Physical Activity in the Elderly Spine Patient

Background Spine disorders, such as low back pain, come with considerable physical limitations, and participation in social events and everyday life can be burdensome2. Efforts to increase physical ability and involvement in everyday life are essential to maintain or heighten quality of life in spite of chronic pain.

Some spine disorders can negatively affect lumbar nerve roots, where the symptoms radiate to the legs. Lumbar Spinal Stenosis (LSS) is one of many chronic spinal pain syndromes, with specific structural abnormalities that can be detected on MRI scans, including narrowing of the spinal canal. Its clinical presentation involves radiation of pain and sensory disturbance to buttocks and legs while walking3. Although there is considerable variation in the diagnostic criteria used, spinal stenosis is common in the elderly, and a recent review reported prevalences between 11% and 38% depending on criteria and study population4. The disease considerably constrains patients' walking ability, which means that patients experience problems with exercise and leisure activities5. Physical activity is significantly reduced, and a recent study shows that individuals with LSS spend 82% of their day sitting or lying down, compared to 35% in healthy adults over 60 years6, leading to an increase in lifestyle diseases such as hypertension7.

Thus, the aging patient with a spine disorder such as LSS or low back pain has to cope with the functional limitations of their disease, as well as the natural decline of function with age1. It is therefore very important for this group of patients that healthcare providers can support their pursuit of an active life. In order to do so, it is necessary for healthcare providers to have reliable knowledge about the individual patients' physical activity and functional impairment in daily life. Such information is typically collected through interviews, physical exams, questionnaires, and the occasional objective test, which only provide indirect, predominantly subjective, information about physical activity in everyday life.

Emerging technology in the form of wearable sensors is breaking new ground and becoming more widespread. Existing research has used sensors such as accelerometers to quantify and differentiate time spent standing, walking, cycling, and sitting or lying down, with high accuracy8. Previous studies have already established that accelerometer-based step counts in elderly people are accurate9-13, but they are influenced by 1) the physical location of the accelerometer on the body14, 15, 2) the method used to transform raw accelerometer data16, and 3) traits of the person wearing it, such as gait speed, use of assistive devices, and age17. As LSS can alter gait characteristics18 and can give severe walking impairment, accelerometer measures of step count developed for healthy adults could be inaccurate in these patients. Since walking impairment is the most prominent disability in LSS, we see the need for a tested and valid measure of walking activity in daily living.

The study consists of two parts, each with a corresponding aim: Part I) develop and examine the validity of an accelerometer-based method of measuring walking activity in daily living in patients with LSS. Part II) uncover objectively identifiable profiles of physical activity in elderly patients with LSS and/or low back pain.

Methods Part I is a method development and validation study containing projects A, B and C.

Project A: Develop an accelerometer-based method of step count for patients with LSS and evaluate its accuracy by comparing it to a gold standard.

Project B: Evaluate the construct validity of the developed method in a free-living environment.

Project C: Evaluate the responsiveness of the developed method. Part II is a cross-sectional cohort study containing projects D, E and F. Project D: Quantify the amount of time spent standing, walking, cycling, and sitting/lying down in patients with confirmed LSS in secondary care.

Project E: Quantify the amount of time spent standing, walking, cycling, and sitting/lying down in patients with low back pain in chiropractic primary care.

Project F: Compare physical activity in LSS and low back pain patients to a randomly selected population of individuals 60 years of age or more.

Part I Project A- Gold standard Project A of the project is completed. Thirty (n=30) patients with lumbar spinal stenosis were included. To investigate the most optimal bodily location to place the accelerometer, each participant wore five accelerometers in different locations: the wrist, thigh, ankle, hip, and lower back, while going through a standardized movement protocol that involved walking, sitting down and standing up, cycling, and walking with walking aids. For validation against a gold standard, we recorded the standardized movement protocol on video and compared the accelerometer data to the actual observed activity on the recordings. An algorithm for quantifying the step count in the accelerometer data was developed based on data from the first 15 patients. The agreement and relationship between the gold standard and accelerometer step count was evaluated for each body location. The correlation between accelerometer step count and manually counted steps were 0.99-1.00 during continuous walking for all bodily locations. They were diminishing but still satisfactory while using a rollator for accelerometers placed on the ankle (0.98) and thigh (0.72). False steps were detected during cycling, but it is possible to correct this with an accelerometer placed on the thigh.

Project B- Construct validity Ninety-five (n=95) patients with lumbar spinal stenosis will be included and wear a single Axivity accelerometer on the thigh for seven days during their normal everyday life. Twenty patients (n=20) will be asked to wear a StepWatch on the right ankle simultaneously. In addition, we gather clinical data, ask participants to perform a Self-Paced Walk Test (SPWT), complete questionnaires and fill out a small walking diary for each day in the week. Please see Appendix I for the questionnaires.

The accelerometer data from patients in project B will be analyzed exploratively, and the raw accelerometer data will be transformed into relevant measures of walking performance, including the number of steps taken per day and the length of continuous walking in minutes.

From the data collected and walking measures calculated, face validity and construct validity will be examined in accordance to the methods suggested by de Vet et al19. The primary hypothesis concerns the correlation between the SPWT results and the accelerometer measures.

Project C- Responsiveness Measures of walking ability has been documented to improve in patients with LSS after surgery20, 21. The patients from project B who after inclusion have had spine surgery to relieve symptoms of lumbar spinal stenosis will be invited to come to the clinic for a follow-up three months after surgery. At follow-up we will repeat the accelerometer measures, walk test, and questionnaires performed in project B. This will enable us to test correlation between change scores in accelerometer measures, walk test and questionnaires and thereby determine whether the accelerometer measures can detect change after surgery.

Part II Project D- Physical activity and lumbar spinal stenosis The raw accelerometer data collected from patients with lumbar spinal stenosis in project B will be used for the purpose stated in project B, as well as to quantify the amount of time spent standing, walking, cycling, and sitting/lying down.

Project E- Physical activity and low back pain One-hundred-and-ten patients with low back pain from chiropractic clinics will be included. The patient will be invited to participate by their chiropractor as part of their visit to the clinic. Clinic personnel will place an accelerometer on the thigh of the patient on the day of inclusion. The patient will be instructed to wear the accelerometer for seven days before returning it to the clinic. Upon return, clinic personnel will download the raw accelerometer data from the accelerometer and upload it to a research database. Questionnaires on pain, function, life quality, and clinical data will be sent to the patient electronically. The chiropractic clinic will be financially compensated for their involvement. The uploaded raw accelerometer data will be analyzed to determine the amount of time spent standing, walking, cycling, and sitting/lying down per day.

Project F- Comparison to background population We will seek to compare the physical activity of patients to individuals 60 years of age or more from the Lolland-Falster Health Study. Participants in the Lolland-Falster Health Study have been randomly selected from the population of Lolland-Falster and have had accelerometer-data collected during every-day life using the same brand accelerometer, Axivity, as in the other parts of this protocol. Data on the participants will be requested from the Lolland-Falster Health Study Steering Committee.

Study population The study will include two study populations from the Region of Southern Denmark. The first population consists of 125 patients with LSS referred from primary or secondary care to the Spine Centre of Southern Denmark, Middelfart. Lumbar spinal stenosis is to be diagnosed via clinical examination and MRI, with pain when walking and relief of pain upon sitting down (neurogenic claudication) with positive answers to a set of six items characteristic to lumbar spinal stenosis22.

The second population consists of 110 patients from chiropractic clinics. The patients suffer from low back pain, with or without radiating pain to the legs.

In addition to their diagnosis, the following eligibility criteria apply to both study populations:

Inclusion criteria:

Age 60 or above. Fluent in Danish.

Exclusion criteria:

Other disease that limit physical activity rather than the patient's spine disorder, such as severe cardiopulmonary diseases; vascular claudication; recent operation or fracture of the spine, pelvis or leg; hip or knee arthrosis (not efficiently treated by hip/knee replacement); systemic muscular diseases; severely impaired vision; wheelchair use; disabling systemic disease.

Dementia. Accelerometry The accelerometer used in this study will be Axivity AX6 and AX3, which has been shown to be valid and accurate with step detection in healthy adults23, 24. The Axivity AX6 is small (2 x 3 x 1 cm), lightweight, offers access to raw accelerometer data, and will be fastened to the skin using a hypo-allergic band-aid. The accelerometer is waterproof and the battery will keep for the full week, and consequently patients do not need to attend to it but can go about their daily lives as they usually would. The algorithm used to detect physical activity will be the method developed by Skotte et al8, and the step detection algorithm developed in this project is a modified version of the algorithm proposed by Hickey et al25. Monitoring will be planned not to take place during larger activities not usually part of their habitual routines, such as trips to foreign countries or holidays.

Sample Size and Statistical Analysis Sample size in project A was 30 patients since this is the recommended number when developing algorithms26 and was sufficient to show a statistically significant two-tailed correlation of 0.5 or higher.

Correlation between questionnaires of pain and function (The Oswestry Disability Index, The ODI) and accelerometer measured step count and continuous walking has been shown to range from around 0.3 to 0.5. Walking tests have been shown to correlate above 0.5 with the ODI27. A sample size of 85 patients is needed to show a correlation of 0.3 or higher as significantly different from 0, with p<0.05 and power of 80%. Therefore, when testing hypotheses of relations between measurements in project B, with ten extra patients to account for drop-outs and missing data, the sample size will be 95.

97 patients from chiropractic clinics will be sufficient to calculate measures that are 95% likely to lie within ten percent of the true population value. An extra 13 patients will be included to account for drop-outs and missing data.

Physical activity will be described by the number of minutes spent in the categories of standing, walking, cycling, and sitting/lying.

Description and statistical analysis of data will be made using the R software. Parametric tests of correlation and difference between means will be used if data are described as normally distributed or following a t-distribution. Ordinal data or data not described as normally distributed will be analyzed using non-parametric statistics.

Facilities and Organization Data will be collected from both private chiropractic practice and the Spine Centre of Southern Denmark, Lillebælt Hospital, Middelfart, where more than 1000 patients are diagnosed with lumbar spinal stenosis each year. Approximately 300 of these undergo surgery for the condition.

Ph.D. student Malin Eleonora av Kák Gustafsson, M.D., will be conducting the study as principal investigator. Malin Eleonora av Kák Gustafsson is part of the spine clinic team in Middelfart and will be responsible for the inclusion of participants, data gathering and statistical analyses. The Ph.D. student will administer the walk test in patients with lumbar spinal stenosis. A research assistant and secretary at the spine center will assist in scheduling patient appointments, gathering questionnaires and accelerometers, and provide support to chiropractor clinics.

The main supervisor is Søren O´Neill, Assoc. Professor, Ph.D., M.Rehab. He is head of research at the Spine Centre of Southern Denmark and has several years of experience in supervising Ph.D. students and performing clinical research in spine diseases.

Co-supervisors are Niels Wedderkopp, M.D., Clinical Professor, Ph.D., Jan Christian Brønd, MSc, postdoc, PhD and Berit Schiøttz-Christensen M.D., professor, Ph.D. Niels Wedderkopp contributes with extensive knowledge on applying and interpreting accelerometer monitoring in clinical research and many years of experience in planning and executing methodologically sound clinical research and work with patients with musculoskeletal degenerative disorders.

Jan Christian Brønd is a postdoc focusing on developing accelerometer measurements of physical activity. He has an engineering background and more than 20 years of experience in software development, and a PhD in health sciences. Jan Christian Brønd will be developing and optimizing the model in phase A.

Berit Schiøttz-Christensen provides the project with a thorough insight into low back pain and spinal stenosis in the primary and secondary sectors and ensures a clinically relevant approach for the measurement method.

Timeline The study will take three years to complete and is planned to finish in October 2023. Project A is finished. The inclusion of patients in project B and follow-up as described in project C is ongoing and will be finished in February 2023. Forty-two of the 95 patients in project B have been included. The inclusion of patients in chiropractic care is planned to start in August 2022 and be completed in March 2023. The last months are reserved for data analysis, publication of articles, dissemination, and Ph.D. thesis.

Ethics and Approvals The study will be conducted in accordance with the Helsinki-II declaration and principles of oral and written consent. Part I of the study has been presented to the Ethical Committees of the Region of Southern Denmark, who has decided that there is no obligation to notify the committees of this project. We expect their assessment regarding the patients in chiropractic care to be in hand in March 2022. Information on all processing of personal data in this project will be added to the records of the Region of Southern Denmark according to the GDPR article 30.

Expected Outcomes of the Study and Clinical Relevance We expect the accelerometer measure to be a feasible and valid measure of physical activity in daily living, including walking activity. The measure is expected to be sensitive enough to detect changes over time, helping patients and caregivers evaluate treatments, stay tuned, and put in extra effort when needed. The method will be well described and accessible for all interested parties, ready for incorporation into user-friendly, self-administered applications. Furthermore, the accelerometer method is expected to stimulate further research into its diagnostic possibilities and prognostic uses.