<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT04477746</url>
  </required_header>
  <id_info>
    <org_study_id>FHMREC19052</org_study_id>
    <nct_id>NCT04477746</nct_id>
  </id_info>
  <brief_title>Surgeon Ergonomics in Robotic-assisted Laparoscopic Vs Standard Laparoscopic Surgery</brief_title>
  <acronym>MURALS</acronym>
  <official_title>Comparing the Musculoskeletal Demands of Surgeons Performing Robotic-assisted Laparoscopic Surgery and Standard Laparoscopic Surgery</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Lancaster University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>National Health Service, United Kingdom</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Lancaster University</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      Musculoskeletal injuries amongst surgeons are prevalent. This project will determine whether&#xD;
      Robotic-assisted Laparoscopic surgery (RALS) offers superior benefits to surgeon's&#xD;
      musculoskeletal health than standard laparoscopic surgery (LS), by identifying the&#xD;
      comparative changes in muscle fatigue during RALS Vs LS surgical procedures, and additionally&#xD;
      identify any cognitive effects of this. The Study if successful, could help reduce injury&#xD;
      rates in surgeons.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The number of surgical procedures being performed using minimal access techniques is on the&#xD;
      rise because of improved recovery times for patients. Thus, surgeons are performing an&#xD;
      increasing number of endoscopic/laparoscopic procedures and are operating for longer periods.&#xD;
      A recent meta-analysis showed that work-related musculoskeletal injuries amongst surgeons are&#xD;
      common (1) and surgeons are amongst those most at risk of work-related musculoskeletal&#xD;
      decline (2). Indeed, the prevalence of degenerative spinal disease is 17%, rotator cuff&#xD;
      pathology 18%, and degenerative lumbar spine disease is 19% (1). Surgeon's experience&#xD;
      work-related musculoskeletal pain in addition to injury, and pain is highly prevalent in the&#xD;
      neck (48%), shoulder (43%), and back (50%) (13).&#xD;
&#xD;
      According to the Office for National Statistics in the UK, musculoskeletal problems amongst&#xD;
      the workforce are the second most common cause for absence (17.7%) and account for 23 days&#xD;
      absence/year (2). This is not dissimilar in the US where the Bureau of Labour Statistics&#xD;
      estimates that 62% of all worker injuries and 32% of missed days from work result from&#xD;
      musculoskeletal problems. Collectively, these data suggest that musculoskeletal problems&#xD;
      caused by careers in surgery can reduce physical health, which is associated with reduced&#xD;
      productivity, career longevity, and even the quality of patient care.&#xD;
&#xD;
      Robotic-assisted laparoscopic surgery (RALS) is a modern technology that could help mitigate&#xD;
      these musculoskeletal problems and thereby improve patient care. In comparison to standard&#xD;
      laparoscopic surgery (LS), RALS offers steadier wrist movements with a reduced fulcrum&#xD;
      effect, thus benefiting the patient (3). There is emerging evidence that RALS is associated&#xD;
      with a lower rate of musculoskeletal problems (23-80%) than LS (70- 100%) (1). RALS may&#xD;
      therefore be an attractive alternative to LS, despite the high cost of equipment and steep&#xD;
      learning curve during training.&#xD;
&#xD;
      No study has compared the demands of RALS vs. LS on musculoskeletal fatigue (and subsequent&#xD;
      injury risk) and whether these changes are underpinned by changes in cognitive fatigue. The&#xD;
      investigators aim to determine whether a career using RALS is associated with better&#xD;
      musculoskeletal health for surgeons than standard LS when performing complex minimally&#xD;
      invasive procedures.&#xD;
&#xD;
      The hypothesis is that RALS will reduce musculoskeletal fatigue and the prevalence of&#xD;
      musculoskeletal injury in surgeons compared to LS. If this is true, RALS should receive&#xD;
      increased support through preserving surgeon's health and thereby reducing costs for&#xD;
      healthcare providers.&#xD;
&#xD;
      Research subjects (surgeons and patients) Surgeons: Investigators will recruit surgeons&#xD;
      completing surgical procedures who have similar levels of experience between RALS and LS&#xD;
      groups. Surgeons will fill a questionnaire regarding working hours and experience, physical&#xD;
      activity level (e.g., sport, bicycling to work or gardening), general health conditions and&#xD;
      musculoskeletal symptoms within the last 12 months using the Standardized Nordic&#xD;
      questionnaires for the analysis of musculoskeletal symptoms (11). The investigators will also&#xD;
      quantify body composition (height, body weight, BMI, muscle mass, fat mass) using&#xD;
      clinically-validated bioelectrical impedance analysis. Surgeons will broadly be matched for&#xD;
      age and surgical experience, anthropometry, and sex. Patients: To complete the work, the&#xD;
      investigators will use data from n = 40 patients being operated upon in RALS and n = 40 LS&#xD;
      groups that will be age, sex, BMI, and pre-operative risk score matched.&#xD;
&#xD;
      Surgical procedure and overall study design Data will be collected during index procedures:&#xD;
      For example prostatectomy or anterior resection using either RALS or LS. Before surgery,&#xD;
      surgeons are fitted with both EMG (to measure muscle fatigue) and EEG (to measure cognitive&#xD;
      fatigue). Surgeons will complete a series of validated questionnaires before and after each&#xD;
      surgery to subjectively determine musculoskeletal strain/pain and cognitive fatigue.&#xD;
&#xD;
      This research is being conducted in real-life surgery and controlling conditions between&#xD;
      operations is uniquely challenging. The study will exclude any operations where complications&#xD;
      result in the surgery taking beyond 50% of the mean average surgery time, to prevent this&#xD;
      skewing the data towards an effect for musculoskeletal fatigue. This mean average time will&#xD;
      also include for specific procedures e.g. Prostatectomy - defining resection margins by&#xD;
      dissecting the endopelvic fascia and mobilising seminal vesicles, rectum and bladder neck,&#xD;
      defining and transecting the prostatic pedicles; transecting the bladder neck, urethra, and&#xD;
      prostate; anastomosing the urethra to bladder neck. Bowel surgery - identifying, transecting&#xD;
      and ligating the pedicle; lateral mobilisation and preserving ureters, and bowel anastomosis.&#xD;
&#xD;
      The investigators will assess acute fatigue by comparing RALS and LS within a single surgery&#xD;
      that is the first surgery of any given day. To determine the cumulative fatigue (chronic&#xD;
      effects of surgery, aim 2), comparison will be made between the subject's first and last&#xD;
      surgery of the day when &gt;2 surgeries have been completed.&#xD;
&#xD;
      Measurement of musculoskeletal fatigue (EMG) EMG justification. The study will utilise&#xD;
      electromyography (EMG) to determine acute and chronic changes in musculoskeletal demands&#xD;
      associated with RALS and LS surgery. Surface EMG is a non-invasive procedure that measures&#xD;
      muscle activity by recording the electrical signal generated during muscle fibre recruitment.&#xD;
      Its ability to assess fatigue has been long established (e.g. (4)) and it has been widely&#xD;
      used in many populations, including athletes (e.g. (5)), dentists (6) and surgeons (e.g.&#xD;
      (7,8)) EMG will be collected for 200 s (9) at 0, 30, 60, 90 and 120 minutes of a ~2-hour&#xD;
      surgical procedure. In addition to these time points, EMG data will be collected during&#xD;
      clinically important tasks (e.g. suturing upon completion of surgery, which typically will&#xD;
      take 10 minutes).&#xD;
&#xD;
      EMG protocol. Surgeons will provide written informed consent prior to participation. Surgeons&#xD;
      will be completing index procedures: For example prostatectomy or anterior resection using&#xD;
      either RALS or LS; the protocol for EMG data collection will be identical. Before surgery,&#xD;
      surgeons will be fitted with wireless EMG sensors. The EMG data collection procedures will&#xD;
      follow established protocols regarding site preparation and electrode placement, as well as&#xD;
      data collection, processing and normalisation (7,12). Briefly, the site will be shaved and&#xD;
      cleansed with alcohol wipes, with the bipolar electrodes placed on the belly of the muscle&#xD;
      and parallel to the muscle's fibres having an inter-electrode distance of 20mm (12).&#xD;
      Electrodes will be placed on muscles of the arm, neck, shoulder and back e.g. flexor carpi&#xD;
      radialis muscles, biceps muscle, bilaterally from the trapezius muscles, and bilaterally from&#xD;
      the erector spinae muscle. These muscles have been selected based on a recent meta-analysis&#xD;
      (13). Electrodes are fitted before surgeons' scrub for surgery and electrodes will be covered&#xD;
      by surgical gowns thereby maintaining a sterile theatre. A wireless EMG system has been&#xD;
      selected so that it is minimally invasive and does not impede a surgeon's movement with&#xD;
      wires.&#xD;
&#xD;
      EMG data analysis. Data will be collected and analysed using EMG Works (Delsys Inc., Boston,&#xD;
      MA, USA), with recommended normalisation, sampling, filtering and smoothing techniques (7).&#xD;
      EMG recordings in previous data show significant changes during LS procedures in 70 - 85% of&#xD;
      surgeons, mainly in neck, shoulders, hands, lower back, and lower extremities muscles. The&#xD;
      recordings from muscles of the arm, neck, shoulder and back will be monitored but lower limb&#xD;
      muscles will not be included because during RALS, Surgeons are seated away from the patient&#xD;
      and having brow- and armrests considerably modifies the workload on the lower limbs making&#xD;
      comparisons of lower-limb muscles in LS not meaningful. Once the EMG signal has been&#xD;
      normalised (10), basic EMG variables, such as frequency and amplitude, can provide&#xD;
      information on how muscle fibre recruitment has changed, both at a single muscle as well&#xD;
      across several muscles (activation / recruitment strategies), while a fatigue score can also&#xD;
      be calculated (11). The normalisation process can afford the ability to compare between&#xD;
      muscles as well as examine the muscles' activity different time points (i.e. within the same&#xD;
      session or after a longer time has elapsed; e.g. (5,12,13).&#xD;
&#xD;
      Measurement of cognitive fatigue (EEG) EEG justification. The study will use&#xD;
      electroencephalography (EEG) to determine if acute or chronic changes in musculoskeletal&#xD;
      demands are associated with changes in motor control and cognitive fatigue. Cognitive fatigue&#xD;
      can be determined via neurophysiological measures, such as the electroencephalogram. The EEG&#xD;
      can measure the ongoing electrical activity of the brain during a given task, such as whilst&#xD;
      driving or during surgery. EEG measures of fatigue can provide an objective quantification of&#xD;
      an individual's cognitive state in real-time, removing reliance on subjective measures such&#xD;
      as self-report or questionnaires that have been found to be unreliable for moderate fatigue&#xD;
      states. The brain oscillates at a number of different frequencies at any given time, and this&#xD;
      information is recorded in the EEG. The power of certain frequency bands has been taken as a&#xD;
      proxy to index cognitive fatigue. Specifically, evidence indicates that alpha-band power&#xD;
      (7-13 Hz) is sensitive to fatigue (for a review see (14)), and has been used to measure&#xD;
      driver fatigue both in real-traffic and simulation exercises (15- 18). When fatigue&#xD;
      increases, alpha-band activity occurs in bursts of 500 milliseconds, which are known as alpha&#xD;
      spindles (19). Alpha spindles are considered to reflect individual fatigue states and can be&#xD;
      quantified in terms of their peak frequency, duration, and amplitude, giving rise to an&#xD;
      individual's alpha signature (20).&#xD;
&#xD;
      EEG protocol. Whilst surgeons are having EMG electrodes fitted, a similar procedure will be&#xD;
      completed for the wireless EEG electrodes. The skin site on the head will be prepared as&#xD;
      previously described (21) and the electrode gel and electrode cap will be applied before the&#xD;
      surgical cap, thereby maintaining the sterility of the surgical theatre. Electrodes will be&#xD;
      placed over the cortex using an 8-channel electrode montage to record ongoing EEG&#xD;
      oscillations during surgery for 200 s (9) at 0, 30, 60, 90 and 120 minutes of a ~2-hour&#xD;
      surgical procedure. Electrodes will be positioned according to the 10-20 international&#xD;
      electrode placement system. The main EEG channels of interest will be positioned over the&#xD;
      occipital and parietal cortex, namely electrode locations O1, O2, P3, P4, P7, P8 where&#xD;
      maximal alpha activity can be detected. In addition to these time points, EEG data will be&#xD;
      collected during clinically important tasks (e.g. suturing upon completion of surgery, which&#xD;
      typically will take 10 minutes). A wireless EEG system has been selected so that it is&#xD;
      minimally invasive and does not cause distraction or restriction due to movement of wires.&#xD;
&#xD;
      EEG data analysis. Data will be collected and analysed using Enobio 8 5G (Neuroelectrics,&#xD;
      Cambridge, MA, USA) using standard referencing, sampling, filtering and smoothing techniques&#xD;
      (21). Investigators will compare peak alpha power, and alpha spindle duration and amplitude,&#xD;
      in RALS compared to LS. Changes in EEG power spectra, specifically in the alpha frequency&#xD;
      band, will be used to monitor alertness, and will provide crucial information about whether&#xD;
      cognitive fatigue, underpins any musculoskeletal fatigue. The study will also be able to&#xD;
      identify how alertness changes over time during surgery through the EEG power spectra.&#xD;
&#xD;
      Measurements of surgeon physical activity and musculoskeletal health It is vital that&#xD;
      musculoskeletal fatigue in the surgeons is not influenced by anything other than the work&#xD;
      environment. We will use tri-axial accelerometery every week throughout data collection to&#xD;
      measure and ensure surgeons are not changing their physical activity patterns (and thus&#xD;
      getting stronger or weaker). Nutrition is also critical in the development of strength, just&#xD;
      like poor nutrition can lead to strength loss. Therefore, surgeons will complete 3-day food&#xD;
      diaries and dietary analysis at weekly intervals throughout the data collection period.&#xD;
&#xD;
      Statistics and data analysis. Power calculation: To address aim 1, The investigators&#xD;
      anticipate a difference in musculoskeletal fatigue of 20% between RALS and LS based upon the&#xD;
      limited evidence available (1). Therefore, based on a predicted effect size (Cohen's d) of&#xD;
      0.82, recruitment of 40 subjects in RALS and 40 subjects in LS (total sample size n = 80)&#xD;
      will be carried out. These numbers will be matched between prostate and bowel surgeries. In&#xD;
      aim 2, data suggest that the level of fatigue between the last surgery of the day versus the&#xD;
      first will be greater than the difference in aim 1 (Cohen's d 0.90), therefore 27&#xD;
      subjects/group are required for this research question. Lastly in aim 3 to investigate&#xD;
      whether changes in musculoskeletal fatigue are underpinned by changes in motor control and&#xD;
      cognitive fatigue, The investigators anticipate an effect size of 0.85 between RALS and LS&#xD;
      and therefore will use data from the 31/group to study this effect. An A priori power&#xD;
      calculation will be used to compute the required sample size using G*Power 3 (22).&#xD;
      Conservatively, the lower of the three values for the power calculation (an effect size of&#xD;
      0.82) has been chosen. Assuming a Cohen's d of 0.82 requires 40 participants per group for&#xD;
      90% power to detect a difference between groups, at an alpha of 0.05.&#xD;
&#xD;
      Statistical analysis: To determine differences in musculoskeletal and cognitive fatigue in&#xD;
      RALS and LS, a mixed-model ANOVA or non-parametric equivalent will be utilised. The data and&#xD;
      conclusions arrived at the end of the study will inform recommendations both in scientific&#xD;
      literature (publications) and dissemination at conferences towards the end of the project&#xD;
      (see Gantt chart). The study is the platform to develop a strong case regarding the long-term&#xD;
      musculoskeletal effects on surgeons performing minimal access procedures in RALS.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">November 12, 2020</start_date>
  <completion_date type="Actual">March 30, 2022</completion_date>
  <primary_completion_date type="Actual">October 30, 2021</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>EMG measurements of Maximal Voluntary Contraction (MVC), frequency and amplitude of contractions across muscle fibres to establish the musculoskeletal demands (demonstrated as muscle fatigue) of RALS and LS surgery</measure>
    <time_frame>Over the 12 weeks of participants involvement in study</time_frame>
  </primary_outcome>
  <secondary_outcome>
    <measure>EEG measurements of peak alpha power, and alpha spindle duration and amplitude during the surgical procedures to determine if changes in musculoskeletal demands are associated with changes in motor control and cognitive fatigue.</measure>
    <time_frame>Over the 12 weeks of participants involvement in study</time_frame>
  </secondary_outcome>
  <number_of_groups>2</number_of_groups>
  <enrollment type="Actual">13</enrollment>
  <condition>Musculoskeletal Pain</condition>
  <condition>Musculoskeletal Strain</condition>
  <condition>Fatigue; Muscle, Heart</condition>
  <condition>Cognitive Impairment</condition>
  <arm_group>
    <arm_group_label>Standard Laparoscopy group (LS)</arm_group_label>
    <description>7 surgeons performing surgical procedures using the standard laparoscopic approach</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Robot- assisted laparoscopic group (RALS)</arm_group_label>
    <description>6 surgeons performing surgical procedures using the robot-assisted laparoscopic approach</description>
  </arm_group>
  <eligibility>
    <study_pop>
      <textblock>
        Surgeons: We will recruit 8 - 10 surgeons per study group (RALS and LS) from four&#xD;
        specialties; Urology, Gynaecology, Colorectal and Hepatobiliary Surgery, with experience in&#xD;
        RALS and LS. They will be monitored performing Four procedures that are broadly 2-hour&#xD;
        long. They will broadly be matched for age and surgical experience, anthropometry, and sex.&#xD;
        They will fill a questionnaire regarding working hours and experience, physical activity&#xD;
        level, general health conditions and musculoskeletal symptoms within the last 12 months&#xD;
        using the Standardized Nordic questionnaires for the analysis of musculoskeletal symptoms&#xD;
        (11). We will quantify body composition using clinically validated bioelectrical impedance&#xD;
        analysis.&#xD;
&#xD;
        Patients: To complete the work, we will use the data obtained from surgeons operating on n&#xD;
        = 40 patients in RALS and n = 40 LS groups. Patients will be matched for characteristics&#xD;
        including sex, age, body mass index (BMI), and pre-operative risk scores.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Healthy surgeons with experience in performing procedures using LS and/or RALS.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Significant co-morbidities&#xD;
&#xD;
          -  Significant musculoskeletal symptoms&#xD;
&#xD;
          -  Procedures that include major complications or requiring &gt;50% more time than the mean&#xD;
             average&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <location>
    <facility>
      <name>East Lancashire Hospitals NHS Trust</name>
      <address>
        <city>Blackburn</city>
        <state>Lancashire</state>
        <zip>BB2 3HH</zip>
        <country>United Kingdom</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Lancashire Teaching Hospitals NHS Foundation Trust</name>
      <address>
        <city>Preston</city>
        <state>Lancashire</state>
        <zip>PR2 9HT</zip>
        <country>United Kingdom</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United Kingdom</country>
  </location_countries>
  <verification_date>September 2022</verification_date>
  <study_first_submitted>July 15, 2020</study_first_submitted>
  <study_first_submitted_qc>July 15, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">July 20, 2020</study_first_posted>
  <last_update_submitted>September 16, 2022</last_update_submitted>
  <last_update_submitted_qc>September 16, 2022</last_update_submitted_qc>
  <last_update_posted type="Actual">September 19, 2022</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Lancaster University</investigator_affiliation>
    <investigator_full_name>Abdulwarith Shugaba</investigator_full_name>
    <investigator_title>Principal Investigator</investigator_title>
  </responsible_party>
  <keyword>Robot-Assisted Laparoscopic</keyword>
  <keyword>Standard Laparoscopic</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Musculoskeletal Pain</mesh_term>
  </condition_browse>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT04477746
org study id: FHMREC19052
nct id: NCT04477746
lead sponsor: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
Musculoskeletal injuries amongst surgeons are prevalent. This project will determine whether
      Robotic-assisted Laparoscopic surgery (RALS) offers superior benefits to surgeon's
      musculoskeletal health than standard laparoscopic surgery (LS), by identifying the
      comparative changes in muscle fatigue during RALS Vs LS surgical procedures, and additionally
      identify any cognitive effects of this. The Study if successful, could help reduce injury
      rates in surgeons.
The number of surgical procedures being performed using minimal access techniques is on the
      rise because of improved recovery times for patients. Thus, surgeons are performing an
      increasing number of endoscopic/laparoscopic procedures and are operating for longer periods.
      A recent meta-analysis showed that work-related musculoskeletal injuries amongst surgeons are
      common (1) and surgeons are amongst those most at risk of work-related musculoskeletal
      decline (2). Indeed, the prevalence of degenerative spinal disease is 17%, rotator cuff
      pathology 18%, and degenerative lumbar spine disease is 19% (1). Surgeon's experience
      work-related musculoskeletal pain in addition to injury, and pain is highly prevalent in the
      neck (48%), shoulder (43%), and back (50%) (13).

      According to the Office for National Statistics in the UK, musculoskeletal problems amongst
      the workforce are the second most common cause for absence (17.7%) and account for 23 days
      absence/year (2). This is not dissimilar in the US where the Bureau of Labour Statistics
      estimates that 62% of all worker injuries and 32% of missed days from work result from
      musculoskeletal problems. Collectively, these data suggest that musculoskeletal problems
      caused by careers in surgery can reduce physical health, which is associated with reduced
      productivity, career longevity, and even the quality of patient care.

      Robotic-assisted laparoscopic surgery (RALS) is a modern technology that could help mitigate
      these musculoskeletal problems and thereby improve patient care. In comparison to standard
      laparoscopic surgery (LS), RALS offers steadier wrist movements with a reduced fulcrum
      effect, thus benefiting the patient (3). There is emerging evidence that RALS is associated
      with a lower rate of musculoskeletal problems (23-80%) than LS (70- 100%) (1). RALS may
      therefore be an attractive alternative to LS, despite the high cost of equipment and steep
      learning curve during training.

      No study has compared the demands of RALS vs. LS on musculoskeletal fatigue (and subsequent
      injury risk) and whether these changes are underpinned by changes in cognitive fatigue. The
      investigators aim to determine whether a career using RALS is associated with better
      musculoskeletal health for surgeons than standard LS when performing complex minimally
      invasive procedures.

      The hypothesis is that RALS will reduce musculoskeletal fatigue and the prevalence of
      musculoskeletal injury in surgeons compared to LS. If this is true, RALS should receive
      increased support through preserving surgeon's health and thereby reducing costs for
      healthcare providers.

      Research subjects (surgeons and patients) Surgeons: Investigators will recruit surgeons
      completing surgical procedures who have similar levels of experience between RALS and LS
      groups. Surgeons will fill a questionnaire regarding working hours and experience, physical
      activity level (e.g., sport, bicycling to work or gardening), general health conditions and
      musculoskeletal symptoms within the last 12 months using the Standardized Nordic
      questionnaires for the analysis of musculoskeletal symptoms (11). The investigators will also
      quantify body composition (height, body weight, BMI, muscle mass, fat mass) using
      clinically-validated bioelectrical impedance analysis. Surgeons will broadly be matched for
      age and surgical experience, anthropometry, and sex. Patients: To complete the work, the
      investigators will use data from n = 40 patients being operated upon in RALS and n = 40 LS
      groups that will be age, sex, BMI, and pre-operative risk score matched.

      Surgical procedure and overall study design Data will be collected during index procedures:
      For example prostatectomy or anterior resection using either RALS or LS. Before surgery,
      surgeons are fitted with both EMG (to measure muscle fatigue) and EEG (to measure cognitive
      fatigue). Surgeons will complete a series of validated questionnaires before and after each
      surgery to subjectively determine musculoskeletal strain/pain and cognitive fatigue.

      This research is being conducted in real-life surgery and controlling conditions between
      operations is uniquely challenging. The study will exclude any operations where complications
      result in the surgery taking beyond 50% of the mean average surgery time, to prevent this
      skewing the data towards an effect for musculoskeletal fatigue. This mean average time will
      also include for specific procedures e.g. Prostatectomy - defining resection margins by
      dissecting the endopelvic fascia and mobilising seminal vesicles, rectum and bladder neck,
      defining and transecting the prostatic pedicles; transecting the bladder neck, urethra, and
      prostate; anastomosing the urethra to bladder neck. Bowel surgery - identifying, transecting
      and ligating the pedicle; lateral mobilisation and preserving ureters, and bowel anastomosis.

      The investigators will assess acute fatigue by comparing RALS and LS within a single surgery
      that is the first surgery of any given day. To determine the cumulative fatigue (chronic
      effects of surgery, aim 2), comparison will be made between the subject's first and last
      surgery of the day when >2 surgeries have been completed.

      Measurement of musculoskeletal fatigue (EMG) EMG justification. The study will utilise
      electromyography (EMG) to determine acute and chronic changes in musculoskeletal demands
      associated with RALS and LS surgery. Surface EMG is a non-invasive procedure that measures
      muscle activity by recording the electrical signal generated during muscle fibre recruitment.
      Its ability to assess fatigue has been long established (e.g. (4)) and it has been widely
      used in many populations, including athletes (e.g. (5)), dentists (6) and surgeons (e.g.
      (7,8)) EMG will be collected for 200 s (9) at 0, 30, 60, 90 and 120 minutes of a ~2-hour
      surgical procedure. In addition to these time points, EMG data will be collected during
      clinically important tasks (e.g. suturing upon completion of surgery, which typically will
      take 10 minutes).

      EMG protocol. Surgeons will provide written informed consent prior to participation. Surgeons
      will be completing index procedures: For example prostatectomy or anterior resection using
      either RALS or LS; the protocol for EMG data collection will be identical. Before surgery,
      surgeons will be fitted with wireless EMG sensors. The EMG data collection procedures will
      follow established protocols regarding site preparation and electrode placement, as well as
      data collection, processing and normalisation (7,12). Briefly, the site will be shaved and
      cleansed with alcohol wipes, with the bipolar electrodes placed on the belly of the muscle
      and parallel to the muscle's fibres having an inter-electrode distance of 20mm (12).
      Electrodes will be placed on muscles of the arm, neck, shoulder and back e.g. flexor carpi
      radialis muscles, biceps muscle, bilaterally from the trapezius muscles, and bilaterally from
      the erector spinae muscle. These muscles have been selected based on a recent meta-analysis
      (13). Electrodes are fitted before surgeons' scrub for surgery and electrodes will be covered
      by surgical gowns thereby maintaining a sterile theatre. A wireless EMG system has been
      selected so that it is minimally invasive and does not impede a surgeon's movement with
      wires.

      EMG data analysis. Data will be collected and analysed using EMG Works (Delsys Inc., Boston,
      MA, USA), with recommended normalisation, sampling, filtering and smoothing techniques (7).
      EMG recordings in previous data show significant changes during LS procedures in 70 - 85% of
      surgeons, mainly in neck, shoulders, hands, lower back, and lower extremities muscles. The
      recordings from muscles of the arm, neck, shoulder and back will be monitored but lower limb
      muscles will not be included because during RALS, Surgeons are seated away from the patient
      and having brow- and armrests considerably modifies the workload on the lower limbs making
      comparisons of lower-limb muscles in LS not meaningful. Once the EMG signal has been
      normalised (10), basic EMG variables, such as frequency and amplitude, can provide
      information on how muscle fibre recruitment has changed, both at a single muscle as well
      across several muscles (activation / recruitment strategies), while a fatigue score can also
      be calculated (11). The normalisation process can afford the ability to compare between
      muscles as well as examine the muscles' activity different time points (i.e. within the same
      session or after a longer time has elapsed; e.g. (5,12,13).

      Measurement of cognitive fatigue (EEG) EEG justification. The study will use
      electroencephalography (EEG) to determine if acute or chronic changes in musculoskeletal
      demands are associated with changes in motor control and cognitive fatigue. Cognitive fatigue
      can be determined via neurophysiological measures, such as the electroencephalogram. The EEG
      can measure the ongoing electrical activity of the brain during a given task, such as whilst
      driving or during surgery. EEG measures of fatigue can provide an objective quantification of
      an individual's cognitive state in real-time, removing reliance on subjective measures such
      as self-report or questionnaires that have been found to be unreliable for moderate fatigue
      states. The brain oscillates at a number of different frequencies at any given time, and this
      information is recorded in the EEG. The power of certain frequency bands has been taken as a
      proxy to index cognitive fatigue. Specifically, evidence indicates that alpha-band power
      (7-13 Hz) is sensitive to fatigue (for a review see (14)), and has been used to measure
      driver fatigue both in real-traffic and simulation exercises (15- 18). When fatigue
      increases, alpha-band activity occurs in bursts of 500 milliseconds, which are known as alpha
      spindles (19). Alpha spindles are considered to reflect individual fatigue states and can be
      quantified in terms of their peak frequency, duration, and amplitude, giving rise to an
      individual's alpha signature (20).

      EEG protocol. Whilst surgeons are having EMG electrodes fitted, a similar procedure will be
      completed for the wireless EEG electrodes. The skin site on the head will be prepared as
      previously described (21) and the electrode gel and electrode cap will be applied before the
      surgical cap, thereby maintaining the sterility of the surgical theatre. Electrodes will be
      placed over the cortex using an 8-channel electrode montage to record ongoing EEG
      oscillations during surgery for 200 s (9) at 0, 30, 60, 90 and 120 minutes of a ~2-hour
      surgical procedure. Electrodes will be positioned according to the 10-20 international
      electrode placement system. The main EEG channels of interest will be positioned over the
      occipital and parietal cortex, namely electrode locations O1, O2, P3, P4, P7, P8 where
      maximal alpha activity can be detected. In addition to these time points, EEG data will be
      collected during clinically important tasks (e.g. suturing upon completion of surgery, which
      typically will take 10 minutes). A wireless EEG system has been selected so that it is
      minimally invasive and does not cause distraction or restriction due to movement of wires.

      EEG data analysis. Data will be collected and analysed using Enobio 8 5G (Neuroelectrics,
      Cambridge, MA, USA) using standard referencing, sampling, filtering and smoothing techniques
      (21). Investigators will compare peak alpha power, and alpha spindle duration and amplitude,
      in RALS compared to LS. Changes in EEG power spectra, specifically in the alpha frequency
      band, will be used to monitor alertness, and will provide crucial information about whether
      cognitive fatigue, underpins any musculoskeletal fatigue. The study will also be able to
      identify how alertness changes over time during surgery through the EEG power spectra.

      Measurements of surgeon physical activity and musculoskeletal health It is vital that
      musculoskeletal fatigue in the surgeons is not influenced by anything other than the work
      environment. We will use tri-axial accelerometery every week throughout data collection to
      measure and ensure surgeons are not changing their physical activity patterns (and thus
      getting stronger or weaker). Nutrition is also critical in the development of strength, just
      like poor nutrition can lead to strength loss. Therefore, surgeons will complete 3-day food
      diaries and dietary analysis at weekly intervals throughout the data collection period.

      Statistics and data analysis. Power calculation: To address aim 1, The investigators
      anticipate a difference in musculoskeletal fatigue of 20% between RALS and LS based upon the
      limited evidence available (1). Therefore, based on a predicted effect size (Cohen's d) of
      0.82, recruitment of 40 subjects in RALS and 40 subjects in LS (total sample size n = 80)
      will be carried out. These numbers will be matched between prostate and bowel surgeries. In
      aim 2, data suggest that the level of fatigue between the last surgery of the day versus the
      first will be greater than the difference in aim 1 (Cohen's d 0.90), therefore 27
      subjects/group are required for this research question. Lastly in aim 3 to investigate
      whether changes in musculoskeletal fatigue are underpinned by changes in motor control and
      cognitive fatigue, The investigators anticipate an effect size of 0.85 between RALS and LS
      and therefore will use data from the 31/group to study this effect. An A priori power
      calculation will be used to compute the required sample size using G*Power 3 (22).
      Conservatively, the lower of the three values for the power calculation (an effect size of
      0.82) has been chosen. Assuming a Cohen's d of 0.82 requires 40 participants per group for
      90% power to detect a difference between groups, at an alpha of 0.05.

      Statistical analysis: To determine differences in musculoskeletal and cognitive fatigue in
      RALS and LS, a mixed-model ANOVA or non-parametric equivalent will be utilised. The data and
      conclusions arrived at the end of the study will inform recommendations both in scientific
      literature (publications) and dissemination at conferences towards the end of the project
      (see Gantt chart). The study is the platform to develop a strong case regarding the long-term
      musculoskeletal effects on surgeons performing minimal access procedures in RALS.
observational model: Cohort
time perspective: Prospective
measure: EMG measurements of Maximal Voluntary Contraction (MVC), frequency and amplitude of contractions across muscle fibres to establish the musculoskeletal demands (demonstrated as muscle fatigue) of RALS and LS surgery
time frame: Over the 12 weeks of participants involvement in study
measure: EEG measurements of peak alpha power, and alpha spindle duration and amplitude during the surgical procedures to determine if changes in musculoskeletal demands are associated with changes in motor control and cognitive fatigue.
time frame: Over the 12 weeks of participants involvement in study
arm group label: Standard Laparoscopy group (LS)
description: 7 surgeons performing surgical procedures using the standard laparoscopic approach
arm group label: Robot- assisted laparoscopic group (RALS)
description: 6 surgeons performing surgical procedures using the robot-assisted laparoscopic approach
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: Accepts Healthy Volunteers
facility: 
facility: 
country: United Kingdom
responsible party type: Principal Investigator
investigator affiliation: Lancaster University
investigator full name: Abdulwarith Shugaba
investigator title: Principal Investigator
mesh term: Musculoskeletal Pain