Levodopa ONOFF-state freezing of gait: Defining the gait and non-motor phenotype.

BACKGROUND: Freezing in the levodopa-medicated-state (ON-state) is a debilitating feature of Parkinson's disease without treatment options. Studies detailing the distinguishing features between people with freezing of gait that improves with levodopa and those whose freezing continues even on levodopa are lacking.
OBJECTIVE: To characterize the gross motor, gait, and non-motor features of this phenotype.
METHODS: Instrumented continuous gait was collected in the levodopa-medicated-state in 105 patients: 43 non-freezers (no-FOG), 36 with freezing only OFF-levodopa (OFF-FOG) and 26 with freezing both ON- and OFF-levodopa (ONOFF-FOG). Evaluation of motor and non-motor disease features was undertaken using validated scales. A linear mixed model with age, sex, disease duration, and motor UPDRS scores as covariates was used to determine differences in spatiotemporal gait and non-motor disease features among the groups.
RESULTS: Compared to OFF-FOG, the ONOFF-FOG group had greater disease severity (on the Unified Parkinson's disease Rating Scale) and worse cognition (on the Montreal Cognitive Assessment, Frontal Assessment Battery and Scales for Outcome in Parkinson's disease-Cognition scales) and quality of life (on the PDQ-39), but similar mood (on the Hamilton depression and anxiety scales) and sleep quality (on Epworth sleepiness scale and RBD questionnaire). For several gait features, differences between the ONOFF-OFF groups were at least as large and in the opposite direction as differences between OFF-no groups, controlling for disease severity. Variability in ONOFF-FOG was greater than in other groups. Using results from our study and others, a power analysis for a potential future study reveals sample sizes of at least 80 ONOFF and 80 OFF-FOG patients would be needed to detect clinically meaningful differences.
CONCLUSIONS: Intra-patient variability in spatiotemporal gait features was much greater in ONOFF-FOG than in the other two groups. Our results suggest that multifactorial deficits may lead to ONOFF-FOG development.

Introduction

Freezing of gait (FOG), due to its impact on quality of life and fall risk, is one of the more debilitating motor features of Parkinson’s disease (PD). The incidence of FOG ranges from 7% in early disease [1], and up to 92% near death [2]. Initially FOG is usually levodopa responsive (OFF-FOG), which may mask its presence until motor fluctuations develop and increased time in the motor OFF state leads to more bothersome freezing. There is also a population of PD patients that develop more resistant, levodopa unresponsive freezing, which has been termed levodopa-unresponsive freezing or ONOFF-FOG [2, 3] to suggest that freezing occurs in these patients in both the ON and OFF levodopa states, irrespective of levodopa dosing. In a previously published autopsy cohort [2], the group that developed ONOFF-FOG did so approximately 10 years after they developed OFF-FOG [2, 4]. Patients with ONOFF-FOG subjectively report little to no benefit in freezing episodes with their levodopa doses, and often have had worsening FOG with trials of increased levodopa dosing [5]. People with ONOFF-FOG also can simultaneously experience dyskinesias, while having freezing episodes, suggesting an otherwise optimally medicated ON-state [6]. A third group of patients who do not experience FOG in the OFF state, but only the ON-state has also been suggested [7] but this phenomenon is not common [3, 6].

It is unclear why only some PD patients develop ONOFF-FOG, and given the lack of dopaminergic response, whether ONOFF-FOG is just a continuum to a more severe freezing state, or a different phenomenon all together. We could find no studies that have reported on the comparison between gait or non-motor phenotypes of OFF- and ONOFF-FOG subtypes to help elucidate differences between the two. However, a few groups have explored select features of ONOFF-FOG compared to either no-FOG, OFF-FOG or a combination thereof and therefore results cannot be combined and are summarized individually.

Lucas McKay et al. [6] performed a levodopa challenge in PD participants, with 45/55 showing a >20% levodopa improvement on the movement disorders society Unified Parkinson’s Disease Rating scale (MDS-UPDRS) motor scores. Of these 76% had dyskinesias and 19 were classified as ONOFF-FOG, 11 OFF-FOG and 15 non-freezers (no-FOG) based on the UPDRS FOG item scores in the OFF and ON state. ONOFF-FOG patients had a range of UPDRS scores that spanned the other groups, and had a more severe phenotype than OFF-FOG patients based on the new freezing of gait questionnaire (N-FOGQ) and MDS-UPDRS activities of daily living (ADL) scores. There was no variation in levodopa response between groups in this study. In an earlier study from the same group, Factor et al. [8] showed that ONOFF-FOG patients had older age and worse UPDRS motor scores than no-FOG and worse visuospatial and executive function than both no-FOG and OFF-FOG. Ferraye et al. [9] used retrospective data available on PD patients who had undergone DBS placement and classified freezers and ONOFF-FOG (levodopa resistant or L-FOG in their manuscript) based on persistent scores on UPDRS ADL FOG Item scores in the ON-levodopa state. They found that ONOFF-FOG patients had worse executive function compared to other PD patients that were a combined group of OFF-FOG and no-FOG. Moretti et al. [10] also classified freezers based on the UPDRS ADL FOG Item score and found that compared to OFF-FOG, ONOFF-FOG patients did worse on a digit span forward task, made more mistakes on the Trail making test and Proverb’s interpretation task, and had a longer execution time and made greater mistakes on the STROOP test and the ten point clock test. Using the Cornell evaluation for depression they suggested that OFF-FOG patients were more depressed than ONOFF-FOG, but they found no differences in the anxiety sub-score of this scale between the groups. In the DEEP-FOG study by Amboni et al. [3], FOG patients (based on item 3 of the FOG-Q) were classified subjectively as ON-FOG, OFF-FOG or ONOFF-FOG based on questions asking them whether they froze in the best (ON), worst (OFF) or both (ONOFF). Of 593 patients, 6 were classified as ON-FOG, 200 OFF-FOG and 119 ONOFF-FOG. Compared to OFF-FOG, ONOFF-FOG patients had higher motor-UPDRS scores, were older at motor onset, were on lower levodopa doses, had lower MMSE scores, and reported similar quality of life on the Parkinson’s disease questionnaire-8 (PDQ-8).

The goal of our study was therefore to identify an objectively quantifiable feature set from gait, gross-motor and non-motor assessments that distinguish between people with PD that have OFF-FOG, ONOFF-FOG or no-FOG phenotypes. A better understanding of these different phenotypes is essential in order for targeted therapeutic options to be developed.

Materials and methods

Protocol approvals, registrations, and patient consents

Patients were recruited from the Movement Disorders Clinic at the University of Arkansas for Medical Sciences (UAMS) from September 2014 to August 2019. The study was approved by the local Institutional Review Board (UAMS IRB# 203234), written informed consent was obtained from all patients, and the study was conducted in accordance with the guidelines of the Declaration of Helsinki.

Study population

Patients with PD based on UK brain bank criteria were enrolled. People with a very high fall frequency of greater than 1 fall per day (due to safety concerns related to objective gait assessments), severe cognitive dysfunction with a Montreal Cognitive Assessment (MoCA) [11] score <10, or those with anti-dopaminergic medication use in the prior year were not enrolled. All patients were evaluated in the levodopa medicated or ON-levodopa state. For the study, patients were allowed to take their regular medication doses, including levodopa doses, as per their normal dosing schedule. The dose and time from last levodopa dose were documented during the study visit and reported in Table 2.

Table 2

Demographics and motor metrics of patients.

		no-FOG (n = 43)	OFF-FOG (n = 36)	ONOFF-FOG (n = 26)
General features:
Female		42%	50%	38%
Right-handed		91%	92%	96%
Right side more affected		56%	56%	50%
PIGD phenotype at visit		40%	78%	100%
Initial symptom:	rest tremor	53%	31%	38%
	gait	14%	22%	35%
Age at motor onset (years)		60.9 ± 9.6	55.6 ± 10.9	60.2 ± 9.7
Disease duration (years)		6.2 ± 4.9	9.4 ± 6.4	10.4 ± 5.1
Age at enrollment (years)		67.1 ± 8.2	64.9 ± 8.6	70.5 ± 8.1
Hoehn & Yahr score		1.8 ± 0.5	2.2 ± 0.5	3.2 ± 0.9
Fall frequency (per month)		0.1 ± 0.2	1.1 ± 5.0	8.1 ± 18.4
FOG duration (years)		-	2.2 ± 2.4	3.4 ± 2.1
Medications:
Daily levodopa dose (mg/day)		533 ± 308	717 ± 411	989 ± 406
levodopa per dose (mg/dose)		150 ± 64	193 ± 121	235 ± 99
Time from levodopa dose (hrs)		2.7 ± 2.3	2.0 ± 1.1	1.2 ± 0.6
Duration on levodopa (years)		2.8 ± 2.9	5.6 ± 5.8	7.7 ± 4.8
On dopamine agonist at visit		19%	22%	15%
On MAO-I at visit		40%	25%	15%
LEDD (l-dopa+agonist+MAO-I)		588 ± 324	786 ± 413	1032 ± 402

Values for continuous variables are mean ± standard deviation, and for categorical variables are percent of the relevant group sample size (n). PIGD: Postural Instability Gait Disorder variant; FOG-Q: Freezing of Gait Questionaire; FOG: Freezing of Gait; MAO-I: monoamine oxidase inhibitor; l-dopa: levodopa; LEDD: levodopa equivalent daily dose.

Patients with a score of 0 on Item 3 of the Freezing of Gait Questionnaire (FOG-Q) [12] were classified as non-freezers (no-FOG). Patients with a score of 1 or more on Item 3 of the FOG-Q, and/or had evidence of FOG on examination by a movement disorders trained neurologist (T.V.) were categorized as freezers (FOG). FOG patients were characterized as OFF-freezers if they 1) reported subjective resolution of freezing with levodopa despite improvement in other motor symptoms such as tremor, rigidity or bradykinesia, and 2) were not witnessed to freeze during their study evaluations that were performed in the levodopa medicated or ON-levodopa state (by T.V). FOG patients were categorized as ONOFF-FOG if they had freezing of gait visualized on examination during study assessments, which were performed in the ON-levodopa state, including the UPDRS and gait assessments (by T.V.), and met at least one of the following 3 criteria: 1) they reported no improvement or worsened freezing after their current daily levodopa doses (for example gait freezing was better in the morning prior to their first levodopa dose in the morning, and worsened after they took the morning dose), 2) they reported lack of improvement in freezing, or worsened freezing with clinical levodopa dose increase trials documented in the UAMS Movement disorders clinic medical record, or 3) they reported freezing while also dyskinetic suggesting a dopamine saturated state. All FOG patients were clinically treated in the UAMS Movement disorders clinic (by T.V.) and therefore had multiple assessments prior to study enrollment and results from prior levodopa adjustments contributed to the accuracy of the categorization. No patients reported freezing in the ON-levodopa only and not the OFF-levodopa state, previously defined as ON-FOG [7]. Of the 105 PD subjects enrolled, 43 were categorized as no-FOG, 36 as OFF-FOG, and 26 as ONOFF-FOG. The differences between measured gross motor, gait and non-motor features between the noFOG to OFF-FOG were used to compare and contrast the differences between the OFF-FOG and ONOFF-FOG groups.

Gait kinematics

Patients walked at a “comfortable” pace, 8 lengths of a 20 foot × 4 foot instrumented gait mat, in the levodopa medicated or ON-levodopa state, and data were collected and analyzed using Protokinetics Movement Analysis Software (PKMAS, Protokinetics, Havertown, PA). Freezing episodes were excluded from analysis during manual foot-print review (by AG and LP). The mean and coefficient of variability (CV) for steady state gait was calculated for 10 spatiotemporal features of gait; stride-length, stride-width, stride-time, stride-velocity, stance-phase-percent, total-double-support-percent, integrated-pressure applied during a step, foot-strike-length, cadence, and ambulation time. The definitions of these gait features are provided in Table 1. The more affected side was determined based on the ratio of the summated right/left scores for UPDRS items 20–26. Gait asymmetry was calculated as the ratio of the more/less affected side for each gait feature.

Table 1

Spatiotemporal gait feature definitions.

Measure	Definition
Stride-length (cm)	the distance between heel strikes of two consecutive footsteps of the same foot, i.e., two right or two left heel strikes along the direction of travel (x-axis)
Stride-width (cm)	the distance between heel strikes of two consecutive footsteps of the same foot, i.e., two right or two left heel strikes, perpendicular to the direction of travel (y-axis)
Stride-time (s) also known as gait cycle time	the time difference (s) between the initial heel contacts with the mat of two consecutive footsteps of the same foot, i.e., two right or two left.
Stride-velocity (cm/s)	the stride length divided by stride time, calculated for each gait cycle.
Stance-phase-percent	percentage measure of time spent in stance phase of the gait cycle and calculated as stance time/gait cycle time.
Total-Double-Support-phase-percent	percentage measure of time spent in the double support phase of the gait cycle and calculated as total double support time/gait cycle time.
Integrated-pressure (pressure x s)	the sum of pressure applied by a footstep at each sampling time (120 Hz sampling rate) in the area of its contact with the ground.
Foot-strike-length (cm)	length of the major axis of the ellipse enclosing each footstep; PKMAS creates an ellipse around each footstep during footstep identification.
Cadence (steps/minute)	total footsteps / cumulative time (in minutes) to walk 8 lengths of the mat
Ambulation time (s)	total time taken to walk 8 lengths of the mat.

Other assessments

The non-gait assessments were also conducted in the levodopa ON-state and included the Unified Parkinson’s Disease Rating Scale (UPDRS) [13], the FOG-Q [12], the MoCA [11], the Frontal Assessment Battery (FAB) [14], the Scales for Outcome in Parkinson’s disease–Cognition (SCOPA-Cog) [15], the Hamilton depression (HAM-D) [16] and anxiety (HAM-A) [17] rating scales, Apathy Evaluation Scale (AES) [18], Parkinson’s disease questionnaire for quality of life (PDQ-39) [19], Epworth Sleepiness scale (ESS) [20], and REM Sleep Behavior Disorder Screening Questionnaire (RBD-Q) [21]. Levodopa equivalent daily dose was calculated using previously accepted formulas for conversion of levodopa extended release formulations and dopamine agonist doses [22, 23].

Statistical analysis

Summary statistics (means ± standard deviations, percentages) of patient characteristics for the three FOG groups are provided in Table 2. For non-gait features, we used a linear mixed model that accounted for FOG group, sex, age, and disease duration; we also allowed each FOG group to have its own variance, so as not to bias the standard errors and increase the chance of rejecting a true null hypothesis. Our primary comparison of interest within each analysis was between the OFF- and ONOFF-FOG groups; and to corroborate known differences between OFF- and no-FOG groups, we also compared these two groups. These comparisons were made with contrasts within the linear mixed model. For gait features, we added motor UPDRS as a covariate and the interaction of FOG group with motor UPDRS to the mixed model. When the interaction between FOG group and motor UPDRS was significant, we made comparisons at low (9.5), middle (13.0), and high (16.0) values of motor UPDRS; specifically, the lower value was the 25th percentile for the OFF-FOG group, 13.0 was the median among no-FOG and OFF-FOG patients, and 16.0 was the 75th percentile for the no-FOG group. For all but 3 features, however, the interaction had p>0.10; for those features, we dropped the interaction term from the model, and compared OFF-FOG to ONOFF-FOG. We note these OFF-FOG vs ONOFF-FOG comparisons account for motor UPDRS so that the two groups are compared at the same motor UPDRS values. Figs 2 and 3 and S1 show the differences along with their 95% confidence intervals for those differences for all the features we analyzed. In order to concisely visualize these differences from 8 to 10 features within a measure type, all having different scales of measurement, we standardized the differences (see the S1 Table with original and standardized numerical results). The S1 File contains a thorough description of the statistical models used.

Fig 2

Comparison of spatiotemporal features for OFF-state freezers compared to ONOFF-state freezers and non-freezers.

The standardized difference between OFF-state freezers and ONOFF-state freezers (OFF-ONOFF, squares) and OFF-state freezers and non-freezers (OFF-No, circles) is shown for (A) mean and (B) stride-to-stride variability (coefficient of variation, CV). Bars denote the 95% confidence intervals. Comparisons with significant group differences are represented by black symbols and bars, while those without significant group differences are represented with gray symbols and bars.

Fig 3

Comparison of asymmetry between more and less affected side for spatiotemporal parameters in OFF-state freezers compared to ON-state freezers and non-freezers.

The standardized differences in the asymmetry ratio (more/less affected side) are also shown for (A) mean and (B) CV. Bars denote the 95% confidence intervals. Comparisons with significant group differences are represented by black symbols and bars, while those without significant group differences are represented with gray symbols and bars.

One patient, #96, had extreme values for most features in all the measure types; and another patient, #80, had extreme values for CV measures. We excluded patient #96 from all analyses, and patient #80 from analyses of CVs. However, to learn whether and how inferences might change with these patients included, we re-ran the above analyses again, and present the results in S1 Fig. The differences in inferences from the reduced dataset to the full dataset were minor: the full dataset revealed significant differences in mean stance phase percent and total double-support percent between OFF-FOG and ONOFF-FOG groups.

Results

Demographics of the PD patients enrolled are shown in Table 2. We did not statistically compare these characteristics among the three groups as we had no hypotheses necessitating such tests. Ages at motor onset and duration of disease did not differ by more than a standard deviation (SD) among FOG groups. Consequently, ages at enrollment also did not differ by more than a standard deviation. Regarding initial symptoms at motor onset, though the ONOFF-FOG group had the highest percentage of patients whose first symptom was in gait, over a third of ONOFF-FOG patients reported rest tremor as their initial symptoms. Hoehn & Yahr scores in the ONOFF-FOG group were higher than the other two groups by about 1½ standard deviations or more and fall frequencies in the ONOFF-FOG group were over 7 times that in the other two groups.

Controlling for age, disease duration, and sex, ONOFF-FOG patients had statistically greater disease severity with higher scores on both the motor-related and non-motor related questions of the UPDRS (Table 3) than in OFF-FOG; consequently, the total UPDRS score was also statistically higher in ONOFF-FOG. Cognitive scores were statistically lower on the MoCA, FAB, and SCOPA-Cog in ONOFF-FOG patients compared to OFF-FOG patients. Quality of life (as measured by the PDQ-39) was also statistically worse in ONOFF-FOG patients. While apathy scores on the AES were greater in OFF-FOG patients by 3.4 points, no difference (i.e. a difference of 0) was also plausible. Finally, there was little to no evidence that these two FOG groups differed in depression (HAM-D), anxiety (HAM-A), or sleep quality (RBD and Epworth Sleepiness Questionnaires).

Table 3

Means (and 95% CIs) for motor and non-motor features, adjusted for sex, age at enrollment, and disease duration.

The differences in means (and 95% CIs) between the OFF and ONOFF-FOG groups are also provided, with the test statistics and p-values. The CIs for differences in means that do not contain 0 are in bold font.

Outcome	no-FOG (n = 43)	OFF-FOG (n = 36)	ONOFF-FOG (n = 26)	OFF-FOG–ONOFF-FOG Estimate (95% CI)	t-statistica p-value
Total UPDRS Score	21.9	31.7	46.4	-14.7	-5.32
	(18.7, 25.1)	(28.2, 35.2)	(42.2, 50.6)	(-20.2, -9.2)	< .001
UPDRS Part III (motor)	12.3	16.8	25.7	-8.9	-4.81
Score	(10.1, 14.5)	(14.5, 19.2)	(22.9, 28.5)	(-12.5, -5.2)	< .001
UPDRS Part I+II (non-motor)	9.6	14.8	20.7	-5.8	-3.99
Score	(7.9, 11.3)	(13.0, 16.7)	(18.5, 22.9)	(-8.8, -2.9)	< .001
FOG-Q score	2.0	8.3	14.1	-5.8	-6.79
	(1.0, 3.0)	(7.2, 9.4)	(12.8, 15.4)	(-7.5, -4.1)	< .001
FOG-Q sub-score q3-6	0	5.4	9.5	-4.1	-6.60
(freezing)	(-0.7, 0.7)	(4.6, 6.2)	(8.6, 10.5)	(-5.4, -2.9)	< .001
FOG-Q sub-score q1-2	2.0	2.9	4.5	-1.6	-4.23
(non-freezing)	(1.6, 2.5)	(2.4, 3.4)	(4.0, 5.1)	(-2.4, -0.9)	< .001
MoCA score	25.8	25.3	21.8	3.4	3.77
	(24.7, 26.8)	(24.1, 26.4)	(20.5, 23.2)	(1.6, 5.2)	< .001
FAB	16.1	15.0	13.5	1.5	2.43
	(15.3, 16.8)	(14.2, 15.8)	(12.5, 14.4)	(0.3, 2.8)	.017
SCOPA-Cog	25.4	22.6	19.3	3.2	2.58
	(23.9, 26.8)	(21.0, 24.2)	(17.4, 21.2)	(0.7, 5.7)	.012
PDQ-39	27.5	43.6	58.5	-15.0	-2.86
Questionnaire	(21.4, 33.6)	(36.9, 50.2)	(50.6, 66.4)	(-25.3, -4.6)	.005
Apathy	9.0	16.4	13.0	3.4	1.73
Evaluation scale	(6.7, 11.3)	(13.9, 18.9)	(10.0, 16.0)	(-0.5, 7.3)	.088
HAM-D	7.0	10.4	9.7	0.7	0.50
	(5.4, 8.6)	(8.6, 12.1)	(7.6, 11.8)	(-2.1, 3.5)	.621
HAM-A	4.9	7.6	7.4	0.2	0.17
	(3.6, 6.2)	(6.2, 9.0)	(5.8, 9.1)	(-2.0, 2.3)	.862
RBD	5.0	5.9	5.2	0.8	0.91
Questionnaire	(4.0, 5.9)	(4.9, 6.9)	(3.9, 6.4)	(-0.9, 2.4)	.363
Epworth Sleepiness	7.6	7.8	9.1	-1.3	-1.13
Questionnaire	(6.2, 9.0)	(6.3, 9.3)	(7.4, 10.9)	(-3.6, 1.0)	.259

UPDRS: Unified Parkinson’s Disease Rating Scale; FOG-Q: Freezing of Gait Questionnaire; MoCA: Montreal Cognitive Assessment Score; FAB: Frontal Assessment Battery; SCOPA-Cog: Scales for Outcome in Parkinson’s Disease-Cognition; HAM-D: Hamilton Depression scale; HAM-A: Hamilton Anxiety scale; RBD: REM sleep behavior disorder.

a All t-statistics had 99 degrees of freedom.

Based on individual question responses on the FOG-Q, mean frequency and duration were both about 1 standard deviation higher in ONOFF-FOG patients than the means in their OFF-FOG peers (3.31±0.62 vs 2.00±1.12 score for item 3 frequency, 2.31±0.93 vs 1.47±0.97 item 4 longest duration and 1.88±0.75 vs 1.06±0.80 for average of items 5–6, average duration).

We controlled for sex, age, disease duration, and motor UPDRS score in all analyses of spatiotemporal gait features. For all but three features, there was little to no evidence that the slope of motor UPDRS depended on FOG group (all interaction ps ≥ 0.130). Compared to no-FOG patients, OFF-FOG patients had statistically greater total double support percent (see Fig 1A for example), stance phase percent, ambulation time, and stride width, slower stride velocity, and shorter stride length; the CV was statistically greater in stance phase percent and foot-strike length (Fig 2A and 2B, black circles). Importantly, the estimated differences between ONOFF-FOG and OFF-FOG patients were at least as large, and in the opposite direction, as the statistically significant differences between no-FOG and OFF-FOG patients for mean total double support percent and stance phase percent, and CV of foot-strike length. However, due to high variability in ONOFF-FOG patients (SDs of these features were 2.1 to 2.5 times greater in the ONOFF-FOG patients), these differences were not statistically significant for the OFF-ONOFF comparison (Fig 1A for example, and Fig 2A and 2B, gray squares). For estimated mean differences, CVs of stride time, integrated pressure, and total double support percent were also at least as large, and in the opposite direction between OFF vs ONOFF-FOG compared to OFF vs noFOG comparisons, but none of these comparisons were statistically significant. The importance of these results are also reviewed in the discussion section and used to provide sample sizes for future studies.

Fig 1

Representative examples of gait features as a function of motor UPDRS.

(A) Slope independent of FOG group. Mean total double support percent is plotted as a function of motor UPDRS scores with mean and 95% confidence intervals shown, as an example of a gait feature where the slope of UPDRS on the feature did not depend upon FOG group; i.e., was the same among the three FOG groups. (B) Slope dependent upon FOG group. CV stride length is plotted as a function of motor UPDRS scores with mean and 95% confidence intervals shown, as an example of a gait feature where the slope of UPDRS on the feature depended upon FOG group; i.e., the slopes were not the same for all FOG groups. Note: The estimated regressions lines for each FOG group span the observed range of UPDRS scores observed for that group.

For three features, there was evidence that the slope of motor UPDRS depended on FOG group (all interaction ps ≤ 0.089). As motor UPDRS increased, CV of stride-length and stride-velocity increased significantly faster in OFF- and ONOFF-FOG patients than in no-FOG patients where motor UPDRS had a near-0 slope (see Fig 1B for example). At midrange and higher values of motor UPDRS, OFF-FOG patients had significantly more variability in stride-length and stride-velocity than in the no-FOG patients; the CVs were between 0.9 and 1.75 percentage points (pp) higher in the OFF-FOG patients. We note that CV in ONOFF-FOG patients was (a constant) 1.5 pp higher than OFF-FOG patients for stride-length and (a constant) 1.9 pp higher for stride-velocity, but as the residual standard deviation of ONOFF-FOG patients was at least 3.6 times greater than that for the OFF-FOG patients, these differences were not significant.

Gait asymmetry

To determine if asymmetry in gait played a role in developing ONOFF-FOG, we analyzed the ratio of each spatiotemporal gait feature for the more affected/less affected side for each patient. We found no statistical differences when comparing OFF-FOG patients to each of ONOFF-FOG and no-FOG patients for either mean (Fig 3A) or CV (Fig 3B). However, comparisons of CV ratios between OFF- and ONOFF-FOG were more extreme and in the opposite direction as the same comparisons between OFF-and no-FOG for foot length, stride time, stride velocity, stance phase percent, and total double support percent (Fig 3B).

Multiple testing

In Figs 2 and 3 and S1 and Table 3, we conducted 80 comparisons. Of those, 18 were significant at the 0.05 significance level. We computed the positive False Discovery Rate, which estimates how many of the significant results may be Type I errors [24]. The positive False Discovery Rate was 0.14, with a 95% confidence upper bound of 0.23; this means, we are 95% confident that there were less than 5 false discoveries in the 18.

Discussion

In this manuscript we report the motor, non-motor, and gait phenotypes of PD patients with freezing of gait that occurs in the levodopa ON- and OFF-state (or levodopa unresponsive freezing) compared to those with freezing that occurs only in the levodopa OFF-state (or levodopa-responsive freezing), using objective testing. In our cohort of FOG patients with approximately the same disease duration, and age at onset, ONOFF-FOG patients had greater cognitive dysfunction [3, 8, 10], greater motor disease severity [3, 8], and lower quality of life [6] than OFF-FOG patients. Regarding spatiotemporal gait, in several features, the separation in means between OFF-FOG and ONOFF-FOG patients was at least as large, and in the opposite direction, as the separation in means between OFF-FOG and no-FOG patients; this, accounting for sex, age at onset, disease duration, and disease severity (motor UPDRS score). The variability of these spatiotemporal gait features in ONOFF-FOG patients was also markedly greater than in OFF-FOG and no-FOG patients, with standard deviations being about twice as large. Consequently, comparisons between OFF- and ONOFF-FOG patients are not known as precisely as those between OFF- and no-FOG patients.

Because of the increased variability of spatiotemporal gait features in ONOFF-FOG patients, power was reduced in our study. We used summary statistics from our study and Amboni et al. Table 1 [3] to perform a power analysis for a potential future study. Fig 4 presents the power plotted by total sample size for several effect sizes, σ, where σ is the standard deviation for the OFF-FOG population, after controlling for sex, age at onset, disease duration, and disease severity. The important assumption in the power analysis is that the standard deviation for the ONOFF-FOG group is twice that of the OFF-FOG group. Details of the power analysis are in the S1 File. In order to detect a difference in means of size σ/2, 160 patients (80 OFF- and 80 ONOFF-FOG) would be needed to have 0.80 power on a 0.05 significance level test. We found statistical differences of size between OFF-FOG and noFOG groups in this study, but larger differences between OFF-FOG and ONOFF-FOG groups were not significant; see Fig 2A for example.

Fig 4

Power plotted by total sample size for several effect sizes.

Effect sizes are expressed in terms of the population standard deviation, σ, of the OFF-FOG group, after accounting for sex, age at onset, disease duration, and disease severity. The power calculations assume that the population standard deviation of the ON-FOG group is 2σ. More details of the power analysis are in the S1 File.

Our work corroborates prior work on several noted differences between those who have FOG while on levodopa (OFFON-FOG) and those who do not (OFF-FOG); specifically the differences were older age at onset [3, 8], worse UPDRS motor scores [3, 8], worse freezing severity [6], worse cognition scores (e.g., MMSE, MoCA or neuropsychological testing batteries) [3, 8, 10] and worse quality of life scores (e.g. UPDRS part II or PDQ) [6]. Worse quality of life, worse cognition and higher freezing severity scores were also reported in OFFON-FOG compared to a general PD group [9]. Importantly, we have gone beyond prior studies by examining objective gait measures, depression, anxiety, apathy, RBD and sleep quality on validated scales; to our knowledge, such evaluation between OFF and ONOFF-FOG groups have not been reported in previous studies.

Continuous gait abnormalities have been well documented in PD patients, and a recent meta-analysis showed consistent reduction in stride-length, swing-time and hip excursion compared to healthy controls [25]. In FOG patients continuous gait abnormalities including decreased stride length setting [26-30], increased foot-strike length variability [28], and asymmetry in stride or steppage [31, 32] have suggested that the threshold to achieve motor program breakdown, and therefore a freeze is reduced in PD FOG patients [33]. In our study, mean stance phase and total double support, and the CV of foot-strike length in ONOFF-FOG patients were all greater than in OFF-FOG patients by margins that exceeded the confirmed increases found in the same features when comparing OFF-FOG to no-FOG patients (Fig 1). Because standard deviations of these features in ONOFF-FOG patients were over 2 times that in OFF-FOG patients, coupled with relatively small group sizes (26 ONOFF-FOG and 36 OFF-FOG patients), these results did not reach statistical significance. As a result, we cannot confidently say that these spatiotemporal gait dynamics differences reflect a fundamental difference in underlying disease pathology between the OFF-FOG and ONOFF-FOG groups. However, the fact that dopamine improves episodic freezing in one group and not the other, suggests that the pathways leading to break-down may involve more non-dopaminergic circuits in ONOFF-FOG.

PD-FOG patients have been reported to have greater sleepiness [34, 35] and REM sleep behavior disorder (RBD) [35, 36], than in no-FOG. The pedunculopontine nucleus (PPN) plays an important role in sleep-wake cycles and may play a role in integrating gait control with sleep function [37, 38]. PPN stimulation has also been proposed as a treatment for freezing of gait in Parkinson’s disease [39, 40]. In our cohort, the ONOFF-FOG group were not significantly worse than those in the OFF-FOG group on sleep or RBD scales; further, 0 was in the middle half of the confidence intervals for the difference between the ONOFF- and OFF-FOG groups, suggesting that this pathway was not significantly different between the ONOFF- vs OFF-FOG phenotypes. Apathy [41], depression [35], and anxiety [35, 42], have also been reported to be worse in FOG patients compared to noFOG. Anxiety [43] and depression have also been reported to be possible predictors of future FOG development. In our cohort, 0 was in the middle third of the confidence intervals for the difference between ONOFF- and OFF-FOG groups for HAM-A and HAM-D scores, suggesting that limbic pathways may not lead to the differential pathophysiology.

In our cohort PD ONOFF-FOG patients had higher FOG-Q scores on questions 3–6, indicating a greater frequency and duration of freezing episodes than their OFF-FOG counterparts. While these questions are based on subjective report and can be confounded by recall bias, it would suggest that ONOFF-FOG patients not only have a greater deficit in gait initiation than OFF-FOG patients, but also a decreased ability to return to normal gait after freezing occurs. Future analysis of the freezing episodes themselves and the response of the freezing episodes to dopamine supplementation could help shed further light on this process. Additionally, anticipatory postural adjustments (APAs) have been previously reported to contribute to gait initiation deficits in PD patients [44] and FOG patients [45-47] and further work is needed to determine how these may defer between ONOFF- and OFF-FOG patients and whether impaired APAs impact the extent of freezing duration in the different groups.

While our study did not have an imaging component to provide us with pathophysiologic correlates, we can still speculate. It has been suggested that dysfunction in cholinergic pathways leads to FOG, with neocortical cholinergic denervation [48] and decreased vesicular acetylcholine transporter binding in the striatum, temporal and mesofrontal limbic regions [49]. Imaging during imagined gait has also suggested involvement of the cerebellar locomotor region [50]. It is possible that FOG is modulated by both dopamine and cholinergic pathways. Initial dopaminergic denervation leads to a dopamine responsive gait freezing (OFF-FOG) and with progression of disease, more cholinergic denervation leads to development of a dopamine insensitive freezing (ONOFF-FOG). No cases of ONOFF-FOG developing as an initial manifestation of freezing in PD have been reported to our knowledge. As cholinergic pathways also modulate cognition, this could provide the link between freezing and cognitive decline. It is however still possible that ONOFF-FOG is a separate phenomenon altogether and further imaging and longitudinal progression studies monitoring multiple modalities of PD dysfunction would be needed to tease this out.

It should also be taken into consideration that freezing is likely on a continuum. People without reported freezing of gait, could be in the “honeymoon period” where their symptoms are better on levodopa and therefore they do not notice freezing develop till it progresses beyond a “micro freeze” that is undetectable visually on exam and does not affect function. Similarly freezing of gait that subjectively resolves with levodopa may also exist on a continuum with freezing that occurs irrespective of motor fluctuations in other levodopa sensitive symptoms such as rigidity and bradykinesia. Development of accurate objective freeze detection algorithms could help resolve these issues as well. We have also included people with freezing that did not improve with levodopa and people whose freezing worsened with their levodopa doses, or with higher levodopa doses in the same group and these could be different sub-phenotypes on the continuum as well.

In our cohort, there was an increasing percentage of people meeting the PIGD phenotype designation going from noFOG to OFF-FOG to ONOFF-FOG. It remains unclear whether these two phenotypes, PIGD and FOG are independent risk factors for one another, or possibly the same phenotype. Similar to the increasing incidence of FOG from 7% in early disease [1] to 92% at death [2], the PIGD phenotype has also been reported to increase with disease duration with one cohort study reporting 54% PIGD participants at initial visit, 73% at 4-year follow-up and 88% at 8-year follow-up [51], albeit limited by drop-out over this period in the total population due to deaths in the cohort. Disease features associated with the PIGD phenotype are also similar to FOG including longer disease duration, greater disease severity, lower cognitive scores, impaired postural adjustments and faster disease progression [51-54]. We previously showed that FOG participants show faster spatiotemporal gait decline than noFOG [55]. Clinically OFF-FOG can respond well to levodopa and when motor-fluctuations are not occurring in early PIGD, freezing may go unwitnessed either in the form of micro-freezes, or levodopa responsive freezing. Further work is needed in larger longitudinal cohorts to explore these two different possibilities. Whatever the case, exercise has been shown to help possibly with decreasing disease progression and helping acutely with improving gait, balance and FOG and should be consistently recommended to all PD patients [56-58].

There are limitations to our study. We did not explore the freezing episodes themselves, or the spatiotemporal features before and after freezing episodes such as the progressively shorter stride prior to entering a freeze or trembling of the legs while in the freeze. Future studies exploring the episodic aspects of the freezing may provide more physiologic insight to guide correlation with pathophysiologic dysfunction. Due to the more severe motor phenotype in ONOFF-FOG patients, we were unable to perform assessments in the levodopa OFF condition for this study, and therefore were unable to explore any differential dopamine responsiveness of the continuous gait phenomena between the FOG groups [5]. However, since the OFF-FOG group has improved freezing in the ON-levodopa state while the ONOFF-FOG group still has freezing in the ON-levodopa state, the differences in spatiotemporal gait features that remain in the ON-levodopa state are of primary interest.

In summary, despite similar disease duration to OFF-state freezers, ONOFF-state freezers had greater motor disease severity and cognitive deficits, and lower quality of life, but sleep quality, mood and apathy were similar. The gait phenotype suggests that differences seen between ONOFF- and OFF-FOG patients are at least as large as those seen between OFF- and no-FOG patients, but between-patient variability was larger among ONOFF-FOG patients. These findings suggest multifactorial deficits leading to an ONOFF-FOG phenotype.

Comparison of spatiotemporal parameters for OFF-state freezers compared to ON-state freezers and non-freezers for all participants including those with extreme values.

The standardized difference between OFF-state freezers and ON-state freezers (OFF-ON, squares) and OFF-state freezers and non-freezers (OFF-No, circles) is shown for (A) mean and (B) stride-to-stride variability (CV). The standardized differences in the asymmetry ratio (more/less affected side) are also shown for (C) mean and (D) CV. Bars denote the 95% confidence intervals. Comparisons with significant group differences are represented by black symbols and bars, while those without significant group differences are represented with gray symbols and bars.

(TIF)

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Original and standardized results.

(PDF)

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Minimal dataset.

(CSV)

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Supplementary methods.

(DOCX)

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SAS code.

(SAS)

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R code.

(R)

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8 Jul 2021

PONE-D-21-16241

Levodopa ON-state Freezing of Gait: Defining the Gait and Non-motor Phenotype

PLOS ONE

Dear Dr. Virmani,

Thank you for submitting your manuscript to PLOS ONE. This is an interesting area that caused some difference of opinion between reviewers.

After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

In particular, in a design that has used traditional hypothesis testing, statements discussing features of data that were not statistically significant should be significantly shortened or eliminated, as suggested by one of the reviewers. Because of the direct relevance to unresponsive FOG, please see whether this work from our center would be an appropriate reference: https://www.nature.com/articles/s41531-019-0099-z

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes

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Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #3: Yes

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5. Review Comments to the Author

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Reviewer #1: This manuscript aims to characterize persons with Parkinson’s disease (PD) who experience freezing of gait (FoG) while on parkinsonian medications and contrast these characteristics against those of persons with PD who either only experience FoG when off of their medications or do not experience FoG at all. The authors report that persons with PD + FoG when medicated had worsened disease severity, cognition, quality of life, and global gait characteristics than participants in the other groups. I found the topic of the study to be interesting; however, the reporting of the results is challenging to follow given the qualitative nature with which the results are reported and interpreted. The introduction also lacks important background that could help the reader to better understand the motivations behind the study.

ABSTRACT

In the Objective statement, I recommend revising “motor” to “gross motor”, given that gait is a motor function but mentioned separately.

In the final sentence of the Results section, please revise “Variability” to “Gait variability” (or, ideally, a more specific gait variability metric – e.g., step length variability).

In the Conclusions statement, I recommend revising or omitting the second sentence. This manuscript provides primarily descriptive information about the different subgroups of persons with PD and does not provide causal evidence of factors that may drive levodopa-resistant FoG in PD.

INTRODUCTION

The introduction is quite short and provides only a limited background of information regarding FoG in PD. There are significant bodies of literature investigating the motor response to levodopa in persons with PD and FoG that could help the reader to understand the direction and hypotheses of the study. As currently written, the introduction lacks focused hypotheses about what motor and non-motor features may be expected to differ among the groups of interest and why. Such hypotheses could be formed logically with a more thorough background of proposed mechanisms of both the motor response to levodopa and development of FoG in PD. What might we expect to differ between persons with and without levodopa-resistant FoG and why?

While I agree with the authors in that I am also not familiar with any studies that have directly compared persons with PD and levodopa-resistant FoG to those with levodopa-responsive FoG, there have been studies contrasting persons with PD and levodopa-resistant FoG against a more general population of persons with PD (e.g., Ferraye et al., Eur Neurol, 2013). These studies are relevant but currently omitted from the background.

METHODS

Given the stated goal of the study (identifying differences between persons with levodopa-resistant/levodopa-responsive FoG), it is not clear why a no-FOG group was included.

What was the reason for excluding frequent fallers? I understand that there could be safety concerns, but one would imagine that procedures could be put in place to minimize fall risk. It seems like omitting frequent fallers would exclude many potential participants particularly within the ON-FOG group.

Did all participants take their medications at the same time relative to the start time of their participation in the study (e.g., one hour prior to participation)?

It would be helpful to define the gait parameters “foot-strike-length” and “ambulation time”.

Line 84 – “were enrolled” is repeated.

Line 141 – what is meant by “low, middle, and high values of motor UPDRS”?

RESULTS

Several of the results sections are reported very descriptively without statistics to support claims made. This makes interpretation of the results challenging because it is not clear which comparisons resulted in statistically significant differences vs. which comparisons are being made qualitatively. Please include results from your statistical analyses throughout this section.

Please revise the headings in Figure 3 to read “affected” rather than “effected”.

DISCUSSION

In line with the comment above regarding the results, it is difficult to comment on the discussion given that it is not clear which results were statistically significant.

I found the contextualization of the findings within previously proposed models of FoG to be challenging to follow. It was not clear to me how comparisons being made between two populations that both experience FoG (levodopa-responsive FoG and levodopa-resistant FoG) provide evidence for or against models of FoG development; it would seem that comparisons between populations with and without FoG would be more insightful in testing these models.

Reviewer #2: INTRODUCTION:

• Incorrect use of the word mechanistic line 71

• Line 72, are non-motor features not objective? Clarify

• Should discuss prior work on levodopa induced FOG, and pseudo-ON FOG, as well as work on cognitive differences between pharmacologic subtypes.

• Provide reference for the assertion that FOG is initially dopa-responsive then becomes unresponsive

METHODOLOGY

• Clarify criteria for non-freezers. Did they have to have a 0 on item one of the fogq?

• Why was the nfogq not used? If not, this is a limitation of the study and should be mentioned. The original version had several limitations which is why the new version was introduced

• classification of ON FOG is unclear and confusing as it is written, please rewrite sentence beginning with “freezers…” in line 93

o it appears you are including levodopa induced FOG as ON FOG

o discussion regarding multiple classifications of dopa response is critical here. Some groups will define ON FOG as dopa induced FOG, others as any FOG in the ON state, and others as FOG that does not respond to dopamine, it looks like all of these were included in this group making it quite heterogenous

o OFF FOG group may also classified based on its dopa response

• There was no evaluation of objective gait parameters in the OFF state, major limitation

• It looks like there was no adjustment for multiple comparisons

RESULTS

• Please indicate on table 1, which differences were statistically significant

• Line 184, clarify what evidence there was of any differences

• Table 2 needs to be clarified, label specifically what factors are statistically significantly different, not just state that CI’s that don’t include zero are significant, there is no legend to explain what the bolded entries represent

• Cannot report “statistically significant” differences if did not correct for multiple comparisons

• Should not report non statistically significant differences even if there were trends that were not significant due to variance

DISCUSSION

• “In FOG participants with approximately the same disease duration, and age at onset, ON-FOG participants had greater cognitive dysfunction, greater motor disease severity, and lower quality of life than OFF-FOG participants. “ All of this is well known and previously reported. Authors should acknowledge this is well known, and reference prior work in the initial paragraph.

• I see no value in reported and much less discussing non significant trends.

• Sentence starting in line 278 needs a reference

• It does not follow that based on the fact that there are inter episodic gait changes in FOG there are four models of FOG. There are many other models than those proposed in 2013.

• I don’t see how the discussion of these 4 models is helpful in explaining the findings of the work presented here.

• I suggest only statistically significant findings between groups that survive multiple comparisons be reported and discussed.

• Specifically there is no discussion of the findings of figure 1 which imply that the changes that are seen, if they survive multiple comparisons are more likely due to overall motor decline that FOG itelf

Reviewer #3: Manuscript: Levodopa ON-state Freezing of Gait: Defining Gait and Non-motor Phenotype

This is an excellent contribution to freezing of gait in Parkinson’s disease, both in the OFF and ON states. The additional data on non-motor features distinguishing these subtypes further enhances this study.

Overall significance of the paper:

This study demonstrated that ON freezers had greater disease severity, cognitive deficits, and lower quality of life as compared to OFF freezers with similar disease duration.

The authors acknowledged a limitation in not exploring the freezing episodes themselves in detail, in addition to the spatiotemporal indices pre- and post- freezing. This would be a useful next step, as it may yield further distinguishing features between these 2 subgroups.

In addition, a future study utilizing 3D motion capture (in this cohort or perhaps collaborating with another institute with such data) would provide further data points, with particular attention to 3D kinematics of arms (i.e. arm-swing), leg swing, and heel/foot strike.

Other:

Page 4: Line 84 – Duplicate “were enrolled.” Please delete one.

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Reviewer #2: No

Reviewer #3: No

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15 Sep 2021

Please see attached document "response to reviewers"

Submitted filename: Landes et al - Response to Reviewers v2.docx

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4 Jan 2022

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2. Is the manuscript technically sound, and do the data support the conclusions?

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Reviewer #2: Yes

Reviewer #3: Yes

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6. Review Comments to the Author

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Reviewer #1: The authors have partially addressed the prior comments. The statistical reporting remains an issue. If the authors choose not to perform statistical analyses on certain aspects of the data, they should refrain from interpreting the data; that is, if demographic data are included to provide purely descriptive information about each group, the authors should not make statements such as "were not notably dissimilar" and "clearly the highest" without some type of quantitative statistical analysis to substantiate these claims. Certainly, the reader can see the data and ascertain for themselves which numbers are larger than others without additional need for interpretation if there are no statistical results to report.

Table 3 provides indicators of statistical significance but does not provide specific test statistics or p-values (as are provided for the gait data in the S1 Table).

Reviewer #2: The authors present a well written report of a comparative study between PD patients with freezing exclusively in the OFF state and those that have FOG in the ON and in the OFF state. They collect data on multiple domains to replicate prior work, and focus on reporting of quantitative gait findings that may separate the groups. While I do agree that quantitative measurements of gait, outside the FOG episode is of value in FOG, conceptually, there is a flaw in the premise that there would be phenomenological differences in based on dopa-response. Largely, this study fails to find significant behavioral differences in the recorded spatiotemporal parameters between OFF and ONOFF FOG, which is the main premise of the study, and the authors attribute to variability. The differences that are observed in cognition, quality of life, etc., can largely be explained by a greater disease severity. Moreover, these findings have been previously reported, particularly in cognition, with more thorough analyses, and this study did not add significantly to these findings. The discussion is well written and extensive, however, I do not see how the discussion of models of FOG is relevant to the findings of the study. I do agree on their depiction of the literature, the models, and dopa-response in FOG as a continuum, but again, I do not see how the data they present supports these assertions. There is a very transparent presentation of the data, and their analysis, and given the data presented, I believe their statistical approach, whereby FDR and effect sizes are presented, is justified.

Reviewer #3: I agree with Reviewer #1 regarding renaming the various FOG subgroups as it was difficult to follow the data at times without this added detail.

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4 Feb 2022

please see attached response to reviewers document.

Submitted filename: PONE-D-21-16241R1 - Response to Reviewers v4.docx

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26 Apr 2022

27 Apr 2022

Please see attached file with response to reviewers.

Submitted filename: Landes et al. - Response to reviewers revision 3-v1.docx

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18 May 2022

Levodopa ONOFF-state Freezing of Gait: Defining the Gait and Non-motor Phenotype

PONE-D-21-16241R3

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23 May 2022

PONE-D-21-16241R3

Levodopa ONOFF-state Freezing of Gait: Defining the Gait and Non-motor Phenotype

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