Impact of a Bike Fitting Assessment and Interventions by a Physiotherapist in Recreational Cyclists With Knee Pain.

Background With the COVID-19 pandemic, cycling became more popular in many Western countries including Canada. Despite all its health benefits, cycling is often associated with non-traumatic injuries. Among these, knee pain represents one of the most prevalent injuries that leads to stop cycling and to seek medical assistance. Knee pain can be due to changes in cycling parameters and/or positioning on the bicycle.

Bike fitting was first destined to the professional cyclist and has really taken off in the glorious years of Lance Armstrong in the 1990s. In the 2000s, with the increase in popularity of recreational cycling, the access to a bike fit became more accessible for the population and is commonly used to decrease pain, discomfort and fatigue while cycling. Howsoever, the bike fit done in clinics by a physiotherapist is quite new. During these sessions, the physiotherapist will assess the cyclist's physical condition and capacity, training habits and fitting on the bike. In terms of interventions, the physiotherapist will optimize the cyclist position on the bike, while providing education and prescribe exercises when indicated.

Since 2015, the Physiovélo clinic has been a pioneer in the care of cyclists in physiotherapy in Quebec. Through constant growth over the past few years, the clinic served more than 1000 cyclists in 2021. Our physiotherapy service is distinguished by the evaluation and cycling positioning that allow patients to be received with their own bike in order to address cycling pathologies at the source by ensuring optimal adjustments on the bike.

However, the clinical efficacy of a bike fit among cyclists with knee pain has yet to be formally evaluated.

Objectives and Hypothesis The aim of this proposal is to prospectively describe physiotherapy care (bike fit, education and exercises) and evaluate change in knee-related pain and disability among recreational cyclists with knee pain.

Our hypothesis is that significant improvement in knee-related pain and disability will be observed at 1 and 3 months after physiotherapy care (including a bike fit) among recreational cyclists.

Methods Study design Prospective observational longitudinal study. Study settings This study will take place at Physiovélo, a physiotherapy clinic specialized in bike fitting and in the assessment of cyclists with musculoskeletal disorders located in Longueuil, QC. Three physiotherapists with certification ranging from BikePT bronze to gold are currently working at Physiovélo. They assess more than 1000 cyclists per year, in which about a third are presenting for knee pain.

Physiovélo is already fully equipped to address cyclists' problems on the bike and outside the bike. There is a vast inventory of bike parts and tools to ensure a complete optimization of the bike at the end of the bike fit. There are also two different platforms with home trainers that permit the physiotherapist to work in an efficient and ergonomic position. Those platforms are equipped with a dynamic balance system, specially developed for bike fit at Physiovélo. This device permits the evaluation of the center of mass of the cyclist in correlation with the center of mass of the bike.

Participants Consecutive cyclists with knee pain while cycling consulting for a BikeFit at Physiovélo for the first time. To be included, cyclists must be at least 18 years old, be legally able to consent and understand and speak French or English.

Data collection Prior to being assessed, eligible participants will answer a questionnaire covering sociodemographic characteristics, cycling data such as cycling distance, frequency per week and mean cadence and knee-related pain and disability questionnaires. Cycling data (distance, frequency and mean cadence), treatment compliance, cointerventions and knee-related pain and disability outcomes will also be collected at 4 and 12 weeks after the assessment. Based on their initial assessment, the physiotherapist will complete a standardized form indicating their diagnoses and treatment plan in terms of bike adjustment, education, advice, exercises, and other relevant physiotherapy interventions. All data will be collected through the Centre de Recherche de l'Hôpital Maisonneuve-Rosemont (CRHMR) REDCap data collection portal which uses a Transport Layer Security (SLL/TLS) encryption to secure data. For participants who prefer to fill out the questionnaires in a paper format, the results will be transcribed into the REDCap data collection portal by a member of the research team.

Outcome measures The primary outcomes will be worst, least, and average knee pain during the last bike ride as measured with the numerical pain rating scale (NPRS, 0-10). As secondary outcomes, current knee pain will be measured with the NPRS, disability will be measured with the Knee Outcome Survey of the Activities of Daily Living Scale (KOS-ADLS) which is valid, reliable and translated in French. A modified version of the Knee Outcome Survey Sports Activities Scale (KOS-SAS), The KOS-SAS will be modified and adapted to cyclists, including questions on pain and pain-related disability during cycling. It will be translated in French in a back-translation method. A 11-point Global Rating of Change (GRoC) score will also be used to measure global perceived imporvement. The MCID for a 11-point GRoC is 2 points. Satisfaction with care will be measured with the visit-specific satisfaction questionnaire (VSQ-9). Adverse events related to the interventions will be collected.

Statistical analyses A repeated measure ANOVA will be used to determine whether outcomes differ across time points (baseline, 4 and 12 weeks). Sphericity will be tested with Mauchly's test. If sphericity is rejected (variances of the difference are not equal), correction will be used to determine if repeated measures ANOVA test is statistically significant. Multiple regression will be performed to assess the impact of independent variables (sociodemographic characteristics, physiotherapy care, treatment compliance, cointerventions and cycling data) on dependent variables (pain and disability). Alpha levels will be set at 0.05. All analyses will be carried out using the SPSS software (IBM Corp. Released 2021. IBM SPSS Statistics for Windows, Version 27.0) and the Excel software (Microsoft Corporation. 2018. Microsoft Excel for Windows).

Sample Size The sample size required is based on the primary outcome measure, the NPRS. The NPRS has an estimated minimum clinically important difference of 1.5 points, and an estimated SD of 3 points, which correspond to an half a SD effect size. The considered parameters are 0.05 for a type I error (α) with a power of 0.80 (1-β). For an analysis of variance (ANOVA) two-sided, the sample size required is 70 participants. This sample also accounts for a potential 10% loss to follow up at 12 weeks. Sample size calculation was performed with the Excel software using the sample size formula as described by Zhong.

Ethics, Consent and Confidentiality Ethics approval will be obtained from the Comité d'éthique de la recherche du CIUSS de l'Est-de-l'Île-de-Montréal. Participants will need to sign the information and consent form before enrollment in the project. The information and consent form will be presented and electronically signed on the REDCap platform. Electronic and multimedia elements including an explanatory video, dictionary and glossary will be available on the REDCap platform to support participants in the consent process. Members of the research team will be available to discuss with the participants on the phone if needed. Paper version of the information and consent form will also be available for participants who do not have access to a computer or for participants who prefer the paper version. In these circumstances, the information and consent form will be presented to each participant on the phone and will be sent by mail. Participants will need to return the signed consent page by mail. Nominal data will be kept in an electronic file protected by a password and separately from all other data. Participants will be attributed an identification code. Data will be encrypted and only the members of the research team whose functions require access to this information will be allowed access. All research personnel will sign confidentiality agreements.