Mobile health technologies to improve walking distance in people with intermittent claudication
Abstract
Objectives
This is a protocol for a Cochrane Review (intervention). The objectives are as follows:
To assess the effectiveness of mobile health technologies to improve walking distance in people with intermittent claudication.
Background
Description of the condition
Peripheral arterial disease (PAD) refers to the obstruction or narrowing of the large arteries of the lower limbs, most commonly caused by atheromatous plaque or thrombus. The resulting stenosis or occlusion, if severe enough, can result in impairment of oxygen supply to the muscle and other tissues during exercise that results in limiting symptoms. In more severe cases, blood flow becomes inadequate to meet the resting metabolic demands of the tissue resulting in ischaemic rest pain, ischaemic ulceration or gangrene. Although in many cases of less severe disease people can be asymptomatic, the major clinical manifestations of PAD are intermittent claudication (IC) and critical limb ischaemia (CLI) (Imparato 1975; McDaniel 1989). PAD is classified into five categories ranging from asymptomatic to ulceration or gangrene (or both) of the limb, as shown in Table 1 (Fontaine 1954). About 20% of people with PAD progress to suffer from IC according to Trans‐Atlantic Inter‐Society Consensus (TASC II) and the American College of Cardiology/American Heart Association (ACC/AHA). While a further 5% to 10% develop CLI and 1% to 2% progress to amputations (Norgren 2007).
| Stage | Description |
|---|---|
| I | Asymptomatic |
| II | Mild claudication pain |
| IIa | Claudication distance > 200 m |
| IIb | Claudication distance < 200 m |
| III | Rest pain (especially at night) |
| IV | Ulceration or gangrene (or both) of the limb |
PAD affects more than 236 million people globally and is the third most common atherosclerotic disease, after coronary artery disease and cerebrovascular arterial disease (Song 2019). PAD does not only cause limitation of activity, but it is considered an independent predictor of cardiovascular morbidity and mortality (Cacoub 2009). The major risk factors for PAD are the same as those for coronary artery disease, namely smoking, diabetes, dyslipidaemia and hypertension (Norgren 2007). People living with PAD are at increased risk of morbidity and mortality from cardiovascular events including myocardial infarction and stroke (Dormandy 1999; Fowkes 2008; Hooi 2004; Pande 2011).
IC is defined as an impairment in functional capacity due to lower extremity pain or discomfort on exertion, from which relief is generally gained by rest (Norgren 2007). Therefore, IC often causes restriction of movement in daily life (Imparato 1975; McDaniel 1989). There is an association between IC and reduction of quality of life (QoL) in people with PAD (Wu 2017), yet the most critical complication in people with PAD is amputation of the affected extremity, and there is a relation between decreasing pain‐free walking distance and further disease progression (Harwood 2016).
The overall incidence rate of IC is 6.4 per 1000 person‐years (Meijer 2002), with the prevalence of IC appearing to increase by age, from about 3% in people aged 40 years to 6% in people aged 60 years (Norgren 2007). A five‐year prognosis from TASC II estimated that 20% of PAD patients with IC were expected to develop non‐fatal cardiovascular events and have a mortality rate ranging between 10% and 15%, predominantly due to vascular causes (Norgren 2007). ACC/AHA guidelines published comparable predictions of non‐fatal cardiovascular events similar to the TASC II document during a five‐year period. However, ACC/AHA predicted a higher mortality rate (15% to 30%), with vascular complications again being the major cause of mortality (Gerhard‐Herman 2017).
Diagnosis and management
Guidelines addressing the diagnosis and management of PAD have been produced by several bodies, including the National Institute for Health and Care Excellence (NICE; NICE 2012), the American Heart Association (Gerhard‐Herman 2017; Rooke 2011), the European Society of Cardiology (ESC; Tendera 2011), and European Society for Vascular Surgery (Aboyans 2018); these organisations broadly agree on the overall diagnosis and management of PAD.
Following a thorough clinical history and physical examination of the lower limbs including the peripheral pulses, a diagnosis of PAD may be confirmed using the ankle brachial index (ABI; an ABI less than 0.90 is suggestive of PAD) or non‐invasive imaging (or both); Doppler ultrasound of the lower limbs can establish the extent of atherosclerosis, and magnetic resonance (MR) or computerised tomography (CT) angiography may be undertaken to provide additional information on the anatomy of stenosis or occlusion if required prior to revascularisation (NICE 2012; Rooke 2011; Tendera 2011).
Initial treatment of PAD for people with IC, involves reduction of cardiovascular risk factors (including the use of statins and antiplatelet medication), with the main aim of reducing the risk of other cardiovascular diseases including myocardial infarction and stroke (Gerhard‐Herman 2017; NICE 2012; Tendera 2011). Risk factor optimisation coupled with exercise programmes (Lane 2017; NICE 2012), and medical management (Gerhard‐Herman 2017; NICE 2012; Tendera 2011), help minimise the progression of IC towards CLI (Norgren 2007). Individuals with CLI are more urgently referred for possible revascularisation after thorough assessment by a vascular multidisciplinary team and adequate pain management (NICE 2012). Revascularisation procedures including angioplasty, stenting and bypass grafting may be required in people in whom disease is severe or does not improve with non‐surgical interventions (Antoniou 2017; Bachoo 2010; Samanci 2020). Finally, in people with disease that is not suitable for revascularisation procedures, or where there is established gangrene, amputation may be needed (NICE 2012).
Hospitalisation expenses of treatment represents a burden for people with PAD; this was estimated at USD 6.31 billion per year in 2014 (Kohn 2019). The mean annual expenditures per individual for people with PAD are higher by USD 7334 when compared to people without, this was contributed to growing prescribed medications, inpatient care and primary care expenditures (Scully 2018). This indicates that for people with PAD and the healthcare framework, avoiding hospitalisation and surgery through preventive intervention and management may have a financial benefit.
Description of the intervention
On various levels, attempting to engage people with IC in walking exercise interventions has been challenging. Supervised exercise programmes for people with IC, for example, have shown low levels of engagement and high attrition rates (Makris 2012). One systematic review identified the barriers to walking in people with IC in patient‐centred exercise programme; these included social (i.e. walking partner and family support), physical (i.e. walking limitation pain) and environmental (i.e. inclement weather and lack of/poor pavements) factors (Abaraogu 2018).
New communication technologies may be useful tools when it comes to promoting physical activity practice (Feter 2019; Romeo 2019; Silva 2020). As stated by Harries 2016, some minimal features made applications‐based interventions effective in increasing physical activity level in adults: applications running automatically, low financial investment (no additional devices are needed) and promotion of engagement through simple curiosity.
Improvements in technology and the popularity of smartphones, in combination with limited human and financial resources for healthcare, have caused a global increase in the use of mobile health technology among various fields of medicine (World 2011). Mobile health technology is defined as wireless devices and sensors that can be transmitted over the Internet or computer networks; such as, mobile phones, smartphones, tablets, short messaging services (SMS) or text messaging, specialised software applications and wearable technology (Kumar 2013). These devices are intended to be worn, carried or accessed by the person during normal daily activities. Mobile health technology applications are being developed and evaluated in various fields, including diabetes (Quinn 2011), obesity and physical activity (Bexelius 2010), smoking cessation (Ali 2012), stress management (Plarre 2011), and depression treatment (Burns 2011).
Advanced technological features, most notably their connection to the Internet, global positioning systems and inbuilt accelerometers are essential features of mobile health technology (Wu 2012). Furthermore, personalised and interactive apps, which gather and analyse real‐time data, can be installed in these devices (Riley 2011). Some studies have investigated if physical activity can be reinforced via mobile health technology. Bittel and colleagues concluded that "Apps running on smartphones can be used to improve exercise performance to better match the prescription provided by the therapist or physician, thereby improving therapeutic benefit" (Bittel 2017). Similarly, one systemic review of 15 studies concluded that using smartphone apps can improve physical activity (moderate effect size) (Coughlin 2016).
How the intervention might work
There are challenges associated with implementing conservative management of people with PAD. First, the availability of resources for supervised exercise programme is uncommon (Harwood 2017; McDermott 1997; Welten 2008). In comparison to people with coronary artery disease, people with PAD are relatively under‐supported and poorly resourced (McDermott 1997; Welten 2008). Second, adherence by people with PAD to recommended guidelines in terms of physical activity is generally poor (Duscha 2018; Hageman 2018). For example, people with comorbidities that limit mobility may find it difficult to engage in exercise. Poor adherence is not only common to people with PAD but also prevalent among treating physicians who do not regularly follow up on progress of the physical activity of the patients (Reinecke 2015). As people with PAD have the financial burden of increased expenditures and contribute to the overall healthcare framework cost, providing a remote system with the potential to improve their symptoms and avoid disease progression and hospitalisation has the potential to alleviate this financial burden.
The use of remote exercise, such as mobile health‐related technology, may result in increasing the potential of accessing supervised exercise, as well as decreasing the requirement for personnel and institutional resources. Mobile health‐related technologies have the potential to solve the current dilemma of low adherence and inadequate infrastructure through focusing on personalised mobile health, promoting health education and adjusting patients' health‐related behaviour (Argent 2018; Burke 2015; Kostkova 2015). The self‐monitoring features of these devices (i.e. feedback on performance, prompt specific goal setting and providing contingent rewards) is the primary reason for patients to be highly engaged with performing the targeted activity (Middelweerd 2014). Some remote technologies enable patients to be observed or supervised by a practitioner, allowing the patient to participate in a supervised workout programme while exercising remotely in their own environment (Harzand 2020). Furthermore, remote healthcare monitoring enables patients to remain at home instead of staying in costly healthcare facilities (i.e. hospitals and nursing homes), which provides a more efficient and cost‐effective option than on‐site clinical monitoring (Deen 2015).
Why it is important to do this review
Exercise therapy is acknowledged to be an important part of the rehabilitation process for people with IC (Fakhry 2012). Supervised exercise is an effective option for conservative management of PAD. The ideal programme recommendations are 30 to 60 minutes per exercise session for a minimum of three times per week for three to six months (Fakhry 2012; Gerhard‐Herman 2017; Parmenter 2013; Treat‐Jacobson 2019). Supervised exercise improves blood flow in the extremities via dilation of arterioles and changes in microcirculation and endothelial function, which results in improved pain‐free walking distance, overall functional status and health‐related quality of life (HRQoL) in people with symptomatic PAD (Lane 2017; McDermott 2017; Parmenter 2013).
There is no Cochrane systematic review evaluating the effectiveness of mobile health technologies to improve walking distance in people with IC. In this systematic review, we aim to evaluate the effectiveness of these mobile health technologies to improve walking distance. Mobile technologies could be either assessed by self‐reporting or by outcome assessment. This review will enable clinicians, patient groups, educators, policymakers and funding bodies to make informed decisions on whether mobile health technologies can improve walking distance in people with IC compared to the conventional approach of exercise advice. There are several guidelines that will likely be influenced by this review including the Society for Vascular Surgery (SVS) (Conte 2015), the American College of Cardiology Foundation (ACCF) (Gerhard‐Herman 2017), the National Institute of Health, ESC (Halliday 2018), and NICE (NICE 2012), as well as practice within local and regional Health Services Executives (HSE) and advocacy groups.
Objectives
To assess the effectiveness of mobile health technologies to improve walking distance in people with intermittent claudication.
Methods
Criteria for considering studies for this review
Types of studies
We will include randomised controlled trials (RCTs). We will include cluster‐randomised, quasi‐randomised trials and cross‐over trials. For cross‐over trials, we will only include the first exposure period (and the washout period must meet the minimum requirement of the follow‐up period).
Types of participants
We will include people aged 18 years or greater with symptomatic PAD and a clinical diagnosis of IC. IC is defined as muscular discomfort in the lower extremities, which is induced by exertion and relieved by rest within 10 minutes (Norgren 2007). Participants will be classified as Fontaine IIa and IIb (Fontaine 1954). PAD will be diagnosed using one or more of the following approaches: ABI less than 0.90 in at least one lower extremity; toe‐brachial index less than 0.60; evidence of arterial occlusive disease in one lower extremity detected by duplex ultrasonography, CT angiography, or MR angiography (Norgren 2007). Clinical evaluation of Fontaine classification (Fontaine 1954) will be based on the clinical history and examination as per the investigator. We will exclude asymptomatic people (Fontaine I) and people with CLI (Fontaine III and IV) (Fontaine 1954). We will exclude people with comorbidities that limit mobility; for example, metabolic dysregulation disorders, skeletal muscle atrophy, particular levels of sarcopenia, histories of hip fracture and osteoporosis. If a trial includes participants with PAD without specifying if the person is diagnosed with IC or CLI, then we will contact the study authors, and include the study if the majority of the participants had IC.
Types of interventions
We will include RCTs evaluating the effectiveness of mobile health technology interventions to improve walking distance for people with PAD with a clinical diagnosis of IC compared to no intervention, exercise advice or supervised exercise programmes.
Mobile health technology interventions may include the following approaches:
-
mobile health applications that remotely monitor participant's activity either in form of mobile phone apps or wearable technology. Participant's activity could be either self‐monitored or remotely monitored by a practitioner;
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remotely monitored exercise programmes through either telephone or SMS or text communication between the participant and the investigator. This can include studies where participants report their physical activity or studies that only involve reminders to engage in physical activity.
We will compare mobile health technologies to:
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no intervention;
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exercise advice: participants are verbally advised by their clinician to maintain at least 30 minutes per day, five days per week of moderate‐intensity physical activity or 15 minutes per day, five days per week of vigorous intensity physical activity (Piepoli 2016), without the exercise advice being monitored. We will include studies where the comparator includes any level of exercise advice or if the advice was delivered verbally, by a leaflet or provision of literature. We will include studies regardless of if the advice included information on stopping periods for recovery or not;
-
supervised exercise programmes: any exercise programme where the participant is physically observed and monitored by a professional individual while preforming the exercise; and followed up on regular basis (Guidon 2013), aside from any mobile health technology intervention.
As these participants have documented PAD, we would expect that they will be receiving medical therapy (i.e. statins and antiplatelet therapy). We will include studies that confirm that all participants involved in the intervention and comparator arms were on similar medical therapy regimens. If this is not explicitly documented, we will contact the study authors to confirm. We will exclude any studies where there is a discrepancy in medical therapy regimen between intervention and comparator arms. Similarly, we will only include studies that involve adjunct interventions if the adjunct intervention is identical in both the intervention and comparator.
The minimal period for the duration of the intervention will be at least 12 weeks as in various supervised exercise trials on people with PAD (Duscha 2018; Gardner 2011; Harwood 2016).
We will stratify the main analyses for the following comparisons, to address heterogeneity and aid interpretation of findings.
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Mobile health applications versus no intervention.
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Mobile health applications versus exercise advice.
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Mobile health applications versus supervised exercised programme.
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Remotely monitored exercise programmes versus no intervention.
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Remotely monitored exercise programmes versus exercise advice.
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Remotely monitored exercise programmes versus supervised exercised programme.
Types of outcome measures
Follow‐up periods of interest will be divided to the following categories.
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Short follow‐up: trials with up to three months' follow‐up.
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Medium follow‐up: trials from three months' to one year' follow‐up.
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Long follow‐up: trials from one year' to five years' follow‐up.
Primary outcomes
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Change in absolute walking distance from baseline. This will be assessed at the end of the intervention. If sufficient data are available, we will report this outcome at short, medium and long follow‐up time points. Absolute walking distance is defined as the distance walked when claudication pain becomes so severe that the person is forced to stop (Gardner 2001). This will be measured by objective methods that are included by the study authors, for example (and not limited to) treadmill test, 6‐minute walking test and shuttle test.
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Change in claudication distance from baseline. This will be assessed at the end of the intervention. If sufficient data are available, we will report this outcome at short, medium and long follow‐up time points. Claudication distance is defined as the distance walked to the onset of claudication pain (Gardner 2001). This will be measured by objective methods that are included by the study authors, for example (and not limited to) treadmill test, 6‐minute walking test and shuttle test.
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Amputation‐free survival: defined as time spent free from any major above‐ amputation (Stoner 2016). This will be reported at follow‐up time points.
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Revascularisation‐free survival: defined as time free from any revascularisation procedure regardless of type of procedure (i.e. endovascular intervention or an open surgery) (Stoner 2016). This will be reported at follow‐up time points.
Secondary outcomes
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Major adverse cardiovascular events (MACE): defined as any major cardiovascular event such as myocardial infarction, cerebrovascular accident or death (Stoner 2016). This will be assessed at the end of the intervention and at short, medium and long follow‐up time points.
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Major adverse limb events (MALE): defined as any major amputation or revascularisation procedure (Stoner 2016). This will be assessed at the end of the intervention and short, medium and long follow‐up periods.
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Above‐ankle amputation: defined as above‐ankle amputation of affected limb (Stoner 2016). This will be reported at the end of the intervention and short, medium and long follow‐up periods.
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Quality of life (QoL): assessed using a HRQoL tool such as EQ‐5D, VascuQoL, 36‐item Short Form (SF‐36) health questionnaires, or Dartmouth Co‐operative Information Project (COOP) measure (Dyer 2010; Streiner 2015). This will be assessed at the end of the intervention. If sufficient data are available, we will report on this outcome at short, medium and long follow‐up periods.
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Adverse events: assessed as number of participants with at least one adverse event and individual adverse events, defined by the authors of the included trials. This will be assessed at the end of the intervention. If sufficient data are available, we will report on this outcome at short, medium and long follow‐up periods.
Search methods for identification of studies
Electronic searches
The Cochrane Vascular Information Specialist aims to identify all relevant RCTs regardless of language or publication status (published, unpublished, in press or in progress).
The Information Specialist will search the following databases for relevant trials:
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Cochrane Vascular Specialised Register via the Cochrane Register of Studies (CRS‐Web);
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Cochrane Central Register of Controlled Trials (CENTRAL) via the Cochrane Register of Studies Online (CRSO);
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MEDLINE (Ovid MEDLINE Epub Ahead of Print, In‐Process & Other Non‐Indexed Citations, Ovid MEDLINE Daily and Ovid MEDLINE) (1946 onwards);
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Embase Ovid (from 1974 onwards);
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CINAHL Ebsco (from 1982 onwards).
The Information Specialist has devised a draft search strategy for RCTs for MEDLINE, which is displayed in Appendix 1. This will be the basis for search strategies for the other databases listed.
The Information Specialist will search the following trials registries:
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World Health Organization International Clinical Trials Registry Platform (who.int/trialsearch);
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ClinicalTrials.gov (clinicaltrials.gov).
Searching other resources
We will check reference lists of all relevant primary studies and review articles for additional references. We will examine any relevant retraction statements and errata for included studies. We will search OpenGrey for unpublished studies. We will perform citation searches on key articles. We will contact experts in the field for information of unpublished and ongoing trials.
Data collection and analysis
Selection of studies
Two review authors (ME and DD) will independently screen all titles and abstracts identified via searches to identify those that might meet the review inclusion criteria. We will retrieve the full text of studies identified as potentially relevant by at least one review author. The same review authors will independently screen full‐text articles for inclusion or exclusion. We will resolve disagreements by discussion, or if necessary, we will consult a third review author (WT). We will list all studies excluded at the full‐text review stage and provide reasons for their exclusion in the 'Characteristics of excluded studies' table. We will depict the screening and selection process in an adapted PRISMA flowchart (Liberati 2009).
Where studies have multiple publications, we will collate the reports of the same study so that each study, rather than each report, is the unit of interest for the review, and such studies have a single identifier with multiple references.
Data extraction and management
Two review authors (ME and DD) will independently extract data from eligible studies using an adapted data extraction form provided by Cochrane Vascular. We will resolve disagreements by discussion, or, if necessary, we will consult with a third review author (WT). One review author (ME) will enter all extracted data into Review Manager 5 (Review Manager 2020), and a second review author (DD) will check entered data for accuracy and consistency against the data extraction sheets. We will record the following information in a 'Characteristics of included studies' table.
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Methods (study design, number participants, exclusions after randomisation, losses to follow‐up, intention‐to‐treat analysis, duration of study).
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Diagnosis of IC.
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Demographic characteristics of participants (country, setting, age, ethnicity, sex, inclusion and exclusion criteria).
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Types of interventions and comparators. We will list all treatment groups even if they are not used in the review.
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Outcomes reported.
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Funding sources and declaration of interest of the study authors.
Assessment of risk of bias in included studies
Two review authors (ME and DD) will independently assess the risk of bias of all included studies using Cochrane's risk of bias tool, described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We will judge the risk of bias in the following seven domains to be low, high or unclear.
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Random sequence generation (selection bias).
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Allocation concealment (selection bias).
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Blinding of participants and personnel (performance bias).
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Blinding of outcome assessors (detection bias).
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Incomplete outcome data (attrition bias).
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Selective outcome reporting (reporting bias).
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Other sources of bias.
We will follow the guidance in the Cochrane Handbook for Systematic Review of Interventions for cluster‐randomised trials (Higgins 2011). We will resolve disagreements by discussion, or if necessary, we will consult with a third review author (WT).
Measures of treatment effect
We will process data in accordance with the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011).
Continuous data
In the context of this review, it is clinically valid to measure the change from baseline instead of a comparison of postintervention values for the outcomes 'change in absolute walking distance', 'change in claudication distance' and 'QoL'. The preferred statistical approach to accounting for baseline measurements of the outcome variable is to include the baseline outcome measurements as a covariate in a regression model or analysis of covariance (ANCOVA) (Higgins 2011). Therefore, we will analyse outcomes via the generic inverse variance method. We will calculate mean differences (MD) with 95% confidence intervals (CI) if the studies included a mixture of change‐from‐baseline and post‐intervention value scores. Where feasible, we will convert distance units to the metric system. If conversion is not feasible and studies use different scales of measurement, we will calculate standardised mean differences (SMD) with 95% CI.
Time‐to‐event data
We will use survival analysis to report time‐to‐event data (amputation‐free survival, revascularisation‐free survival, MALE and MACE), and will express the intervention effect as a hazard ratio (HR) with associated 95% CI.
Dichotomous data
We will express results for dichotomous outcome measures (above‐ankle amputation and adverse events) using risk ratio (RRs) and associated 95% CIs to reflect uncertainty of the point estimate of effects.
Unit of analysis issues
We will take the individual participant as the unit of analysis. For cluster‐randomised trials, we will follow the guidance in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2019b), which states that trials should account for clustering in the data (e.g. based on a multilevel model or generalised estimating equation). We will seek statistical advice to determine if the analysis methods are appropriate. If the study authors have not properly accounted for clustering, we will record this in the risk of bias section. If possible, we will approximate the correct analyses where the following information can be extracted.
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The number of clusters (or groups) randomised to each intervention group and the total number of participants in the study; or the mean size of each cluster.
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The outcome data ignoring the cluster design for the total number of individuals (e.g. the number or proportion of individuals with events, or means and standard deviation for continuous data).
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An estimate of the intracluster (or intraclass) correlation coefficient (ICC).
If ICC estimates are not available in published reports, we will use external estimates obtained from similar studies, or use an estimate based on known patterns in ICCs for particular types of cluster or outcome.
Dealing with missing data
We will record missing and unclear data for each included study. If possible, we will perform all analyses using an intention‐to‐treat approach. That is, we will analyse all participants and their outcomes within the groups to which they were allocated regardless of whether they received the intervention. Where possible, we will use Review Manager 5 to calculate missing standard deviations using other data from the trial, such as CI, based on methods outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2019a; Review Manager 2020). If ICC estimates were not available in published reports, we will use external estimates obtained from similar studies, or use an estimate based on known patterns in ICCs for particular types of cluster or outcome. If necessary, we will contact study authors to request missing data and verify key study characteristics.
Assessment of heterogeneity
We will assess the degree of heterogeneity by visually inspecting forest plots and by examining the Chi² test for heterogeneity. We will assess heterogeneity of the overall results for main outcomes using Chi², I², and Tau² statistics, according to the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011), which states that 30% to 60% may represent moderate heterogeneity; 50% to 90% may represent substantial heterogeneity and 75% to 100% may represent considerable heterogeneity.
We will regard statistical heterogeneity as substantial if the I² statistic is greater than 50% and either Tau2 is greater than zero, or the P value is low (less than 0.10) in the Chi² test for heterogeneity. If we identify considerable clinical, methodological or statistical heterogeneity across included trials, we will not perform a meta‐analysis, and we will instead report results narratively.
Assessment of reporting biases
We will investigate publication bias by using funnel plots if we include 10 or more studies in the review, as recommended by the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). If we have sufficient studies for a funnel plot, we will perform a formal statistical test for asymmetry (Egger 1997).
Data synthesis
We will conduct statistical analyses by using Review Manager 5 (Review Manager 2020). We will use a fixed‐effect model to synthesise data when it is reasonable to assume that trials are estimating the same underlying treatment effect. If clinical heterogeneity is sufficient to expect that underlying treatment effects differ between trials, or if we detect substantial statistical heterogeneity, we will use a random‐effects model to produce an overall summary, when the mean treatment effect is clinically meaningful.
Subgroup analysis and investigation of heterogeneity
If we identify substantial heterogeneity (I² statistic is greater than 50%) between studies, we will perform subgroup analyses to investigate possible causes. We plan to conduct the following subgroup analyses.
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Intervention duration: 12 weeks' intervention versus longer than 12 weeks' intervention.
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Fontaine IIa versus Fontaine IIb (Fontaine 1954).
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Type of the intervention: medical health applications versus remotely monitored.
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Self‐reported intervention versus remotely supervised interventions.
We will use the formal test for subgroup differences in Review Manager 5 and base our interpretation on this (Review Manager 2020).
Sensitivity analysis
We will repeat the analyses including high‐quality trials only. For the purposes of this review, we will classify trials as high‐quality if they are judged at low risk of bias for sequence generation, allocation concealment and blinding of outcome assessment. We will also repeat the analyses including RCTs only; and explore the robustness of our results by repeating analyses after excluding studies with missing data or those where estimates are required (if ICC estimates were not available in published reports). We will use external estimates obtained from similar studies, or use an estimate based on known patterns in ICCs for particular types of cluster or outcome (Higgins 2019a).
Summary of findings and assessment of the certainty of the evidence
We will create summary of findings tables to provide the key information presented in the review using GRADEpro software (GRADEpro GDT). We will include the following outcomes.
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Change in absolute walking distances from baseline.
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Change in claudication distance from baseline.
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Amputation‐free survival.
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Revascularisation‐free survival.
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Major adverse cardiovascular events (MACE).
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Major adverse limb events (MALE).
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Above‐ankle amputation.
We will follow the methods described by the Cochrane Handbook for Systematic Reviews of Interventions (Schünemann 2019). The population will consist of people with PAD who have been diagnosed with IC, and we will compare mobile health technology with no intervention or exercise for improving walking distance. We will create a separate summary of findings table for each comparison. We will assign one of four levels of certainty: high, moderate, low or very low, based on overall risk of bias, directness of the evidence, inconsistency of results, precision of the estimates and risk of publication bias as previously described (Higgins 2011). We will justify all decisions to downgrade the certainty of the evidence using footnotes, and we will make comments to aid the reader's understanding of the review where necessary. We have included an example summary of findings table (Table 2). The review authors will be responsible for making judgements about evidence (FJ, GF and JME) working independently, with disagreements resolved by discussion or involving a fourth review author (WT). We will justify, document and incorporate judgements into reporting of results for each outcome. We plan to extract study data, format our comparisons in data tables and prepare summary of findings tables before writing the results and conclusions of our review.
| Mobile health technologies compared with no intervention or exercise to improve walking distance in people with intermittent claudication | ||||||
| Patient or population: people with symptomatic PAD with IC Settings: community Intervention: mobile health technologies Comparison: no intervention or exercise | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | No of participants | Certainty of the evidence | Comments | |
|---|---|---|---|---|---|---|
| Risk with no intervention or exercise | Risk with mobile health technologies | |||||
| Change in absolute walking distance [follow‐up] | The mean change in absolute walking distance ranged across control groups from 0 | The mean change in absolute walking distance in the intervention groups was 0 (0 to 0) | (RCTs) | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ | ||
| Change in claudication distance [follow‐up] | The mean change in claudication distance ranged across control groups from 0 | The mean change in claudication distance in the intervention groups was 0 (0 to 0) | (RCTs) | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ | ||
| Amputation‐free survival [follow‐up] | Study population | HR [0] ([0] to [0]) | (RCTs) | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ | ||
| [0] per 1000 | [0] per 1000 | |||||
| Revascularisation‐free survival [follow‐up] | Study population | HR [0] ([0] to [0]) | (RCTs) | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ | ||
| [0] per 1000 | [0] per 1000 | |||||
| MACE [follow‐up] | Study population | HR [0] ([0] to [0]) | (RCTs) | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ | ||
| [0] per 1000 | [0] per 1000 | |||||
| MALE [follow‐up] | Study population | HR [0] ([0] to [0]) | (RCTs) | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ | ||
| [0] per 1000 | [0] per 1000 | |||||
| Above‐ankle amputation [follow‐up] | Study population | RR [0] ([0] to [0]) | (RCTs) | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ | ||
| [0] per 1000 | [0] per 1000 | |||||
| *The risk in the intervention group (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). CI: confidence interval; HR: hazard ratio; IC: intermittent claudication; MACE: major adverse cardiovascular events; MALE: major adverse limb events; PAD: peripheral arterial disease; RCT: randomised controlled trial; RR: risk ratio. | ||||||
| GRADE Working Group grades of evidence | ||||||
| Stage | Description |
|---|---|
| I | Asymptomatic |
| II | Mild claudication pain |
| IIa | Claudication distance > 200 m |
| IIb | Claudication distance < 200 m |
| III | Rest pain (especially at night) |
| IV | Ulceration or gangrene (or both) of the limb |
| Mobile health technologies compared with no intervention or exercise to improve walking distance in people with intermittent claudication | ||||||
| Patient or population: people with symptomatic PAD with IC Settings: community Intervention: mobile health technologies Comparison: no intervention or exercise | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | No of participants | Certainty of the evidence | Comments | |
|---|---|---|---|---|---|---|
| Risk with no intervention or exercise | Risk with mobile health technologies | |||||
| Change in absolute walking distance [follow‐up] | The mean change in absolute walking distance ranged across control groups from 0 | The mean change in absolute walking distance in the intervention groups was 0 (0 to 0) | (RCTs) | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ | ||
| Change in claudication distance [follow‐up] | The mean change in claudication distance ranged across control groups from 0 | The mean change in claudication distance in the intervention groups was 0 (0 to 0) | (RCTs) | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ | ||
| Amputation‐free survival [follow‐up] | Study population | HR [0] ([0] to [0]) | (RCTs) | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ | ||
| [0] per 1000 | [0] per 1000 | |||||
| Revascularisation‐free survival [follow‐up] | Study population | HR [0] ([0] to [0]) | (RCTs) | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ | ||
| [0] per 1000 | [0] per 1000 | |||||
| MACE [follow‐up] | Study population | HR [0] ([0] to [0]) | (RCTs) | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ | ||
| [0] per 1000 | [0] per 1000 | |||||
| MALE [follow‐up] | Study population | HR [0] ([0] to [0]) | (RCTs) | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ | ||
| [0] per 1000 | [0] per 1000 | |||||
| Above‐ankle amputation [follow‐up] | Study population | RR [0] ([0] to [0]) | (RCTs) | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ | ||
| [0] per 1000 | [0] per 1000 | |||||
| *The risk in the intervention group (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). CI: confidence interval; HR: hazard ratio; IC: intermittent claudication; MACE: major adverse cardiovascular events; MALE: major adverse limb events; PAD: peripheral arterial disease; RCT: randomised controlled trial; RR: risk ratio. | ||||||
| GRADE Working Group grades of evidence | ||||||
