Laparoscopic surgical box model training for surgical trainees with limited prior laparoscopic experience

  • Protocol
  • Intervention

Authors


Abstract

This is the protocol for a review and there is no abstract. The objectives are as follows:

To compare the benefits and harms of box model training for surgical trainees with limited prior laparoscopic experience.

Background

Description of the condition

Surgical training has traditionally been one of apprenticeship, where the surgical trainee learns to perform surgery under the supervision of a trained surgeon. Different procedures have different learning curves (Herrell 2005; Tekkis 2005a; Tekkis 2005b). Surgeons experienced in one procedure may not be experienced in another, and results improve with experience in an individual procedure (Herrell 2005; Tekkis 2005a; Tekkis 2005b).

An increasing number of surgical procedures are being done laparoscopically (abdominal key hole surgery). This includes laparoscopic cholecystectomy (removal of gallbladder), laparoscopic anti-reflux procedures (surgery for heartburn), laparoscopic hysterectomy (removal of uterus), and laparoscopic nephrectomy (removal of kidney) (Ghezzi 2006; Keus 2006; Salminen 2007; Venkatesh 2007). The different methods of laparoscopic surgical training include live animal training, human and animal cadaver training, training using a box trainer (also called video trainer), and virtual reality training (training using computer simulation) (Munz 2004).

Although the price of the simulators can vary depending upon the learning outcome, traditional training is not without costs. The operating time increases significantly for junior surgeons compared to senior surgeons (Farnworth 2001; Babineau 2004; Wilkiemeyer 2005; Kauvar 2006; Harrington 2007). Bridges and Diamond reported the average costs of this increased operating time to be about USD 12,000 per year per resident during the period 1993 to 1997 (Bridges 1999). The complication rate is also higher for junior surgeons compared to senior surgeons (Wilkiemeyer 2005; Kauvar 2006). Bridges and Diamond did not include the cost of the complications in their cost analysis. Thus, the cost of the simulators has to be balanced against the costs of increased operating time and complication rates during traditional surgical training.

Description of the intervention

Training using a box model involves performance of tasks that are encountered in laparoscopic surgery by using animal tissues, plastic models, foam, cloth, or other materials. The images can be obtained using a laparoscope (camera) and viewed on monitors. This is called a video-box trainer. Another type of box trainer is the mirrored-box trainer in which mirrors are used to show the working field and direct vision of the working field is prevented (Keyser 2000).

How the intervention might work

Laparoscopic surgery is different from open surgery because of: increased need for hand-eye co-ordination to perform tasks when looking at a screen, to compensate for not being able to operate under direct vision; increased need for manual dexterity to compensate for the use of long instruments, which can amplify any error in movement; the fulcrum effect of the body wall, that is, when the surgeon moves his hand to the patient's right the operating end of the instrument moves to the patient's left on the monitor (Gallagher 1999); the need for handling tissues carefully (to compensate for the lack of sensation of touch using the hands); and the lack of three-dimensional images. Training by box trainer may work by repeated practice and improvement in the hand-eye co-ordination and manual dexterity.

Why it is important to do this review

We showed that virtual reality training can supplement standard laparoscopic training (Gurusamy 2008; Gurusamy 2009a). Sutherland et al concluded there was no evidence that a box trainer was effective in laparoscopic training (Sutherland 2006). There has been no Cochrane review on this topic.

Objectives

To compare the benefits and harms of box model training for surgical trainees with limited prior laparoscopic experience.

Methods

Criteria for considering studies for this review

Types of studies

Randomised clinical trials irrespective of blinding, language, publication status, and sample size will be included. Quasi-randomised studies (for example, allocation by date of birth, day of the week, etc) will be excluded but reports of harm from these studies will be included in our review.

Types of participants

Surgical trainees with limited prior laparoscopic experience. It is difficult to define limited prior laparoscopic experience. In general, we would expect that these surgical trainees would need supervision for laparoscopic operations. We also expect that these surgical trainees have at least assisted in one or more laparoscopic procedures as the laparoscopic camera holder. Effectiveness of box model training for surgical trainees with no prior laparoscopic experience will be considered in another review (Gurusamy 2013).

Types of interventions

The following comparisons will be included.

  • Box model training supplementing standard laparoscopic training versus standard laparoscopic training.

  • Box model training supplementing standard laparoscopic training versus animal model training supplementing standard laparoscopic training.

  • Video-box trainer versus mirrored-box trainer supplementing standard laparoscopic training.

  • One type of video-box trainer versus another type of video-box trainer supplementing standard laparoscopic training.

  • One type of mirrored-box trainer versus another type of mirrored-box trainer supplementing standard laparoscopic training.

Co-interventions will be allowed if they are delivered equally to both intervention groups.

Types of outcome measures

Primary outcomes
  1. Surgical mortality and morbidity for patients operated on by surgical trainees. For surgical morbidity, we will use the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use - Good Clinical Practice (ICH-GCP) definition of severe adverse events (ICH-GCP 1997). Severe adverse events are defined as any event that would increase mortality; is life-threatening; requires inpatient hospitalisation; results in a persistent or significant disability; or any important medical event which might have jeopardised the patient or requires intervention to prevent it (ICH-GCP 1997).

  2. Patient quality of life (measured on any validated continuous scale such as EuroQol (EQ)-5D, Short Form (SF)-36).

Secondary outcomes
  1. Operating time (minutes).

  2. Hospital stay (days).

  3. Trainee satisfaction (however defined by authors).

  4. Accuracy (e.g., accuracy in placing sutures at the correct location) (however defined by authors).

  5. Errors (e.g., gallbladder perforations or liver lacerations) (however defined by authors).

Search methods for identification of studies

Electronic searches

We will search the Cochrane Hepato-Biliary Group Controlled Trials Register (Gluud 2013), the Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library, MEDLINE, EMBASE, and Science Citation Index Expanded (Royle 2003). We have given the preliminary search strategies with the expected time spans of the searches in Appendix 1. As the review progresses, we will improve the search strategies if necessary.

Searching other resources

We will search the references of the identified trials to identify further relevant trials. We will search the metaRegister of Controlled Trials (mRCT) (http://www.controlled-trials.com/mrct/). The meta-register includes the ISRCTN Register and National Institutes of Health (NIH) ClinicalTrials.gov Register among other registers.

Data collection and analysis

We will perform the systematic review following the instructions given in the Cochrane Handbook for Systematic Reviews of Intervention (Higgins 2011) and the Cochrane Hepato-Biliary Group Module (Gluud 2013).

Selection of studies

Two authors (KG and another author) will identify the trials for inclusion independently of each other. We will list the excluded studies with the reasons for the exclusion. Any differences will be resolved through discussion.

Data extraction and management

Both authors will independently extract the following data.

  1. Year and language of publication.

  2. Country.

  3. Year of conduct of the trial.

  4. Inclusion and exclusion criteria.

  5. Sample size.

  6. Details of the previous experience of surgical trainees.

  7. Details of the box trainer used.

  8. Details of the training regimen used.

  9. Outcomes (described above).

  10. Risk of bias (described below).

Any unclear or missing information will be sought by contacting the authors of the individual trials. If there is any doubt whether the trials share the same patients, completely or partially (by identifying common authors and centres), we will contact the authors of the trials to clarify whether the trial report has been duplicated. We will resolve any differences in opinion through discussion.

Assessment of risk of bias in included studies

We will follow the instructions given in the Cochrane Handbook for Systematic Reviews of Intervention (Higgins 2011) and the Cochrane Hepato-Biliary Group Module (Gluud 2013). According to empirical evidence (Schulz 1995; Moher 1998; Kjaergard 2001; Wood 2008; Lundh 2012; Savovic 2012; Savovic 2012a), the risk of bias of the trials will be assessed based on the following bias risk domains.

Allocation sequence generation
  • Low risk of bias: sequence generation was achieved using computer random number generation or a random number table. Drawing lots, tossing a coin, shuffling cards, and throwing dice are adequate if performed by an independent person not otherwise involved in the trial.

  • Uncertain risk of bias: the method of sequence generation was not specified.

  • High risk of bias: the sequence generation method was not random.

Allocation concealment
  • Low risk of bias: the participant allocations could not have been foreseen in advance of, or during, enrolment. Allocation was controlled by a central and independent randomisation unit. The allocation sequence was unknown to the investigators (for example, if the allocation sequence was hidden in sequentially numbered, opaque, and sealed envelopes).

  • Uncertain risk of bias: the method used to conceal the allocation was not described so that intervention allocations may have been foreseen in advance of, or during, enrolment.

  • High risk of bias: the allocation sequence was likely to be known to the investigators who assigned the participants.

Blinding of participants and personnel*
  • Low risk of bias: blinding was performed adequately, or the assessment of outcomes was not likely to be influenced by lack of blinding.

  • Uncertain risk of bias: there was insufficient information to assess whether blinding was likely to introduce bias on the results.

  • High risk of bias: no blinding or incomplete blinding, and the assessment of outcomes were likely to be influenced by lack of blinding. 

*It is impossible to blind the surgical trainees and any assisting personnel. Provided that the outcome assessors are blinded, we will consider that there is low risk of bias due to lack of blinding of participants and any assisting personnel for all outcomes except for surgical trainee satisfaction.

Blinding of outcome assessors

Since it is not possible to blind the surgical trainee (participant), it is important that the outcome assessors are different from the participants and have no knowledge about the group of the participant.

  • Low risk of bias: blinding was performed adequately, or the assessment of outcomes was not likely to be influenced by lack of blinding.

  • Uncertain risk of bias: there was insufficient information to assess whether blinding was likely to induce bias on the results.

  • High risk of bias: no blinding or incomplete blinding, and the assessment of outcomes were likely to be influenced by lack of blinding. 

Incomplete outcome data
  • Low risk of bias: missing data were unlikely to make treatment effects depart from plausible values. Sufficient methods, such as multiple imputation, has been employed to handle missing data.

  • Uncertain risk of bias: there was insufficient information to assess whether missing data in combination with the method used to handle missing data were likely to induce bias on the results.

  • High risk of bias: the results were likely to be biased due to missing data.

Selective outcome reporting
  • Low risk of bias: all outcomes were pre-defined and reported, or all clinically relevant and reasonably expected outcomes were reported. For this purpose, the trial should have been registered either on the www.clinicaltrials.gov web site or a similar register, or there should be a protocol,  eg, published in a paper journal. In the case when the trial was run and published in the years when trial registration was not required, we will carefully scrutinize all publications reporting on the trial to identify the trial objectives and outcomes and determine whether usable data are provided in the publications results section on all outcomes specified in the trial objectives.

  • Uncertain risk of bias: it is unclear whether all pre-defined and clinically relevant and reasonably expected outcomes were reported.

  • High risk of bias: one or more clinically relevant and reasonably expected outcomes were not reported, and data on these outcomes were likely to have been recorded.

For-profit bias
  • Low risk of bias: the trial appears to be free of industry sponsorship or other kind of for-profit support that may manipulate the trial design, conductance, or results of the trial.

  • Uncertain risk of bias: the trial may or may not be free of for-profit bias as no information on clinical trial support or sponsorship is provided.

  • High risk of bias: the trial is sponsored by the industry or has received other kind of for-profit support.

We will consider trials which are classified as low risk of bias in all the above domains as trials with low risk of bias and the remaining as trials with high risk of bias.

Measures of treatment effect

For dichotomous outcomes, we will calculate the risk ratio (RR) with 95% confidence interval (CI). Risk ratio calculations do not include trials in which no events occurred in either group, whereas risk difference calculations do. We will report the risk difference if the results using this association measure were different from risk ratio. For continuous outcomes, we will calculate the mean difference (MD) with 95% CI for outcomes such as hospital stay, and standardised mean difference (SMD) with 95% CI for quality of life (where different scales might be used).

Unit of analysis issues

The unit of analysis will be the aggregate data on surgical trainees who underwent training according to randomised group.

Dealing with missing data

If trialists have used valid methods (for example, multiple imputation) to deal with missing data and report the results from an intention-to-treat analysis we will use these data in our analysis. If trialists only report complete case analysis or have used an invalid method of dealing with missing data (for example, last observation carried forward) we will perform an intention-to-treat analysis (Newell 1992) whenever possible. We will impute data for binary outcomes using various scenarios such as good outcome analysis, bad outcome analysis, best-case scenario, and worst-case scenario (Gurusamy 2009b; Gluud 2013).

For continuous outcomes, we will use available case analysis. We will impute the standard deviation from P values according to the instructions given in the Cochrane Handbook for Systematic Reviews of Intervention (Higgins 2011), and we will use the median for the meta-analysis when the mean is not available. If it is not possible to calculate the standard deviation from the P value or the confidence interval, we will impute the standard deviation as the highest standard deviation in the other trials included under that outcome, fully recognising that this form of imputation will decrease the weight of the study for calculation of mean differences and bias the effect estimate to no effect in the case of standardised mean difference (Higgins 2011).

Assessment of heterogeneity

We will explore heterogeneity by the Chi2 test with significance set at a P value less than 0.10, and measure the quantity of heterogeneity by the I2 statistic (Higgins 2002). We will also use overlapping of confidence intervals on the forest plot to determine heterogeneity.

Assessment of reporting biases

We will use visual asymmetry on a funnel plot to explore reporting bias if 10 or more trials are identified (Egger 1997; Macaskill 2001). We will perform the linear regression approach described by Egger 1997 to determine the funnel plot asymmetry. Selective reporting will also be considered as evidence for reporting bias.

Data synthesis

We will perform the meta-analyses using the software package Review Manager 5 (RevMan 2012) and following the recommendations of The Cochrane Collaboration (Higgins 2011) and the Cochrane Hepato-Biliary Group Module (Gluud 2013). We will use both a random-effects model (DerSimonian 1986) and a fixed-effect model (DeMets 1987) meta-analysis. In the case of discrepancy between the two models we will report both results; otherwise we will report the results of the fixed-effect model. We will use the generic inverse method to combine the hazard ratios for time-to-event outcomes.

Subgroup analysis and investigation of heterogeneity

We will perform the following subgroup analyses.

  • Trials with low risk of bias compared to trials with high risk of bias.

  • Different types of box trainers.

  • Different levels of prior laparoscopic experience.

  • Different types of operations.

We will use the 'test for interaction' to identify the differences between subgroups (Altman 1995).

Sensitivity analysis

  • We will perform a sensitivity analysis by imputing data for binary outcomes using various scenarios such as good outcome analysis, bad outcome analysis, best-case scenario, and worst-case scenario (Gurusamy 2009b; Gluud 2013). We will perform a sensitivity analysis by excluding the trials in which the mean and the standard deviation were imputed.

Trial sequential analysis

The underlying assumption of trial sequential analysis is that testing for significance may be performed each time a new trial is added to the meta-analysis. We will add the trials according to the year of publication, and if more than one trial was published in a year the trials will be added alphabetically according to the last name of the first author. On the basis of the required information size, trial sequential monitoring boundaries will be constructed. These boundaries determine the statistical inference one may draw regarding the cumulative meta-analysis that has not reached the required information size; if the trial sequential monitoring boundary is crossed before the required information size is reached, firm evidence may perhaps be established and further trials may turn out to be superfluous. On the other hand, if the boundaries are not surpassed, it is most probably necessary to continue doing trials in order to detect or reject a certain intervention effect (Brok 2008; Wetterslev 2008; Brok 2009; Thorlund 2009; Wetterslev 2009; Thorlund 2010).   

We will apply trial sequential analysis (CTU 2011; Thorlund 2011) using a required sample size calculated from an alpha error of 0.05, a beta error of 0.20, a control event proportion obtained from the results, and a relative risk reduction of 20% for surgical mortality and morbidity if there are two or more trials reporting this outcome to determine whether more trials are necessary on this topic (if the trial sequential alpha-spending monitoring boundary or the futility zone is crossed, then more trials may be unnecessary) (Brok 2008; Wetterslev 2008; Brok 2009; Thorlund 2009; Wetterslev 2009; Thorlund 2010). For quality of life, the required sample size will be calculated from an alpha error of 0.05, a beta error of 0.20, the variance estimated from the meta-analysis results of low risk of bias trials, and a standardised mean difference of 0.25.

Summary of findings table

We will summarise the results of all the outcomes in a summary of findings table prepared using GRADEPro 3.6 (http://ims.cochrane.org/revman/gradepro).

Acknowledgements

To the Cochrane Hepato-Biliary Group.

Peer Reviewers: Antonia Stergiopoulou, Greece; Mubashir G Mulla, UK; Anthony G Gallagher, Ireland.
Contact Editors: Saboor A'Khan, UK; Janus Christian Jakobsen, Denmark.

This project was funded by the National Institute for Health Research.
Disclaimer of the Department of Health: 'The views and opinions expressed in the review are those of the authors and do not necessarily reflect those of the National Institute for Health Research (NIHR), National Health Services (NHS), or the Department of Health'.

Appendices

Appendix 1. Search strategies for identification of studies

DatabasePeriod of SearchSearch Strategy
Cochrane Hepato-Biliary Group Controlled Trials RegisterDate will be given at review stage.(laparoscop* OR coelioscop* OR celioscop* OR peritoneoscop*) AND (video OR mirror OR box OR simulat*) AND train*
Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library (Wiley)Latest issue.

#1 laparoscop* OR coelioscop* OR celioscop* OR peritoneoscop*

#2 MeSH descriptor Laparoscopy explode all trees

#3 #1 OR #2
#4 video OR mirror OR box OR simulat*

#5 train*

#6 #3 AND #4 AND #5

MEDLINE (PubMed)1987 to the date of search.(laparoscop* OR coelioscop* OR celioscop* OR peritoneoscop* OR "Laparoscopy"[Mesh]) AND (video OR mirror OR box OR simulat*) AND train* AND ((randomised controlled trial [pt] OR controlled clinical trial [pt] OR randomised [tiab] OR placebo [tiab] OR drug therapy [sh] OR randomly [tiab] OR trial [tiab] OR groups [tiab]) NOT (animals [mh] NOT humans [mh]))
EMBASE (OvidSP)1987 to the date of search.

1. exp crossover-procedure/ or exp double-blind procedure/ or exp randomised controlled trial/ or single-blind procedure/  

2. (random* OR factorial* OR crossover* OR placebo*).af.

3. 1 OR 2

4. (laparoscop$ or coelioscop$ or celioscop$ or peritoneoscop$).af.
5. exp Laparoscopic surgery/
6. 4 or 5
7. (video OR mirror OR box OR simulat*).af.
8. simulator/
9. 7 OR 8
10. train*.af.
11. surgical training/
12. 10 OR 11
13. 3 AND 6 AND 9 AND 12

Science Citation Index Expanded (ISI Web of Knowledge) (http://apps.isiknowledge.com/)1987 to the date of search.

#1 TS=(laparoscop* OR coelioscop* OR celioscop* OR peritoneoscop*)

#2 TS=(video OR mirror OR box OR simulat*)

#3 TS=(train*)
#4 TS=(random* OR rct* OR crossover OR masked OR blind* OR placebo* OR meta-analysis OR systematic review* OR meta-analys*)
#5 #4 AND #3 AND #2 AND #1

metaRegister of Controlled Trials (http://www.controlled-trials.com/mrct/)Date will be given at review stage.(laparoscop* OR coelioscop* OR celioscop* OR peritoneoscop*) AND (video OR mirror OR box OR simulat*) AND (train*)

Contributions of authors

KS Gurusamy wrote the protocol and will assess the trials for inclusion and extract data on included trials at the review stage. A second author will independently assess the trials for inclusion and extract data on included trials at the review stage. The protocol was developed after discussion with BR Davidson.

Declarations of interest

None

Sources of support

Internal sources

  • None, Not specified.

External sources

  • National Insitute for Health Research (NIHR), UK.

    NIHR is the health research wing of the UK Government. It part funds Dr K Gurusamy's salary and funds all the materials needed for the preparation of this review.

Ancillary