Skip to main content
Download PDF

Postoperative complications and mobilisation following major abdominal surgery with vs. without fitness tracker-based feedback (EXPELLIARMUS): study protocol for a student-led multicentre randomised controlled trial (CHIR-Net SIGMA study group)

Trials volume 21, Article number: 293 (2020) Cite this article

Abstract

Background

Postoperative complications following major abdominal surgery are frequent despite progress in surgical technique and perioperative care. Early and enhanced postoperative mobilisation has been advocated to reduce postoperative complications, but it is still unknown whether it can independently improve outcomes after major surgery. Fitness trackers (FTs) are a promising tool to improve postoperative mobilisation, but their effect on postoperative complications and recovery has not been investigated in clinical trials.

Methods

This is a multicentre randomised controlled trial with two parallel study groups evaluating the efficacy of an enhanced and early mobilisation protocol in combination with FT-based feedback in patients undergoing elective major abdominal surgery. Participants are randomly assigned (1:1) to either the experimental group, which receives daily step goals and a FT giving feedback about daily steps, or the control group, which is mobilised according to hospital standards. The control group also receives a FT, however with a blackened screen; thus no FT-based feedback is possible. Randomisation will be stratified by type of surgery (laparoscopic vs. open). The primary endpoint of the study is postoperative morbidity within 30 days measured via the Comprehensive Complication Index. Secondary endpoints include number of steps as well as a set of functional, morbidity and safety parameters. A total of 348 patients will be recruited in 15 German centres. The study will be conducted and organised by the student-led German Clinical Trial Network SIGMA.

Discussion

Our study aims at investigating whether the implementation of a simple mobilisation protocol in combination with FT-based feedback can reduce postoperative morbidity in patients undergoing major abdominal surgery. If so, FTs would offer a cost-effective intervention to enhance postoperative mobilisation and improve patient outcomes.

Trial registration

Deutsches Register Klinischer Studien (DRKS, German Clinical Trials Register): DRKS00016755, UTN U1111-1228-3320. Registered on 06.03.2019.

Peer Review reports

Background

Postoperative morbidity, mortality and patient-reported outcomes are arguably the most relevant outcome parameters in surgery, enabling a full risk-benefit assessment of surgical interventions. Although mortality for major abdominal surgery has decreased significantly over the last decades, morbidity remains high [1,2,3,4]. Complication rates between 30 and 60% have repeatedly been reported in randomised controlled trials (RCTs) for pancreatic [5,6,7,8], hepatobiliary [9], colorectal [10,11,12] and upper gastrointestinal surgery [13,14,15]. Interestingly, non-surgical complications like pulmonary and cardiac complications constitute a substantial part of overall morbidity [13].

Postoperative ambulation/mobilisation has been postulated to decrease postoperative complications in abdominal surgery and is part of all Enhanced Recovery After Surgery (ERAS) guidelines [16, 17]. However, the quality of the evidence to support this recommendation is very low [18,19,20,21]. Therefore, it is still unknown whether early and enhanced mobilisation can independently improve outcomes after major abdominal surgery and, if so, how this is best implemented in daily clinical practice [22].

Although designed as a consumer product to help motivate individuals to be physically active, wearable fitness trackers (FTs) are becoming increasingly popular as measurement tools in clinical research [23]. Importantly, FTs can be used to objectively measure outcomes like steps or distance covered and can thus be used as a feedback tool to meet prespecified mobilisation targets through feedback via the FT display. Few trials have studied FTs in the postoperative setting, and none used standardised assessment of postoperative complications as a primary outcome measure [24,25,26,27,28,29].

Rationale for the trial

The high rate of postoperative complications following major abdominal surgery warrants clinical trials that investigate interventions which could potentially reduce postoperative morbidity. Early and enhanced postoperative mobilisation has been advocated to reduce postoperative complications, but it is still unknown whether it can independently improve outcomes after major abdominal surgery. FTs are a promising tool to improve postoperative mobilisation following major abdominal surgery, but their effect on postoperative complications and recovery has not been studied in high-quality clinical trials.

Study aims and objectives

The objective of this study is to determine whether daily step goals and feedback via a FT reduces the rate of postoperative complications following elective major abdominal surgery.

Student-led clinical research

The teaching of clinical research and its associated scientific methodology is underdeveloped in medical schools, leading to an expected deficit in academic faculty across Europe [30, 31]. Research-based learning is a concept that refers to a trend in higher education: to provide students with the opportunity to gain knowledge by conducting their own scientific inquiries or investigations [32]. In 2017 the study network of the German Surgical Society (CHIR-Net [33];) founded a student-led clinical trial network across Germany (SIGMA; Student-Initiated German Medical Audit, [34]) [35, 36]. SIGMA has performed an observational study investigating patient-reported outcome measures and complications after surgery [37] and will perform the EXPELLIARMUS trial. To our knowledge, this is the first multicentre RCT ever to be performed by medical students.

Methods/design

Trial design

EXPELLIARMUS is a multicentre RCT with two parallel study groups.

Requirements for participating centres

Participating trial centres require at least one investigator (surgeon) and at least two medical students who are acquainted with the trial protocol and electronic case report form (eCRF). Furthermore, approval from the local ethics committee according to respective rules and regulations is mandatory.

Recruitment of study sites

Fifteen regional centres of the clinical trial network (CHIR-Net, [33]) have committed to participate in the EXPELLIARMUS trial; all are university hospitals or tertiary care centres in Germany.

Participants

Preoperative inclusion criteria

Participants must fulfil the following criteria:

  1. 1.

    Patients scheduled for elective major abdominal surgery defined as procedures expected to last more than 2 h, or with an anticipated blood loss greater than 500 ml [38]

  2. 2.

    Ability to understand the character and individual consequences of the clinical trial

  3. 3.

    Open or laparoscopic or robotic surgery or any variant (laparoscopic-assisted, hybrid procedures, etc.)

  4. 4.

    Provision of written informed consent

  5. 5.

    Age ≥ 18 years.

Preoperative exclusion criteria

The preoperative exclusion criteria are as follows:

  1. 1.

    American Society of Anesthesiologists (ASA) grade > 3

  2. 2.

    Preoperative immobility or inability to walk unaided

  3. 3.

    Participation in another interventional trial with interference of intervention and outcome of this study

  4. 4.

    Expected postoperative stay in the intensive care or intermediate care ward ≥ 4 days

  5. 5.

    Planned re-operation within 30 days after index operation

  6. 6.

    Planned abdominal-thoracic operations (two-field surgeries).

Intra/postoperative inclusion criteria

The intra/postoperative inclusion criteria are as follows:

  1. 1.

    Expected postoperative stay on intensive care or intermediate care ward of less than 4 days

  2. 2.

    No planned re-operation within 30 days

  3. 3.

    Confirmed major abdominal surgery (as defined in “Preoperative inclusion criteria”).

Intervention

In the experimental group, patients are fitted with a wearable FT (ActiGraph GT9X Link, ActiGraph, ProCare, Groningen, the Netherlands) on their dominant wrist after the operation for the duration of their postoperative stay until discharge or a maximum of 30 days. If the FT cannot be placed on the dominant wrist, it should be fitted on the non-dominant wrist. If this is also not possible, the FT should be fitted to any part of the patient’s body with a clip. Patients receive real-time visual feedback via the display of their tracker regarding daily steps taken and are encouraged to meet predefined daily step goals. In addition, ambulation is encouraged by the interprofessional care teams to meet predefined step goals.

The predefined step goals/instructions (mobilisation protocol) are as follows:

  1. 1.

    “Please ambulate/mobilise as much as possible and allowed by your doctors”

  2. 2.

    “Please take more steps than yesterday”

  3. 3.

    “Your daily step goal should be 4000 steps per day or more. Don’t worry if you do not reach this goal immediately”

  4. 4.

    “You should reach this daily 4000-step target latest on postoperative day 5 in the case of laparoscopic surgery or on postoperative day 8 in the case of open surgery”.

In the control group, patients are fitted with a wearable fitness tracker (ActiGraph GT9X Link, ActiGraph, ProCare) on their dominant wrist for the duration of their postoperative stay until discharge or a maximum of 30 days. The display of the device is disabled (blackened), and accordingly no feedback via the device is given. Patients are allowed to mobilise at will, i.e. as tolerated. If possible, mobilisation is performed according to ERAS guidelines on the morning of postoperative day 1 (POD 1) or according to in-house regimes [18, 19, 21]. Ambulation is encouraged by the interprofessional care teams according to local standards (current practice), but no specific mobilisation protocol is provided.

Assignment of intervention and randomisation

In order to achieve comparable study groups, patients will be randomly assigned to one of the two groups using a centralised web-based tool (www.randomizer.at). The online randomisation procedure provides information regarding the group allocation. Block randomisation with variable block sizes is used. Randomisation will be stratified by type of surgery (laparoscopic vs. open). Laparoscopic-assisted or hybrid procedures are counted as laparoscopic surgeries. Conversions from laparoscopic to open surgery are counted as open procedures. Randomisation will be performed on the day of surgery (visit 2) at the time of skin closure or later. Randomisation will be carried out only if all intraoperative inclusion criteria are fulfilled (see above). The online randomisation tool ensures concealment of the randomisation schedule. It is a computer-generated, concealed schedule that is not accessible by any trial participant or investigator. Randomisation will only be done by authorised trial personnel (investigator, medical student or designated representative) with their login data. Patients are recruited to the trial at least 24 h before surgery.

Blinding

Neither patients nor outcome assessors will be blinded to the intervention, as this is unfeasible and contradicts the pragmatic character of the trial. However, given the objective nature of the primary and most secondary endpoints, the risk of bias is limited.

Withdrawal

Patients may decide to withdraw from the study at any time without providing any specific reason for their decision. If, in the investigator’s opinion, continuation of the trial intervention would be detrimental to the subject’s well-being, the FT-based feedback will be discontinued (screen blackened). In addition, the feedback by the interprofessional care team will be discontinued, and the patient will not receive any more step goals. In both cases, the reason for withdrawal must be recorded in the CRF and in the patient’s medical records. If patient enrolment is unsatisfactory with respect to quality or quantity, or data recording is severely inaccurate or incomplete, as well as if externally respective evidence is given, the trial may be prematurely closed by the coordinating investigator in consultation with the responsible statistician and the CHIR-Net SIGMA steering committee. If the FT is removed, breaks or is otherwise unavailable, the clinical investigators will seek to replace it as soon as possible to guarantee complete step counts.

Outcome measures

The primary endpoint of the study is defined as postoperative morbidity measured via the Comprehensive Complication Index (CCI) [2, 3] within 30 days after the index operation. The CCI is calculated for an individual patient based on the assessment of all complications according to the Dindo-Clavien classification [39, 40]. This classification grades postoperative complications according to their sequelae and has gained universal acceptance. Although it allows for an objective assessment of complications, it provides neither definitions of complications nor a measure of the entire impact of complications for an individual patient. The latter is addressed by the CCI, which measures the overall morbidity for an individual patient on a scale from 0 (no complication) to 100 (death). The CCI summarises all postoperative complications instead of focusing on specific complications and is thus an objective measure to assess the full burden and impact of complications in a single patient [39, 40].

The following secondary endpoints will be assessed in the EXPELLIARMUS trial:

  1. 1.

    Number of steps for each POD until POD 8 or until discharge, whichever comes first. This serves as a measure of success for the trial intervention.

  2. 2.

    Patient-completed quality of recovery assessment according to Quality of Recovery 15 (QoR-15) at baseline and on POD 4 (or at discharge, whichever comes first) [41, 42]. QoR-15 is a validated short-term measure of postoperative recovery with 15 questions [41]; it has been developed from the longer QoR-40 [42]. It covers some, but not all aspects of postoperative recovery that are important to patients and experts [38]. As for the QoR-40, it can be assumed that QoR-15 results normalise within a week after major abdominal surgery [43]; thus, assessment at baseline and on POD 4 seems reasonable to elucidate potential differences between the two groups.

  3. 3.

    Activity data (via the wearable device for each POD until discharge or a maximum of 30 days):

    1. (a)

      Metabolic equivalents of tasks (METs) rates

    2. (b)

      Energy expenditure

    3. (c)

      Raw acceleration

    4. (d)

      Activity and sedentary bouts

    5. (e)

      Physical activity intensity

    6. (f)

      Total sleep time.

These data are provided by the FT used in the EXPELLIARMUS trial and allow correlating activity data with clinical outcomes for exploratory analyses.

  1. 4.

    Health-related quality of life (HRQoL) measured via the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire C30 (EORTC QLQ-C30) at baseline, on POD 8 (or at discharge, whichever comes first) and on POD 30 [44]. Although the HRQoL measure EORTC QLQ-C30 has been developed and validated for patients with cancer, it is the most comprehensive tool to cover aspects of postoperative recovery that are important to patients and experts [38]. Importantly, it elucidates aspects of postoperative recovery that are not covered by the QoR-15 [38].

  2. 5.

    Six-min walking test (6-MWT) on POD 6 (or at discharge, whichever comes first). The 6-MWT is a well-established, widely used performance-based functional test. Patients walk for 6 min along a long, flat, straight enclosed corridor with a hard surface supervised by a medical student or investigator. The test is performed according to recommendations by the American Thoracic Society [45]. Functional tests are an important aspect of postoperative recovery that are infrequently analysed in mobilisation trials [22].

  3. 6.

    Time (in days) until return of bowel function measured via the gastrointestinal-2 (GI-2) score defined as “The patient has tolerated solid intake (no vomiting) for 24 hours AND has passed stool” [46]. The GI-2 score is a widely used and well-established measure for the return of postoperative bowel function [46]. This assessment is completed by the patient.

  4. 7.

    Postoperative pulmonary complications according to the Melbourne group score [13] during hospital stay.

  5. 8.

    Deep vein thrombosis until POD 30. Diagnosis needs to be based on imaging results.

  6. 9.

    Pulmonary embolism until POD 30 (based on imaging results and/or clinical diagnosis).

  7. 10.

    Time in days from date of index operation to achieve uninterrupted ambulation greater than 10 min. These data will be extracted from the FT device. Similar to the 6-MWT, this is a measure of functional outcome that has been used in prior clinical trials [47].

  8. 11.

    Thirty-day mortality. Mortality is an important outcome measure for any surgical clinical trial. Postoperative mortality is equivalent to a grade V complication in the Dindo-Clavien classification.

  9. 12.

    Length of hospital stay in days (from day of surgery until day of discharge after index operation).

  10. 13.

    Discharge destination from the acute hospital ward (home, rehabilitation facility, nursing home or other hospital). This is an important health-care system parameter and an indirect indicator of patient fitness.

  11. 14.

    Pain scores according to the numeric rating scale (NRS) on PODs 2, 4 and 6 at rest and during movement. Pain will be measured using an established patient-reported outcome measure, the NRS (0-no pain to 10-worst possible pain). Furthermore, pain is one of the main barriers to adequate postoperative mobilisation [48]. Finally, increased pain could hypothetically be associated with the intervention (enhanced mobilisation) and will thus be analysed in our trial.

  12. 15.

    Postoperative unintended falls/collapses until day of discharge. An increased rate of intended postoperative falls/collapses could potentially be associated with the intervention and will thus be assessed as a safety measure. Clinical consequences of the falls/collapses will be accounted for by the primary endpoint (complications according to the Dindo-Clavien classification). The number is obtained by asking the treating interprofessional care team (nurses, doctors) and the patients themselves.

Patient time line

All consecutive patients are screened preoperatively and are enlisted in a screening list. Reasons for non-enrolment must be stated. Patients are enrolled given their ability to understand the extent and nature of the trial, their written informed consent after detailed patient information and fulfilment of all preoperative inclusion and exclusion criteria. Baseline data are collected during screening/baseline visit. Surgical data are collected during visit 2. Primary and secondary outcome parameters are collected during visits 3–8 within 30 PODs. Table 1 gives an overview of data items and activities for each trial visit.

Table 1 Trial visits, data items and activities of the EXPELLIARMUS trial
Full size table

Visit 1 (preoperative, informed consent)

All consecutive patients are screened for potential inclusion. Eligible patients are asked for informed consent. Enrolled patients are instructed on how to use the wearable FT (see “Intervention”). In addition, the following data items will be collected: (1) demographic data; (2) baseline data; (3) medical history/comorbidities; (4) HRQoL (EORTC QLQ-C30) [44]; (5) baseline functional data via the QoR-15 questionnaire [41, 42]; (6) status of physical activity via the Duke Activity Status Index (DASI) [49].

Visit 2 (day of surgery, postoperative day 0)

On the day of surgery, data concerning the performed procedure are collected, including duration of surgery, blood loss, type of surgery and type of surgical access (open vs. laparoscopic). Furthermore, data regarding number and types of abdominal drains, nasogastric tubes, urinary catheters and postoperative analgesic are collected. At this time, randomisation will be performed (see above) and the wearable FT is attached.

Visits 3–6 (postoperative days 2, 4, 6 and 8 (± 1 day))

Visits 3–6 have equivalent contents with the exception of the QoR-15 questionnaire, which is only administered at visit 4, the 6-MWT, which is performed only at visit 5 (or at discharge, whichever comes first) and HRQoL assessment (EORTC QLQ-C30), which is only performed at visit 6. If the patient is discharged before undergoing visits 3–6, the respective visits are skipped and the discharge visit (visit 7) is performed.

Visits 3–6 include assessment of postoperative complications according to Dindo-Clavien (primary endpoint). In addition, all secondary endpoints will be assessed. Furthermore, data on physiotherapy and mobilisation support by health-care team members other than physiotherapists (e.g. nursing staff) are collected. Finally, patients in the experimental group receive instructions about their step goals, and it is assessed whether these mobilisation targets have been met since the last visit.

Visit 7 (day of discharge, ± 1 day)

On the day of discharge, the FTs are collected, and the data are read out and transferred over a secure upload server. Furthermore, all data items of visits 3–6 will be assessed. Finally, the discharge destination from the hospital needs to be documented. If discharge occurs before visit 5, the 6-MWT test needs to be performed at visit 7.

Visit 8 (postoperative day 30 (± 4 days) or premature study termination)

If the patient has not been discharged, a clinical visit will be performed. In case of prior discharge, either a telephone visit can be performed or the patient can be seen in the outpatient clinic. Assessments include complications and re-operations, pulmonary complications, pulmonary embolism or deep vein thrombosis, duration of drain placements, the health-related quality of life questionnaire EORTC QLQ-C30 and data on potential physiotherapy. If the patient is still in hospital, the FTs are collected, and the data are read out and transferred over a secure upload server.

Sample size calculation

The sample size calculation is based on the primary endpoint “CCI within 30 days after the index operation”. Assumptions are based on the literature [39, 40, 50]: a decrease of the CCI by 10 points is considered relevant by patients and clinicians (minimal important difference, [40]) and a conservative standard deviation of 20 is assumed. The CCI in major abdominal surgery (control intervention) is assumed to be 22 [39, 40]. We hypothesise to decrease the CCI by 10 points in the interventional group (minimal important difference, [40]). The primary endpoint is tested simultaneously using a two-sided t test in the subgroup of patients with a minimally invasive surgery and the subgroup of patients experiencing an open surgery. The ratio of minimally invasive to open is expected to be 1:1. Therefore, the overall two-sided significance level of α = 0.05 is adjusted by Bonferroni correction, yielding α = 0.025 for each of the two subgroups. Thus, to achieve a power of 80%, a sample size of n = 156 (78 per group) has to be recruited per subgroup with a total required sample size of the trial of n = 312 (156 per therapy group). To compensate for drop-outs and lost-to-follow-ups, a further 10% of patients will be randomised, leading to a total sample size of n = 348 (174 per group). Patients who die during the observation period receive the maximum number of 100 CCI points per definition [39, 40].

Statistical analysis

For the examination of the primary endpoint “CCI within 30 days after the index operation”, the hypotheses to be assessed for each subgroup (minimally invasive or open) in the primary analysis are as follows: H0: μ1 = μ2 vs. H1: μ1 ≠ μ2, where μ1 and μ2 denote the mean CCI in the control and the intervention group respectively. The significance level is set to a two-sided α = 0.025 per subgroup test. Due to the stratified randomisation and relatively large number of centres in relation to the sample size, inclusion of centre as a random effect is recommended [51]. Therefore, the primary endpoint will be examined in the respective subgroup (minimally invasive or open) using a linear mixed model including centre as random intercept and group as fixed effect, which leads to equal or even increased power as compared to using a conventional two-sided t test [52].

The primary analysis will be conducted based on the full analysis set according to the intention-to-treat (ITT) principle and comprises all patients in the group they were randomised to. In the ITT analysis, missing data for the primary outcome variable will be replaced by using multiple imputation, which takes the covariates treatment group and centre into account by application of the fully conditional specification method [53]. The per protocol (PP) set consists of all patients treated per protocol; no missing data will be imputed. An additional mobility population consists of all patients who were randomised, had no re-operation within 30 days and had not been on the intensive or intermediate care ward for ≥ 4 days during the first postoperative week.

In general, for the full analysis set, all baseline values and secondary outcomes will be evaluated descriptively, and descriptive p values are reported together with 95% confidence intervals for the corresponding effects. Thereby, secondary endpoints will be evaluated descriptively using regression models including group as fixed effect and centre as random intercept as specified for the primary endpoint.

In further exploratory analyses, the association of variables with the primary and secondary outcomes will be assessed. In addition, subgroup analyses will be carried out. The safety analysis includes calculation of frequencies and rates of complications together with 95% confidence intervals. All analyses will be done using SAS version 9.4 or higher. The analyses will be described in further detail in the statistical analysis plan, which will be written before database closure.

It is planned to make all trial data publicly available after the publication of trial results.

Risk of bias

In order to ensure that both treatment groups are well balanced for known and unknown confounders, the assignment to the two groups is based on randomisation. In order to document potential selection bias, all consecutive screened patients are listed in a screening list. To exclude the quality of surgery as a key factor for postoperative complications, randomisation is performed at the time of skin closure or later. In order to standardise outcome assessment, medical students are trained during a clinical investigator training (CIT) course in study-specific procedures as well as good clinical practice to reduce detection bias. The curriculum of the CIT has been described elsewhere [36]. Furthermore, obligatory online training material is available to all participating students. In addition, medical students are supported by surgeons experienced in clinical trials (clinician scientists) at their local sites. Blinding, however, is impractical in our study setting, as it would require ornate blinding methods, which contradict the pragmatic trial design. However, in order to counteract the risk of bias introduced by the unblinded study design, we have chosen a primary endpoint robust against unconscious or intentional influence, namely the Comprehensive Complication Index (CCI). The Dindo-Clavien complication classification, on which the CCI is based, is an objective outcome measure, as it grades complications according to their sequelae (e.g. death, re-operation, re-intervention, etc.) and can hardly be influenced by subjective impressions. However, this does not hold true for some of the secondary outcomes, e.g. patient-reported measures like pain. Furthermore, follow-up is limited to 30 days; thus, few missing values are expected. Since patients are still hospitalised for parts of this period, the attrition bias is expected to be low.

In addition, known courses for postoperative recovery will be meticulously recorded during follow-up in order to record potential confounders. These include the preoperative physical fitness (assessed via the DASI score), the impact of surgery (laparoscopic vs. open), the type of recovery programme, analgesic regime, duration of catheter, drain and tube placement and the degree of physiotherapy.

Risk-benefit assessment

All patients will receive medical treatment including surgery as defined by their treating physicians (gold standard). No changes in medical or surgical therapy will occur due to the trial. However, all participating patients have an additional time burden of filling out the patient-reported outcome measures (QoR-15 questionnaire, EORTC QLQ-C30) and the time needed for the clinical trial visits. In addition, patients in the interventional group might have the added risk of ambulation-associated adverse events like burst abdomen, unintended falls and increased pain during mobilisation. However, evidence indicates that early and enhanced ambulation is beneficial rather than harmful for patients [22]. Consequently, all current guidelines recommend enhanced postoperative mobilisation [16, 17]. Thus, patients in the control group rather than the interventional group have an added risk for immobilisation-associated complications like deep vein thrombosis and postoperative pulmonary complications. However, whether or not FTs enhance postoperative ambulation following major abdominal surgery is unclear. Furthermore, it is unclear whether or not FTs are able to reduce immobilisation-associated adverse events. In summary, based on current evidence, clinical equipoise is given, which necessitates the current trial.

Data management

An electronic case report form (eCRF) implemented in the REDCap™ system [54] will be used for data collection [55]. All protocol-required information collected during the trial must be entered by the investigator, medical student or designated representative in the eCRF in hospital. For health-related quality of life and patient-reported outcomes, the data must be entered directly by the patients in the eCRF. To this end, tablets or laptops are used. Alternatively, paper-based reported outcome questionnaires may be used and must then be entered by the investigator, medical student or designated representative in the eCRF. For follow-up visits, patients access the eCRF directly online. Data transmission is encrypted with Secure Sockets Layer (SSL) technology. The database server is located in a secure data centre and is protected by a firewall. The system provides an infrastructure to support user roles and rights. Only authorised users are able to enter or edit data, and access is restricted to data of the patients in the respective centre. All changes to data are logged with a computerised timestamp in an audit trail. All clinical data will be pseudonymised.

All protocol-required information collected during the trial must be entered by the investigator, medical student or designated representative in the eCRF. For health-related quality of life and patient-reported outcome data, patients may directly enter the data in the eCRF. Alternatively, paper-based reported outcome questionnaires must be entered by the investigator, medical student or designated representative in the eCRF. The completed eCRF must be reviewed and signed by the local investigator or by a designated sub-investigator.

In order to guarantee high quality of data, the completeness, validity and plausibility of data as defined in a data validation plan will be checked at the time of data entry and using validating programs, which will generate queries (centralised monitoring). The investigator, medical student or the designated representatives are obliged to clarify or explain the queries.

Data from the FTs are collected at each local site according to the manufacturers’ guidelines. Download from data of FTs takes place either at individual end of study or if the FT has to be exchanged for any reason (low battery, inconsistency between patient’s physical activity and FT step count). Raw data files from each patient are stored at the local sites according to the applicable local, national and international regulations. Raw data files are transferred via a secure upload server at the Institute of Medical Biometry and Informatics (IMBI) from the local sites to the IMBI.

All data collected (eCRF data and FT data) will be integrated in a statistical analysis system. During study conduct, database access will be granted to the data manager only. After database closure, access rights will be granted to the responsible biometricians as well. The data will be managed and analysed in accordance with the appropriate Standard Operating Procedures (SOPs) valid at the IMBI, Heidelberg.

Discussion

Reducing postoperative complications in major abdominal surgery is one of the major challenges for the future. Despite innovations like minimally invasive surgery, postoperative complication rates of more than 30% are regularly reported [5,6,7,8,9,10,11,12,13,14,15]. Non-surgical complications including pulmonary and cardiovascular complications contribute a substantial part [13]. Mobilisation has been postulated to reduce postoperative morbidity and is part of all current ERAS guidelines; however, evidence to support this concept is low [18,19,20,21]. A number of studies have investigated mobilisation as one part of a “bundle of interventions” (as in ERAS programmes), frequently with favourable outcome [56, 57]. We hypothesise that patients in the interventional group have a significantly higher step count than patients in the control group. The size of the contribution of each individual treatment component within a care bundle, however, limits interpretation of findings. In line with this, the real effect of fast-track protocols on postoperative complications in minimally invasive surgery is controversial [10]. Interestingly, only 20–28% of patients were mobilised on the first postoperative day after liver surgery, despite predefined mobilisation targets [58,59,60]. Others reported that only a minority of patients achieved the preset mobilisation targets following colorectal cancer surgery, which could not be improved by the implementation of an ERAS pathway [61].

A systematic review investigating postoperative mobilisation identified only three RCTs and one observational study with poor methodological quality, including merely 225 patients [22]. None of these studies used postoperative complications as the primary outcome parameter, but looked at surrogate parameters like number of steps. Furthermore, none of the trials applied standardised outcome definitions for postoperative complications.

Importantly, the intervention known as “early and enhanced” mobilisation is not clearly defined, as studies use different postoperative mobilisation protocols. Thus, it is unknown whether postoperative “mobilisation targets” have any beneficial effect and, if so, how these targets should be defined. Hence, our pragmatic trial is a step towards a standardised mobilisation protocol in major abdominal surgery and adheres to high methodological standards. Future studies could then refine step goals in different clinical settings (e.g. laparoscopic vs. open surgery) and based on an individual’s personal fitness, eventually enabling evidence-based personalised mobilisation regimens.

Mobilisation is no trivial aspect in the postoperative course, as recent research suggests that enforcing early mobilisation targets requires substantial staff time. The lack of manpower is a main barrier to this practice [62]. Furthermore, many patients fail common ERAS mobilisation targets in major abdominal surgery [48].

FTs are becoming increasingly popular as measurement tools in clinical research [23]. Potential advantages of using FTs in postoperative surgical patients are (1) real-time continuous feedback; (2) objective, validated outcome measurement of physical activity including step counts rather than subjective, error-prone assessment by patients themselves or hospital staff; (3) reduction of staff time and manpower to enforce mobilisation targets, thereby (4) increasing the cost-effectiveness of mobilisation interventions, which has been identified as a main barrier to its implementation [62].

As with mobilisation, evidence to support FTs in the postoperative setting is limited. A major difficulty in comparing results of studies including wearable fitness devices is the heterogeneity of interventions and high risk of bias [63]. Studies analysing the association of early postoperative mobilisation and clinical outcome focus on step counts rather than patient-relevant outcome measures like complications [26, 28, 64]. Cook et al. and Daskivich et al. reported a prognostic relationship between the number of postoperative steps and length of stay [29, 65]. Wolk et al. performed a single-centre RCT in major abdominal surgery comparing the use of FTs plus a daily step goal vs. FTs with blinded display and no daily step goal (standard of care). The mean number of steps within the first 5 postoperative days (PODs) was increased after laparoscopic but not after open abdominal surgery [24]. Ni et al. performed an exploratory single-centre RCT in hepatic surgery using FTs as step count and enforced “early and enhanced” mobilisation by health-care team workers. They reported faster return of gastrointestinal function and a decreased length of hospital stay in favour of the mobilisation group, although postoperative complications were not significantly different between the groups [25]. Thus, the actual impact of feedback by wearable devices and health-care staff on physical activity remains uncertain.

The proposed trial has several strengths and limitations. Our trial addresses common limitations associated with the use of FTs. First, the accuracy of commercially available devices in the clinical setting is low (see e.g. [23, 66, 67]) owing to specificities of the postoperative period like shuffling gait. Second, concerns about data protection are inadequately addressed by commercial FTs. We created a secure digital environment (eCRF) which allows the storage and analysis of data according to European and national regulations. Third, most commercial FTs do not provide raw data, as is needed for unbiased trial analysis, but rather aggregated data [67]. By using devices especially made for clinical research and which provide raw data, our study circumvents these problems. Fourth, EXPELLIARMUS will evaluate mobilisation with rigorous methodology, using validated outcome measures. Accordingly, EXPELLIARMUS has a multicentre RCT design to test the efficacy of enhanced mobilisation and FT-based feedback. It will use the validated and internationally accepted CCI as the primary endpoint, thus focusing on the most patient-relevant outcome. Fifth, mobilisation is assessed by numerous functional parameters like the 6-MWT or ambulation > 10 min, as has been proposed before [22]. In addition, validated patient-reported outcome measures like the QoR-15 or EORTC QLQ-C30 as well as safety measures will be assessed to give a comprehensive picture of the potential risks and benefits of FT-based enhanced mobilisation. Finally, as a unique characteristic of our trial, the organisation, conduct and analysis will be done by a network of medical students with the support of experienced surgeons, clinician scientists and statisticians in a large research-based learning project. By planning, conducting and analysing a clinical trial, students will not only gain clinical knowledge and experience, but also scientific competencies. Projects to provide such research experiences are emerging and show that medical students can improve their clinical capabilities by contributing to student-initiated clinical trials [68, 69]. A student-led initiative in the UK has successfully performed a number of large observational studies in a national cohort following gastrointestinal surgery, demonstrating the feasibility of this concept [70, 71]. On an even larger scale, the EuroSurg collaborative demonstrated the feasibility of this concept across multiple European countries [72].

Despite successful student-led initiatives in other countries [73] and studies by the SIGMA network itself [37], this set-up could also be viewed as a major limitation. All previous studies were observational studies with a much simpler design, and it is unknown whether medical students can successfully conduct an RCT. In addition, it is unknown whether medical students assess and report postoperative complications with a quality comparable to that of trained clinician scientists. Another limitation of the trial is the unblinded trial design. Thus, we cannot exclude performance bias in both groups. However, the Dindo-Clavien classification, on which the CCI is based, grades postoperative complications according to their sequelae. Grade III (requiring endoscopic, radiologic or surgical intervention), IV (requiring intensive care treatment) and V (death) complications are objective and can hardly be influenced even in an unblinded study setting. However, grade I (any deviation from the normal postoperative course without the need for pharmacological treatment) to grade II (pharmacological intervention) complications are more prone to subjective interpretation and might be prone to bias in our study. However, grade I and II complications give only a few CCI points, and our outcome assessors (medical students) have no incentive to “fake” complications. As patients are aware of being part of a mobilisation trial, patients in the control group might be especially motivated to ambulate. Furthermore, as randomisation occurs on an individual level, we cannot exclude “contamination” of treatment groups. However, by using an objective, well-standardised primary outcome measure, we believe our results are robust against potential bias due to unblinding.

Conclusions

EXPELLIARMUS will provide high-quality data on the efficacy of fitness tracker-based feedback following major abdominal surgery. Supported by surgeons and trained study staff, this large multicentre RCT will provide medical students with an opportunity to acquire scientific competencies and clinical research skills in a large research-based learning project.

Trial status

The protocol is version 1.1. (5 March 2019). Recruitment started (first patient in) on 5 June 2019; 219 patients have been included in the trial (31 January 2020). The approximate date when recruitment will be completed is 31 May 2020.

Availability of data and materials

Data sharing is not applicable to this article, as no datasets were generated or analysed. The pseudonymised data of the EXPELLIARMUS study will be available to the participating clinical trials sites for further analyses if the planned post hoc analyses are performed in accordance with data protection laws and ICH-GCP guidelines. Anonymised data of the EXPELLIARMUS study may be available to other researchers if their planned analyses are performed in accordance with data protection laws and ICH-GCP guidelines.

Abbreviations

6-MWT:

6-min walking test

ASA:

American Society of Anesthesiologists

CCI:

Comprehensive Complication Index

CHIR-Net :

Clinical Trial Network of the German Surgical Society

CIT:

Clinical investigator training

CRF:

Case report form

DASI:

Duke Activity Status Index

DRKS:

Deutsches Register Klinischer Studien. The German Registry of Clinical Trials (WHO-compatible)

EORTC QLQ-C30:

European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire C30

ERAS:

Enhanced Recovery After Surgery

F/U:

Follow-up

FT:

Fitness tracker

GCP:

Good clinical practice

GI-2:

Gastrointestinal-2 (score)

HRQoL:

Health-related quality of life

ITT:

Intention-to-treat

NRS:

Numeric rating scale

POD:

Postoperative day

PP:

Per protocol

QoR-15:

Quality of Recovery 15 questionnaire

RCT:

Randomised controlled trial

SIGMA:

Student-Initiated German Medical Audit

References

  1. Gouma DJ, van Geenen RC, van Gulik TM, de Haan RJ, de Wit LT, Busch OR, et al. Rates of complications and death after pancreaticoduodenectomy: risk factors and the impact of hospital volume. Ann Surg. 2000;232(6):786–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Gordon TA, Bowman HM, Bass EB, Lillemoe KD, Yeo CJ, Heitmiller RF, et al. Complex gastrointestinal surgery: impact of provider experience on clinical and economic outcomes. J Am Coll Surg. 1999;189(1):46–56.

    Article  CAS  PubMed  Google Scholar 

  3. Birkmeyer JD, Siewers AE, Finlayson EVA, Stukel TA, Lucas FL, Batista I, et al. Hospital volume and surgical mortality in the United States. N Engl J Med. 2002;346(15):1128–37.

    Article  PubMed  Google Scholar 

  4. Birkmeyer JD, Sun Y, Wong SL, Stukel TA. Hospital volume and late survival after cancer surgery. Ann Surg. 2007;245(5):777–83.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Diener MK, Seiler CM, Rossion I, Kleeff J, Glanemann M, Butturini G, et al. Efficacy of stapler versus hand-sewn closure after distal pancreatectomy (DISPACT): a randomised, controlled multicentre trial. Lancet. 2011;377(9776):1514–22.

    Article  PubMed  Google Scholar 

  6. Diener MK, Hüttner FJ, Kieser M, Knebel P, Dörr-Harim C, Distler M, et al. Partial pancreatoduodenectomy versus duodenum-preserving pancreatic head resection in chronic pancreatitis: the multicentre, randomised, controlled, double-blind ChroPac trial. Lancet. 2017;390(10099):1027–37.

    Article  PubMed  Google Scholar 

  7. Probst P, Haller S, Bruckner T, Ulrich A, Strobel O, Hackert T, et al. Prospective trial to evaluate the prognostic value of different nutritional assessment scores in pancreatic surgery (NURIMAS Pancreas). Br J Surg. 2017;104(8):1053–62.

    Article  CAS  PubMed  Google Scholar 

  8. Ironside N, Barreto SG, Loveday B, Shrikhande SV, Windsor JA, Pandanaboyana S. Meta-analysis of an artery-first approach versus standard pancreatoduodenectomy on perioperative outcomes and survival. Br J Surg. 2018;105(6):628–36.

    Article  CAS  PubMed  Google Scholar 

  9. Stockmann M, Vondran FWR, Fahrner R, Tautenhahn HM, Mittler J, Bektas H, et al. Randomized clinical trial comparing liver resection with and without perioperative assessment of liver function. BJS Open. 2018;2(5):301–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Maggiori L, Rullier E, Lefevre JH, Régimbeau J-M, Berdah S, Karoui M, et al. Does a combination of laparoscopic approach and full fast track multimodal management decrease postoperative morbidity?: a multicenter randomized controlled trial. Ann Surg. 2017;266(5):729–37.

    Article  PubMed  Google Scholar 

  11. Bennett-Guerrero E, Pappas TN, Koltun WA, Fleshman JW, Lin M, Garg J, et al. Gentamicin–collagen sponge for infection prophylaxis in colorectal surgery. N Engl J Med. 2010;363(11):1038–49.

    Article  CAS  PubMed  Google Scholar 

  12. Bianco F, Romano G, Tsarkov P, Stanojevic G, Shroyer K, Giuratrabocchetta S, et al. Extralevator with vs nonextralevator abdominoperineal excision for rectal cancer: the RELAPe randomized controlled trial. Color Dis. 2017;19(2):148–57.

    Article  CAS  Google Scholar 

  13. Boden I, Skinner EH, Browning L, Reeve J, Anderson L, Hill C, et al. Preoperative physiotherapy for the prevention of respiratory complications after upper abdominal surgery: pragmatic, double blinded, multicentre randomised controlled trial. BMJ. 2018;360:j5916.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Cunningham D, Allum WH, Stenning SP, Thompson JN, Van de Velde CJH, Nicolson M, et al. Perioperative chemotherapy versus surgery alone for resectable gastroesophageal cancer. N Engl J Med. 2006;355(1):11–20.

    Article  CAS  PubMed  Google Scholar 

  15. Schuhmacher C, Gretschel S, Lordick F, Reichardt P, Hohenberger W, Eisenberger CF, et al. Neoadjuvant chemotherapy compared with surgery alone for locally advanced cancer of the stomach and cardia: European Organisation for Research and Treatment of Cancer randomized trial 40954. J Clin Oncol. 2010;28(35):5210–8.

    Article  PubMed  PubMed Central  Google Scholar 

  16. ERAS Society. ERAS guidelines. ERAS. http://erassociety.org/guidelines/list-of-guidelines/. Accessed 12 Dec 2018.

  17. Ljungqvist O, Scott M, Fearon KC. Enhanced Recovery After Surgery: a review. JAMA Surg. 2017;152(3):292–8.

    Article  PubMed  Google Scholar 

  18. Melloul E, Hübner M, Scott M, Snowden C, Prentis J, Dejong CHC, et al. Guidelines for perioperative care for liver surgery: Enhanced Recovery After Surgery (ERAS) Society recommendations. World J Surg. 2016;40(10):2425–40.

    Article  PubMed  Google Scholar 

  19. Gustafsson UO, Scott MJ, Schwenk W, Demartines N, Roulin D, Francis N, et al. Guidelines for perioperative care in elective colonic surgery: Enhanced Recovery After Surgery (ERAS®) Society recommendations. World J Surg. 2013;37(2):259–84.

    Article  CAS  PubMed  Google Scholar 

  20. Mortensen K, Nilsson M, Slim K, Schäfer M, Mariette C, Braga M, et al. Consensus guidelines for enhanced recovery after gastrectomy. BJS. 2014;101(10):1209–29.

    Article  CAS  Google Scholar 

  21. Lassen K, Coolsen MME, Slim K, Carli F, de Aguilar-Nascimento JE, Schäfer M, et al. Guidelines for perioperative care for pancreaticoduodenectomy: Enhanced Recovery After Surgery (ERAS®) Society recommendations. World J Surg. 2013;37(2):240–58.

    Article  PubMed  Google Scholar 

  22. Castelino T, Fiore JF, Niculiseanu P, Landry T, Augustin B, Feldman LS. The effect of early mobilization protocols on postoperative outcomes following abdominal and thoracic surgery: a systematic review. Surgery. 2016;159(4):991–1003.

    Article  PubMed  Google Scholar 

  23. Feehan LM, Geldman J, Sayre EC, Park C, Ezzat AM, Yoo JY, et al. Accuracy of Fitbit devices: systematic review and narrative syntheses of quantitative data. JMIR Mhealth Uhealth. 2018;6(8):e10527.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Wolk S, Linke S, Bogner A, Sturm D, Meißner T, Müssle B, et al. Use of activity tracking in major visceral surgery—the Enhanced Perioperative Mobilization trial: a randomized controlled trial. J Gastrointest Surg. 2019;23(6):1218–26.

    Article  PubMed  Google Scholar 

  25. Ni C-Y, Wang Z-H, Huang Z-P, Zhou H, Fu L-J, Cai H, et al. Early enforced mobilization after liver resection: a prospective randomized controlled trial. Int J Surg. 2018;54(Pt A):254–8.

    Article  PubMed  Google Scholar 

  26. Massouh F, Martin R, Chan B, Ma J, Patel V, Geary MP, et al. Is activity tracker-measured ambulation an accurate and reliable determinant of postoperative quality of recovery? A prospective cohort validation study. Anesth Analg. 2019;129(4):1144–52.

    Article  PubMed  Google Scholar 

  27. Low CA, Bovbjerg DH, Ahrendt S, Choudry MH, Holtzman M, Jones HL, et al. Fitbit step counts during inpatient recovery from cancer surgery as a predictor of readmission. Ann Behav Med. 2018;52(1):88–92.

    Article  PubMed  Google Scholar 

  28. Ghomrawi HM, Baumann LM, Kwon S, Hebal F, Hsiung G, Williams K, et al. Using accelerometers to characterize recovery after surgery in children. J Pediatr Surg. 2018;53(8):1600–5.

    Article  PubMed  Google Scholar 

  29. Cook DJ, Thompson JE, Prinsen SK, Dearani JA, Deschamps C. Functional recovery in the elderly after major surgery: assessment of mobility recovery using wireless technology. Ann Thorac Surg. 2013;96(3):1057–61.

    Article  PubMed  Google Scholar 

  30. European Science Foundation (ESF). Investigator-driven clinical trials. Strasbourg: ESF; 2009. http://archives.esf.org/fileadmin/Public_documents/Publications/IDCT.pdf.

    Google Scholar 

  31. DFG Ständige Senatskommission für Grundsatzfragen in der Klinischen Forschung. Etablierung eines integrierten Forschungs- und Weiterbildungs-Progranmms für “Clinician Scientists” parallel zur Facharztweiterbildung. 2015. http://www.dfg.de/download/pdf/dfg_im_profil/reden_stellungnahmen/2015/empfehlungen_clinician_scientists_0415.pdf. Accessed 29 Sept 2015.

  32. Huber L, Hellmer J, Schneider F. Forschendes Lernen im Studium. Aktuelle Konzepte und Erfahrungen. 2nd ed. Bielefeld: UVW Universitäts Verlag; 2009. p. 227.

    Google Scholar 

  33. CHIR-Net. http://www.chir-net.de/. Accessed 5 Aug 2019.

  34. SIGMA-Studies. https://sigma.university/. Accessed 5 Aug 2019.

  35. Frey P-E, Friedrich M, Rädeker L, Fink CA, Leuck A, Tenckhoff S, et al. Encouraging student-driven clinical research in Germany: the CHIR-Net SIGMA network. Innov Surg Sci. 2017;2(4):255–60.

    PubMed  PubMed Central  Google Scholar 

  36. Rädeker L, Schwab M, Frey PE, Friedrich M, Sliwinski S, Steinle J, Fink CA, Leuk A, Ganschow P, Ottawa GB, Klose C, Feißt M, Dörr-Harim C, Tenckhoff S, Mihaljevic AL. Design und Evaluation eines Prüf-Studierenden-Kurses für studentische prospektive Multicenterstudien – ein CHIR-Net-SIGMA-Projekt zum forschenden Lernen [Design and Evaluation of a Clinical Investigator Training for Student-lead Prospective Multicentre Clinical Trials: a CHIR-Net SIGMA Research-based Learning Project]. Zentralbl Chir. 2019 Oct 28. German. doi: 10.1055/a-1007-1995. Epub ahead of print.

  37. Fink CA, Friedrich M, Frey P-E, Rädeker L, Leuck A, Bruckner T, et al. Prospective multicentre cohort study of patient-reported outcomes and complications following major abdominal neoplastic surgery (PATRONUS) - study protocol for a CHIR-Net student-initiated German medical audit study (CHIR-Net SIGMA study). BMC Surg. 2018;18(1):90.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Lee L, Dumitra T, Fiore JF, Mayo NE, Feldman LS. How well are we measuring postoperative “recovery” after abdominal surgery? Qual Life Res. 2015;24(11):2583–90.

    Article  PubMed  Google Scholar 

  39. Slankamenac K, Graf R, Barkun J, Puhan MA, Clavien P-A. The comprehensive complication index: a novel continuous scale to measure surgical morbidity. Ann Surg. 2013;258(1):1–7.

    Article  PubMed  Google Scholar 

  40. Slankamenac K, Nederlof N, Pessaux P, de Jonge J, Wijnhoven BPL, Breitenstein S, et al. The comprehensive complication index: a novel and more sensitive endpoint for assessing outcome and reducing sample size in randomized controlled trials. Ann Surg. 2014;260(5):757–62 discussion 762–3.

    Article  PubMed  Google Scholar 

  41. Kleif J, Waage J, Christensen KB, Gögenur I. Systematic review of the QoR-15 score, a patient-reported outcome measure measuring quality of recovery after surgery and anaesthesia. Br J Anaesth. 2018;120(1):28–36.

    Article  CAS  PubMed  Google Scholar 

  42. Stark PA, Myles PS, Burke JA. Development and psychometric evaluation of a postoperative quality of recovery score: the QoR-15. Anesthesiology. 2013;118(6):1332–40.

    Article  PubMed  Google Scholar 

  43. Gornall BF, Myles PS, Smith CL, Burke JA, Leslie K, Pereira MJ, et al. Measurement of quality of recovery using the QoR-40: a quantitative systematic review. Br J Anaesth. 2013;111(2):161–9.

    Article  CAS  PubMed  Google Scholar 

  44. EORTC. Questionnaires at EORTC. http://groups.eortc.be/qol/eortc-qlq-c30. Accessed 22 Nov 2015.

  45. American Thoracic Society. ATS Statement: guidelines for the six-minute walk test. Am J Respir Crit Care Med. 2002;166:111–7.

    Article  Google Scholar 

  46. van Bree SHW, Bemelman WA, Hollmann MW, Zwinderman AH, Matteoli G, El Temna S, et al. Identification of clinical outcome measures for recovery of gastrointestinal motility in postoperative ileus. Ann Surg. 2014;259(4):708–14.

    Article  PubMed  Google Scholar 

  47. Boden I, Sullivan K, Hackett C, Winzer B, Lane R, McKinnon M, et al. ICEAGE (Incidence of Complications following Emergency Abdominal surgery: Get Exercising): study protocol of a pragmatic, multicentre, randomised controlled trial testing physiotherapy for the prevention of complications and improved physical recovery after emergency abdominal surgery. World J Emerg Surg. 2018;13:29.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Wolk S, Distler M, Müssle B, Söthje S, Weitz J, Welsch T. Adherence to ERAS elements in major visceral surgery-an observational pilot study. Langenbeck's Arch Surg. 2016;401(3):349–56.

    Article  Google Scholar 

  49. Hlatky MA, Boineau RE, Higginbotham MB, Lee KL, Mark DB, Califf RM, et al. A brief self-administered questionnaire to determine functional capacity (the Duke Activity Status Index). Am J Cardiol. 1989;64(10):651–4.

    Article  CAS  PubMed  Google Scholar 

  50. Dindo D, Demartines N, Clavien P-A. Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg. 2004;240(2):205–13.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Kahan BC, Harhay MO. Many multicenter trials had few events per center, requiring analysis via random-effects models or GEEs. J Clin Epidemiol. 2015;68(12):1504–11.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Chu R, Thabane L, Ma J, Holbrook A, Pullenayegum E, Devereaux PJ. Comparing methods to estimate treatment effects on a continuous outcome in multicentre randomized controlled trials: a simulation study. BMC Med Res Methodol. 2011;11(1):21.

    Article  PubMed  PubMed Central  Google Scholar 

  53. van Buuren S. Flexible imputation of missing data. Boca Raton: Chapman and Hall; 2012. http://www.crcpress.com/product/isbn/9781439868249. Accessed 15 Nov 2014.

    Book  Google Scholar 

  54. REDCap. https://www.project-redcap.org/. Accessed 5 Aug 2019.

  55. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research Electronic Data Capture (REDCap) - a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81.

    Article  PubMed  Google Scholar 

  56. Henriksen MG, Jensen MB, Hansen HV, Jespersen TW, Hessov I. Enforced mobilization, early oral feeding, and balanced analgesia improve convalescence after colorectal surgery. Nutrition. 2002;18(2):147–52.

    Article  CAS  PubMed  Google Scholar 

  57. Feo CV, Lanzara S, Sortini D, Ragazzi R, De Pinto M, Pansini GC, et al. Fast track postoperative management after elective colorectal surgery: a controlled trial. Am Surg. 2009;75(12):1247–51.

    PubMed  Google Scholar 

  58. Koea JB, Young Y, Gunn K. Fast track liver resection: the effect of a comprehensive care package and analgesia with single dose intrathecal morphine with gabapentin or continuous epidural analgesia. HPB Surg. 2009;2009:271986.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Hendry PO, van Dam RM, Bukkems SFFW, McKeown DW, Parks RW, Preston T, et al. Randomized clinical trial of laxatives and oral nutritional supplements within an enhanced recovery after surgery protocol following liver resection. Br J Surg. 2010;97(8):1198–206.

    Article  CAS  PubMed  Google Scholar 

  60. van Dam RM, Hendry PO, Coolsen MME, Bemelmans MHA, Lassen K, Revhaug A, et al. Initial experience with a multimodal enhanced recovery programme in patients undergoing liver resection. Br J Surg. 2008;95(8):969–75.

    Article  PubMed  Google Scholar 

  61. Gustafsson UO, Hausel J, Thorell A, Ljungqvist O, Soop M, Nygren J, et al. Adherence to the enhanced recovery after surgery protocol and outcomes after colorectal cancer surgery. Arch Surg. 2011;146(5):571–7.

    Article  PubMed  Google Scholar 

  62. Pearsall EA, Meghji Z, Pitzul KB, Aarts M-A, McKenzie M, McLeod RS, et al. A qualitative study to understand the barriers and enablers in implementing an enhanced recovery after surgery program. Ann Surg. 2015;261(1):92–6.

    Article  PubMed  Google Scholar 

  63. Böhm B, Karwiese SD, Böhm H, Oberhoffer R. Effects of mobile health including wearable activity trackers to increase physical activity outcomes among healthy children and adolescents: systematic review. JMIR Mhealth Uhealth. 2019;7(4):e8298.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Li Z, Peng X, Zhu B, Zhang Y, Xi X. Active mobilization for mechanically ventilated patients: a systematic review. Arch Phys Med Rehabil. 2013;94(3):551–61.

    Article  PubMed  Google Scholar 

  65. Daskivich TJ, Houman J, Lopez M, Luu M, Fleshner P, Zaghiyan K, et al. Association of wearable activity monitors with assessment of daily ambulation and length of stay among patients undergoing major surgery. JAMA Netw Open. 2019;2(2):e187673.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Alinia P, Cain C, Fallahzadeh R, Shahrokni A, Cook D, Ghasemzadeh H. How accurate is your activity tracker? A comparative study of step counts in low-intensity physical activities. JMIR Mhealth Uhealth. 2017;5(8):e106.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Evenson KR, Goto MM, Furberg RD. Systematic review of the validity and reliability of consumer-wearable activity trackers. Int J Behav Nutr Phys Act. 2015;12:159.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Khatri C, Chapman SJ, Bhangu A, Nepogodiev D, Kelly M, Glasbey JCD, et al. Promoting research and audit at medical school: evaluating the educational impact of participation in a student-led national collaborative study. BMC Med Educ. 2015;15(1):1–11.

    Article  Google Scholar 

  69. Nikkar-Esfahani A, Jamjoom AAB, Fitzgerald JEF. Extracurricular participation in research and audit by medical students: opportunities, obstacles, motivation and outcomes. Med Teach. 2012;34(5):e317–24.

    Article  PubMed  Google Scholar 

  70. STARSurg Collaborative. Multicentre prospective cohort study of body mass index and postoperative complications following gastrointestinal surgery. Br J Surg. 2016;103(9):1157–72.

    Article  Google Scholar 

  71. STARSurg Collaborative. Safety of nonsteroidal anti-inflammatory drugs in major gastrointestinal surgery: a prospective, multicenter cohort study. World J Surg. 2017;41(1):47–55.

    Article  Google Scholar 

  72. EuroSurg Collaborative. EuroSurg: a new European student-driven research network in surgery. Color Dis. 2016;18(2):214–5.

    Article  Google Scholar 

  73. IMAGINE_v2.1.pdf. Google Docs. https://drive.google.com/file/d/0B5mofOTagcEWZlU3dXZsdlV1NDA/view?usp=embed_facebook. Accessed 5 Aug 2019.

Download references

Acknowledgements

Not applicable.

Funding

We acknowledge financial support for covering the publication fees by the Deutsche Forschungsgemeinschaft, the Baden-Württemberg Ministry of Science, Research and the Arts and by Ruprecht-Karls Universität Heidelberg within the funding programme “Open Access Publishing”. No funding for and no influence on the design, conduct, analyses, interpretation or publication of the clinical trial exist.

Author information

Author notes

  1. Marius Schwab, Niall Brindl, Alexander Studier-Fischer, Thomas Tu, Julia Gsenger, Max Pilgrim, Mirco Friedrich, Pia-Elena Frey, Christina Achilles, Alexander Leuck and Thore Bürgel contributed equally to this work.

Authors and Affiliations

  1. Faculty of Medicine, University of Heidelberg, Im Neuenheimer Feld 346, 69120, Heidelberg, Germany

    Marius Schwab, Niall Brindl, Alexander Studier-Fischer, Thomas Tu, Julia Gsenger, Max Pilgrim, Mirco Friedrich, Pia-Elena Frey, Christina Achilles & Alexander Leuck

  2. Health Data Science Unit, University Hospital Heidelberg, BioQuant, Im Neuenheimer Feld 267, 69120, Heidelberg, Germany

    Thore Bürgel

  3. Institute of Medical Biometry and Informatics, University Hospital Heidelberg, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany

    Manuel Feisst & Christina Klose

  4. CHIR-Net Coordination Centre at the Study Centre of the German Surgical Society (SDGC), University Hospital Heidelberg, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany

    Solveig Tenckhoff

  5. Department of General, Visceral and Transplantation Surgery, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany

    Colette Dörr-Harim & André L. Mihaljevic

Authors
  1. Marius Schwab
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Niall Brindl
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alexander Studier-Fischer
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Thomas Tu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Julia Gsenger
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Max Pilgrim
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Mirco Friedrich
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Pia-Elena Frey
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Christina Achilles
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Alexander Leuck
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Thore Bürgel
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Manuel Feisst
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Christina Klose
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Solveig Tenckhoff
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Colette Dörr-Harim
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. André L. Mihaljevic
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

MS, NB, MFr, PF, CDH and ALM designed and planned the study and drafted this manuscript. MFe planned and wrote the statistical part of the study. ST and CDH planned the study and were involved in trial set-up and organisation. ST is coordinator of the CHIR-Net study network. CK designed and wrote the data management part of the study. ALM and JG are CHIR-Net speakers and were involved in set-up of the study, organisation of trial sites and supervision of the project. All authors critically reviewed the manuscript for intellectual content and read and approved the final manuscript.

Corresponding author

Correspondence to André L. Mihaljevic.

Ethics declarations

Ethics approval and consent to participate

Ethical approval was granted by the independent ethics committee of the Medical Faculty of the University of Heidelberg on 22 March 2019 (version 1.1; reference S-099/2019) including the patient information material and informed consent form. The ethics approval of other participating centres is currently sought. All protocol amendments must be reported to and approved by the participating independent ethics committees. All amendments will be communicated immediately to the participating trial sites. Informed consent will be obtained from all study participants prior to inclusion. It will be emphasised that participation is voluntary and that the patient is allowed to refuse further participation in the study whenever he/she wants to. The EXPELLIARMUS trial will be conducted in agreement with the current version of the Declaration of Helsinki. This study protocol has been written and the study will be conducted and analysed in accordance with relevant national and international rules and regulations including International Conference of Harmonisation of Good Clinical Practice (ICH-GCP) guidelines. This trial will be conducted with no external funding and was instead funded from in-house sources of the Department of General, Visceral and Transplantation Surgery, University Hospital Heidelberg. Financial support for covering the publication fees of this article was given by the Deutsche Forschungsgemeinschaft, the Baden-Württemberg Ministry of Science, Research and the Arts and by Ruprecht-Karls Universität Heidelberg within the funding programme “Open Access Publishing”.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Schwab, M., Brindl, N., Studier-Fischer, A. et al. Postoperative complications and mobilisation following major abdominal surgery with vs. without fitness tracker-based feedback (EXPELLIARMUS): study protocol for a student-led multicentre randomised controlled trial (CHIR-Net SIGMA study group). Trials 21, 293 (2020). https://doi.org/10.1186/s13063-020-4220-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13063-020-4220-8

Keywords

Trials

ISSN: 1745-6215