Surgeon Ergonomics in Robotic-assisted Laparoscopic Vs Standard Laparoscopic Surgery

NCT ID: NCT04477746

Last Updated: 2022-09-19

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 13 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2020-11-12
• Study Completion Date: 2022-03-30

Brief Summary

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.

Detailed Description

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.

Conditions

Musculoskeletal Pain; Musculoskeletal Strain; Fatigue; Muscle, Heart; Cognitive Impairment

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

Standard Laparoscopy group (LS)

7 surgeons performing surgical procedures using the standard laparoscopic approach

No interventions assigned to this group

Robot- assisted laparoscopic group (RALS)

6 surgeons performing surgical procedures using the robot-assisted laparoscopic approach

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

• Healthy surgeons with experience in performing procedures using LS and/or RALS.

Exclusion Criteria

• Significant co-morbidities
• Significant musculoskeletal symptoms
• Procedures that include major complications or requiring >50% more time than the mean average

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

National Health Service, United Kingdom

OTHER_GOV

Sponsor Role: collaborator

Lancaster University

OTHER

Sponsor Role: lead

Responsible Party

Abdulwarith Shugaba

Principal Investigator

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

East Lancashire Hospitals NHS Trust

Blackburn, Lancashire, United Kingdom

Lancashire Teaching Hospitals NHS Foundation Trust

Preston, Lancashire, United Kingdom

Countries

United Kingdom

Other Identifiers

FHMREC19052

Identifier Type: -

Identifier Source: org_study_id