Predictive model for falling in Parkinson disease patients

Cognitive measures predict falls in Parkinson's disease: Insights from the CYCLE-II cohort

BACKGROUND

Accurate prediction of falls in patients with Parkinson's disease (PWP) is crucial for effective prevention efforts. Historically, fall risk models have heavily relied on motor features, overlooking the vital cognitive-motor interplay essential for locomotion.

METHODS

Baseline assessments and year-long fall data from the CYClical Lower Extremity Exercise for Parkinson's disease II (CYCLE-II) trial's control group were utilized. A LASSO logistic regression model assessed thirty-seven demographic, motor, and cognitive variables to identify key fall predictors. To explore the practical implementation of predicting falls in a clinical setting, a second model was developed using a subset of nine candidate measures conducive for retrieval from electronic medical records. Models' accuracy was validated against Paul et al.'s 3-step fall prediction model.

RESULTS

Analysis included 123 participants (mean age 65.3 ± 8.3 years, 66 % males, mean disease duration 4.9 ± 4.1 years). Seventy-two participants (58.5 %) fell at least once; with 33.1 % occurring during walking, 34.4 % resulting in injuries. The initial model identified 8 predictors with an AUC of 0.68. The second model, incorporating disease duration and cognitive tests, achieved an AUC of 0.67, comparable to Paul et al.'s validation (AUC 0.66). Participants with poorer information processing and spatial memory were more prone to falling over the 12-month period.

CONCLUSIONS

Impaired cognitive performance and longer disease duration were powerful predictors in identifying a future fall in PWP. The link between cognitive performance and potential for falling reinforces the strong interplay between gait and cognition.

Evaluating prognostic factors for falls in Parkinson's disease: A sex-based analysis

INTRODUCTION

Falls are a common and debilitating complication in Parkinson's disease (PD). Previous studies have primarily focused on cohorts with prevalent falls or advanced disease stages. This study assessed risk factors for falls in early-stage falls-naïve cohort stratified by sex.

METHODS

A total of 172 PD patients (<5 years disease duration) were selected from a registry-based study that reported no falls at baseline. All patients were assessed with a standardized data extraction form and falls were defined according to UPDRS Item 13. Hazard Ratios were calculated with univariable and stepwise multivariable Cox Proportional Hazard regression models.

RESULTS

Among the study sample, 61 (35.4 %) patients were female. At baseline, female and male PD groups were comparable in terms of age, disease duration, and UPDRS scores, although female PD patients had higher scores for UPDRS IV. Over a mean follow-up period of 3.9 (3.0) years, falls were reported in 13 female (21.3 %) and 18 male (16.2 %) PD patients. In female PD, motor fluctuations (HR [95 %] = 1.8 [1.3 - 2.6], p < 0.001) and postural stability (HR [95 %] = 4.2 [1.6 - 10.6], p = 0.003) emerged as significant predictors for falls, whereas in male PD, stepwise Cox regression selected freezing of gait (HR [95 %] = 2.0 [1.0 - 4.2], p = 0.053) and postural instability (HR [95 %] = 2.2 [0.89 - 5.4], p = 0.089) as the primary predictors for falls, although they were non-significant.

CONCLUSION

Our findings suggest that the risk factors for falls differ between female and male early-stage PD patients, which may have important implications for clinical management.

Anticipating Tomorrow: Tailoring Parkinson's Symptomatic Therapy Using Predictors of Outcome

BACKGROUND

Although research into Parkinson's disease (PD) subtypes and outcome predictions has continued to advance, recommendations for using outcome prediction to guide current treatment decisions remain sparse.

OBJECTIVES

To provide expert opinion-based recommendations for individually tailored PD symptomatic treatment based on knowledge of risk prediction and subtypes.

METHODS

Using a modified Delphi approach, members of the Movement Disorders Society (MDS) Task Force on PD subtypes generated a series of general recommendations around the question: "Using what you know about genetic/biological/clinical subtypes (or any individual-level predictors of outcome), what advice would you give for selecting symptomatic treatments for an individual patient now, based on what their subtype or individual characteristics predict about their future disease course?" After four iterations and revisions, those recommendations with over 75% endorsement were adopted.

RESULTS

A total of 19 recommendations were endorsed by a group of 13 panelists. The recommendations primarily centered around two themes: (1) incorporating future risk of cognitive impairment into current treatment plans; and (2) identifying future symptom clusters that might be forestalled with a single medication.

CONCLUSIONS

These recommendations provide clinicians with a framework for integrating future outcomes into patient-specific treatment choices. They are not prescriptive guidelines, but adaptable suggestions, which should be tailored to each individual. They are to be considered as a first step of a process that will continue to evolve as additional stakeholders provide new insights and as new information becomes available. As individualized risk prediction advances, the path to better tailored treatment regimens will become clearer.

Imbalance and Falls in Patients with Parkinson's Disease: Causes and Recent Developments in Training and Sensor-Based Assessment

Imbalance and falls in patients with Parkinson's disease (PD) do not only reduce their quality of life but also their life expectancy. Aging-related symptoms as well as disease-specific motor and non-motor symptoms contribute to these conditions and should be treated when appropriate. In addition to an active lifestyle, advanced exercise training is useful and effective, especially for less medically responsive symptoms such as freezing of gait and postural instability at advanced stages. As treadmill training in non-immersive virtual reality, including dual tasks, significantly reduced the number of falls in PD patients, the mechanism(s) explaining this effect should be further investigated. Such research could help to select the most suitable patients and develop the most effective training protocols based on this novel technology. Real-life digital surrogate markers of mobility, such as those describing aspects of endurance, performance, and the complexity of specific movements, can further improve the quality of mobility assessment using wearables.

Risk factors for falls in Parkinson's disease: a cross-sectional observational and Mendelian randomization study

Background

Patients with Parkinson's disease (PD) exhibit a heightened risk of falls and related fractures compared to the general population. This study aims to assess the clinical characteristics associated with falls in the patient with PD and to gain further insight into these factors through Mendelian randomization analysis.

Methods

From January 2013 to December 2023, we included 591 patients diagnosed with Parkinson's disease at Shenzhen Baoan People's Hospital. Using univariate and multivariate logistic regression analyses, we identified clinical variables associated with falls. We constructed a nomogram based on these variables and evaluated the predictive efficacy of the model. Additionally, we employed summary statistics from genome-wide association studies to conduct two-sample Mendelian randomization (MR) analyses on key variables influencing falls.

Results

Compared to the control group, we identified osteoporosis, motor dysfunction, higher Hoehn and Yahr scale as significant risk factors for falls in PD patients. Conversely, treatment with levodopa and a higher level of education exhibited a protective effect against the risk of falling. MR analysis further confirmed a causal relationship between osteoporosis, education level and falls in PD patients.

Conclusion

Osteoporosis and educational attainment are correlated with falls in Parkinson's disease.

Development and internal validation of a prognostic model for loss of balance and falls in mid- to late-stage Parkinson's disease

BACKGROUND

Mid- to late-stage Parkinson's disease (PD) is often linked with worsened and significant impairment of motor activities, but existing prognostic markers do not adequately capture the risk of loss of balance in PD patients. This study aims to develop a risk prognostic model for mid- to late-stage PD and identify prognostic factors that are indicative of impending loss of balance and falls.

METHODS

The study included 307 participants of which 75 were diagnosed with idiopathic PD and 232 were neurological or non-neurological controls. Among the PD group, 46 were early-stage (Hoehn and Yahr [H&Y] = 1,2) with no significant loss of balance while 29 were mid- to late-stage (H&Y = 3,4,5) which is characterized by loss of balance and falls. Multivariable logistic regression (MLR) was used to develop a prognostic model for mid- to late-stage PD. Model discrimination was assessed by ROC curves. The model was internally validated through bootstrapping and calibration plots.

RESULTS

The relevant factors identified and included in the final MLR model were shortness of breath, age, swollen joints, heme oxygenase-1 (HO-1) protein, and total salivary protein. The model had an AUC of 0.82 (95% CI = 0.71-0.92) and was well calibrated (calibration slope = 0.77, intercept = 0.03). The likelihood of shortness of breath (OR = 7.91, 95% CI = 1.63-45.12) was significantly higher among mid- to late-stage PD than early-stage. Age and total salivary protein were also significantly higher among mid- to late-stage PD.

CONCLUSION

The MLR prognostic model for mid- to late-stage PD may assist physicians in identifying patients at high risk for loss of balance and falls.

Prognostic factors for falls in Parkinson's disease: a systematic review

BACKGROUND

Falls represent a critical concern in Parkinson's disease (PD), contributing to increased morbidity and reduced quality of life.

PURPOSE

We conducted a systematic review to assess the prognostic factors associated with falls in PD, aiming to provide a comprehensive overview of relevant demographic and clinical parameters, and aid neurologists in identifying subsets of PD patients most susceptible to falls and associated injuries.

METHODS

PubMed and Web of Science databases were searched for prospective studies assessing factors associated with falls in ambulatory PD patients across different settings, from inception to August 2023. Data extraction was conducted using CHARMS-PF checklist and risk of bias was assessed with QUIPS tool. PRISMA guidelines were followed.

RESULTS

The initial search yielded 155 references. Thirty-four studies, involving a total of 3454 PD patients, were included in the final analysis. The mean pooled age was 67.6 years, and 45.1% were women. PD patients presented mild motor impairment (UPDRS III score 27.8) with mean pooled disease duration of 5.7 years. Gait and balance disorders and history of prior falls emerged as the most consistent predictors of falls across studies. Disease duration, disease severity, dysautonomic symptoms, freezing of gait, frontal cognitive functions, and PD medication dosages yielded inconsistent findings. Conversely, dyskinesias, age, sex, and depression were unrelated to future falls in PD. Logistic regression models were most commonly employed to identify factors significantly associated with falls in PD. Substantial heterogeneity prevailed in the inclusion of confounding factors.

CONCLUSION

The evidence suggests that previous history of falls, gait disorders, and poor balance are robust prognostic markers for falls in PD.

Gait and turning characteristics from daily life increase ability to predict future falls in people with Parkinson's disease

Objectives

To investigate if digital measures of gait (walking and turning) collected passively over a week of daily activities in people with Parkinson's disease (PD) increases the discriminative ability to predict future falls compared to fall history alone.

Methods

We recruited 34 individuals with PD (17 with history of falls and 17 non-fallers), age: 68 ± 6 years, MDS-UPDRS III ON: 31 ± 9. Participants were classified as fallers (at least one fall) or non-fallers based on self-reported falls in past 6 months. Eighty digital measures of gait were derived from 3 inertial sensors (Opal® V2 System) placed on the feet and lower back for a week of passive gait monitoring. Logistic regression employing a "best subsets selection strategy" was used to find combinations of measures that discriminated future fallers from non-fallers, and the Area Under Curve (AUC). Participants were followed via email every 2 weeks over the year after the study for self-reported falls.

Results

Twenty-five subjects reported falls in the follow-up year. Quantity of gait and turning measures (e.g., number of gait bouts and turns per hour) were similar in future fallers and non-fallers. The AUC to discriminate future fallers from non-fallers using fall history alone was 0.77 (95% CI: [0.50-1.00]). In contrast, the highest AUC for gait and turning digital measures with 4 combinations was 0.94 [0.84-1.00]. From the top 10 models (all AUCs>0.90) via the best subsets strategy, the most consistently selected measures were variability of toe-out angle of the foot (9 out of 10), pitch angle of the foot during mid-swing (8 out of 10), and peak turn velocity (7 out of 10).

Conclusions

These findings highlight the importance of considering precise digital measures, captured via sensors strategically placed on the feet and low back, to quantify several different aspects of gait (walking and turning) during daily life to improve the classification of future fallers in PD.

Dual-Task Treadmill Training for the Prevention of Falls in Parkinson's Disease: Rationale and Study Design

Various factors, such as fear of falling, postural instability, and altered executive function, contribute to the high risk of falling in Parkinson's disease (PD). Dual-task training is an established method to reduce this risk. Motor-perceptual task combinations typically require a patient to walk while simultaneously engaging in a perceptual task. Motor-executive dual-tasking (DT) combines locomotion with executive function tasks. One augmented reality treadmill training (AR-TT) study revealed promising results of a perceptual dual-task training with a markedly reduced frequency of falls especially in patients with PD. We here propose to compare the effects of two types of concurrent tasks, perceptual and executive, on high-intensity TT). Patients will be trained with TT alone, in combination with an augmented reality perceptual DT (AR-TT) or with an executive DT (Random Number Generation; RNG-TT). The results are expected to inform research on therapeutic strategies for the training of balance in PD.

Applicability and tolerability of electrical stimulation applied to the upper and lower leg skin surface for cueing applications in Parkinson's disease

Due to possible sensory impairments in people with Parkinson's disease, several methodological aspects of electrical stimulation as a potential cueing method remain to be explored. This study aimed to investigate the applicability and tolerability of sensory and motor electrical stimulation in 10 people with Parkinson's disease. The study focused on assessing the electrical stimulation voltages and visual analogue scale discomfort scores at the electrical sensory, motor, discomfort, and pain thresholds. Results show that sensory electrical stimulation at the tibialis anterior, soleus, hamstrings, and quadriceps stimulation sites was applicable and tolerable for 6/10, 10/10, 9/10, and 10/10 participants, respectively. Furthermore, motor electrical stimulation at the tibialis anterior, soleus, hamstrings, and quadriceps stimulation sites were applicable and tolerable for 7/10, 7/10, 7/10, and 8/10 participants, respectively. Interestingly, the thresholds for the lower leg were higher than those of the upper leg. The data presented in this paper indicate that sensory and motor electrical stimulation is applicable and tolerable for cueing applications in people with Parkinson's disease. Sensory electrical stimulation was applicable and tolerable at the soleus and quadriceps sites. Motor electrical stimulation was not tolerable for two participants at any of the proposed stimulation sites. Therefore, future studies investigating motor electrical stimulation cueing, should apply it with caution in people with Parkinson's disease.

Health anxiety and illness-related fears across diverse chronic illnesses: A systematic review on conceptualization, measurement, prevalence, course, and correlates

BACKGROUND

Patients with chronic diseases commonly report fears of illness or symptoms recurring or worsening. These fears have been addressed from an illness-specific perspective (e.g., fear of cancer recurrence), a generic illness perspective (e.g., fear of progression), and a psychiatric perspective (DSM-5 illness anxiety disorder and somatic symptom disorder). The broader concept of health anxiety (HA) can also be applied to patients with a chronic disease. This review was conducted to investigate the conceptual, theoretical, measurement-overlap, and differences between these distinct perspectives. We also aimed to summarize prevalence, course, and correlates of these fears in different chronic illnesses.

METHODS

We used PsycINFO, PubMED, CINAHL, Web of Science, SCOPUS, and PSYNDEX to conduct a systematic review of studies pertaining to these fears in chronic illness published from January 1996 to October 2017. A total of 401 articles were retained.

RESULTS

There were commonalities across different conceptualizations and diseases: a high prevalence of clinical levels of fears (>20%), a stable course over time, and a deleterious impact on quality of life. Reviewed studies used definitions, models, and measures that were illness-specific, with only a minority employing a psychiatric perspective, limiting cross-disease generalizability. There appears to be some applicability of DSM-5 disorders to the experience of fear of illness/symptoms in patients with a chronic illness. While conceptualizing HA on a continuum ranging from mild and transient to severe may be appropriate, there is a lack of agreement about when the level of fear becomes 'excessive.' The definitions, models, and measures of HA across chronic illnesses involve affective, cognitive, behavioral, and perceptual features.

CONCLUSIONS

The concept of HA may offer a unifying conceptual perspective on the fears of illness/symptoms worsening or returning commonly experienced by those with chronic disease.

Assessing the Relationship between the Enhanced Gait Variability Index and Falls in Individuals with Parkinson's Disease

Gait impairment and increased gait variability are common among individuals with Parkinson's disease (PD) and have been associated with increased risk for falls. The development of composite scores has gained interest to aggregate multiple aspects of gait into a single metric. The Enhanced Gait Variability Index (EGVI) was developed to compare an individual's gait variability to the amount of variability in a healthy population, yet the EGVI's individual parts may also provide important information that may be lost in this conversion. We sought to contrast individual gait measures as predictors of fall frequency and the EGVI as a single predictor of fall frequency in individuals with PD. 273 patients (189M, 84F; 68 ± 10 yrs) with idiopathic PD walked over an instrumented walkway and reported fall frequency over three months (never, rarely, monthly, weekly, or daily). The predictive ability of gait velocity, step length, step time, stance time, and single support time and the EGVI was assessed using regression techniques to predict fall frequency. The EGVI explained 15.1% of the variance in fall frequency (p < 0.001, r = 0.389). Although the regression using the combined spatiotemporal measures to predict fall frequency was significant (p=0.002, r = 0.264), none of the components reached significance (gait velocity: p=0.640, step length: p=0.900, step time: p=0.525, stance time: p=0.532, single support time: p=0.480). The EGVI is a better predictor of fall frequency in persons with PD than its individual spatiotemporal components. Patients who fall more frequently have more variable gait, based on the interpretation of the EGVI. While the EGVI provides an objective measure of gait variability with some ability to predict fall frequency, full clinical interpretations and applications are currently unknown.

Double-Tap Interaction as an Actuation Mechanism for On-Demand Cueing in Parkinson's Disease

Freezing of Gait (FoG) is one of the most debilitating symptoms of Parkinson’s disease and is an important contributor to falls. When the management of freezing episodes cannot be achieved through medication or surgery, non-pharmacological methods, such as cueing, have emerged as effective techniques, which ameliorates FoG. The use of On-Demand cueing systems (systems that only provide cueing stimuli during a FoG episode) has received attention in recent years. For such systems, the most common method of triggering the onset of cueing stimuli, utilize autonomous real-time FoG detection algorithms. In this article, we assessed the potential of a simple double-tap gesture interaction to trigger the onset of cueing stimuli. The intended purpose of our study was to validate the use of double-tap gesture interaction to facilitate Self-activated On-Demand cueing. We present analyses that assess if PwP can perform a double-tap gesture, if the gesture can be detected using an accelerometer’s embedded gestural interaction recognition function and if the action of performing the gesture aggravates FoG episodes. Our results demonstrate that a double-tap gesture may provide an effective actuation method for triggering On-Demand cueing. This opens up the potential future development of self-activated cueing devices as a method of On-Demand cueing for PwP and others.

Falls in persons with Parkinson's disease: Do non-motor symptoms matter as much as motor symptoms?

ABSTRACT Falls are common among persons with Parkinson's disease (PD). On the other hand, predicting falls is complex as there are both generic and PD-specific contributors. In particular, the role of non-motor symptoms has been less studied. Objective: The objective of this study was to identify the role of non-motor predictors of falling in persons with PD (PwP). Methods: A cross-sectional study was carried out in PwP recruited from a movement disorders clinic. Clinical and demographical data were collected. All PwP were assessed using the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and the Non-Motor Symptoms Scale (NMSS). Variables were assessed at the bivariate level. Significant variables were put into a logistic regression model. Results: A total of 179 PwP were included. Overall, 16.8% of PwP had fallen in the past 12 months, with 53.3% of them being recurrent fallers. The mean number of monthly falls was 2.5 ± 3.3. Factors associated with falling in the bivariate analysis included the disease duration, Hoehn and Yahr stage, MDS-UPDRS part I and II, postural instability/gait disturbance (PIGD) subtype, NMSS urinary domain, NMSS miscellaneous domain, and non-motor severity burden (all p-values < 0.05). After multivariate analysis, only the disease duration (p = 0.03) and PIGD (p = 0.03) remained as independent risk factors. Conclusion: Disease duration and the PIGD subtype were identified as relevant risk factors for falls in PwP Non-motor symptoms appear to have a less important role as risk factors for falls.

A Technological Review of Wearable Cueing Devices Addressing Freezing of Gait in Parkinson's Disease

Freezing of gait is one of the most debilitating symptoms of Parkinson’s disease and is an important contributor to falls, leading to it being a major cause of hospitalization and nursing home admissions. When the management of freezing episodes cannot be achieved through medication or surgery, non-pharmacological methods such as cueing have received attention in recent years. Novel cueing systems were developed over the last decade and have been evaluated predominantly in laboratory settings. However, to provide benefit to people with Parkinson’s and improve their quality of life, these systems must have the potential to be used at home as a self-administer intervention. This paper aims to provide a technological review of the literature related to wearable cueing systems and it focuses on current auditory, visual and somatosensory cueing systems, which may provide a suitable intervention for use in home-based environments. The paper describes the technical operation and effectiveness of the different cueing systems in overcoming freezing of gait. The “What Works Clearinghouse (WWC)” tool was used to assess the quality of each study described. The paper findings should prove instructive for further researchers looking to enhance the effectiveness of future cueing systems.