5 May
OA affects 20% of all dogs older than one year of age and financial costs for owners treating their pets with OA are significant. The veterinary profession – individually and collectively – has a responsibility to ensure the treatment we recommend is effective, but yet we still don’t purposefully review our OA patients as often as we should.
One author speaking in 2012 stated: “The need for objective outcome measures in veterinary physiotherapy and orthopaedics is flagrant”(Hyytiäinen et al, 2012). Have we improved this element of our care over the past 10 years, or do we still too much rely on unreliable clinical impressions and subjective assessments?
This article will seek to outline some of the current means for reviewing our OA patients and give insight into some innovative technologies that could play a part in us improving OA management.
The need to develop a comprehensive management plan for our OA patients – with the aim of managing pain, discomfort and seeking to modify disease progression – is gaining increased acceptance. Such plans involve modifications to diet, lifestyle, exercise and elements of rehabilitation, as well as medical pain management (Figure 1).
Owner education and “on-boarding” are also key steps for treating OA patients, as they are for any chronic disease requiring long-term care.
The choice of pain management medications has expanded significantly in the past 10 to 15 years and we have recently seen the launch of a number of innovative products such as anti-nerve growth factor and a recently licensed stem-cell therapy – both step changes in the medications licensed for treating OA patients. Great choice, but with all treatments we need to know they have desired impact, not only claims.
Despite having multimodal management plans for OA patients, an insufficient uptake still exists for properly reviewing or “following up” our OA patients. This may be due to various reasons Panel 1.
This results in many OA patients still being told to “get in touch if things change”, or being partially reassessed during medication reviews rather than during prescheduled OA management reviews.
This leaves the responsibility on monitoring and managing OA to owners, rather than leading it as a veterinary team. Undoubted scope exists to improve this element of OA management through a collaborative, team approach, and this has been outlined more comprehensively in previous articles (Allan and Carmichael, 2020a; b).
Clinical metrology instruments (CMIs) have been developed as a means of assessing OA and are currently the most commonly used means of assessing OA patient progress. These use a series of questions, answered based on the observations or experiences of the person completing to give an overall “patient score”.
At least six CMIs are reported for measuring the severity of OA in dogs, with Liverpool Osteoarthritis in Dogs, Canine Brief Pain Inventory and the Helsinki Chronic Pain Index being among the most frequently used (Walton et al, 2013; Muller et al, 2016).
The limitations of CMIs, as well as their advantages, are recognised. Would objective OA assessment be better? Is this as it seems?
Many techniques have been described for objectively assessing osteoarthritic patients, enabling data to be collected and reviewed at the time of OA patient review. Some are easier to perform in practice and more likely to give reliable results (Table 1).
| Table 1. In-clinic objective assessment tools – each with advantages and disadvantages in clinical use | ||
|---|---|---|
| OA objective clinical assessment tools | Advantages | Disadvantages |
| Goniometry | Inexpensive and quick to perform | Difficulty in reliably reproducing identical assessment of joints |
| Limb circumference | Inexpensive and works well alongside goniometry | Similar to goniometry although landmarks can be used, identical reassessment is difficult |
| Kinetic data | Accuracy of measurements, often viewed as “gold standard” | Expensive, time consuming and technically challenging There is evidence that pain may have improved but peak-vertical force may not have, i.e. the objective assessment might not correlate with patient experience |
| Quadruped stance analyser | Quick and simple to use | Not all patients will comply Some difficulty in drawing strong opinions from data |
Goniometry has been shown to be a simple, cost-effective and non-invasive means of assessing joint angles to objectively assess joint function (Clarke et al, 2020). These can be simple handheld and/or adapted to use x-rays, photos and videos. Normal goniometric angles of key joints have also been described for various breeds (Clarke et al, 2020).
Limb circumference measurements to assess muscle volume is also easily performed in-clinic, and with muscle atrophy being shown to be correlated to joint pain in dogs, this can be a simple technique to assess status.
While kinetic data, such as ground reaction forces, are recognised as the gold standard for objective assessment of lameness and response to treatment, the complexity of capturing this data means they are not really suitable for use in clinical practice (Adrian and Brown, 2022).
Pressure-sensitive walkways have been developed – which could, in theory, be used in clinic – but some trials have shown significant overlap when comparing ground reaction forces measured in dogs with OA compared to clinically healthy dogs, meaning this method for diagnostic purposes in dogs with OA cannot currently be recommended (Nielsen et al, 2020). Pressure-sensitive walkways might be better suited to monitoring patients, but the costs and complexity of use means they are unlikely to enter clinics soon.
A computerised, quadruped stance analyser has been developed to assess static load-bearing and bathroom scales have also been shown to be a reliable, simple and cost-effective method for objectively measuring static weight-bearing, which could be used as an outcome measure when rehabilitating dogs with osteoarthritic changes in the hindlimbs (Hyytiäinen et al, 2012).
All of these techniques for capturing objective data still have challenges – could technology be the answer?
The global market for human wearable devices is projected to reach almost 180 million units by the end of 2023 and more than half of people purchasing a smart watch say physical health is their main reason to do so (UK Wearable Technology Market Report, 2021).
Current human wearable devices provide continuous measurements of a user’s pulse, motion and movement, and publications describe the growing support within human health care to use wearable technologies to enhance current OA management (Panel 2; Papi et al, 2016).
Using the data collected, scope exists for software algorithms to start to inform on disease management. A recent HMGOV publication stated that “digital medicine, artificial intelligence [AI] and robotics could significantly change the roles and functions of clinical staff by 2040, delivering improvements in patient care, labour productivity of health care staff and reduced costs” (Government Office for Science, 2021).
The use of wearable technology might also enable the monitoring of OA progression and potentially give scope to deliver more targeted therapy earlier in the disease procress (Holeka et al, 2022). Additionally, in humans, capturing gait kinematics using wearables has a large potential for use in clinical trials, and for monitoring treatment success in patients with knee or hip OA, and this could be a major advancement in research on musculoskeletal diseases (Nüesch et al, 2021).
While the variation in veterinary patient size will be challenge for software algorithms giving “results”, it is likely that, in time, systems will be developed for veterinary patients that give objective data not only of general activity levels, but also for of specific motion patterns, potentially adding to our ways of “measuring” OA.
For our veterinary patients, this continuous passive data collection with scope to assess longer-term “trends” could add another means of monitoring patients, and being objective – based on the patient’s own data outwith the consult room – would also reduce clinical bias when interpreting the owners’ history.
It is worth outlining at this point the difference between a medical device and the “wearable” wellness many of us own, such as a Fitbit, Garmin watch or other personal trackers. We may draw conclusions from their results, but limitations exist.
Medical devices are very different. The current wearable medical device that we might be familiar with in veterinary patients is the Holter monitor.
This is used for cardiology arrhythmias, where the data received and reported has been validated as being accurate enough to make clinical decisions.
In human health, medical device use is tightly regulated and controlled; the regulations for similar use in veterinary patients less so.
Attached to the collar, pet wearables use an accelerometer to track daily activity levels, sleep and estimate calories burned, with the results based on software algorithms and bodyweight. GPS data is collected on some devices, but results in more rapid battery use (Figure 2).
Of the over 20 pet wearables currently available to consumers, some are validated to Actical – an accelerometer that itself is validated as accurate as a measure of activity and distance moved in dogs (Belda et al, 2018). but many have not.
The scope for diagnostic and therapeutic monitoring is also still very much in its infancy. The “health data” captured is reliant on algorithms, and these are the closely guarded intellectual property of the device manufacturers.
None of these algorithms have yet been validated and published in dogs (Johnson et al, 2022) – in part likely due to the high costs of performing research and development studies, and time required to perform and publish such studies.
Despite this lack of published data, claims of health “benefits” are starting to appear. One manufacturer stated its device could “catch potential health issues before they become problems… analyses licking, scratching, drinking and sleeping week over week to alert you to any abnormalities”(Whistle, 2023), while another states “Felcana Go tracks and stores data of your pet’s individual activity, which you may not always observe” (Companion Animal Health, 2023).
It is in this area where a need exists for the profession to learn more. As we become wrapped in the “internet of things”, health data will have an increasing relevance and value. The ability to collect, assess this data, identify trends and link it to clinical patterns or presentation will be attractive.
But questions will surround who owns it, what it means and to whom it has the most value. Technology is only of value if it does truly improve patient care. Can pet wearable technology companies develop their products and evidence to demonstrate they meet a clinical need?
One fascinating element of wearable technology that could likely benefit our veterinary patients is compliance – were our recommendations followed?
Wearable technologies would allow review of pets’ actual activity levels and exercise type. It is likely that owners being able to “see” this data would improve their compliance with our management plans. In the simplest form, “10 minutes’ walk 3 times a day” is something owners and vets would be able to visualise and review.
For clinicians in practice, this is a reason that, while still in their infancy, wearable technologies could have true impacts, improving compliance and owner engagement (Papi et al, 2016).
Wearables alone will not be a panacea for OA management, but trends in objective data (such as movement type, time and activity levels) will be of benefit viewed over weeks, months and years. This could be useful to follow the waxing and waning progress of OA.
However, a key risk is what clinical staff want, and what devices offer. With a collective desire for an “accurate update” on patient progress (“traffic light” or similar) it is essential that algorithms give us the results we require. These results must be reliable and accurate for the patient, and not only suit devices. This is likely to be a topic that will require careful assessment by the profession and ongoing review should wearable devices with clinical claims come into regular use.
Another concern is that wearable devices alone would miss the mark in what could be titled the “holistic care” of OA patients. Subjective feedback from owners, their perception of how their pet “feels” and some behavioural changes are still of value. There will still be reasons to collect CMI and “soft” or more subjective data.
The earlier route of adoption for wearable technology might be for use as an OA screening tool – perhaps using AI to identify changes in activity levels or patterns before owners are aware.
Some current devices already assess “scratching” and sleeping trends, and the latter may be an early means of assessing comfort that could be impacted by OA – this would seem a good starting point.
In clinical practice we all appreciate the clarity of biomarker objective data when speaking to owners.
A “high” or “normal” blood sample result gives us confidence to recommend a diagnostic or treatment plan to owners, and when repeated the reassurance that our treatment made a difference, or progressing as expected.
In OA, increasing awareness and research exists into biomarkers that could be a useful way of assessing patients and monitoring response to therapies. These could help predict the structural changes within joints, progression of pain/symptoms and monitor the effects of treatment at an individual level (Henrotin, 2022).
Another key aim is to uncover “pre-OA” biomarkers that may be present prior to irreversible joint disease and could enable earlier interventions, which may be able to reverse OA progression (Jones et al, 2022).
A future generation of wearable devices might also bridge the gap between biomarkers and wearable technology/medical devices, and be capable of giving quantitative real-time measurements of biomarkers in point of care settings.
These could be similar to some of the current wearable blood glucose monitors and enable continuous monitoring of patients’ OA biomarkers alerting owners and vets to changes in status.
While furry, “poorly sweating” patients might have technical challenges for wearable biomarker collection, it is entirely likely that wearable devices with scope to assess biomarkers will be developed.
These could collect activity and biomarker data – either via patches or microneedles (Brophy et al, 2021) – and process it via layered, complex algorithms, with the aim of giving objective data based not only on activity levels (accelerometer), but combined with biomarker data.
The trends in this data might be what helps us monitor many chronic diseases in decades to come.
Pre-scheduled reviews of our OA patients is a fundamental element of an OA management patient plan.
This article has sought to outline some of the tools we have for this review – now, but also provide an insight into new technologies might start to contribute to the “picture” we have of our patients as we accompany them on their OA journey.
While technology is likely to enable clinics to be presented with more objective data, and trends in status will undoubtedly be useful, fundamental requirements will be the validation of this data and the algorithms that process and present it to us.
For these reasons, the holistic review – encompassing subjective/CMI assessment, alongside objective data – will be important. Technology and objective data will not replace, but should be of additional value to complement the feedback we get from owners and our clinical assessment.
