Associating the Bulbar and Respiratory Dysfunctions in Patients

with Amyotrophic Lateral Sclerosis

by

Nicholas Alexander Wasylyk

A thesis submitted in conformity with the requirements

for the degree of Master of Science

Rehabilitation Science Institute

University of Toronto

© Copyright by Nicholas Alexander Wasylyk (2018)

ii

Associating the Bulbar and Respiratory Dysfunctions in Patients with

Amyotrophic Lateral Sclerosis

Nicholas Alexander Wasylyk

Master of Science

Rehabilitation Science Institute

University of Toronto

2018

Abstract

Motivated by the need to establish clinical measures of bulbar motor dysfunction, this study

investigated the associations between bulbar and respiratory measures in patients with

amyotrophic lateral sclerosis (ALS). A secondary analysis of 158 participants (female=59)

evaluated: (1) group differences in bulbar motor measures between patients with normal

respiratory function (ALSnr) and those with impaired respiratory function (ALSir); and (2)

correlations between the bulbar motor and respiratory measures. A significantly larger percent

pause time during passage reading was revealed in the ALSir (24.4±7.1) as compared to ALSnr

(19.6±6.5) group. A significant negative correlation between percent pause time and forced vital

capacity (%FVC) was identified; a partial correlation between percent pause time and speaking

rate remained significant after controlling for %FVC. The findings suggested that the respiratory

deficit minimally affected the selected bulbar motor measures, thus supporting their use in

clinical assessment of bulbar ALS.

iii

Acknowledgments

My learning throughout my graduate studies was influenced by many individuals. Although only

a few of them are mentioned below, I am grateful for everyone who contributed to my graduate

experience.

I express my sincerest gratitude towards Dr. Yana Yunusova, my primary supervisor. Her shared

knowledge, support and guidance have shaped me into the student I am today. I will forever be

thankful for the opportunity to join Dr. Yunusova’s lab and contribute to her research. My future

achievements will be attained in part because of what I learned through my experiences with Dr.

Yunusova.

Dr. Rosemary Martino, my co-supervisor, allowed me to partake in many learning opportunities

within her lab as well. I am thankful for all of Dr. Martino’s encouragement and contribution

towards the completion of my graduate studies.

Dr. Dina Brooks truly completed my supervisory committee. Her insight and expertise have

greatly assisted with the completion of this thesis.

Dr. Madhura Kulkarni, Dr. Elaine Kearney, Sanjana Shellikeri, Dr. Andrea Bandini, Elissa

Greco, Victoria Sherman, Dr. Ana Furkim and Dr. Gabriela Vanin have made my graduate

studies more enjoyable. They impacted me greatly, and I am thankful for all I have learned from

them and the bonds we developed.

Last, but definitely not least, my accomplishments would mean nothing without my family and

girlfriend—Len Wasylyk, Nina Alpejev, Natalie Wasylyk, Stephanie Wasylyk and Nadia

Larocca. They made the long days and stressful times all the more worthwhile. I cherish every

moment they shared with me and their never-ending love and support. They will always hold a

special place in my heart.

Table of Contents

Acknowledgments.......................................................................................................................... iii

List of Tables ................................................................................................................................. vi

List of Figures ............................................................................................................................... vii

Introduction and Literature Review .........................................................................1

1.1 Introduction ..........................................................................................................................1

1.2 ALS as a Disease of the Motor System ...............................................................................1

1.3 ALS Epidemiology ..............................................................................................................2

1.4 Subtypes of ALS ..................................................................................................................3

1.5 Bulbar ALS ..........................................................................................................................4

1.6 Clinical Assessment of Bulbar Function..............................................................................4

1.7 The Subsystem Approach towards Measuring Bulbar Dysfunction in ALS .......................6

1.8 Physiological Measures of Bulbar Function by Subsystem ...............................................11

1.8.1 Articulatory Subsystem ..........................................................................................11

1.8.2 Respiratory Subsystem...........................................................................................13

1.8.3 Resonatory Subsystem ...........................................................................................14

1.8.4 Phonatory Subsystem .............................................................................................15

1.8.5 Summary of the Identified Subsystem-Based Bulbar Measures............................16

1.9 Clinical Measures of Respiratory Dysfunction in ALS .....................................................17

1.9.1 Forced Vital Capacity ............................................................................................17

1.9.2 Peak Expiratory Airflow ........................................................................................18

1.10 Research Objectives and Hypothesis ................................................................................18

Methods..................................................................................................................20

2.1 Study Design ......................................................................................................................20

2.2 Participants: Inclusion Criteria ..........................................................................................20

v

2.3 Data Collection Protocol: Instrumentation and Tasks .......................................................21

2.4 Statistical Analysis .............................................................................................................22

Results ....................................................................................................................24

3.1 Participant Characteristics: ALS Group Combined and ALS Subgroups .........................24

3.2 Physiological Subsystem Measures and ALS Subgroup Comparisons .............................27

3.3 Associations between Physiological Subsystem Measures and %FVC ............................29

3.4 Associations between Physiological Subsystem Measures and PEF .................................30

3.5 Partial Correlation between Percent Pause Time and Speaking Rate, Controlling for

%FVC ................................................................................................................................31

Discussion ..............................................................................................................32

4.1 Summary ............................................................................................................................32

4.2 Use and Interpretation of Physiological Subsystem Measures in the Assessment of

Bulbar ALS ........................................................................................................................32

4.3 Percent Pause Time During a Reading Task and Respiratory Dysfunction ......................35

4.4 PEF as a Measure of Respiratory Decline in ALS .............................................................36

4.5 Contribution to the Literature ............................................................................................37

4.6 Nature of Measures: Maximum versus Submaximal Performance ...................................37

4.7 Limitations of the Present Study ........................................................................................38

4.8 Conclusions ........................................................................................................................39

4.9 Future Directions ...............................................................................................................40

References ......................................................................................................................................41

vi

List of Tables

Table 1: Summary of descriptive statistics for physiological subsystem measures in healthy

adults. ............................................................................................................................................ 17

Table 2: Clinical respiratory measures and associated instruments and instructions. .................. 21

Table 3: Physiological subsystem measures and associated instruments and instructions. .......... 22

Table 4: Participant demographic and clinical characteristics.. .................................................... 26

Table 5: Participant demographic and clinical characteristics for ALSnr and ALSir subgroups.. 26

Table 6: Descriptive statistics of the subsystem measures by subgroup. ..................................... 28

Table 7: Test statistics for the group comparisons of the physiological subsystem measures

between the ALSnr and ALSir subgroups. ................................................................................... 28

Table 8: Correlations between physiological subsystem measures and %FVC. .......................... 30

Table 9: Correlations between physiological subsystem measures and PEF. .............................. 31

vii

List of Figures

Figure 1: The four speech subsystems. ........................................................................................... 7

Figure 2: Likelihood of maintaining function over time of speech intelligibility, speaking rate

and the four physiological subsystems. .......................................................................................... 9

Figure 3: A CONSORT diagram of study flow. .......................................................................... 25

Figure 4: Boxplot dipslaying percent pause time group comparison. .......................................... 29

Figure 5: Scatterplot displaying the correlation between percent pause time and %FVC. ........... 30

1

Introduction and Literature Review

1.1 Introduction

The aim of this thesis is to better understand the association between bulbar motor and

respiratory dysfunction in patients with amyotrophic lateral sclerosis (ALS). This research is

important because bulbar motor and respiratory functions are interlinked in the production of

speech and swallowing, and respiratory dysfunction may affect bulbar dysfunction

measurements. The current assessment of bulbar dysfunction in ALS is limited to symptom

reports and global measures of function such as speech intelligibility and speaking rate; there is a

substantial need for assessments capable of detecting early signs of bulbar dysfunction and

monitoring the bulbar disease progression over the course of disease progression (Ball, Willis,

Beukelman, & Pattee, 2001; Green et al., 2013; Yorkston, Strand, Miller, Hillel, & Smith, 1993).

Recent research into the instrumental physiological measures of speech shows that these

measures have the potential to improve clinical practice and the design of therapeutic drug trials

by identifying early changes of the bulbar musculature prior to significant loss of speech and/or

swallowing functions as well as provide a method for tracking disease progression (Allison et al.,

2017; Green et al., 2016; Rong, Yunusova, Wang, et al., 2016). However, the same measures

may be affected by the underlying respiratory deficit common in ALS, and their associations

with respiratory dysfunction need to be examined. This thesis aims to examine the association

between bulbar motor and respiratory dysfunction in a large group of participants with ALS. The

present chapter will provide an overview of ALS as a disease of the motor system as well as

summarize the literature regarding the current state of assessment of bulbar dysfunction. It will

also detail the rationale for the present study.

1.2 ALS as a Disease of the Motor System

ALS is a rapidly progressing and fatal neurodegenerative disease that has recently been termed a

multisystem disorder because of its effects on both motor and extra-motor (e.g., cognitive and

language) neural pathways (Phukan et al., 2012; Schreiber et al., 2005; Shellikeri et al., 2017).

Although cognitive and language dysfunction is often reported in ALS, the primary impairment

involves the motor system (Strong et al., 2017). The upper motor neurons (UMN) relay the

neural impulses from the brain to the cranial and spinal nerves along the corticobulbar and

2

corticospinal tracts. The lower motor neurons (LMN) then relay these neural impulses to the

muscles to instigate movement. In ALS, UMN and LMN degeneration results in functional

motor changes involving the limbs, trunk and head and neck musculature (Andersen et al., 2012).

UMN degeneration results in hyperreflexia and muscle spasticity, whereas LMN degeneration

results in muscle weakness, muscle atrophy and fasciculations (Brooks, Miller, Swash, &

Munsat, 2000).

Diagnosing ALS is a challenge for clinicians because a biomarker of the disease has yet to be

identified. A clinical diagnosis is provisional and provided based on the El Escorial Diagnostic

Criteria (Brooks et al., 2000). To receive a definite diagnosis of ALS, a patient must exhibit signs

of UMN and LMN degeneration in three regions (i.e., either 3 spinal regions or 2 spinal regions

and the bulbar region). A probable diagnosis is given to patients displaying signs of UMN and

LMN degeneration in two regions, or when one region displays signs of UMN degeneration and

two regions exhibit laboratory evidence of LMN degeneration. A possible diagnosis of ALS is

provided to patients exhibiting either UMN and LMN degeneration in one region, UMN

degeneration in two regions, or signs of LMN degeneration located rostrally to signs of UMN

degeneration (Brooks et al., 2000). Notably, UMN signs are difficult to detect as LMN signs

often mask them (Huynh et al., 2016; Swash, 2012). LMN signs in turn are challenging to detect

due to the limitations of muscle electromyography (EMG), the gold standard of LMN function

assessment (Dyck, 1990). These EMG limitations are particularly notable when assessing

muscles of the bulbar region (Finsterer, Fuglsang-Frederiksen, & Mamoli, 1998; Ludlow et al.,

1994). The lack of sensitive diagnostic measures contributes to the diagnostic delay, which is

approximately 12 months in bulbar onset ALS cases and over 2 years in spinal onset ALS cases

(Turner, Brockington, et al., 2010; Turner, Scaber, et al., 2010). To add to the diagnostic

challenge, several conditions (e.g., multifocal motor neuropathy with conduction block,

hereditary spastic paraparesis and spinobulbar muscular atrophy) resemble various signs and

symptoms of ALS requiring clinicians to distinguish ALS from these conditions (Turner &

Talbot, 2013).

1.3 ALS Epidemiology

ALS is a rare disease with an incidence rate of 1.90 (IQR = 1.37 – 2.40) for every 100,000

individuals across North America, South America, Europe and Asia (Chiò et al., 2013). For

3

every 100,000 individuals, the median prevalence of ALS is 4.48 (IQR = 3.03 – 6.70) (Chiò et

al., 2013). In Canada, the age-adjusted incidence rate of ALS ranges between 2.0-2.3 per

100,000 people (Wolfson, Kilborn, Oskoui, & Genge, 2009). The typical age of onset is between

50-65 years but can range from early to late adulthood (Kiernan et al., 2011; Nichols et al., 2013;

Talbot, 2009; Turner & Talbot, 2013). The incidence and prevalence of ALS occurs at a slightly

increased rate in men as compared to women; population-based studies reported that 1.11-2.32

men develop ALS relative to women (Cetin et al., 2015; McCombe & Henderson, 2010).

There is currently no known definitive cause of ALS (Blokhuis, Groen, Koppers, van den Berg,

& Pasterkamp, 2013; Talbott, Malek, & Lacomis, 2016). Genetic mutations (e.g., C9ORF72,

SOD1, TDP-43 and FUS) have been identified as leading to ALS in approximately 10% of

patients (Blokhuis et al., 2013; Kiernan et al., 2011; Talbott et al., 2016). The remaining

individuals are said to have a sporadic disease. In individuals with a sporadic form of ALS,

potential risk factors (e.g., exposure to various metals, pesticides and trauma, engagement in

professional sports and contribution to military service) have also been suspected (Talbott et al.,

2016).

Patients with ALS have an average life expectancy of 2-5 years from symptom onset with less

than 10% of patients surviving longer than 10 years (Berlowitz et al., 2015; Kasarskis,

Berryman, Vanderleest, Schneider, & McClain, 1996; Milonas, 1998; Weikamp, Schelhaas,

Hendriks, de Swart, & Geurts, 2012). Respiratory complications (e.g., respiratory failure,

aspiration and aspiration pneumonia) are the leading causes of death in ALS (Lechtzin,

Rothstein, Clawson, Diette, & Wiener, 2002). Respiratory distress, increased age, significant

weight loss and site of symptom onset – specifically bulbar onset ALS – are associated with

reduced survival (Kasarskis et al., 1996; Talbot, 2009).

1.4 Subtypes of ALS

ALS is an extremely heterogeneous disease and several methods of patient subgrouping have

been used in clinical practice and research (Swinnen & Robberecht, 2014; Turner & Talbot,

2013). Patients have been subgrouped by the genetic causes of the disease (e.g., SOD1,

C9ORF72), the rate of disease progression (e.g., fast versus slow progressors) or the relative

degree and type of motor (e.g., predominantly UMN or LMN presentation) or cognitive (e.g.,

ALS with cognitive deficit and ALS-Frontotemporal Dementia) dysfunction (Strong et al., 2017;

4

Talbot, 2009). The most common method for subgrouping participants, however, is based on the

region of symptom onset. Approximately, 70-80% of the ALS population initially display

symptoms involving the limb motor system (i.e., spinal onset), affecting mobility and arm/hand

use. The remaining 20-30% of patients with ALS present with oropharyngeal dysfunction (i.e.,

bulbar onset), affecting speech and swallowing functions. Approximately 2% or less of patients

with ALS present with respiratory dysfunction (i.e., respiratory onset), affecting the ability to

breathe independently and to clear the airway effectively (Shoesmith, Findlater, Rowe, & Strong,

2007).

1.5 Bulbar ALS

Although only 20-30% of patients develop bulbar deficits at the disease onset, more than 80% of

patients with spinal onset ALS will develop signs and symptoms of bulbar neurodegeneration as

the disease progresses (Sitver & Kraat, 1982; Talbot, 2009). Patients have indicated that the loss

of bulbar function is the most debilitating consequence of ALS (Hecht et al., 2002; Rosen, 1978).

The initially mild speaking and swallowing dysfunction progresses rapidly towards a state of

anarthria (i.e., complete loss of oral communication) and severe dysphagia (Brooks et al., 1990;

Clavelou, Blanquet, Peyrol, Ouchchane, & Gerbaud, 2013). The median time from onset to

anarthria and to gastrostomy is 18 months and 13 months, respectively, in patients with bulbar

onset ALS (Turner, Scaber, et al., 2010). Patients with ALS may require the use of alternative

communication devices to facilitate speech, exhibit rapid weight loss and be prone to aspirating

as well as developing aspiration pneumonia (Beukelman, Fager, & Nordness, 2011; Clavelou et

al., 2013; Kuhnlein et al., 2008; Mazzini et al., 1995; Turner, Scaber, et al., 2010). Bulbar signs

and symptoms are associated with a short life expectancy, which is approximately 24 months

after the development of bulbar signs (Gautier et al., 2010). Patients with bulbar symptoms

report feelings of helplessness, social isolation and psychological problems (Hecht et al., 2002).

The rapid progression and the consequences of bulbar neurodegeneration result in a reduced

quality of life (Bongioanni, 2012).

1.6 Clinical Assessment of Bulbar Function

The main goals of bulbar function assessment are to inform clinicians about the presence and

severity of bulbar deficit, to estimate the rate of the bulbar and overall disease progression and to

plan potential interventions needed to maintain function (e.g., alternative methods of

5

communication and nutrition supplements) (Andersen et al., 2012; Beukelman et al., 2011).

Clinically, the current standard assessment tools of bulbar function are the Amyotrophic Lateral

Sclerosis Functional Rating Scale-Revised (ALSFRS-R) and the Speech Intelligibility Test (SIT)

(Beukelman, Yorkston, Hakel, & Dorsey, 2007; Cedarbaum et al., 1999; Plowman, Tabor,

Wymer, & Pattee, 2017). Because dysarthria often emerges prior to dysphagia (Talbot, 2009),

the assessment of bulbar function often focuses on the changes in the speech production (Green

et al., 2013). The gold-standard swallowing assessment method – a videofluoroscopic assessment

of swallow (VFS) study – is not often used in the assessment of bulbar function in ALS because

it is perceived to not contribute to the medical management given the predictable rapid decline in

swallow ability (Plowman et al., 2017). As such, patients are instead often referred for a feeding

tube placement early in the course of their disease so that enteral nutritional support can be

graduated based on emerging patient reported dysphagia symptoms (e.g., choking) (Andersen et

al., 2012; Plowman et al., 2017).

The ALSFRS-R is a patient reported outcome measure that assesses patients’ symptoms and self-

perceived functioning ability during several activities of daily living, including speech and

swallowing (Cedarbaum et al., 1999). This scale includes questions related to gross and fine

limb, bulbar and respiratory functions. The ALSFRS-R total score ranges from 0 to 48, with a

score less than 48 indicating the presence of symptoms associated with the motor neuron

degeneration. The ALSFRS-R assesses bulbar dysfunction using three questions surveying

dysarthria, dysphagia and sialorrhea. The ALSFRS-R bulbar subscore ranges from 0 to 12 and an

ALSFRS-R bulbar subscore less than 12 indicates the presence of bulbar related symptoms

associated with at least 1 of these 3 impairment areas. The ALSFRS-R displays good internal

consistency, excellent inter- and intra-reliability as well as criterion-related validity (Cedarbaum

et al., 1999; Franchignoni, Mora, Giordano, Volanti, & Chiò, 2013; Gordon, Miller, & Moore,

2004; Kaufmann et al., 2007).

The SIT quantifies speech intelligibility and speaking rate based on an orthographic transcription

of 11 sentences read by the patient at their normal comfortable speaking rate and loudness and

transcribed by an unfamiliar listener (Beukelman et al., 2007). Speech intelligibility refers to the

percentage of words that are understood by the naive listener during this task, and speaking rate

refers to the number of words uttered per minute (Yorkston, Beukelman, & Tice, 1996). Speech

intelligibility is judged to be normal when it is between 97% and 100% (Green et al., 2013).

6

Using SIT, the normal speaking rate is considered at and above 190 words per minute (WPM)

(Beukelman et al., 2011; Yorkston, Hammen, Beukelman, & Traynor, 1990).

The ALSFRS-R and SIT possess great clinical utility. The ALSFRS-R is commonly used across

North America to monitor the disease progression and predict survival in patients with ALS both

in clinical trials and clinical practice (Kimura et al., 2006; Plowman et al., 2017; Ratti et al.,

2015). Clinical trials also use the ALSFRS-R to determine if symptoms related to bulbar,

respiratory and limb function improve or cease to worsen with the use of pharmaceutical

interventions (Smith et al., 2017). Speech intelligibility informs the ALS management team

about the severity of the dysarthria (Yorkston et al., 1993). Speaking rate declines prior to speech

intelligibility and has increased utility in tracking bulbar disease progression (Ball, Beukelman,

& Pattee, 2002; Rong, Yunusova, Wang, & Green, 2015). Moreover, speaking rate is the primary

measure used to inform the recommendation for prescription of the augmentative and alternative

communication systems to support daily communication (i.e., when speaking rate is 125 WPM

or less) (Beukelman et al., 2011).

Despite their advantages, the ALSFRS-R and the SIT measures fail to detect early functional

changes. As subjective assessment tools, these measures are limited in their usefulness in aiding

ALS diagnosis and tracking relatively small changes in performance with disease progression

(Allison et al., 2017). The ALSFRS-R does not effectively detect early functional changes since

symptoms of motor neuron degeneration emerge after the majority of motor neurons have

already been lost (Bouche, Le Forestier, Maisonobe, Fournier, & Willer, 1999). The SIT is a

perceptual test and is prone to many limitations of such assessments (see Kent, 1996). Both

speech intelligibility and speaking rate decline relatively late in the disease course and are

influenced by multiple components of speech production (e.g., articulator function,

velopharyngeal function, laryngeal function and respiratory function) (Rong, Yunusova, Wang,

et al., 2015). To improve the assessment of bulbar function in ALS, measures capable of

addressing these limitations are urgently needed (Green et al., 2013).

1.7 The Subsystem Approach towards Measuring Bulbar Dysfunction

in ALS

Recently, our group has been systematically testing physiological instrumental measures of

bulbar dysfunction conceptualized in the form of the four motor speech subsystems –

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articulatory, resonatory, phonatory and respiratory – based on the framework proposed by

Ronald Netsell (see Figure 1) (Netsell, Lotz, & Barlow, 1989). The articulatory subsystem

consists of the lips, jaw and tongue musculature. The resonatory subsystem is comprised of the

velum and posterior pharyngeal wall. The phonatory subsystem includes the larynx. The

respiratory subsystem consists of the respiratory (e.g., expiratory and inspiratory) musculature.

Figure 1: The four speech subsystems.

Reprinted from “Bulbar and speech motor assessment in ALS: Challenges and future directions,”

Green et al, 2013, Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, 14(7-8), p.

495. Copyright 2013 Informa Healthcare.

Across the four physiological subsystems, over one hundred measures assessing acoustic,

kinematic or aerodynamic features of speech have been identified as potential candidates in the

assessment of bulbar ALS (Yunusova, Green, Wang, Pattee, & Zinman, 2011). Subsequently, a

series of studies identified an association of a number of these physiological subsystem measures

with the clinical measures of bulbar dysfunction such as speaking rate and speech intelligibility

(Rong, Yunusova, Wang, et al., 2015; Rong, Yunusova, Wang, et al., 2016). These studies

revealed that among the articulatory subsystem measures, the upper and lower lip velocity during

sentence reading as well as the syllable rate and count achieved during an alternate motion rate

(AMR) task were the most promising bulbar disease indicators. Articulatory rate has also been

shown to correlate with bulbar function and statistically differ between patients with motor

8

impairments and healthy controls as well as patients with cognitive impairments (Nishio &

Niimi, 2006; Yunusova et al., 2016). Rong, Yunusova, Wang, et al (2015) found the most

promising of the resonatory subsystem measures included the median nasalance score achieved

during sentence reading and the peak nasal flow obtained during the production of syllables

containing a plosive consonant. The maximum fundamental frequency (F0 max) was identified

as sensitive to the phonatory subsystem impairment (Rong, Yunusova, Wang, et al., 2015; Rong,

Yunusova, Wang, et al., 2016). The respiratory speech subsystem is represented by the

percentage of time spent pausing (percent pause time), pause events and total pause duration

obtained from passage reading in addition to the maximum oral pressure obtained from serial

repetitions of syllables containing a plosive consonant (Rong, Yunusova, Wang, et al., 2015;

Rong, Yunusova, Wang, et al., 2016).

These studies revealed that these physiological subsystem measures are highly associated with a

decline in speaking rate and speech intelligibility, but also that they decline prior to both

speaking rate and speech intelligibility (see Figure 2), making the physiological subsystem

measures ideal for tracking bulbar dysfunction in ALS (Rong, Yunusova, Wang, et al., 2015;

Rong, Yunusova, Wang, et al., 2016). Furthermore, these physiological subsystem measures

displayed more accurate detection of bulbar changes compared to clinician perceptual ratings and

symptom report (Allison et al., 2017; Rong, Yunusova, Wang, et al., 2015; Rong, Yunusova,

Wang, et al., 2016). The use of these physiological subsystem measures in the assessment of

bulbar dysfunction is very promising, and research is ongoing to determine their diagnostic

sensitivity, specificity, responsiveness and clinical interpretability.

9

Figure 2: Likelihood of maintaining function over time of speech intelligibility, speaking rate

and the four physiological subsystems in patients diagnosed with ALS with an end-point of 120

words per minute speaking rate.

Reprinted from “Predicting early bulbar decline in amyotrophic lateral sclerosis: A speech

subsystem approach,” Rong et al, 2015, Behavioral Neurology, p. 7. Copyright 2015 Panying

Rong et al.

The long-term goal of the work by our research group is to improve bulbar motor assessment by

utilizing physiological subsystem measures. The problem, however, is that the physiological

subsystem measures may be highly dependent on the integrity of respiratory function, which is

the driving force behind speech and a critical component of swallowing (Hixon & Hoit, 2005;

Weismer, 2006). Motor speech disorders most often occur as a result of an impairment affecting

oropharyngeal musculature, but changes in speech may also occur due to the respiratory

10

dysfunction alone (Hixon, 1973; Hixon, Goldman, & Mead, 1973). For example, patients

diagnosed with cystic fibrosis demonstrate changes in voice quality – rough and breathy voice –

and reduced loudness when compared to age-matched controls (Lourenço, Costa, & da Silva

Filho, 2014). Patients with spinal cord injury show reduced loudness but also can present with

reduced utterance length (Brown, DiMarco, Hoit, & Garshick, 2006). Patients with chronic

obstructive pulmonary disease display short phrase durations (Binazzi, Lanini, Gigliotti, &

Scano, 2013). Likewise, shortness of breath and muscle fatigue may result in longer pauses to

increase the time available for gas exchange in patients with lung disease (Lee, Loudon,

Jacobson, & Stuebing, 1993).

In ALS, bulbar and respiratory dysfunction often co-occurs (Hardiman, Van Den Berg, &

Kiernan, 2011; Similowski et al., 2000; Yorkston, Strand, & Miller, 1996). Patients with bulbar

onset ALS are said to develop respiratory dysfunction soon after the onset of bulbar symptoms

and earlier in the disease progression than patients with spinal onset ALS (Brooks, 1996;

Clavelou et al., 2013; Pinto, Pinto, & de Carvalho, 2007; Pinto, Turkman, Pinto, Swash, & de

Carvalho, 2009; Poloni, Mento, Mascherpa, & Ceroni, 1983). Patients with bulbar onset ALS

exhibit a more significant and rapid decline in respiratory function during the initial 6 months

post-diagnosis when compared to patients with spinal onset ALS (Clavelou et al., 2013). As the

disease progresses, bulbar symptoms and respiratory dysfunction seem to decline at similar rates

in patients regardless of region of onset (Clavelou et al., 2013; Yorkston, Strand, et al., 1996).

Some researchers have hypothesized that the proximity of the brainstem motor neurons to the

respiratory brainstem centers as well as the neurodegeneration of shared neural pathways may be

responsible for these findings (Aydogdu, Tanriverdi, & Ertekin, 2011; Pinto et al., 2007; Richter

& Smith, 2014).

However, the bulbar and respiratory dysfunction might not be completely linked. Patients with

ALS can display either bulbar dysfunction with normal respiratory function or respiratory

dysfunction with normal bulbar function early in the disease and, occasionally, with disease

progression (De Carvalho et al., 1996; Lyall, Donaldson, Polkey, Leigh, & Moxham, 2001). A

number of studies have reported the absence of a connection between the region of onset and the

development of respiratory dysfunction in ALS (Chandrasoma et al., 2012; Easterling, Antinoja,

Cashin, & Barkhaus, 2013; Talakad, Pradhan, Nalini, Thennarasu, & Raju, 2009). For example,

both Chandrasoma et al. (2012) and Talakad et al. (2009) reported a lack of differences in

11

spirometric measures when comparing patients with ALS subgrouped by region of onset, bulbar

versus spinal. In another study, the longitudinal decline of respiratory function did not differ

between patients with ALS subgrouped by onset (Easterling et al., 2013). The development of

bulbar and respiratory dysfunction may simply relate to the natural course of the disease

progression (i.e., disease severity) rather than a potential interaction between the two

impairments, but this must be further investigated. Below, we review the physiological measures

by subsystem followed by measures of respiratory dysfunction.

1.8 Physiological Measures of Bulbar Function by Subsystem

Multiple physiological subsystem measures have been identified as important in assessing bulbar

function in ALS based on their ability to identify bulbar dysfunction earlier than the current

clinical standards and to predict bulbar motor and speech intelligibility decline (Allison et al.,

2017; Green et al., 2013; Rong, Yunusova, Wang, et al., 2015; Rong, Yunusova, Wang, et al.,

2016; Yunusova et al., 2016). The specific measures that may be influenced by respiratory

dysfunction were identified through literature review of normal and disordered speech

physiology and are presented, by subsystem, below.

1.8.1 Articulatory Subsystem

1.8.1.1 Syllable Count during an AMR task

The alternate motion rate (AMR) task is a maximum performance task executed on a single

breath. Patients are asked to repeat the syllables /pa/, /ta/ or /ka/, eliciting the rapid contraction of

the lips, anterior portion of the tongue and posterior portion of the tongue, respectively. The total

duration of the syllable train and syllable count and rate (syllables per second) are reported

during this task. The total syllable count assists with assessing dysarthria because the total

syllable count decreases as bulbar function declines (Darley, Aronson, & Brown, 1975, p. 93;

Kent et al., 1991; Mulligan et al., 1994; Nishio & Niimi, 2000; Yorkston et al., 1993). Males and

females typically produce a similar syllable count (number of cycles) ranging between

approximately 50 and 120 syllables when performing an AMR task involving the syllable /ta/

(Rong, Yunusova, Richburg, & Green, in press).

The syllable count has been identified as a sensitive measure of bulbar decline in ALS that is

capable of distinguishing patients with bulbar symptoms from patients without bulbar symptoms

12

(Allison et al., 2017; Rong, Yunusova, Wang, et al., 2016). A reduction in syllable count below

35 repetitions predicted a rapid decline in speech intelligibility and preceded speaking rate

decline (Rong et al., in press). However, respiratory decline, in addition to the reduction in rate

of articulatory muscle contractions, may affect the performance on this task, resulting in a

smaller number of syllables produced on one breath. The association between the syllable count

obtained during the AMR task and respiratory function has not been established in ALS.

1.8.1.2 Articulatory Rate during Passage Reading

Articulatory rate reflects the rate of syllable production during a passage reading task, when

pauses are excluded (Jacewicz, Fox, O'Neill, & Salmons, 2009). The contraction rate of the

articulatory musculature is primarily reflected in this measure (Mefferd, Pattee, & Green, 2014).

This measure aids in dysarthria assessment since articulatory rate is often altered in neurological

diseases that affect the integrity of oro-facial musculature (e.g., Parkinson’s disease,

Huntington’s disease and multiple sclerosis) (Kuo & Tjaden, 2016; Niimi & Nishio, 2001; Rusz

et al., 2014). Adult male and female speakers typically produce a similar articulatory rate ranging

between 220 and 350 syllables per minute when reading a passage (Jacewicz et al., 2009; Lee &

Doherty, 2017; Yunusova et al., 2016).

Articulatory rate is a promising measure in bulbar ALS assessment. In ALS, articulatory rate is

known to be sensitive to the early changes in bulbar function, and statistically significant

declines in articulatory rate occur as bulbar dysfunction progresses (Rong, Yunusova, & Green,

2015; Rong, Yunusova, Wang, et al., 2015; Yunusova et al., 2016). However, it is not well

understood whether and how articulatory rate may be influenced by respiratory dysfunction in

this disease. Normal speakers seem to adjust their articulatory rate depending on their pausing

behaviour preferences; individuals who tend to naturally pause more speak at slower articulatory

rates (Healey & Adams, 1981; Turner & Weismer, 1993). Similarly, patients with ALS displayed

similar articulatory rate adjustments in relation to pausing behaviour as exhibited by normal

speakers (Turner & Weismer, 1993). However, the association between articulatory rate and

respiratory deficit has not yet been investigated in ALS.

13

1.8.2 Respiratory Subsystem

1.8.2.1 Speech and Pause Measures in a Passage Reading Task

Pauses during a passage reading task serve to restore lung volume during connected speech

(Goldman-Eisler, 1972; Hixon & Hoit, 2005; Zellner, 1994). Passage reading requires speech

pauses to be produced according to the passage’s syntactical structure (Goldman-Eisler, 1972).

During passage reading, healthy adults, both males and females, generally spend between 10 and

20 percent of reading time pausing, with an approximate average phrase (i.e. breath group)

duration of 3.5 seconds and pause duration of 0.6 seconds (Solomon & Hixon, 1993; Wang,

Green, Nip, Kent, & Kent, 2010; Winkworth, Davis, Ellis, & Adams, 1994; Yunusova et al.,

2016). The speech and pause measures are often affected when dysarthria develops (Duffy,

2013; Green, Beukelman, & Ball, 2004; Lee et al., 1993; Yunusova et al., 2011). For example,

patients with dysarthria due to traumatic brain injury or Parkinson’s disease display increases in

the percentage of time spent pausing during speech (Campbell & Dollaghan, 1995; Hammen &

Yorkston, 1994).

Increased dependence on pausing frequency and duration has been reported in patients with ALS

as well (Nishio & Niimi, 2000; Turner & Weismer, 1993). Patients with ALS displayed

significant changes in pausing features of speech that were linked to reduced speech

intelligibility (Green et al., 2013; Rong, Yunusova, Wang, et al., 2015; Rong, Yunusova, Wang,

et al., 2016). Obtaining a percent pause time greater than 18% during passage reading greatly

increased the likelihood of participants having ALS (Allison et al., 2017). Additionally, the

measure of percent pause time displayed strong sensitivity and specificity when differentiating

between participants with ALS with bulbar symptoms and patients with ALS without bulbar

symptoms (Allison et al., 2017). In a study exploring the impact of motor and cognitive

dysfunction on pausing during continuous speech, the mean phrase duration and the percent

pause time were uniquely associated with primarily respiratory decline, whereas the total number

of pause events and the total pause duration were associated with the bulbar subscore of

ALSFRS-R (Yunusova et al., 2016). The initial findings from the Yunusova et al. (2016) study

were preliminary and need to be validated on a large sample of participants as well as target the

association between a variety of pause and speech measures and respiratory measures.

14

1.8.2.2 Maximum Oral Pressure

Oral pressure obtained during the production of voiceless plosive consonants is said to represent

subglottal pressure generated in the lungs for speech production (Hixon, Hawley, & Wilson,

1982). More specifically, when the lips and the velum are sealed and the vocal folds are

abducted, a closed space forms. In this moment, the oral pressure corresponds with the pressure

generated within the lungs (Baken & Orlikoff, 2000, p. 308; Ketelslagers, De Bodt, Wuyts, &

Van de Heyning, 2007), representing respiratory muscle function. Adult men and women

produce a similar maximum oral pressure ranging between 5 and 12 cm H2O when repeating

syllable /pi/ at a normal loudness (Andreassen, Smith, & Guyette, 1992; Baken & Orlikoff, 2000;

Zajac, 2000). A reduction in oral pressure can contribute to the development of dysarthric speech

as phoneme discrimination becomes impaired, which can reduce speech intelligibility (Barbosa,

Mangilli, Andrade, & Alonso, 2012; Ketelslagers et al., 2007; Solomon & Hixon, 1993).

Limited literature exists on oral pressure changes in ALS. Oral pressure has been found to

contribute to the decline of speech intelligibility and speaking rate in this clinical population

(Rong, Yunusova, Wang, et al., 2015; Rong, Yunusova, Wang, et al., 2016). As a measure

representing the respiratory motor speech subsystem (Yunusova et al., 2011), it is important to

assess the effect of a respiratory deficit on this measure in ALS.

1.8.3 Resonatory Subsystem

1.8.3.1 Peak Nasal Airflow and Nasalance

Peak nasal airflow is an aerodynamic measure used to assess the adequacy of the velopharyngeal

closure (Yunusova et al., 2011). Peak nasal airflow is obtained during the serial production of

syllables containing the plosive consonant /p/ followed by a vowel, either /a/ or /i/. Peak nasal

airflow is recorded when oral pressure is at its maximum for plosive consonants. Plosive

consonants are characterized by relatively high oral pressure and minimal nasal airflow (Ball et

al., 2001; Warren, Dalston, Morr, Hairfield, & Smith, 1989). A peak nasal flow below

approximately 10 mL/s when participants repeated the syllable /pi/ is considered normal for

males and females (Andreassen et al., 1992; Baken & Orlikoff, 2000; Zajac, 2000).

Nasalance, defined as a ratio between the oral to nasal acoustic energy, is obtained during the

reading of nasal (e.g., /Momma Made Lemon Jam/) and non-nasal (e.g., /Buy Bobby a Puppy/)

15

sentences using a device called the Nasometer (Bressmann et al., 2000). Normally, nasalance is

low when reading a non-nasal sentence compared to reading a nasal sentence (Hardin, Van

Demark, Morris, & Payne, 1992; Yunusova et al., 2011). Healthy males and females produce a

nasalance score below 25% when reading the sentence /Buy Bobby a Puppy/ (Gauster, 2009;

Gauster, Yunusova, & Zajac, 2010; Hutchinson, Robinson, & Nerbonne, 1978). Hypernasality, a

perceptual consequence of high nasalance, can result in a lack of clarity and vocal projection

during speech, thus affecting speech intelligibility (Calnan, 1959; Hoodin & Gilbert, 1989).

In ALS, an inadequate seal develops between the velum and posterior pharyngeal wall as

velopharyngeal muscles weaken (Delorey, Leeper, & Hudson, 1999), leading to notable

hypernasality and nasal emissions (Darley et al., 1975; Green et al., 2013; Kelhetter, 2013).

Aerodynamic measures of velopharyngeal function have been identified to aid in the early

assessment of speech loss in ALS (Allison et al., 2017; Green et al., 2013; Rong, Yunusova, &

Green, 2016; Rong, Yunusova, Wang, et al., 2016; Yunusova et al., 2011). Although indicators

of the velopharyngeal dysfunction, normal peak nasal airflow and median nasalance rely on

adequate airflow and pressure generation by the respiratory apparatus (Baken & Orlikoff, 2000,

p. 476) as the velopharyngeal and respiratory systems are tightly coupled (Sapienza, Brown,

Williams, Wharton, & Turner, 1996). Clinically, patients who exhibit velopharyngeal

dysfunction but normal respiratory performance often increase their respiratory effort during

speech by increasing frequency of breaths and decreasing utterance length (Kummer, 2018, p.

37). In ALS, a respiratory deficit may influence the measures of velopharyngeal function. The

potential influence of respiratory dysfunction on peak nasal airflow and nasalance has not been

investigated in ALS.

1.8.4 Phonatory Subsystem

1.8.4.1 Maximum Fundamental Frequency in a “High Pitch” Task

A high pitch phonation task requires participants to vocalize a vowel sound (e.g., /ah/), adjusting

one’s pitch from normal to the highest pitch possible for a short period of time. The F0 max is

recorded when pitch is at its highest (Baken & Orlikoff, 2000, p. 147). Healthy males and

females typically produce a F0 max between 390 and 600 Hz when performing a high pitch

phonation (Aithal, Bellur, John, Varghese, & Guddattu, 2012; Lin, Mautner, Ormond, &

Hornibrook, 2007). F0 max is often used in the assessment of dysarthric speech because

16

laryngeal spasticity and weakness often leads to a reduction in the F0 max (Goberman &

Blomgren, 2008; Kent et al., 2000; Kim, Kent, & Weismer, 2011).

The F0 max obtained during a high pitch phonation has been used to predict bulbar function

decline in ALS. A rapid decline in speech intelligibility occurred once the F0 max declined to

280 Hz or less in patients with ALS (Rong, Yunusova, Wang, et al., 2016). Although primarily

dependent on glottal tension, the vocal fold vibrations require adequate subglottal pressure and

thus adequate respiratory support (Lieberman, Knudson, & Mead, 1969; Marchal, 2009, p. 53;

Weismer, 2006, pp. 104-105). Increased respiratory effort can increase the F0 obtained (Lester &

Story, 2013; Sato, Watanabe, & Moriya, 2016). It is important to determine the extent to which

respiratory dysfunction may be associated with the F0 max obtained during a high pitch

phonation in patients with ALS.

1.8.5 Summary of the Identified Subsystem-Based Bulbar Measures

In summary, the following bulbar motor measures were identified by others as potentially

affected by respiratory dysfunction in patients with ALS: syllable count, articulatory rate, percent

pause time, total pause duration, pause events, maximum oral pressure, peak nasal flow, median

nasalance and F0 max. The expected ranges in healthy males and females for each of these

specific measures have been summarized in Table 1.

17

Table 1: Summary of means and standard deviations for physiological subsystem measures used

in this study obtained from healthy controls and available from published literature.

Subsystem Measure, Unit, Task Normative Data

Mean ± Standard Deviation

Articulatory Syllable Count, #, AMR 82.0 ± 48.6a

Articulatory Rate, syllables/min, Bamboo Passage 285.8 ± 29.9b

Respiratory

Percent Pause Time, %, Bamboo Passage 15.1 ± 3.2b

Total Pause Duration, s, Bamboo Passage 5.2 ± 1.5b

Pause Events, #, Bamboo Passage 8.4 ± 2.0b

Maximum Oral Pressure, cm H2O, /pi/ 6.6 ± 1.2c

Resonatory Peak Nasal Flow, mL/s, /pi/ 3.0 ± 3.4c

Median Nasalance, %, /Buy Bobby a Puppy/ 15.3 ± 6.8d

Phonatory F0 max, Hz, High Pitch Phonation 422.5 ± 82.0e

a: (Rong et al., in press)

b: (Yunusova et al., 2016)

c: (Andreassen et al., 1992)

d: (Gauster et al., 2010)

e: (Aithal et al., 2012)

1.9 Clinical Measures of Respiratory Dysfunction in ALS

Numerous methods are available for assessing respiratory dysfunction in ALS. Invasive

respiratory measures (e.g., needle EMG) are sensitive to early changes in respiratory muscle

function (Polkey et al., 2016); however, these measures are not ideal for serial measurements

(Lechtzin et al., 2002). Non-invasive measures (e.g., spirometry) are often utilized in clinical

settings since they are non-invasive, are implemented quickly and can monitor longitudinal

decline (Andersen et al., 2012; Polkey et al., 2016). Below, the clinical respiratory measures

incorporated into the present study are described and their justification for inclusion is provided.

1.9.1 Forced Vital Capacity

The percentage of the predicted forced vital capacity (%FVC), which varies by height, sex, age

and ethnicity (Miller et al., 2005; Ranu, Wilde, & Madden, 2011), indicates respiratory

dysfunction when it measures below 80% (Andersen et al., 2012; Wheaton et al., 2013).

Physiologically, this measure represents the adequacy of the inspiratory musculature (i.e., the

diaphragm, external intercostals and accessory muscles of respiration) as well as the expiratory

muscles (i.e., the abdominal muscles and the internal intercostal muscles) by determining the

proportion of volume of air forcefully expired following a maximal inhalation (Mitsumoto,

Przedborski, & Gordon, 2005, p. 738). It has been reported that an increasing residual volume, in

18

addition to a decreased total lung volume, could contribute to a reduction in %FVC in patients

with ALS (Chandrasoma et al., 2012; Fallat, Jewitt, Bass, Kamm, & Norris, 1979; Poloni et al.,

1983).

%FVC is frequently used to assess respiratory function in both clinical trials and clinical practice

due to its ability to track the progression of respiratory dysfunction over time and its value as a

surrogate marker of survival in patients with ALS (Andersen et al., 2012; Lyall et al., 2001;

Polkey et al., 2016; Rutkove, 2015; Schmidt et al., 2006). %FVC has been shown to predict

survival and disease progression, after adjusting for age, sex, site of onset, diagnostic delay,

riluzole use and respiratory support (Czaplinski, Yen, & Appel, 2006). As such, %FVC is the

current gold standard measure used to assess respiratory dysfunction in ALS (Andersen et al.,

2012). %FVC values are also critical in the clinical management of patients with ALS as they are

used to determine the need of ventilatory support and often direct the start of enteral nutrition

(Andersen et al., 2012; Berlowitz et al., 2015; Kleopa, Sherman, Neal, Romano, & Heiman-

Patterson, 1999).

1.9.2 Peak Expiratory Airflow

Peak expiratory airflow (PEF) is used primarily to assess the integrity of expiratory musculature

and the large airways (Sieck, Ferreira, Reid, & Mantilla, 2013; Yamada et al., 2016). In the

absence of an obstructed airway, PEF is said to represent the expiratory force generated

(Devadiga, Varghese, Bhat, Baliga, & Pahwa, 2015; Suárez et al., 2002). The clinical use of PEF

in ALS is limited, likely because PEF is more indicative of obstructive airway disease rather than

restrictive lung disease (e.g., ALS). However, patients with ALS have displayed significant

reductions in peak expiratory airflow in comparison to healthy adults (Suárez et al., 2002). PEF

has the potential to be important to evaluate speech of patients with ALS since speech typically

occurs during the expiratory phase of breathing (Hixon & Hoit, 2005; Weismer, 2006).

1.10 Research Objectives and Hypothesis

The overall goal of this study was to contribute to the understanding of the potential impact of

respiratory dysfunction on the clinical assessment of bulbar motor function using the

physiological subsystem-based measures. The specific objectives were to:

19

1. Compare selected physiological bulbar motor measures between patients with ALS

stratified by %FVC into groups with either normal or impaired respiratory function;

2. Examine the association between the physiological subsystem measures and %FVC;

3. Explore the association between the physiological subsystem measures and PEF; and

4. Explore the effect of respiratory function on the association between speaking rate and

the physiological subsystem measures.

We expected (1) group differences in physiological subsystem-based measures of bulbar

dysfunction between patients with normal respiratory function (ALSnr) and those with impaired

respiratory function (ALSir), (2) statistically significant correlations between these measures and

%FVC, (3) as well as statistically significant correlations between these measures and PEF.

Finally, (4) we expect that respiratory measures would contribute independently to the

association between the overall measure of bulbar dysfunction indexed by speaking rate and the

subsystem-based bulbar motor measures.

20

Methods

2.1 Study Design

Participants were recruited to participate in a multi-centre longitudinal study investigating the

progression of bulbar deterioration in patients with ALS. Data collected from two prospective

studies, with similar data collection protocols, were combined for the present retrospective study.

The first prospective study recruited participants from the Sunnybrook Health Sciences Centre

(Toronto, Ontario, Canada) and the University of Nebraska (Lincoln, Nebraska, USA) between

2009 and 2013. The second prospective study, ongoing, recruited participants from the

Sunnybrook Health Sciences Centre and the Massachusetts General Hospital Institute of Health

Professions (Boston, Massachusetts, USA) since 2014. For the present study, participants

recruited as part of the second prospective study were included up to June 2017. A total of 216

participants recruited between 2009 and June 2017 were potentially eligible for the present study.

The present study was a cross-sectional analysis using the last recorded session with a %FVC as

the time point of interest. Objective 1 was completed by subgrouping participants with ALS

according to their respiratory status; participants with a %FVC equal to or greater than 80%

formed the ALSnr (normal respiration) subgroup and participants with a %FVC less than 80%

entered the ALSir (impaired respiration) subgroup (Andersen et al., 2012). In contrast, for

objectives 2, 3 and 4, participants were analyzed as a single group.

2.2 Participants: Inclusion Criteria

The two prospective studies required participants with ALS to have: a definite or probable

diagnosis of ALS, as defined by the El Escorial Criteria (Brooks et al., 2000); be between 40-85

years of age; exhibit signs of bulbar motor neuron degeneration as determined by a neurologist;

and have no evidence of cognitive impairment, as determined by a score greater than 26 on the

Montreal Cognitive Assessment (Nasreddine et al., 2005). Further, all participants were native

English speakers that could read at a minimum of a grade 5 reading level and did not have any

major vision or hearing issues based on self-report. The sole exclusion criterion in the present

study was the lack of a documented %FVC during study participation.

21

2.3 Data Collection Protocol: Instrumentation and Tasks

All data were typically collected on the same day that participants visited the ALS/MND Clinic

for their regular appointments. When data could not be collected on the same day as a clinic

visit, participants completed the research protocol within 2 weeks of the respective clinic visit.

Often, patients with known bulbar onset ALS re-visited the clinic every 3 months, whereas

patients with spinal onset ALS returned to the clinic every 6 months. Patient demographics and

clinical characteristics were obtained during full medical histories and neurological exams. The

research protocol involved obtaining clinical respiratory measures, including %FVC and PEF, as

well as the physiological subsystem measures of bulbar dysfunction.

Instruments, tasks and instructions associated with obtaining clinical respiratory measures and

the physiological subsystem measures are presented in Table 2 and Table 3, respectively. The

clinical respiratory and physiological subsystem measures were obtained while participants were

in a seated position. Participants were instructed on how to perform the various tasks and were

allowed to practice a task until they were comfortable with the instructions. A forced vital

capacity maneuver was recorded by respiratory technicians with years of experience of operating

the device in a clinical setting; the speech measures were obtained by trained research assistants.

The staff identified any inconsistent measurements within subject attempts and incorrectly

performed procedures and determined if the recording should be repeated.

Table 2: Clinical respiratory measures and associated instruments and instructions.

Task Instrument Instruction

Measure

(Measurement

Unit)

Pulmonary

Function Test

Spirometer (Vmax Encore

22 PFT system,

CareFusion, Yorba Linda,

CA, USA)

Take a deep breath in and

exhale as fast and as hard as

you possibly can; best of 3

attempts recorded

%FVC, %

Phonatory Aerodynamic

System (PAS)

(Model 6600, PENTAX

Medical., Lincoln Park,

NJ, USA)

Take a deep breath in and

exhale fully and forcefully;

best of 2 attempts recorded

PEF, L/s

22

Table 3: Physiological subsystem measures and associated instruments and instructions.

Task Instrument Instruction Measure Subsystem

Alternate

Motion

Rate

Professional

microphone

(Countryman

B6P4FF05B, Menlo

Park, CA, USA); Adobe

Audition (Version 3.0,

Adobe Systems Inc.,

San Jose, CA, USA)

Repeat /ta/ as long

and as fast as you

can on one big

breath; 1 repetition

after practice

Syllable Count, #

Articulatory

Passage

Reading

Professional

microphone; Speech

Pause Analysis (SPA)

Software (Green et al.,

2004)

Read the Bamboo

Passage at your

normal speaking

rate and loudness;

1 repetition

Articulatory

Rate,

syllables/minute

Percent Pause

Time, %

Respiratory

Total Pause

Duration, s

Pause Events, #

Voicing

Efficiency

Protocol

Phonatory Aerodynamic

System (PAS)

Repeat syllable

/pi/; 7 repetitions; 5

middle repetitions

measured

Maximum Oral

Pressure, cm H2O

Peak Nasal Flow,

mL/s

Resonatory Sentence

Reading

Nasometer II (Model

6400, PENTAX

Medical, USA)

Repeat the

sentence /Buy

Bobby a Puppy/ at

your normal

speaking rate and

loudness; 3

repetitions

Median

Nasalance, %

High Pitch

Phonation

Professional

microphone; Multi-

Dimensional Voice

Profile software

(MDVP, Model 5105,

PENTAX Medical)

Start saying /a-a-a/

at a normal level

then increase your

pitch to its highest

level and hold for 5

seconds; 3

repetitions

F0 max, Hz Phonatory

2.4 Statistical Analysis

All statistical analyses were conducted using IBM SPSS Statistics version 24. The descriptive

statistics for the study measures are displayed as mean ± standard deviation or median (3rd

quartile – 1st quartile), depending on the type of their distributions. The differences between

demographic and clinical measures obtained for ALSnr and ALSir subgroups were determined

23

using independent samples t tests or Pearson’s chi-square tests (α was set at .05). In objective 1,

group comparisons between physiological subsystem measures obtained for the ALSnr and

ALSir subgroups were performed using independent samples t tests or Mann-Whitney U tests,

depending on the distribution of the dependent variables. For the independent samples t tests,

Levene’s test for equality of variances was used to determine whether equal variances for each

physiological subsystem measure could be assumed between the subgroups. For objectives 2 and

3, pairwise correlations were utilized to examine the association between each physiological

subsystem measure and %FVC and PEF. Spearman’s rank-order correlation was used when

assumptions for Pearson’s product-moment correlation were violated. For objective 4, any

physiological subsystem measure that achieved a statistically significant correlation with either

of the two clinical respiratory measures was subsequently correlated with speaking rate, while

controlling for the clinical respiratory measure. In all four objectives, the false discovery rate was

used to control for type I errors caused by multiple comparisons (Benjamini & Hochberg, 1995);

α was set at .05 prior to the adjustment.

24

Results

3.1 Participant Characteristics: ALS Group Combined and ALS

Subgroups

Figure 3 displays a CONSORT diagram of the study focusing on inclusion/exclusion and

missing data. Of the 216 potential participants with ALS from the two prospective studies, 158

were included in the present study based on the a priori exclusion criterion. Of these

participants, 135 were recorded in Toronto, Ontario, Canada, 19 were recorded in Lincoln,

Nebraska, USA and 4 were recorded in Boston, Massachusetts, USA. The participants displayed

a wide range of respiratory dysfunction as shown by the range of %FVC values and PEF values.

Missing data resulted from patient fatigue (i.e., the entire study protocol was not completed) and

equipment availability. The sample’s demographics and clinical characteristics, including those

necessary to determine respiratory status and used as independent variables in this study, are

summarized in Table 4.

25

Figure 3: A CONSORT diagram of study flow.

Potentially Eligible Participants n = 216

Study 1 n = 151

Study 2 n = 65

Missing Data

(Due to patient fatigue or equipment availability)

%FVC n = 0

PEF n = 78

Speaking Rate n = 12

Syllable Count n = 81

Articulatory Rate n = 43

Percent Pause Time n = 43

Total Pause Duration n = 43

Pause Events n = 43

Maximum Oral Pressure n = 47

Peak Nasal Flow n = 47

Median Nasalance n = 66

F0 max n = 47

Data Included in Analyses

%FVC n = 158

PEF n = 80

Speaking Rate n = 114

Syllable Count n = 77

Articulatory Rate n = 115

Percent Pause Time n = 115

Total Pause Duration n = 115

Pause Events n = 115

Maximum Oral Pressure n = 111

Peak Nasal Flow n = 111

Median Nasalance n = 92

F0 max n = 111

Participants Missing %FVC n = 58

Study 1 n = 23

Study 2 n = 35

Included Participants n = 158

Study 1 n = 128

Study 2 n = 30

26

Table 4: Participant demographic and clinical characteristics. Values are either counts

(percentage) or mean ± standard deviation (minimum - maximum).

Total N 158

Males, n (%) 99 (62.7%)

Age, years 59.7 ± 9.9 (40 – 88)

Bulbar Onset, n (%) 26 (16.5%)

Time Since Onset, months 40.7 ± 31.5 (2 – 231)

ALSFRS-R Total Score, /48 33.0 ± 7.0 (15 – 47)

ALSFRS-R Bulbar Subscore, /12 9.9 ± 2.1 (3 – 12)

ALSFRS-R Respiratory Subscore, /12 10.2 ± 2.2 (3 – 12)

%FVC, % 73.5 ± 23.6 (23 – 127)

PEF, L/s (n=80) 3.9 ± 2.1 (0.8 – 10.4)

Speaking Rate, words/minute 142.3 ± 44.5 (37.0 – 245.0)

The participant demographics and clinical characteristics by subgroup are displayed in Table 5.

The participants were stratified based on their clinical respiratory status into ALSnr and ALSir

subgroups. Based on independent samples t tests or Pearson’s chi-square tests, participant

demographics and clinical characteristics were similar for age, percentage of patients with

bulbar onset, time since onset, ALSFRS-R bulbar subscore and speaking rate; however the

percentage of males, the ALSFRS-R total score, the ALSFRS-R respiratory subscore, %FVC

and PEF significantly differed between the two subgroups.

Table 5: Participant demographic and clinical characteristics for ALSnr and ALSir subgroups.

Values are either counts (percentage) or mean ± standard deviation.

ALSnr ALSir p value

Total N 66 92

Males, n (%) 33 (50.0%) 66 (71.8%) .005*

Age, years 58.2 ± 10.1 60.72 ± 9.7 .113

Bulbar Onset, n (%) 15 (22.7%) 11 (12.0%) .072

Time Since Onset, months 41.1 ± 35.9 42.2 ± 28.4 .837

ALSFRS-R Total Score, /48 36.2 ± 6.2 30.7 ± 6.7 <.001*

ALSFRS-R Bulbar Subscore, /12 9.9 ± 2.3 9.9 ± 1.9 .999

ALSFRS-R Respiratory Subscore, /12 11.3 ± 1.0 9.4 ± 2.5 <.001*

%FVC, % 96.3 ± 12.2 57.2 ± 14.3 <.001*

PEF, L/s 4.6 ± 2.1 3.4 ± 2.1 .017*

Speaking Rate, words/minute 140.5 ± 48.5 143.6 ± 41.4 .676

* : Significant difference; α = .05

27

3.2 Physiological Subsystem Measures and ALS Subgroup

Comparisons

The summary descriptive statistics for the physiological subsystem measures for ALSnr and

ALSir subgroups are displayed in Table 6. For normally distributed data, means and standard

deviations are reported. For non-normally distributed data, medians and quartiles are reported.

The results of the ALSnr versus ALSir group comparisons are displayed in Table 7. After

adjusting for multiple comparisons, one significant difference was identified. The ALSir

subgroup showed a significantly greater percent pause time (24.4 ± 7.1) as compared to the

ALSnr subgroup (19.6 ± 6.5) [t(113) = -3.510, p < .001]. A bar chart of the significant group

difference is displayed in Figure 4. The data revealed that participants with ALS and respiratory

deficit display significant increases in the proportion of time spent pausing during a reading

task.

28

Table 6: Descriptive statistics of the physiological subsystem measures by subgroup.

ALSnr ALSir

Subsystem Measure N

Mean ±

Standard

Deviation

Median

(3rd

Quartile-

1st

Quartile)

N

Mean ±

Standard

Deviation

Median

(3rd

Quartile-

1st

Quartile)

Articulatory

Syllable

Count, # 37

42.0 (62.5-

22.0) 40

32.0 (46.3-

17.3)

Articulatory

Rate,

syllables/min

47 230.4 ±

60.2 68

253.2 ±

45.6

Respiratory

Percent Pause

Time, % 47 19.6 ± 6.5 68 24.4 ± 7.1

Total Pause

Duration, s 47

9.2 (12.4-

5.6) 68

9.9 (12.9-

7.6)

Pause Events,

# 47

13.0 (16.0-

9.0) 68

14.0 (16.8-

11.0)

Maximum

Oral Pressure,

cm H2O

46 7.3 (9.5-

6.1) 65

7.4 (8.7-

6.4)

Resonatory

Peak Nasal

Flow, mL/s 46

10.0 (30.0-

0.0) 65

20.0 (56.5-

10.0)

Median

Nasalance, % 35

12.0 (19.6-

7.3) 57

11.0 (18.1-

7.2)

Phonatory F0 max, Hz 51

207.5

(301.6-

147.4)

60

186.6

(258.1-

146.0)

Table 7: Test statistics for the group comparisons of the physiological subsystem measures

between the ALSnr and ALSir subgroups.

Subsystem Measure t U d.f. p value

Syllable Count 561.5 .069

Articulatory Rate -2.205 81 .030

Percent Pause Time -3.510 113 <.001**

Total Pause Duration 1348 .155

Pause Events 1256 .051

Maximum Oral Pressure 1459 .829

Peak Nasal Flow 1169.5 .048

Median Nasalance 948 .691

F0 max 1363 .323

** : Significant findings reported at p < FDR-adjusted α

29

Figure 4: Bar chart displaying the mean percent pause time, with 95% confidence internal error

bars, for the ALSnr and ALSir subgroups.

3.3 Associations between Physiological Subsystem Measures and

%FVC

The correlation results between the physiological subsystem measures and %FVC are displayed

in Table 8. After adjusting α according to the false discovery rate procedure, one significant

correlation was identified. A moderate negative correlation was identified between percent

pause time and %FVC [r(113) = -.411, p < .001]. A scatterplot of the statistically significant

correlation with %FVC is displayed in Figure 5. The data revealed that the decline in the

respiratory function was moderately associated with an increase in the percent pause time

obtained during passage reading.

t = -3.510

p < .001

30

Table 8: Correlations between physiological subsystem measures and %FVC.

Subsystem Measure r n p value

Syllable Count .220‡ 77 .055

Articulatory Rate -.216 115 .020

Percent Pause Time -.411 115 <.001**

Total Pause Duration -.181 115 .052

Pause Events -.213 115 .023

Maximum Oral Pressure -.016‡ 111 .871

Peak Nasal Flow -.164‡ 110 .086

Median Nasalance .067‡ 92 .523

F0 max .101‡ 111 .290

** : Significant findings reported at p < FDR-adjusted α

‡ : Spearman Rank-Order Correlation, rs

Figure 5: Correlation between percent pause time and %FVC.

3.4 Associations between Physiological Subsystem Measures and PEF

The correlation results between the physiological subsystem measures and PEF are displayed in

Table 9. One correlation between the physiological subsystem measures and PEF achieved

borderline significance, but none of the correlations was statistically significant after adjusting α

r = -.411

p < .001

31

according to the false discovery rate procedure. Notably, the same measure of percent pause

time had a tendency to be associated with this respiratory performance.

Table 9: Correlations between physiological subsystem measures and PEF.

Subsystem Measure r n p value

Syllable Count .211‡ 58 .111

Articulatory Rate .056 61 .670

Percent Pause Time -.319 61 .012

Total Pause Duration -.252 61 .050

Pause Events -.281 61 .028

Maximum Oral Pressure -.084‡ 71 .487

Peak Nasal Flow -.056‡ 71 .646

Median Nasalance .120‡ 60 .361

F0 max -.113‡ 59 .393

** : Significant findings reported at p < FDR-adjusted α

‡ : Spearman Rank-Order Correlation, rs

3.5 Partial Correlation between Percent Pause Time and Speaking

Rate, Controlling for %FVC

A negative correlation between percent pause time and speaking rate was statistically significant

[r(108) = -.246, p = .010]. A weak, negative partial correlation between percent pause time and

speaking rate, while controlling for %FVC, was statistically significant [r(107) = -.291, p =

.002] as well. The data suggested that controlling for %FVC slightly improved the correlation

between percent pause time and speaking rate.

32

Discussion

4.1 Summary

This study was conducted in order to better understand how respiratory deficit may affect

physiological subsystem measures of bulbar dysfunction in patients with ALS. The objectives of

the present study were to: (1) compare selected physiological subsystem measures between two

groups of patients with ALS stratified by into normal (ALSnr) versus impaired (ALSir)

respiratory function subgroups; (2) examine the associations between the physiological

subsystem measures and %FVC; (3) explore the associations between the same measures and

PEF; and (4) explore the effect of respiratory function on the association between speaking rate

and the bulbar subsystem measures. In our patient sample, group comparisons revealed that the

presence of respiratory dysfunction led to a significant increase in percent pause time during

passage reading, and a significant correlation revealed %FVC decline was associated with

increased percent pause time. Additionally, the correlation between percent pause time and

speaking rate did not change after controlling for %FVC. All other group comparisons and

correlations were non-significant after adjusting for multiple comparisons, suggesting limited

links between declining respiratory function and the selected physiological subsystem measures

of bulbar dysfunction in patients with ALS. These findings and their implications are discussed

in more detail below.

4.2 Use and Interpretation of Physiological Subsystem Measures in

the Assessment of Bulbar ALS

The currently used clinical measures for bulbar assessment such as speech intelligibility and

speaking rate have significant limitations (Green et al., 2013; Kent, 1996). Notably, they are

limited in their ability to detect early bulbar changes (Rong, Yunusova, Wang, et al., 2015),

which is vital for providing timely clinical management to patients with bulbar signs of ALS

(Andersen et al., 2012). Assessment of bulbar motor dysfunction in ALS has recently been

improved by research into the identification of novel physiological measures based on the

physiological subsystem approach (Allison et al., 2017; Green et al., 2016). The physiological

subsystem measures represent one of four physiological speech subsystems; articulatory,

phonatory, resonatory or respiratory (Netsell et al., 1989; Yunusova et al., 2011). The

physiological subsystem measures allow for earlier identification of bulbar motor dysfunction

33

and assist in evaluating the progression of the disease, improving upon the current clinical

bulbar assessment (Allison et al., 2017; Green et al., 2013; Rong, Yunusova, Wang, et al., 2015;

Rong, Yunusova, Wang, et al., 2016; Yunusova et al., 2011).

Although the physiological subsystem measures display promising use, additional research is

needed in order to better understand the potential factors influencing these measures (Green et

al., 2013). The present study investigated the degree to which the physiological subsystem

measures may be affected by a respiratory deficit. This study was needed for two primary

reasons: (1) the subsystem approach incorporates speech and speech-like tasks which are highly

dependent on adequate respiratory support (Hixon & Hoit, 2005) and (2) bulbar and respiratory

dysfunction are often reported simultaneously in patients with ALS (Hardiman et al., 2011;

Similowski et al., 2000; Yorkston, Strand, et al., 1996).

None of the articulatory, resonatory or phonatory subsystem measures differed between the

ALSnr and ALSir subgroups or correlated with either %FVC or PEF. The same was true for

pause events, total pause duration and maximum oral pressure, representing the respiratory

subsystem. We interpreted these results as indicating that respiratory deficit contributed

minimally, if at all, to syllable count, articulatory rate, peak nasal flow, median nasalance and

F0 max, pause events, total pause duration and maximum oral pressure, supporting the use of

these measures in the assessment of bulbar motor dysfunction in ALS.

The articulatory subsystem was represented by syllable count and articulatory rate. Syllable

count is measured as the total number of syllables produced on one maximal breath. Based on

the task characteristics, syllable count may have been influenced by a reduction in respiratory

support. Our findings did not reveal an association between syllable count and the clinical

respiratory measures. Likewise, articulatory rate – calculated by dividing the total number of

syllables by the total duration of speech in the passage with pausing removed – was not

associated with respiratory decline in ALS. It is possible that articulatory rate may have changed

in response to a decline in respiratory function in patients with ALS. In an earlier study by our

group, respiratory dysfunction was found to be associated with a decrease in the mean phrase

duration but not associated with increases in pause events and pause duration during passage

reading (Yunusova et al., 2016). These features combined (i.e., shorter breath groups, but

relatively unchanged pause events and duration) may translate to a faster articulatory rate as

patients attempt to compensate for declining respiratory function. However, the non-significant

34

findings between the ALSnr and ALSir subgroups in addition to the non-significant correlations

between the articulatory subsystem measures and both clinical respiratory measures likely

reflect that respiratory dysfunction exerts minimal influence on both syllable count and

articulatory rate.

The resonatory subsystem measures included the peak nasal flow and median nasalance. Peak

nasal flow is measured during repetitions of syllable /pi/ at the time point when oral pressure is

at its maximum. Normally, nasal flow is less than 10 mL/s (Andreassen et al., 1992; Baken &

Orlikoff, 2000; Zajac, 2000) and median nasalance is typically below 25% when reading the

sentence /Buy Bobby a Puppy/ (Gauster, 2009; Gauster et al., 2010; Hutchinson et al., 1978).

Both nasal flow and nasalance should increase in the presence of velopharyngeal incompetence

(Ball et al., 2001; Hardin et al., 1992; Warren et al., 1989). The two resonatory subsystem

measures were examined because they potentially depend on the generation of pressure by the

respiratory musculature (Hixon & Hoit, 2005). Since peak nasal flow is collected when oral

pressure is at a maximum (Baken & Orlikoff, 2000, p. 308), it is possible that peak nasal flow

will change when respiratory dysfunction is present. However, in our study, maximum oral

pressure neither differed between ALSnr and ALSir subgroups nor correlated with either clinical

respiratory measure. The acoustic measure of nasalance can also be potentially affected by

respiratory changes, but median nasalance was not associated with respiratory changes in our

data. Our findings reveal that there was no difference in median nasalance scores based on

respiratory status alone or associations between median nasalance and either clinical respiratory

measure. Thus, both peak nasal flow and median nasalance most likely reflect changes in

velopharyngeal function, rather than any changes in respiratory muscle function in ALS.

The phonatory subsystem measure included was F0 max. F0 max is determined based on the

frequency of the vocal fold vibrations, which require an adequate subglottal pressure to be

generated and as such a functional respiratory mechanism (Lieberman et al., 1969; Marchal,

2009, p. 53; Weismer, 2006, pp. 104-105). The data revealed the ALSnr and ALSir subgroups

did not statistically differ in regard to F0 max. Additionally, F0 max did not correlate with the

clinical respiratory measures in our patient sample. The findings seem to indicate that changes

in F0 max relate primarily to laryngeal spasticity and atrophy rather than respiratory

dysfunction.

35

This study supports that the respiratory subsystem measures of pause events, total pause

duration and maximum oral pressure link to the bulbar motor rather than respiratory decline in

ALS. The disassociation between pause measures and respiratory deficit supported previous

claims of their links to bulbar dysfunction (Yunusova et al., 2016). Specifically, Yunusova et al.

(2016) reported significant associations between pause events and total pause duration and the

ALSFRS-R bulbar subscore. The finding that maximum oral pressure was unrelated to the

respiratory dysfunction, on the other hand, was surprising because maximum oral pressure

obtained during the production of a plosive consonant relies on the adequate respiratory support

(Hixon et al., 1982). It is possible, however, that patients with ALS are able to compensate for

respiratory deficit during the production of plosive consonants and display oral pressure

reduction only when bulbar motor impairment becomes pronounced. The group comparisons did

not reveal any significant difference in maximum oral pressure between the ALSnr and ALSir

subgroups, suggesting patients with ALS can produce adequate oral pressure even as their

respiratory status declines. Oral pressure can be affected by bulbar dysfunction (e.g., labial

weakness and velopharyngeal dysfunction) in patients with ALS (Campbell & Enderby, 1984);

further investigation is required to understand the sensitivity of oral pressure to detect bulbar

motor deficit in patients with ALS, linking oral pressure measurements to measures of labial

weakness and velopharyngeal insufficiency.

4.3 Percent Pause Time During a Reading Task and Respiratory

Dysfunction

The present study revealed that one physiological subsystem measure in a set of 9 measures was

linked to the respiratory deficit in ALS. A significant difference in percent pause time was

reported between subgroups defined by clinical respiratory status (i.e., normal => 80% FVC or

impaired < 80% FVC) and a statistically significant correlation was identified between percent

pause time and %FVC. Percent pause time refers to the amount of time spent pausing relative to

the total duration of the passage reading. The group difference and correlation involving percent

pause time likely reflects the impact of reduced breath support in ALS. With a depleting source

of breath support, displayed by the reduction in %FVC, patients with ALS appeared to pause for

longer time periods relative to the total duration of speech in order to restore the required breath

support for continuous speech.

36

Percent pause time has been determined to be highly associated with bulbar measures of

speaking rate and speech intelligibility in previous research (Rong, Yunusova, Wang, et al.,

2015; Rong, Yunusova, Wang, et al., 2016). Percent pause time significantly increased in

patients with ALS and was shown to differentiate between patients with ALS with or without

bulbar symptoms (Allison et al., 2017). Percent pause time also responded to pharmacological

treatment with dextromethorphan/quinidine (i.e., Nuedextra) (Green et al., 2016). This current

study suggested that percent pause time was influenced by both respiratory and bulbar deficits,

but the influences were relatively independent from each other. Controlling for %FVC slightly

improved the correlation between percent pause time and speaking rate.

4.4 PEF as a Measure of Respiratory Decline in ALS

PEF, which represents the maximal airflow attained during spirometry (Sieck et al., 2013;

Yamada et al., 2016), was previously examined in conjunction with peak cough airflow to

identify expiratory muscle weakness and bulbar muscle weakness in patients with ALS (Suárez

et al., 2002). Suárez et al. (2002) indicated PEF represents expiratory muscle force and reported

significant reductions in PEF values obtained by patients with ALS in comparison to matched

controls. Since speech primarily occurs during the expiratory phase of breathing (Hixon & Hoit,

2005), PEF provided a unique contribution to the present study. In the present study, the

correlation between percent pause time and PEF approached but did not reach statistical

significance. The correlation with PEF was likely insignificant due to the limited number of

observations as compared to %FVC. PEF data was collected only on a sub-sample of the

participants due to limited equipment availability. Another possible reason for a lack of

significance could be related to the difference in measurement properties between %FVC and

PEF. %FVC is a volumetric measure whereas PEF is an airflow measure. Changes in a

volumetric measure may be more relevant to changes in speech breathing because reduced

breath support affects speech (Lee et al., 1993; Nishio & Niimi, 2000; Turner & Weismer,

1993), compared to only a minimal expiratory force being required to generate speech

(Lieberman et al., 1969; Marchal, 2009, p. 53; Weismer, 2006, pp. 104-105). Further

investigation into PEF is warranted based on the results of this study.

37

4.5 Contribution to the Literature

Previous studies have examined the relationship between respiratory and bulbar function in ALS

by subgrouping patients by region of disease onset (i.e., bulbar versus spinal) (Brooks, 1996;

Pinto et al., 2007; Pinto et al., 2009). Patients with bulbar onset ALS were reported to develop

respiratory dysfunction prior to patients with spinal onset ALS (see Pinto et al., 2007). However,

region of onset may not be sufficient for full understanding of bulbar disease progression in

ALS. In this study, we did not subgroup patients by the onset-site because previous literature

indicated that after the onset of bulbar symptoms in the spinal-onset cohort, the disease

progression is similar to patients with bulbar onset ALS (Turner, Brockington, et al., 2010). We

chose to examine participants based on their respiratory status in order to reveal a contribution

of respiratory dysfunction in the assessment of bulbar motor function.

Previous literature on bulbar motor dysfunction tends to focus on either symptom reports (e.g.,

ALSFRS-R) or global measures of bulbar dysfunction (e.g., speech intelligibility or speaking

rate). Understanding of the potential association between bulbar and respiratory dysfunction

using physiological subsystem measures is the next step in improving the clinical bulbar

assessment (Green et al., 2013). This is possible since physiological subsystem measures can

detect early functional bulbar changes (Rong, Yunusova, Wang, et al., 2015; Rong, Yunusova,

Wang, et al., 2016), with greater sensitivity and specificity than current clinical measures

(Allison et al., 2017). They also are capable of tracking the bulbar disease progression over time

(Green et al., 2013; Rong, Yunusova, & Green, 2015; Shellikeri, 2014; Yunusova et al., 2010;

Yunusova, Green, Lindstrom, Pattee, & Zinman, 2013). Since the physiological subsystem

measures represent four distinct motor speech subsystems innervated by specific bulbar motor

neurons (Netsell et al., 1989), the relative decline of the physiological subsystem measures

relative to the clinical respiratory measures may help reveal the origin of the neurodegeneration

and support patient subgroupings beyond the site of onset.

4.6 Nature of Measures: Maximum versus Submaximal Performance

The method of measurement collection is important to consider when discussing the findings of

this study. Both %FVC and PEF are maximal performance measures, whereas the majority of

physiological subsystem measures were collected using submaximal speech-based tasks. This

difference may have contributed to the weak and moderate correlations that were reported

38

(Rosenthal, 1996). Maximal performance measures often require peak effort; the maximal

performance measures are subsequently influenced by a participant’s willingness to exert

maximal effort (Lemstra, Olszynski, & Enright, 2004). The pulmonary function tests are often

more physically taxing when compared to the speech-based tasks (Godin & Hansen, 2015;

Lively, Pisoni, Van Summers, & Bernacki, 1993). Conversely, submaximal performance

measures assess habitual performance. Although submaximal measures do not account for

maximal effort, they may reveal various compensatory behaviours. For example, increased

lower lip and jaw movement speed seems to occur during the early stages of bulbar ALS

progression, possibly in response to the early velopharyngeal dysfunction (Rong, Yunusova,

Wang, et al., 2015). Utilizing submaximal measures may be more beneficial in ALS clinical

settings since subclinical changes in function can occur prior to clinically detectable changes

(Allison et al., 2017; Rong, Yunusova, Wang, et al., 2015).

4.7 Limitations of the Present Study

A number of limitations must be considered when interpreting the results. First, participants in

the present study were largely exhibiting a mild form of ALS, which is typical for these studies

(Chio et al., 2011). Patients with ALS are very difficult to recruit in the moderate or advanced

stages of the disease (Mehta, Antao, & Horton, 2015); ALS studies often have a high dropout

rate because patient fatigue and rapid disease progression result in missing data and censoring

(Aggarwal & Cudkowicz, 2008). In the present study, a total of 58 potential participants were

excluded because they did not obtain a %FVC during their participation in the study. Patient

fatigue during a typical data collection session lasting for approximately 1 to 1.5 hours also

resulted in missing data. Thus, it is important to note that the results of the study are likely more

generalizable to patients with ALS displaying a relatively mild disease severity. Patients with a

severe ALS status would likely display more extreme changes to the physiological subsystem

measures, which would potentially result in stronger correlations between bulbar motor and

respiratory measures.

Furthermore, the included clinical respiratory measures (i.e., %FVC and PEF) possess

limitations. First, %FVC and PEF were collected using different instruments. Although both

were obtained during a pulmonary function test, the use of two different instruments may have

impacted the results based on patient effort, equipment availability, different calibration

protocols and different environmental settings (i.e., clinic versus research). Second, performance

39

during the pulmonary function tests may have been impeded by muscle weakness and fatigue

(Lechtzin et al., 2002; Pinto et al., 2007). Also, although the most widely used clinical

respiratory measure (Plowman et al., 2017), %FVC is less sensitive to detecting respiratory

dysfunction compared to other spirometric measures (e.g., maximum inspiratory and expiratory

pressure and sniff nasal inspiratory pressure) (Polkey et al., 2016). Lastly, the inquiry regarding

comparing maximum to submaximal performance measures may be explored by utilizing a

plethysmograph (Sackner, Nixon, Davis, Atkins, & Sackner, 1980) or an accelerometer (Bates,

Ling, Geng, Turk, & Arvind, 2011).

Furthermore, the selection of measures evaluated in this study was based on our prior research

and knowledge and not all of the potential bulbar motor measures have been evaluated. The

development of novel measures is ongoing (Rong, Yunusova, Richburg, & Green, in press), and

the effect of the respiratory deficit on these measures would have to be evaluated as part of

measure validation. Additionally, more advanced statistical methods accounting for variance

due to sex, age and the site of data collection would have produced different results. More

sophisticated statistical modeling on a larger sample of data is planned for the future.

4.8 Conclusions

This study investigated group differences in physiological subsystem measures between

participants with ALS displaying either normal or impaired respiratory function and the

association between physiological subsystem measures and two clinical respiratory measures in

ALS. Findings generally support a notion that respiratory function decline does not affect the

selected physiological subsystem measures. The percent pause time measure was significantly

correlated with %FVC, yet the contribution of the respiratory impairment to this measure was

relatively independent of the association between percent pause time and speaking rate. As such,

all examined measures can be useful indicators of bulbar motor dysfunction in the assessment of

ALS. This study contributes to the literature examining the use of the subsystem approach to

monitor and track the decline of bulbar motor function in patients with ALS. Findings suggest

utilizing the selected articulatory, phonatory, resonatory and respiratory measures of speech in

the assessment of bulbar disease.

40

4.9 Future Directions

Future studies should continue developing the use of physiological subsystem measures in the

assessment of bulbar motor function in patients with ALS. These studies should examine the

longitudinal declines of the physiological subsystems and clinical respiratory measures.

Examining the relative longitudinal declines may reveal possible links and pathways between

the neurodegeneration of the bulbar and respiratory networks in ALS. The ongoing work in our

lab focuses on delineating diagnostic properties of the instrumental measures (e.g., sensitivity,

specificity, responsiveness, minimal detectable differences, etc.) in patients with ALS. With the

physiological subsystem measures being shown to effectively detect early bulbar changes and

track the disease progression, focus is currently placed on clinical implementation of these

measures, including technology development aspects such as the creation of automatic analysis

methods (e.g., Speech Pause Analysis algorithm) (Green et al., 2004). This work is expected to

improve clinical care and design of clinical trials for effective ALS management.

41

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