankin Scale and <12 forthe modified Barthel Index.

• Neurological status was quantified with the National Institutes of Health StrokeScale (Brott et al., 1989; Goldstein & Samsa, 1997). Obtained scores were usedexcept when this measure was dichotomized. A cut-off score of 8 was used fordichotomized analyses.

Dysphagia-Specific Evaluations

The speech pathologist assigned to this study administered clinical protocols

specific to dysphagia and functional oral intake including:

• Clinical evaluation of dysphagia was completed with the Mann Assessment ofSwallowing Ability (MASA; Mann, 2002). On this clinical tool, a score of lessthan 178 identifies patients with clinical symptoms and signs of dysphagia.

• Ability to consume food/liquid by mouth was documented with the FunctionalOral Intake Scale (FOIS; Crary, Carnaby, & Groher, 2004). This ordinal ratingscale was used to describe the amount of oral food and liquid intake consumed bypatients in the study. When this scale was dichotomized, a score below 6 out of amaximum of 7 was used to reflect limitations in oral intake of food and liquid.

Nutrition-Specific Evaluations

Nutritional assessment was also completed by the speech pathologist on this

study:

• Body Mass Index (BMI: wt in kg/ht in m2). A BMI of under 18.0 representspatients in the poor nutrition category. A BMI of over 30 represents patients whoare obese.

16

• Percent body fat (% fat) computed from 3 site skinfold measurement. Langeskinfold calipers were used to make these measurements. From male patients,skinfold measurements were obtained from lateral chest, abdomen, and thigh. Forfemale patients, skinfold measurements were obtained from tricep, suprailliacregion, and thigh. Body fat percentages were used as a general assessment ofnutritional status reflected in body composition.

• Mini Nutritional Assessment (MNA; Vellas, Guigos, Garry, & Albarede, 1994).On this assessment tool, a score of less that 23.5 is indicative of “at risk” formalnutrition. This cut-off score was used to identify patients with clinicallymeasured poor nutritional status.

These clinical measures were selected as representative of commonly used and

widely accepted estimates of nutritional status. Funding was unavailable to obtain serum

markers of nutritional status. However, the MNA is highly correlated with both energy

intake (r = 0.50, p < .001) and serum albumin levels (r = 0 .71, p < .001) (Vellas et al.,

2000).

Power Analysis and Sample Size Feasibility

Sample size was estimated using an a priori alpha level of .05 with a beta level of

.80. Sample size was based on expected prevalence of dysphagia and poor nutritional

status compared to previously published rates. Dysphagia rates have been estimated to

be from 40% to 60% among acute stroke patients. Malnutrition rates have been

estimated to be from 16% to 22% in the same population. Tables 3-1 and 3-2 summarize

the power analysis.

Based on these analyses and feasibility of recruitment based on the initial 30

patients and in consideration of the prevalence of both dysphagia (.40) and poor

nutritional status (.21) in that initial sample, a study sample of at least 50 patients was

required to estimate adequate power. This number was feasible given the fiscal resources

supporting this study and the number of patients admitted to the Shands Jacksonville

stroke unit on an annual basis. Time available for data collection was just under 6

17

months. Approximately 40 to 50 stroke patients are admitted to the unit monthly, not all

of whom have ischemic strokes. Of this total numbers of admissions, the speech

pathologist was requested to maintain a recruitment rate of at least 10 patients per month

or approximately 25% of the total number of patients admitted to the unit.

Table 3-1. Dysphagia prevalence estimated at 60%.P1 Delta Sample Size.35 .25 30.40 .20 47.45 .15 86.50 .10 216

Table 3-2. Malnutrition prevalence estimated at 20%P1 Delta Sample Size.45 .25 23.40 .20 36.35 .15 63.30 .10 129

Statistical Analyses

Subject demographic variables were described by mean and variance statistics for

continuous variables or prevalence statistics for categorical variables. Correlation

analyses were used to examine potential relationships among continuous variables.

Subgroups were identified based on dysphagia and poor nutrition cutoffs scores on

clinical protocols (MASA and MNA). Demographic variables were then examined

between subgroups using chi-square analyses and odds ratios with 95% confidence

intervals to identify any variable significantly associated with dysphagia or poor

nutrition. Variables that were highly related to the primary outcome measures (dysphagia

or poor nutrition) were entered into a logistic regression analysis to identify independent

predictors of each outcome.

18

CHAPTER 4RESULTS

Timing of Assessments

Table 4-1 presents information on the time intervals between stroke onset,

admission to the hospital, neuroradiologic evaluations (CT or MRI), admission to the

stroke unit, and completion of the clinical outcome measure evaluations. The average

interval between recognition of stroke symptoms and hospital admission was 0.34 days.

The majority of patients (76%) were admitted the same day that stroke symptoms were

recognized. Within one day of stroke onset, 96% of the patients had been admitted to the

hospital.

Table 4-1. Time intervals between stroke onset, admission to hospital, admission tostroke unit, neuroradiologistic evaluations, and clinical outcome evaluations.Zero (0) indicates same day event.

Time Interval Mean no. days S.D. Minimum MaximumStroke—hospital .34 .81 0 5Hospital—CT .28 .50 0 2Hospital—MRI .82 .99 0 5Hospital—unit .47 .80 0 4Unit—clinical 2.00 1.24 0 4Stoke—clinical 2.81 1.51 0 8

Once admitted, 75% of patients received a CT examination on the same day and

100% within one day (Table 4-1). MRI scans, when completed, were slightly more

delayed than CT scans as only 43% of patients received these procedures on the day of

admission, 84% within one day, and 98% within three days. The average interval

between hospital admission and completion of neuroradiologic examinations was 0.28

days and 0.82 days for CT and MRI, respectively.

19

Patients were quickly transferred into the stroke unit as evidenced by an average

interval of 0.47 days between hospital admission and stroke unit admission. Sixty-four

percent (64%) of patients were transferred to the stroke unit on the day of hospital

admission. Ninety-four percent (94%) of patients were transferred to the stroke unit

within a single day.

On average, patients were recruited into the study and completed clinical outcome

measure evaluations within 2 days of being admitted to the stroke unit. Seventy percent

(70%) of all clinical evaluations were completed within two days of admission to the

stroke unit and all evaluations were completed within 4 days. Collectively, patients were

evaluated with the clinical outcome measures on an average of 2.81 days following

recognition of stroke symptoms. Seventy-two percent (72%) of patients were evaluated

within 2 days and 96% within 5 days.

Patient Characteristics

Fifty-five (55) patients were recruited into the study satisfying the a priori power

analysis. Descriptive data for continuous variables is presented in Table 4-2. Descriptive

data for categorical variables is presented in Table 4-3. Scores from the NIHSS,

modified Barthel Index (Table 4-2) and the modified Rankin scale (Table 4-3) identified

this patient group as moderately impaired. The majority of strokes (Table 4-3) were

partial anterior circulation infarcts (PACI) with lower numbers of patients demonstrating

total anterior circulation infarcts (TACI).

Gender was approximately equally distributed within this sample as was race, and

marital status, though slightly more Caucasian patients and slightly more patients who

were not married at the time of stroke were recruited into the study (Table 4-3). Diabetes

was identified in just over 21.9% of patients, but hypertension was more prevalent at

20

nearly 72.7%. The clear majority of patients did not report extensive tobacco or alcohol

use. Few patients had histories or clinical findings of coronary artery disease or atrial

fibrilation, but just over 27.3% had identified hyperlipidemia. rTPA therapy was

provided to just over 9.1% of this sample (Table 4-3).

Table 4-2. Descriptive data for continuous variables obtained from 55 acute ischemicstroke patients

Variable* Mean SD 95% Cl Minimum MaximumAge 65.2 12.4 61.5–68.9 36 85NIHSS 7.0 6.5 5.05–8.9 0 22mBI 9.7 7.0 7.6–11.8 0 20MASA 171.0 27.8 162.8–179.4 107 200MNA 24.8 4.0 23.6–26.0 15 30% Fat 30.0 6.2 28.4–32.1 10 39BMI 27.0 4.5 25.9–28.6 17 36

*NIHSS = National Institutes of Health stroke scale, mBI = modified Barthel index,MASA = Mann assessment of swallowing ability, MNA = mini nutritional assessment,% Fat = percent body fat, BMI = body mass index

Also presented in Table 4-3 are data obtained from 2004 statistics provided by the

American Heart Association (AHA, 2004). These data suggest that gender, prior stroke,

diabetes, smoking history, and coronary artery disease characteristics in the study sample

are closely matched to the general population of stroke patients (or in some instances

general population estimates) studied by the AHA. The frequency of African American

participation in the current study is somewhat lower than the age-adjusted incidence of

African-American versus Caucasion stroke patients (2:1) in the AHA data. This finding

may be related to the demographics of the recruitment area (approximately 28% African-

American), or to other factors inherent in the geographic region or in community health

care practices. In addition, only 27% of the study sample was identified as presenting

with hyperlipedemia. The AHA reports that just over 50% of both men and women have

total cholesterol over 200 mg/dL, one of the criteria for identification of hyperlipidemia

in this study.

21

Table 4-3. Descriptive data for ordinal and categorical variables obtained from 55 acuteischemic stroke patients

Variable* Level Percent**Number of

Patients AHA 2004Gender Male 49 27 47%

Female 51 28 53%Race African-American 44 24 2:1 age

adjustedincidence

Caucasian 55 30Marital Status Married 42 23

Not Married 56 31Prior Stroke Yes 31 17 29%

No 62 34 71%Diabetes Yes 22 16 13% (female)

No 67 37 18% (male)Hypertension Yes 73 40 32.1% (female)

33.1% (male)No 24 13

Smoking Nonsmoker 76 42Smoker or Recent Hx 18 10 22.8%

(population)Alcohol Drinker 6 3

Nondrinker 89 49CAD Yes 7 4 6.0% (female)

6.9% (male)No 89 49

AFIB Yes 6 3No 91 50

Hyperlipidemia Yes 27 15 50.7%(population)

No 69 38Stroke Type(Bamford)

TACI 11 6

PACI 53 29LACI 20 11POCI 13 7

rTPA Yes 9 5No 89 49

Mod Rankin Scale 01

67

3 4

2 20 113 20 114 26 145 18 10

FOIS 1 2 12 0 0

Table 4-3. Continued

22

Variable* Level Percent**Number of

Patients AHA 20043 6 34 13 75 27 156 13 77 38 21

*Refer to Table 1-1 for description of variables**Values not equaling 100% are due to missing data.CAD = coronary artery disease, AFIB = atrial fibrilation, rTPA = treatment with rTPA,FOIS = functional oral intake scale

Table 4-4 presents dichotomized data from dysphagia, nutrition, and stroke

severity variables. Just over half (50.9%) of the sample was identified as demonstrating

dysphagia based on the MASA examination with 47.3% demonstrating some limitation

in oral intake of food and liquid as reflected in the FOIS scale. Based on the MNA,

nearly one-quarter of the patients (23.6%) were classified at having poor nutritional

status. However, BMI scores identified a much smaller percentage of malnourished

patients (1.8%). The BMI scores indicated that 30.9% of this sample was obese. Stroke

impairment as measured by the NIHSS, mRS, and mBI suggest that approximately one

half of this sample demonstrated at least moderate impairment.

Table 4-4. Frequency of impairment of dysphagia, nutrition, and stroke severityvariables. Individual measures and cut off scores are identified withinparentheses

MeasureNumber of patients

impaired Percent impairedDysphagia (MASA < 178) 28 50.9Dysphagia (FOIS <6) 26 47.3Nutrition (MNA < 23.5) 13 23.6Nutrition (BMI Low < 18) 1 1.8Nutrition (BMI High = Obese > 30) 17 30.9Stroke (mRS >3) 35 63.6Stroke (NIHSS >8) 18 32.7Stroke (mBI <12) 30 54.5

MASA = Mann assessment of swallowing ability; FOIS = functional oral intake scale;MNA = mini nutritional assessment; BMI = body mass index, mRs = modified rankingscale; NIHSS = National Institutes of Health stroke scale; mBI = modified Barthel index

23

Correlation and Association Analyses

Table 4-5 presents results of correlation analyses among continuous variables for stroke

severity, dysphagia, and nutritional status. Both dysphagia measures (MASA, FOIS)

correlate significantly with stroke severity measures (NIHSS: -0.665, -0.581; mRS: -

0.697, -0.584; mBI: 0.552, 0.469), but not with any measure of nutritional status (MNA:

0.018, -0.003; % Fat: 0.188, 0.176; BMI: 0.269, 0.206). Likewise, none of the nutritional

measures (MNA, % Fat, BMI) correlated significantly with any of the stroke severity

measures. The stroke severity measures tend to correlate with each other as do the

dysphagia measures. Results from the MNA do not correlate with the remaining

nutritional measures (BMI or % Fat).

Table 4-5. Correlations among outcome measures for dysphagia, nutritional status, andstroke severity in 55 patients with acute ischemic stroke

MASA FOIS MNA %Fat BMI Age NIHSS mRs mBIMASA .836* .018 .188 .269+ -.107 -.665* -.697* .552*FOIS -.003 .176 .206 -.072 -.581* -.584* .469*MNA .231 .232 .077 .107 -.160 .024%Fat .477* -.042 - .019 -.215 -.100BMI -.372* .230 -.206 .140Age -.112 .144 -.252NIHSS .729* -.609*mRs -.638**Significant beyond the .05 level+ p = .056MASA = Mann Assessment of Swallowing Ability, FOIS = Functional Oral Intake Scale,MNA = Mini Nutritional Assessment, % Fat = percent body fat, BMI = body mass index,NIHSS = National Institutes of Health Stroke Scale, mRs = Modified Ranking Scale,mBI = Modified Barthel Index

Tables 4-6 and 4-7 present results of association analyses among categorical

(dichotomized) variables for dysphagia (Table 4-6) and poor nutritional status

(Table 4-7). As seen in Table 4-6, only 4 variables are significantly associated with the

presence of dysphagia. Scores on the mRS (OR 10.9, 95% CI 2.6–45.6), NIHSS (OR

6.5, 95% CI 1.7–24.68), mBI (OR 3.7, 95% CI 1.6–11.9), and FOIS (OR 20.2, 95% CI

24

5.0–8.5) are significantly associated with dysphagia. Other variables (gender,

hypertension, smoking, atrial fibrillation, and TACI) revealed elevated odds ratios

suggesting trends of association with dysphagia; however, these were not statistically

significant.

Table 4-6. Odds ratios (OR), 95% confidence intervals (CI), and chi-square (X2) resultsfor categorical variable comparisons with dysphagia (+/-). Continuous andordinal variables were dichotomized using accepted or clinically plausiblecut-points for this analysis.

Comparison Chi-Square OR 95% CI

mRs 12.8* 10.9 2.6–45.6NIHSS 8.6* 6.5 1.7–24.7mBI 5.0* 3.7 1.6–11.9rTPA - - -Prior stroke 0.04 0.89 .3–2.9Gender 2.7 2.5 .8–7.4Marital status 0.4 1.4 .5–4.1Race 0.1 1.1 .4–3.4Diabetes 1.7 0.5 .1–1.5Hypertension 1.1 2 .5–7.0Smoking 2 2.8 .6–12.4Alcohol - - -CAD 1.2 0.3 .0–3.0AFIB 0.3 2 .2–23.5Hyperlipidemia 1 0.5 .2–1.8Poor nutrition 0.2 0.7 .2–2.6FOIS 21.6* 20.2 5.0–8.5Obesity 0.8 0.6 .2–1.9Bamford Type TACI PACI LACI POCI

2.7 1.2 .0 .3

5.4 .5 1.1 .7

.6–50.1 .2–1.6 .3–4.3 .1–3.3

* Significant beyond the .05 level+ p = .074

Treatment with rTPA or excessive alcohol use were not analyzed with these

procedures owing to small event rates (N = 5 and 3 respectively) and empty cells in the 2

25

X 2 matrix. However, at the descriptive level all patients who were treated with rTPA

and all patients who were identified to use alcohol excessively were identified as

dysphagic.

Only a single variable, smoking, was significantly associated with poor nutrition

as defined in this study (OR 9.4, 95% CI 1.9 – 47.1). Additional variables (alcohol, atrial

fibrilation, hyperlipidemia, and LACI) revealed elevated odds ratios suggesting trends of

association with poor nutritional status; however, these were not statistically significant.

Table 4-7. Odds ratios (OR), 95% confidence intervals (CI), and chi-square (X2) resultsfor categorical variable comparisons with nutritional status (+/-). Continuousand ordinal variables were dichotomized using accepted or clinically plausiblecut-points for this analysis.

Comparison Chi-Square OR 95%mRs 0.11 0.8 .2–3.0NIHSS 0.07 1.2 .3–4.5mBI 0.14 1.3 .4rTPA 0.57 0.2 .3–14.0Prior Stroke 0.5 .6 .1–2.6Gender 0.01 1.0 .3–3.4Marital Status 0.12 1.3 .4–4.5Race 0.4 1.5 .4–5.5Diabetes 0.4 0.6 .2–2.7Hypertension 2.774 0.3 .1–1.3Smoking 9.112* 9.4 1.9–47.1Alchohol .734 3.3 .2–56.7CAD .002 0.9 .1–10.0AFIB .315 2 .2–23.5Hyperlipidemia 1.418 2.3 .6–8.9Dysphagia .241 0.7 .2–2.6FOIS .000 1 .3–3.6Obesity (BMI) .791 0.6 .2–1.9Bamford Type TACI PACI LACI POCI

.220 .0571.3792.776

1.51.22.4 .7

.3–9.6 .3–4.1 .6–10.3 .6–.9

* Significant beyond the .05 level

26

Predictors of Dysphagia or Poor Nutritional Status

Given the low event rate for poor nutritional status as defined in this study

(N = 13) and the resulting correlation and association analyses identifying only a single

significantly associated variable, no regression analysis was completed on this outcome

variable. The event rate for dysphagia (N = 26) was deemed sufficient only to support a

pilot or exploratory regression analysis to identify independent predictors of this outcome

variable. However, only four variables were significantly associated with dysphagia at

the univariate level: NIHSS, mRS, mBI, and FOIS. As seen in Table 4-5, these variables

were highly intercorrelated, with the FOIS demonstrating the highest correlation with

dysphagia as measured by the MASA. However, since the FOIS score is the result of

dysphagia it is unsuited to serve as a predictor of dysphagia following stroke. Of the

remaining variables, the mRS demonstrated the strongest univariate relationship with

dysphagia. Thus, of all the variables considered in this study, stroke severity, specifically

as reflected by the modified Rankin scale (mRS), emerged as the best independent

predictor of post stroke dysphagia (OR 10.9, 95% CI 2.6 – 45.6).

Smoking was the only variable significantly associated with poor nutritional

status (OR 9.4, 95% CI 1.9 – 47.1). The large confidence intervals associated with both

variables indicate relatively large variability, and hence instability, around the point

estimate.

27

CHAPTER 5DISCUSSION

This study found no significant associations between dysphagia and nutritional

status in a sample of acute ischemic stroke patients. Furthermore, while dysphagia was

related to stroke severity, nutritional status was not. Collectively, these findings raise

questions focusing on the procedures used to assess nutritional status in this study and,

more generally, the timing of nutritional assessments preceding and following stroke.

The primary nutritional outcome measure in this study was the Mini Nutritional

Assessment (MNA). This tool appears to be a better indicator of premorbid nutritional

status than nutritional changes following stroke. Items on the MNA include dietary

changes, weight loss, and stress factors that may have occurred 3 months prior to the

evaluation. In addition, anthropomorphic measures such as BMI, mid-arm

circumference, and calf circumference are included. These measures would not be

expected to reflect rapid changes in nutritional status as they rely on physical changes in

weight or body fat that are reactive to a prolonged state of poor nutrition. Other items in

the MNA, specifically pressure sores or skin ulcers, also reflect more chronic nutritional

problems. Therefore, though the MNA has demonstrated a strong relationship with both

energy intake (r = 0.50, p < .001) and serum albumin (r = 0.71, p < .001), it is not well

suited to assess acute, potentially rapid changes in nutritional status. It is similar to the

Subjective Global Assessment (SGA), which has been used recently to study the impact

of premorbid nutritional status on stroke outcome (Davis et al., 2004). In that regard, the

28

present study is better considered as an assessment of premorbid nutritional status on

stroke severity and post stroke dysphagia. The results of the present study would suggest

that premorbid nutritional status as defined by MNA results does not impact either stroke

severity nor the presence or severity of post stroke dysphagia.

The lack of association between nutritional status and dysphagia is in agreement

with earlier findings in acute stroke reported by Davalos and colleagues (1996) who

reported no nutritional differences between patients with and without swallowing

problems at admission. These investigators used a combination of blood serum markers

(serum albumin) and anthropomorphic markers (triceps skin fold and mid-arm muscle

circumference) to estimate nutritional status. Likewise, preliminary results from the

FOOD Trial (FOOD Trial Collaboration, 2003) reported no descriptive differences in the

percent of patients with swallowing impairment among undernourished, normal, and

overweight stroke patients. These investigators used various combinations of clinical

impression, anthropomorphic measures, and/or blood serum markers to assess nutritional

status within an average time interval of 7 days following stroke symptom onset. No

other studies have examined potential relationships between swallowing ability and

nutritional status in the acute stroke patient. Thus, the results of the present study in

combination with prior and ongoing investigations suggest that nutritional status is not

related to the presence of dysphagia in the acute stroke patient.

In the present study, dysphagia was significantly associated to multiple measures

of stroke severity. At least one prior study has suggested that stroke severity was an

important predictor of dysphagia in the post stroke patient. Mann and Hankey (2001)

reported that disabling stroke as measured by the Barthel Index (score < 60 on the full

index) was a significant predictor of dysphagia (assessed by radiographic procedure) in a

29

group of 128 acute stroke patients. In the present study, all indices of stroke severity

(NIHSS, mRS, and mBI) were significantly associated with the presence of dysphagia

with the modified Rankin Scale (mRS) demonstrating the strongest association (OR 10.9,

95% CI 2.6–45.6).

Nutritional status did not correlate or associate with any of the stroke severity

measures. Davalos et al. (1996) reported that malnourished status (serum album, triceps

skinfold or mid-arm circumference) was significantly associated with stroke severity

(Canadian Stroke Scale < 5) at admission. The criteria for “malnourished” in their study

was either low serum albumin or triceps skin fold or mid-arm circumference less than the

10th percentile of their reference population. These investigators did not account for

potential premorbid functional limitations that might impact their measures. Conversely,

Davis and colleagues (2004) found that stroke severity as measured by the NIHSS was

not associated with poor nutritional status as measured by the Subjective Global

Assessment (SGA) in acute stroke patients. These investigators did use a premorbid

modified Rankin Scale to identify a significant association with premorbid nutritional

status measured by the SGA. One conclusion is that premorbid functional level may

impact nutritional status preceding or following stroke. This observation may be

supported by the finding in the present study that smoking was the only premorbid

variable significantly associated (OR 9.4, 95% CI 1.9–47.1) with poor nutritional status

as measured by the MNA.

In the present study, only 13 patients were identified to reflect poor nutritional

status based on results of the MNA. On the dichotomized modified Barthel Index and the

modified Rankin Scale, 61.5 % (N = 8) of the patients with poor nutritional status were

considered impaired while 38.5% (N = 5) were above the established cut-off for

30

impairment. These proportions did not result in significant associations. The resulting

proportions based on the NIHSS cut-off score were reversed. The majority of patients

with poor nutritional status (61.5%) were not identified as beyond the cut-off for

impairment. Collectively, these findings may reflect the somewhat arbitrary nature of

dichotomizing these scales, and certainly reflect the small sample size. Future studies

should evaluate not only larger samples but also multiple cut-off scores based on specific

criteria. At a descriptive level, more patients with poor nutritional status were classified

as impaired by the mRS and mBI. This finding may or may not have been maintained

with a larger sample.

One strength of this study was the inclusion of standard clinical assessment

protocols for both dysphagia and nutritional assessment. The Mann Assessment of

Swallowing Ability (MASA) was specifically developed and validated to assess

dysphagia in post stroke patients. This is a commonly used tool that is widely accepted

and accessible for replication efforts. Likewise, the Mini Nutritional Assessment (MNA)

was developed and validated to assess nutritional status in elderly patients. However,

this tool has not been specifically validated for use in post stroke patients. Thus, while

validated and accessible methods were employed for both dysphagia and nutritional

assessments, this study was the first attempt to utilize the MNA to evaluate nutritional

status in a sample of post stroke patients. One result of that application is the implication

that this tool may be biased to premorbid factors that impact nutritional status in the post

stroke patient. This implication is one potential limitation of the present study.

Potential limitations of this study arise primarily from limited sample size and

from limitations in outcome assessment protocols, especially for nutritional assessment

as mentioned above. Though small, this sample did reflect certain characteristics

31

associated with general health characteristics and/or characteristics of stroke patients

from national surveys (Table 4-3). Also, the prevalence of both dysphagia and poor

nutritional status as defined in this study parallels that reported in several prior studies

using varying assessment protocols. Thus, though this study may suffer from small

sample size and associated limitations in statistical power, the subject sample does have

some degree of external validity.

A primary limitation in the interpretation of obtained results was the choice of the

nutritional status measures. As discussed above, it is likely that the MNA as used in this

study is more sensitive to premorbid nutritional status than to changes in nutritional

status that might be induced by stroke. The same argument may be applied to both BMI

and percent body fat. These methods may be relatively insensitive to very rapid changes

in nutritional status. Davalos (1996) reported that nutritional indices deteriorated during

the first week post stroke. This finding is consistent with many observations of

nutritional decline following stroke (Axelsson et al., 1988; Davalos et al., 1996; Gariballa

et al., 1998a). Additionally, poor nutritional status is often associated with poorer stroke

outcome and with measures of severity and other comorbidities subsequent to the

immediate post stroke period (Davalos et al., 1996; Davis et al., 2004; Dziedzic et al.,

2004). It is conceivable that in the immediate post stroke period, nutritional status is

more representative of premorbid status and that with time nutritional decline, when

present, results from stroke-related factors. From this perspective, combining an

assessment technique that identifies rapid nutritional changes with techniques that reflect

more long-term changes in nutritional status would prove beneficial. One possibility

would be to use serum markers such as prealbumin to identify short-term protein changes

that reflect rapid changes in nutritional status. Combined with more long-term markers

32

such as serum albumin or clinical and anthropomorphic measures such as the MNA and

SGA, a more complete profile of nutritional status and change over time might result.

Future studies should include a follow up period to study the impact of dysphagia

and poor nutritional status, both individually and combined, on functional outcome in the

stroke survivor. While prior studies have addressed one or the other of these factors, no

study has looked at their combined impact. Prior to addressing this task, however,

follow-up studies should evaluate the potentially changing relationship between

dysphagia and nutritional status during the poststroke recovery period. The natural

history of potential interactions between dysphagia and nutritional status following stroke

has not been examined. Combined with improved nutritional surveillance, follow up

studies will have the potential to provide significant insight into two prevalent limitations

encountered by the stroke survivor and to evaluate the combined impact of these

morbidities.

A subsequent step to this study will involve use of biochemical markers of

nutritional status and a pre-defined time table of follow up to identify changes in

nutritional status and dysphagia over time and to estimate the impact of these variables,

individually and combined, on functional outcome. Specifically, serum albumin levels

will be used as an estimate of longer-term nutritional status that will reflect the prestroke

condition. This measure will be supplemented by premorbid assessment of nutritional

parameters assessed by both the MNA and the SGA. Also, premorbid level of

stroke-related disability will be assessed using the mBI and the mRS. Serum prealbumin

levels will be used as a reflection of post-stroke changes in nutritional status. Dysphagia

presence and severity (MASA) and feeding patterns (FOIS) will be used to identify

swallowing factors that may impact changes in nutritional status following stroke. To

33

detail the natural history of these variables, premorbid estimates will be obtained from

family members upon admission to the hospital. Likewise, serum albumin and

prealbumin levels will be obtained upon admission and at one week post-stroke or upon

discharge from the stroke unit, whichever occurs first. Finally, a systematic program of

follow up evaluations will be implemented at one, three, and six months following

discharge from the stroke unit. These changes will facilitate better description of

longitudinal changes in stroke severity, dysphagia, and nutritional status and permit study

of the potential dynamic nature of the interaction between dysphagia and nutritional

status in the stroke survivor.

One final aspect to consider is whether or not to evaluate biochemical aspects of

the post-stroke stress factor. Many biochemical markers have been used to evaluate this

phenomenon. Therefore, the research team must consider which if any aspects of the

stress factor to evaluate.

In summary, the present study found no significant relationship between

dysphagia and nutritional status in the acute ischemic stroke patient. Furthermore, while

dysphagia was significantly related to stroke severity, nutritional status was not. The

potential influence of prestroke parameters must be considered when evaluating

poststroke nutritional status. Likewise, nutritional parameters sensitive to more rapid

changes in status should be employed. Finally, it will be imperative to follow stroke

patients over time to fully understand the potential interaction of the two dynamic

morbidities.

34

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37

BIOGRAPHICAL SKETCH

Michael A. Crary, Ph.D., is a Professor of Speech-Language Pathology and

Director of the Florida Dysphagia Institute at the University of Florida Health Science

Center. Dr. Crary's current clinical and research interests revolve around disorders of

swallowing, specifically improving assessment and treatment strategies. Current research

projects include studies of the clinical and instrumental evaluation of dysphagia and

outcomes of various treatments. He has a long history as a practicing clinician and

remains active in patient care. He has written and lectured extensively, including

internationally, on these topics. His latest project is the text The Introduction to Adult

Swallowing Disorders. He has served as assistant director of the ASHA Special Interest

Division #13: Dysphagia. He is a former nominee for the DiCarlo award from ASHA, a

recipient of the Outstanding Clinical Achievement Award from ASHA, and has been

elected as a Fellow of ASHA.