Skip to main content
BJS Open logoLink to BJS Open
. 2022 Oct 25;6(5):zrac116. doi: 10.1093/bjsopen/zrac116

Quality of reporting of robot-assisted cholecystectomy in relation to the IDEAL recommendations: systematic review

Emily N Kirkham 1,2, Conor S Jones 3,4, George Higginbotham 5, Sarah Biggs 6, Ffion Dewi 7, Lauren Dixon 8,9, Marc Huttman 10,11, Barry G Main 12,13,14,15, Jozel Ramirez 16,17, Harry Robertson 18,19, Darren L Scroggie 20,21, Benjamin Zucker 22,23, Jane M Blazeby 24,25, Natalie S Blencowe 26,27,28, Samir Pathak 29,; RoboSurg Collaborative
PMCID: PMC9593068  PMID: 36281734

Abstract

Introduction

Robotic cholecystectomy (RC) is a recent innovation in minimally invasive gallbladder surgery. The IDEAL (idea, development, exploration, assessment, long-term study) framework aims to provide a safe method for evaluating innovative procedures. This study aimed to understand how RC was introduced, in accordance with IDEAL guidelines.

Methods

Systematic searches were used to identify studies reporting RC. Eligible studies were classified according to IDEAL stage and data were collected on general study characteristics, patient selection, governance procedures, surgeon/centre expertise, and outcome reporting.

Results

Of 1425 abstracts screened, 90 studies were included (5 case reports, 38 case series, 44 non-randomized comparative studies, and 3 randomized clinical trials). Sixty-four were single-centre and 15 were prospective. No authors described their work in the context of IDEAL. One study was classified as IDEAL stage 1, 43 as IDEAL 2a, 43 as IDEAL 2b, and three as IDEAL 3. Sixty-four and 51 provided inclusion and exclusion criteria respectively. Ethical approval was reported in 51 and conflicts of interest in 34. Only 21 reported provision of training for surgeons in RC. A total of 864 outcomes were reported; 198 were used in only one study. Only 30 reported a follow-up interval which, in 13, was 1 month or less.

Conclusion

The IDEAL framework was not followed during the adoption of RC. Few studies were conducted within a research setting, many were retrospective, and outcomes were heterogeneous. There is a need to implement appropriate tools to facilitate the incremental evaluation and reporting of surgical innovation.


Robotic cholecystectomy (RC) is a recent innovation in minimally invasive gallbladder surgery. Disparity between adoption of new techniques and robust evaluation has been observed in other areas of surgery and we sought to evaluate whether IDEAL guidelines were followed in the context of RC. We found that the IDEAL framework was not followed, few studies were conducted within a research setting, many were retrospective, and outcomes were heterogeneous. This lack of incremental evidence impairs surgeons’ ability to draw meaningful conclusions, undermining shared decision-making with patients. There is a need to implement appropriate tools to facilitate the incremental evaluation and reporting of surgical innovation

Introduction

Approximately 70 000 cholecystectomies are undertaken each year in England at a cost of around £111 million1. More than 90 per cent of these are performed using laparoscopic techniques1. Laparoscopic cholecystectomy (LC) typically results in less postoperative pain, faster recovery, improved cosmesis, and a shorter hospital stay compared with open surgery2. Single-incision laparoscopic cholecystectomy (SILC) was developed in 20103 in an attempt to further improve cosmesis and decrease postoperative pain4; however, ergonomic limitations and a lack of clear clinical benefit have hindered its adoption into routine practice5–7.

Robotic cholecystectomy (RC) is the most recent technological innovation for minimally invasive gallbladder surgery. It is performed through single or multiple small incisions, by an operating surgeon seated at a console away from the sterile field8. RC has perceived benefits, including enhanced tactile feedback, reduced musculoskeletal strain on the surgeon, better exposure, easier manipulation of the instruments, high-definition three-dimensional visualization, and fewer instrument collisions5,8. Due to these purported advantages, it is becoming increasingly popular; in the USA, rates of RC increased from 0.02 per cent of all cholecystectomies performed in 2008 to 3.2 per cent in 20179. This increase may in part be due to surgeons using RC as a means of developing their robotic skills for more complex operations10; however, convincing evidence of clinical benefit over conventional laparoscopic methods has not been forthcoming11,12. The disparity between adoption of new techniques and robust evaluation has been observed in other areas of gastrointestinal surgery13, leading to calls for tighter regulation of the field14. Although surgical robots are considered devices and subject to regulatory approval, there is currently no requirement for individual procedures such as RC to undergo robust clinical evaluation before implementation in clinical practice.

The idea, development, exploration, assessment, long-term follow-up (IDEAL) framework was developed in 2009 and updated in 201915, to provide a stepwise approach for the evaluation and reporting of innovative surgical procedures (Table 1).

Table 1.

Summary of idea, development, exploration, assessment, long-term study stages and recommendations

IDEA (1) Development (2a) Evaluation (2b) Assessment (3) Long-term (4)
Purpose Proof of concept Establish technical details and replicate early results Learning Assessment Surveillance
Design Structured case report Prospective case series Prospective comparative case series, feasibility RCT RCT Audit, registry, database
Number of patients 1 Few (<30) Many (>30) Guided by sample size calculation Often large numbers
Inclusion criteria Highly selected Selected Widening Wide Wide
Technical modifications Report success and failures (inception) Modifications allowed (development) Modifications allowed (refinement) No further modifications (stable) No further modifications (stable)
Considered innovative procedure Yes* Yes* Yes* No No
Surgeon and centre expertise Details of pre-human work Details of surgeon training Details of mentoring and learning curve Surgeons should be past learning curve Surgeons should be past learning curve
Outcomes Proof of concept; technical achievement; dramatic success; adverse events, surgeon views of the procedure Mainly safety; technical and procedural success Safety; clinical outcomes (specific/graded); short-term outcomes; patient-centred/reported outcomes; feasibility outcomes Clinical outcomes (specific and graded); potential patient-reported outcomes, health economic outcomes Rare events; long-term outcomes; quality assurance

Adapted from Hirst 201915 and Currie 201516.

*

Specific consent regarding innovation is required. RCT, randomized clinical trial.

Specific recommendations include details about patient selection, governance measures, surgeon expertise, and standardized outcome reporting, all which are critical to the safe introduction of new surgical procedures. By providing a stepwise framework to report the evolution of innovations, IDEAL seeks to facilitate incremental learning17, whereby researchers build on previous reports and add value to the existing evidence base. It is presently unclear whether this process occurred during the adoption and evaluation of RC.

The aims of this study are to understand how RC has been adopted into clinical practice, and to establish whether the evaluation and reporting of RC occurred in accordance with IDEAL guidelines.

Methods

The methods are based on a previously published protocol that aimed to investigate the introduction of a robotic procedure for diseases of the oropharynx5. Reporting was conducted in line with PRISMA 2020 guidelines18 (Tables S1 and S2).

Search strategy and study selection

Searches were undertaken in MEDLINE, Embase, Cochrane Library, and Web of Science databases, from inception to February 2020. Searches consisted of subject headings and text words, combining terms for ‘robotic surgery’ with ‘cholecystectomy’ using the Boolean operator ‘AND’ (Table S3).

Study eligibility

Searches were limited to studies of adults aged 18 years or older and written in English. All primary research study designs (such as case reports, case series, and comparative studies) were eligible for inclusion. Presentations and conference abstracts were excluded because of the high probability of incomplete data. Further exclusions included studies where the main focus was not the surgical procedure (such as anaesthesia, perioperative physiotherapy, or nutrition); describing indications for cholecystectomy other than cholelithiasis or polyps (such as cancer); where a combination of robotic procedures was described (such as when results of RC were reported alongside other robotic procedures and could not be separated); and investigating robotic camera holders rather than RC itself.

Identification and selection of papers

Search results were de-duplicated and uploaded to Rayyan software (Rayyan - a web and mobile app for systematic reviews)19. Titles and abstracts were screened independently by at least two authors. The full-text versions of papers retained after title and abstract screening were further assessed for eligibility. Disagreements were first discussed between the reviewers, and any unresolved conflicts referred to the senior authors (N.B. and S.P.); the final decision was the majority opinion. Data from full-text papers were extracted independently by at least two assessors.

Data collection

Data collection was based on IDEAL recommendations and included information about general study characteristics, patient selection, regulatory and governance arrangements, centre and operator expertise, and outcome reporting13,20.

General study characteristics and identification of IDEAL stage

The study design, year, and journal of publication, country of origin, and number of participating centres and patients were extracted. The presence and nature of comparison interventions and the type of robotic device used in each study were documented.

Where authors reported an IDEAL stage, it was recorded. Where this information was not provided, a flow diagram designed by the IDEAL Collaboration was used to establish the IDEAL stage21. Any difficulties assigning IDEAL stages to papers were recorded. Risk of bias assessments were undertaken for randomized clinical trials (RCTs) using the revised Cochrane Risk of Bias tool22.

Any reported rationale for why the study was undertaken was documented in the following categories: assessment of safety and efficacy; support for regulatory approval (such as the Medicines and Healthcare Products Regulatory Agency); description of technique; evaluation of learning curves; description of a centre’s experience; prediction of patient outcomes; and/or ‘other’.

Patient selection

Inclusion and exclusion criteria for patients undergoing RC were documented for each study. The number of patients declining RC was recorded, along with any stated reasons.

Regulatory and governance arrangements

The reporting of conflicts of interest, study funding and governance approvals (such as ethics committees, institutional review boards, or clinical effectiveness committees) was collected. Statements relating to patient consent, and whether patients were specifically informed of the innovative nature of RC, or of modifications made to the surgical technique, were recorded.

Centre and surgeon expertise

Information about centre expertise, such as the volume of robotic and non-robotic cholecystectomies undertaken at the institution(s), was recorded. Information about the number of surgeons performing the operation, and the expertise of those surgeons was also extracted, including their grade and experience with RC, and any details of specific training and mentorship in RC.

Outcome selection, measurement, and reporting

Outcomes reported in each manuscript were recorded verbatim and categorized into domains by two researchers (E.K. and C.S.J.; Table S4). To determine the number of distinct outcomes, those with the same meaning but different wording, were rationalized within each domain. Where reported, the duration of follow-up for each study was documented.

Data synthesis

Results were summarized in a narrative synthesis, with descriptive statistics where appropriate. The study did not aim to investigate the effectiveness of RC, therefore meta-analyses were not performed. To evaluate whether studies’ rationale and outcomes evolved over time, data were presented by IDEAL stage.

Results

Of 1425 abstracts and 303 full-text articles screened, a total of 90 articles, published between 2001 and 2020, were included (Fig. 1). There were two large database studies, collectively reporting short-term outcomes from 827 386 patients (823 807 LC and 3579 RC). The remaining 88 studies included a total of 15 074 patients (median 58, range 1–3255), of which 7009 underwent RC (median 38, range 1–925) and 7867 LC (median 50, range 5–3149).

Fig. 1.

Fig. 1

PRISMA diagram

General study characteristics

Among the 90 studies there were five case studies, 38 case series, 44 non-randomized comparative studies and three RCTs. Most studies were single-centre (n = 64) and only 15 were prospective (Table 2). All three RCTs compared RC with LC, and were published in 201423 (single-centre, n = 22), 201524 (single-centre, n = 60), and 201725 (multicentre, n = 136; Table S5). The risk of bias was unclear in two23,25, and in one24 there was a large (more than 20 per cent) loss to follow-up.

Table 2.

Characteristics of included studies

Number of studies (n = 90)
Non-comparative studies  
 Case reports 5
 Case series 38
  Prospective 12
  Retrospective 15
  Mixed 2
  Not specified 9
Comparative studies  
 Non-randomized comparative studies 44
  Prospective 3
  Retrospective 34
  Mixed 3
  Not specified 4
 Randomized clinical trials 3
Number of centres  
 Single 64
 Multiple 6
 Not specified 20
Type of centres  
 Tertiary/specialist 28
 Secondary/general 1
 Mixed 1
 Not specified 59
Country of study  
 USA 40
 South Korea 10
 Switzerland 9
 The Netherlands 8
 Italy 6
 Austria 3
 Turkey 2
 Germany 2
 Taiwan 2
 Other* 7
Comparator interventions  
 Laparoscopic cholecystectomy 31
 Single-incision cholecystectomy 11
 RC 3
  Single versus multiple port 1
  With and without cholangiography 1
  Emergency versus elective 1
*

Brazil, Hong Kong, France, UK, Canada, Greece, Multiple: all n = 1. RC, robotic cholecystectomy.

The most commonly used robots were Da Vinci systems (Intuitive Surgical (California, US)., 66). Seventeen studies provided no description of the system used.

No studies reported an IDEAL stage. The first study (a case series of 20 patients published in 2001) was considered to be IDEAL stage 1. Forty-three studies were identified as IDEAL 2a, 43 as IDEAL 2b, and three as IDEAL 3 (the RCTs), with no studies meeting the criteria for IDEAL stage 4. We experienced difficulties assigning IDEAL stages to many of the included papers. Overall, 49 studies were retrospective in nature and therefore did not strictly meet the IDEAL criteria, and had a further problem was the lack of detail about technique description or modifications, making it difficult to differentiate between stage 2a and 2b. Although two studies undertook data analysis from large databases, they only included information about short-term adverse events and, as such, did not meet the criteria for IDEAL stage 4. Although the number of IDEAL 2b studies has increased over time, only three were conducted prospectively. IDEAL stage 2a studies are still being conducted, despite the fact that the first RCT was published in 2014. There is, therefore, minimal evidence of evolution of study design as per the IDEAL recommendations (Fig. 2).

Fig. 2.

Fig. 2

Progression of idea, development, exploration, assessment, long-term study stage of included studies over time

Of the 90 studies, 73 reported a rationale. Most commonly, this was to assess safety, efficacy, and adverse events (n = 38). Others included descriptions of a centre’s experience (n = 18), prediction of outcomes (n = 13), evaluation of the learning curve (n = 11), and/or descriptions of the surgical technique (n = 7). There was no correlation between study rationale and IDEAL stage (the rationale did not evolve despite advancing IDEAL stage; Table 3).

Table 3.

Reporting of study rationale by idea, development, exploration, assessment, long-term study stage

Rationale IDEAL 1 (n = 1) IDEAL 2a (n = 43) IDEAL 2b (n = 43) IDEAL 3 (n = 3)
Studies reporting a rationale 1 (100) 33 (77) 37 (86) 3 (100)
Rationale(s)* of study
 Safety and efficacy 1 15 21 3
 Technique description 1 4 2 0
 Evaluation of learning curve 0 5 5 0
 Description of centre's experience 0 9 9 0
 Predicting patient outcomes 0 6 7 0

values are n (%). *Some studies reported multiple rationales. IDEAL (idea, development, exploration, assessment, long-term study) suggest that each IDEAL stage should fulfil the following purposes: IDEAL 1, proof of concept; IDEAL 2a, establish technical details and replicate early results; IDEAL 2b, learning; IDEAL 3, assessment; IDEAL 4, surveillance (Table 1).

Patient selection

Sixty-four and 51 studies provided inclusion and exclusion criteria respectively (Tables 4 and 5). Eight studies reported that there were no exclusion criteria. A total of 15 studies described how patients were selected for robotic surgery over conventional approaches: availability of the robot (n = 8), surgeon’s discretion (n = 4), willingness to pay (n = 1), the time interval of recruitment (before and after the robot became available, n = 1), and one study stated that there were no formal selection criteria. No studies specifically commented on the number of patients declining RC.

Table 4.

Summary of inclusion criteria reported in the included studies

Inclusion criteria Number of studies (n = 64)
Disease-related
 Indication 46
  Gallstones 38
  Other benign non-inflammatory diseases (biliary dyskinesia, adenomyomatosis, polyps) 14
  Acute cholecystitis 9
  Chronic cholecystitis 5
  Gallstone pancreatitis 5
  Choledocholithiasis 1
  ‘Gallbladder disease’ (unspecified) 6
 Symptoms 31
  Symptomatic 30
  Asymptomatic 1
Patient-related
 Age (years) 20
  >18 10
  18–80 9
  23–78 1
 BMI 6
  <30 2
  >30 1
  >25 1
  No limit 2
 Co-morbidity 9
  ASA grade 1–3 5
  ASA grade 1–2 2
  Mild-moderate severity of illness score 1
  Based on anaesthetic risk 1
 No previous upper abdominal surgery 3
Surgery-related
 Urgency 16
  Elective 15
  Emergency and elective 1
 Fluorescent imaging 2
Other
 Consent 7
 Financial 1

Table 5.

Summary of exclusion criteria reported in the included studies

Number of studies (n = 51)
Disease-related
 Indication 51
  Acute cholecystitis 24
  CBD stone(s) 12
  Pancreatitis 10
  Gallbladder malignancy 6
  Gallbladder empyema 1
 Acute systemic illness 6
 Deranged liver function test 3
Patient-related
 Age (years) 3
  <18 3
 Co-morbidity 16
  Cognitive impairment 7
  High anaesthetic risk 7
  Liver cirrhosis 6
  Coagulopathy 5
  ASA grade >2 3
  ASA grade 4 1
  Other 3
 Previous upper abdominal surgery 22
 BMI 6
  Not a cause for exclusion 2
  Severe/morbid obesity 2
  >32 1
  >33 1
 Pregnancy 12
 Iodine allergy 4
 Ability to consent 3
Surgery-related
 Urgency 3
  Emergency surgery 3
 Co-intervention 6
  Concurrent surgery 5
  Intraoperative cholangiogram 1
 Adverse event 3
  Conversion to open 2
  Anaesthetic complication 1
 Single incision 1
Other
 ‘No exclusion criteria’ 8
 Consent 3
 Incomplete records 3

Regulatory and governance arrangements

Ethical approval was reported in 51 of the 90 studies (institutional review boards, n = 41 and ethics committee, n = 10) and four reported registration within a trials register (ClinicalTrials.gov, n = 3 and Australian New Zealand Clinical Trials Registry, n = 1). Conflicts of interest were common, with 11 studies funded by the robot manufacturer and a further 23 reporting conflicts of interest between the author(s) and the manufacturer.

Although patient consent for study participation was explicitly documented in 42 studies, just four stated that patients were informed of the innovative nature of RC10,26–28. Of the 10 studies reporting modifications to the robotic technique during the study, none reported that patients were informed of this.

Centre and operator expertise

Four studies defined the participating centres’ usual caseload for RC (range 50–500 per year). The number of surgeons performing robotic surgery was reported in 51 studies (median 2, range 1–42). The grade of operating surgeon(s) was reported in 12 studies (consultant/attending, n = 2 and mixed trainee and consultant, n = 10). Provision of training in RC was reported in 21 studies, mostly consisting of animal-based (n = 12), simulation (n = 10), and dry laboratory (n = 6; Table 6). Proctorship and dual-consultant operating were each reported in four studies.

Table 6.

Details of training in robotic cholecystectomy reported within included studies

Author, year* Pre-clinical Clinical  
Simulation Dry laboratory Cadaver Animal Observation of surgical cases Assisting Proctorship Other
Kim, 200229
Bodner, 200230
Ruurda, 200231
Hourmont, 200332
Vuilleumier, 200333
Miller, 200434
Nio, 200435
Caratozzolo, 200536
Vidovszky, 200637
Breitenstein, 200838
Spinoglio, 201239
Pietrabissa, 201226
Angus, 201440
Nelson, 201441
Ayloo, 201442
Juza, 201443
Gonzalez, 201644
Ayabe, 201845
O'Leary, 201846
Melling, 201947
Lee, 201948
Total (n = 21) 10 6 3 12 4 4 4 8
*

Only studies that reported any training information are included.

Outcome selection, measurement, and reporting

A total of 842 outcomes were reported across all included studies. Of these, there were 280 distinct outcomes, of which 198 were used in only one study each. No single outcome, or outcome domain, was reported in all studies (median 8, interquartile range 6–12; Table 7). Outcomes relating to technical/operative factors (n = 377, 87 studies), complications (n = 236, 80 studies), and health economics (n = 139, 70 studies) were used most frequently. Four studies reported surgeon-focused outcomes and 24 provided patient-centred outcomes. There was no clear progression in the type of outcomes reported with advancing IDEAL stage (Table 7). Only 30 studies reported a follow-up interval (range 14 days to 46 months) and of these, 13 lasted 1 month or less.

Table 7.

The selection and reporting of outcomes by domain and idea, development, exploration, assessment, long-term study stage

Domain IDEAL 1 (n = 1) IDEAL 2a (n = 43) IDEAL 2b (n = 43) IDEAL 3 (n = 3) Total
Outcomes Studies Outcomes Studies Outcomes Studies Outcomes Studies Outcomes
Complications 1 1 105 42 125 35 5 2 236
Technical 4 1 211 42 158 42 4 2 377
Health economic 0 0 33 29 105 40 1 1 139
Patient-centred 0 0 18 12 17 10 6 2 41
Laboratory and imaging 0 0 4 3 7 4 5 1 16
Surgeon-centred 0 0 13 3 1 1 0 0 14
Survival 0 0 5 5 6 6 0 0 11
Trends and learning curve 0 0 2 2 2 2 0 0 4
Pathological 0 0 3 3 1 1 0 0 4
Total 5  - 394 - 422  - 21 - 842

IDEAL (idea, development, exploration, assessment, long-term study) suggest the following outcomes at each stage: IDEAL 1, proof of concept, technical achievement, dramatic success, adverse events, surgeon views of the procedure; IDEAL 2a, mainly safety, technical and procedural success; IDEAL 2b, safety, clinical outcomes (specific/graded), short-term outcomes, patient-centred/reported outcomes, feasibility outcomes; IDEAL 3, clinical outcomes (specific and graded), potential patient-reported outcomes, health economic outcomes (Table 1).

Discussion

This comprehensive review of the reporting of the adoption of RC summarizes information from 90 studies published between 2001 and 2020. The current evidence base for RC is formed largely by retrospective observational studies from single centres. Although three RCTs were identified, they were small and poorly designed. Most studies aimed to assess the safety of RC, with little evolution of study rationale or design that would be expected based on synthesis of preceding evidence. Details of regulatory and governance arrangements were infrequently reported, and conflicts of interest were common. Selection criteria were inconsistently reported, limiting understanding of which patients were offered the new procedure and why. Provision of training in RC was poorly reported with only four studies reporting any ongoing monitoring or proctorship. Outcome selection and reporting was heterogeneous, with 198 of the outcomes used just once. This review highlights that RC has been adopted into clinical practice without adequate comparative or prospective evidence and without the parameters of the IDEAL recommendations. This means that uncertainties about the efficacy, effectiveness, and cost-effectiveness of RC remain, which has inherent risks for clinical practice. More rigorous methods for evaluation of surgical innovation are therefore recommended.

Two meta-analyses comparing RC and LC have been undertaken. The first (2016) included one RCT and 12 observational studies. The second (2017) included five RCTs (two of which were outside the inclusion criteria for our review) and 21 observational studies11,12. Neither identified any significant difference in complications, readmission rates, or hospital stay, although operating time and the incidence of postoperative incisional hernia were higher after RC11; however, these meta-analyses were based primarily on retrospective observational studies and therefore must be interpreted with caution due the presence of confounders, selection bias, and differences in study design22. Both studies highlighted the issue of heterogeneous outcomes, which reduced the number of studies available for meta-analysis. This finding is consistent with our own study and illustrates how heterogeneous outcomes can impair evidence synthesis49–51. The COMET (Core Outcome Measures in Effectiveness Trials) Initiative52 recommends the development of core outcome sets (an agreed minimum set of outcomes that should be measured and reported in all clinical trials of a specific disease or trial population)53 with an expectation that core outcomes will be collected and reported, making it easier for the results of studies to be compared, contrasted, and combined as appropriate52,54. Core outcome sets are increasingly mandated by journals before publication; streamlining the outcomes reported in robotic surgery would enable the efficacy and effectiveness of robotic procedures to be clearly detailed, subsequently optimizing transparency, maximizing patient benefit, and reducing harms.

To our knowledge, this review represents the first in-depth case study to summarize published evidence of how a robot-assisted procedure was adopted into clinical practice. Although the inclusion of all study types allowed a comprehensive review of the evidence base for RC, this study has some limitations. First, the exclusion of non-English language papers may have resulted in some relevant papers being missed. Second, reporting standards and expectations change with time; 19 of the included studies were published before the introduction of the IDEAL framework in 2009 and benchmarking such studies against these criteria may be considered unfair, although the principles underpinning IDEAL represent the foundations of evidence-based surgery. A third limitation is that the IDEAL Collaboration’s flow chart for determining stage of innovation was challenging to use because most papers did not provide information about technique descriptions or modifications, creating difficulties in distinguishing between 2a and 2b studies. Furthermore, many of the studies were difficult to classify given their retrospective nature; however, aside from the temporality of the study, other criteria to classify the IDEAL stage were met and they were therefore assigned stages while acknowledging this limitation. Retrospective categorization of studies to IDEAL stages has been recorded in the literature in line with this55. It is widely recognized that there is still a need for the quality of surgical research to improve, including the heavy reliance on retrospective study designs due to their inherent limitations.

In conclusion, this review highlights a lack of standardized reporting and adherence to IDEAL guidelines across studies underpinning the adoption of RC. This impairs surgeons’ ability to draw meaningful conclusions from available evidence and undertake shared decision-making with patients. Inadequate descriptions of inclusion criteria and heterogeneous outcome selection obstruct effective evidence synthesis and may cause research waste. Improved reporting would enable greater transparency and interpretability, and facilitate the safe, evidence-based adoption of new procedures into clinical practice. For RC, high-quality RCTs assessing patient-centred, surgeon-focused, and health economic outcomes are now required to guide its future use. We support greater adoption of tools to facilitate the generation of robust evidence for robotic surgical procedures, including the IDEAL reporting guidelines56 and robot-specific core outcome sets.

Collaborators

RoboSurg Collaborative

A Vallance, A Wilkinson, A Smith, A Torkington, A Jones, A Abbas, BG Main, B Zucker, B Turner, CS Jones, C Thomas, C Hoffmann, DL Scroggie, D Henshall, EN Kirkham, E Boden, E Gull, E Sewart, F Dewi, F Wood, F Loro, F Hollowood, G Fowler, G Higginbotham, G Sellers, H Robertson, H Richards, I Hughes, I Handa, JM Blazeby, J Olivier, J Ramirez, J Rees, K Chalmers, K Siang Lee, L Dixon, L Leandro, L Paynter, L Huppler, L Gourbault, M Huttman, M Wijeyaratne, M Dewhurst, M Shah, M Kiandee, M Dada, NS Blencowe, O Brewster, P Lok, R Winayak, R Ranat, R Macefield, R Purves, R Lawrence, R Millar, S Biggs, S Lawday, S Dalmia, S Cousins, S Pathak, S Rozwadowski, T Robinson, T Perra, T Wei Leow, T Brankin-Frisby, W Baker, W Hurst, Y Embury Young.

Supplementary Material

zrac116_Supplementary_Data

Contributor Information

Emily N Kirkham, Bristol Centre for Surgical Research, Population Health Sciences, University of Bristol, Bristol, UK; Musgrove Park Hospital, Taunton, UK.

Conor S Jones, Bristol Centre for Surgical Research, Population Health Sciences, University of Bristol, Bristol, UK; North Bristol NHS Foundation Trust, Bristol, UK.

George Higginbotham, North Bristol NHS Foundation Trust, Bristol, UK.

Sarah Biggs, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK.

Ffion Dewi, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK.

Lauren Dixon, Bristol Centre for Surgical Research, Population Health Sciences, University of Bristol, Bristol, UK; University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK.

Marc Huttman, Bristol Centre for Surgical Research, Population Health Sciences, University of Bristol, Bristol, UK; University College Hospital, University College London Hospitals NHS Foundation Trust, London, UK.

Barry G Main, Bristol Centre for Surgical Research, Population Health Sciences, University of Bristol, Bristol, UK; University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK; Bristol Dental School, University of Bristol, Bristol, UK; NIHR Bristol Biomedical research centre, Bristol, UK.

Jozel Ramirez, Bristol Centre for Surgical Research, Population Health Sciences, University of Bristol, Bristol, UK; University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK.

Harry Robertson, Bristol Centre for Surgical Research, Population Health Sciences, University of Bristol, Bristol, UK; Imperial College Healthcare NHS Trust, London.

Darren L Scroggie, Bristol Centre for Surgical Research, Population Health Sciences, University of Bristol, Bristol, UK; University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK.

Benjamin Zucker, Bristol Centre for Surgical Research, Population Health Sciences, University of Bristol, Bristol, UK; University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK.

Jane M Blazeby, Bristol Centre for Surgical Research, Population Health Sciences, University of Bristol, Bristol, UK; NIHR Bristol Biomedical research centre, Bristol, UK.

Natalie S Blencowe, Bristol Centre for Surgical Research, Population Health Sciences, University of Bristol, Bristol, UK; University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK; NIHR Bristol Biomedical research centre, Bristol, UK.

Samir Pathak, St James’s University Hospital, Leeds Teaching Hospitals NHS Trust, Leeds, UK.

RoboSurg Collaborative:

A Vallance, A Wilkinson, A Smith, A Torkington, A Jones, A Abbas, B G Main, B Zucker, B Turner, C S Jones, C Thomas, C Hoffmann, D L Scroggie, D Henshall, E N Kirkham, E Boden, E Gull, E Sewart, F Dewi, F Wood, F Loro, F Hollowood, G Fowler, G Higginbotham, G Sellers, H Robertson, H Richards, I Hughes, I Handa, J M Blazeby, J Olivier, J Ramirez, J Rees, K Chalmers, K Siang Lee, L Dixon, L Leandro, L Paynter, L Huppler, L Gourbault, M Huttman, M Wijeyaratne, M Dewhurst, M Shah, M Kiandee, M Dada, N S Blencowe, O Brewster, P Lok, R Winayak, R Ranat, R Macefield, R Purves, R Lawrence, R Millar, S Biggs, S Lawday, S Dalmia, S Cousins, S Pathak, S Rozwadowski, T Robinson, T Perra, T Wei Leow, T Brankin-Frisby, W Baker, W Hurst, and Y Embury Young

Funding

This study is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at the University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol.

Acknowledgements

We would like to acknowledge S. Dawson for designing and running the search strategy. E.N.K. and C.S.J. are joint first authors.

Disclosure

The views expressed are those of the authors and not necessarily those of the UK National Health Service, NIHR, or Department of Health. J.B. is an NIHR Senior Investigator. N.B. is a Medical Research Council Clinician Scientist.

This work was not preregistered with an analysis plan in an independent, institutional registry.

Supplementary material

Supplementary material is available at BJS Open online

Data availability

We are willing to make our data, analytic methods, and study materials available to other researchers on request.

References

  • 1. NICE Guidance . Costing Statement: Gallstone Disease. implementing the NICE Guideline on Gallstone Disease (CG188). 2014. https://www.nice.org.uk/guidance/cg188/resources/costing-statementpdf-193298365#:∼:text=About%2066%2C660%20cholecystectomies%20are%20performed,of%20these%20are%20laparoscopic%20cholecystectomies (accessed 14 August 2020)
  • 2. Vaughan J, Gurusamy KS, Davidson BR. Day-surgery versus overnight stay surgery for laparoscopic cholecystectomy. Cochrane Database Syst Rev 2013:CD006798. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3. Hodgett SE, Hernandez JM, Morton CA, Ross SB, Albrink M, Rosemurgy AS. Laparoendoscopic single site (LESS) cholecystectomy. J Gastrointest Surg 2009;13:188–192 [DOI] [PubMed] [Google Scholar]
  • 4. Evers L, Bouvy N, Branje D, Peeters A. Single-incision laparoscopic cholecystectomy versus conventional four-port laparoscopic cholecystectomy: a systematic review and meta-analysis. Surg Endosc 2017;31:3437–3448 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Barrera K, Chung P, Sugiyama G. Robotic approach to cholecystectomy, updates in gallbladder diseases. In: Abdeldayem H (ed.), Updates in Gallbladder Diseases. London: IntechOpen, 2017, page numbers 9 [Google Scholar]
  • 6. Cheng Y, Jiang ZS, Xu XP, Zhang Z, Xu TC, Zhou CJet al. Laparoendoscopic single-site cholecystectomy vs three-port laparoscopic cholecystectomy: a large-scale retrospective study. World J Gastroenterol 2013;19:4209–4213 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. Arezzo A, Passera R, Forcignanò E, Rapetti L, Cirocchi R, Morino M. Single-incision laparoscopic cholecystectomy is responsible for increased adverse events: results of a meta-analysis of randomized controlled trials. Surg Endosc 2018;32:3739–3753 [DOI] [PubMed] [Google Scholar]
  • 8. Kroh M, El-Hayek K, Rosenblatt S, Chand B, Escobar P, Kaouk Jet al. First human surgery with a novel single-port robotic system: cholecystectomy using the Da Vinci single-site platform. Surg Endosc 2011;25:3566–3573 [DOI] [PubMed] [Google Scholar]
  • 9. Aguayo E, Dobaria V, Nakhla M, Seo YJ, Hadaya J, Cho NYet al. National trends and outcomes of inpatient robotic-assisted versus laparoscopic cholecystectomy. Surgery 2020;168:625–630 [DOI] [PubMed] [Google Scholar]
  • 10. Jayaraman S, Davies W, Schlachta CM. Getting started with robotics in general surgery with cholecystectomy: the Canadian experience. Can J Surg 2009;52:374–378 [PMC free article] [PubMed] [Google Scholar]
  • 11. Han C, Shan X, Yao L, Yan P, Li M, Hu Let al. Robotic-assisted versus laparoscopic cholecystectomy for benign gallbladder diseases: a systematic review and meta-analysis. Surg Endosc 2018;32:4377–4392 [DOI] [PubMed] [Google Scholar]
  • 12. Huang Y, Chua TC, Maddern GJ, Samra JS. Robotic cholecystectomy versus conventional laparoscopic cholecystectomy: a meta-analysis. Surgery 2017;161:628–636 [DOI] [PubMed] [Google Scholar]
  • 13. Kirkham EN, Main BG, Jones KJB, Blazeby JM, Blencowe NS. Systematic review of the introduction and evaluation of magnetic augmentation of the lower oesophageal sphincter for gastro-oesophageal reflux disease. Br J Surg 2020;107:44–55 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Sheetz KH, Claflin J, Dimick JB. Trends in the adoption of robotic surgery for common surgical procedures. JAMA Netw Open 2020;3:e1918911. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Hirst A, Philippou Y, Blazeby J, Campbell B, Campbell M, Feinberg Jet al. No surgical innovation without evaluation: evolution and further development of the IDEAL framework and recommendations. Ann Surg 2019;269:211–220 [DOI] [PubMed] [Google Scholar]
  • 16. Currie A, Brigic A, Blencowe NS, Potter S, Faiz OD, Kennedy RHet al. Systematic review of surgical innovation reporting in laparoendoscopic colonic polyp resection. Br J Surg 2015;102:e108–e116 [DOI] [PubMed] [Google Scholar]
  • 17. McCulloch P, Altman DG, Campbell WB, Flum DR, Glasziou P, Marshall JCet al. No surgical innovation without evaluation: the IDEAL recommendations. Lancet 2009;374:1105–1112 [DOI] [PubMed] [Google Scholar]
  • 18. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CDet al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan—a web and mobile app for systematic reviews. Syst Rev 2016;5:210. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. Main BG, Blencowe NS, Howes N, Cousins S, Avery KNL, Gormley Aet al. Protocol for the systematic review of the reporting of transoral robotic surgery. BMJ Open 2018;8:e019198. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Bilbro N MPH, Hirst A, McCulloch P. IDEAL Stage Flowchart.https://www.ideal-collaboration.net/the-ideal-framework/ (accessed 9 September 2020)
  • 22. Sterne JAC, Savović J, Page MJ, Elbers RG, Blencowe NS, Boutron Iet al. Rob 2: a revised tool for assessing risk of bias in randomised trials. BMJ 2019;366:l4898. [DOI] [PubMed] [Google Scholar]
  • 23. Heemskerk J, Zandbergen HR, Keet SW, Martijnse I, van Montfort G, Peters RJet al. Relax, it's just laparoscopy! A prospective randomized trial on heart rate variability of the surgeon in robot-assisted versus conventional laparoscopic cholecystectomy. Dig Surg 2014;31:225–232 [DOI] [PubMed] [Google Scholar]
  • 24. Pietrabissa A, Pugliese L, Vinci A, Peri A, Tinozzi FP, Cavazzi Eet al. Short-term outcomes of single-site robotic cholecystectomy versus four-port laparoscopic cholecystectomy: a prospective, randomized, double-blind trial. Surg Endosc 2016;30:3089–3097 [DOI] [PubMed] [Google Scholar]
  • 25. Kudsi OY, Castellanos A, Kaza S, McCarty J, Dickens E, Martin Det al. Cosmesis, patient satisfaction, and quality of life after da Vinci single-site cholecystectomy and multiport laparoscopic cholecystectomy: short-term results from a prospective, multicenter, randomized, controlled trial. Surg Endosc 2017;31:3242–3250 [DOI] [PubMed] [Google Scholar]
  • 26. Pietrabissa A, Sbrana F, Morelli L, Badessi F, Pugliese L, Vinci Aet al. Overcoming the challenges of single-incision cholecystectomy with robotic single-site technology. Arch Surg 2012;147:709–714 [DOI] [PubMed] [Google Scholar]
  • 27. Uras C, Böler DE, Ergüner İ, Hamzaoğlu İ. Robotic single port cholecystectomy (R-LESS-C): experience in 36 patients. Asian J Surg 2014;37:115–119 [DOI] [PubMed] [Google Scholar]
  • 28. Lee H, Lee DH, Kim H, Han Y, Kim SW, Jang JY. Single-incision robotic cholecystectomy: a special emphasis on utilization of transparent glove ports to overcome limitations of single-site port. Int J Med Robot 2016;13:e1789. [DOI] [PubMed] [Google Scholar]
  • 29. Kim VB, Chapman WH, Albrecht RJ, Bailey BM, Young JA, Nifong LWet al. Early experience with telemanipulative robot-assisted laparoscopic cholecystectomy using Da Vinci. Surg Laparosc Endosc Percutan Tech 2002;12:33–40 [DOI] [PubMed] [Google Scholar]
  • 30. Bodner J, Schmid T, Wykypiel H., Bodner E.. First experiences with robotic-assisted laparoscopic cholecystectomies. Eur Surg 2002;34:166–169 [Google Scholar]
  • 31. Ruurda JP, Visser PL, Broeders IA. Analysis of procedure time in robot-assisted surgery: comparative study in laparoscopic cholecystectomy. Comput Aided Surg 2003;8:24–29 [DOI] [PubMed] [Google Scholar]
  • 32. Hourmont K, Chung W, Pereira S, Wasielewski A, Davies R, Ballantyne GH. Robotic versus telerobotic laparoscopic cholecystectomy: duration of surgery and outcomes. Surg Clin North Am 2003;83:1445–1462 [DOI] [PubMed] [Google Scholar]
  • 33. Vuilleumier H, Halkic N. Implementation of robotic laparoscopic cholecystectomy in a university hospital. Swiss Med Wkly 2003;133:347–349 [DOI] [PubMed] [Google Scholar]
  • 34. Miller DW, Schlinkert RT, Schlinkert DK. Robot-assisted laparoscopic cholecystectomy: initial mayo clinic Scottsdale experience. Mayo Clin Proc 2004;79:1132–1136 [DOI] [PubMed] [Google Scholar]
  • 35. Nio D, Bemelman WA, Busch OR, Vrouenraets BC, Gouma DJ. Robot-assisted laparoscopic cholecystectomy versus conventional laparoscopic cholecystectomy: a comparative study. Surg Endosc 2004;18:379–382 [DOI] [PubMed] [Google Scholar]
  • 36. Caratozzolo E, Recordare A, Massani M, Bonariol L, Jelmoni A, Antoniutti Met al. Telerobotic-assisted laparoscopic cholecystectomy: our experience on 29 patients. J Hepatobiliary Pancreat Surg 2005;12:163–166 [DOI] [PubMed] [Google Scholar]
  • 37. Vidovszky TJ, Smith W, Ghosh J, Ali MR. Robotic cholecystectomy: learning curve, advantages, and limitations. J Surg Res 2006;136:172–178 [DOI] [PubMed] [Google Scholar]
  • 38. Breitenstein S, Nocito A, Puhan M, Held U, Weber M, Clavien PA. Robotic-assisted versus laparoscopic cholecystectomy: outcome and cost analyses of a case-matched control study. Ann Surg 2008;247:987–993 [DOI] [PubMed] [Google Scholar]
  • 39. Spinoglio G, Lenti LM, Maglione V, Lucido FS, Priora F, Bianchi PPet al. Single-site robotic cholecystectomy (SSRC) versus single-incision laparoscopic cholecystectomy (SILC): comparison of learning curves. First European experience. Surg Endosc 2012;26:1648–1655 [DOI] [PubMed] [Google Scholar]
  • 40. Angus AA, Sahi SL, McIntosh BB. Learning curve and early clinical outcomes for a robotic surgery novice performing robotic single site cholecystectomy. Int J Med Robot 2014;10:203–207 [DOI] [PubMed] [Google Scholar]
  • 41. Nelson EC, Gottlieb AH, Müller HG, Smith W, Ali MR, Vidovszky TJ. Robotic cholecystectomy and resident education: the UC Davis experience. Int J Med Robot 2014;10:218–222 [DOI] [PubMed] [Google Scholar]
  • 42. Ayloo S, Roh Y, Choudhury N. Robotic cholecystectomy: training of residents in use of the robotic platform. Int J Med Robot 2014;10:88–92 [DOI] [PubMed] [Google Scholar]
  • 43. Juza RM, Haluck RS, Won EJ, Enomoto LM, Pauli EM, Rogers AMet al. Training current and future robotic surgeons simultaneously: initial experiences with safety and efficiency. J Robot Surg 2014;8:227–231 [DOI] [PubMed] [Google Scholar]
  • 44. Gonzalez A, Murcia CH, Romero R, Escobar E, Garcia P, Walker Get al. A multicenter study of initial experience with single-incision robotic cholecystectomies (SIRC) demonstrating a high success rate in 465 cases. Surg Endosc 2016;30:2951–2960 [DOI] [PubMed] [Google Scholar]
  • 45. Ayabe RI, Parrish AB, Dauphine CE, Hari DM, Ozao-Choy JJ. Single-site robotic cholecystectomy and robotics training: should we start in the junior years? J Surg Res 2018;224:1–4 [DOI] [PubMed] [Google Scholar]
  • 46. O'leary MP, Ayabe RI, Dauphine CE, Hari DM, Ozao-Choy JJ. Building a single-site robotic cholecystectomy program in a public teaching hospital: is it safe for patients and feasible for residents to participate? Am Surg 2018;84:188–191 [PubMed] [Google Scholar]
  • 47. Melling N, Barr J, Schmitz R, Polonski A, Miro J, Ghadban Tet al. Robotic cholecystectomy: first experience with the new Senhance robotic system. J Robot Surg 2019;13:495–500 [DOI] [PubMed] [Google Scholar]
  • 48. Lee SE. Current status of single-port laparoscopic cholecystectomy. J Minim Invasive Surg 2016;19:5–8 [Google Scholar]
  • 49. Whistance RN, Forsythe RO, McNair AG, Brookes ST, Avery KN, Pullyblank AMet al. A systematic review of outcome reporting in colorectal cancer surgery. Colorectal Dis 2013;15:e548–e560 [DOI] [PubMed] [Google Scholar]
  • 50. Coulman KD, Hopkins J, Brookes ST, Chalmers K, Main B, Owen-Smith A, et al. A core outcome set for the benefits and adverse events of bariatric and metabolic surgery: the BARIACT project. PLOS Med 2016;13:e1002187. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51. Welford P, Blencowe NS, Pardington E, Jones CS, Blazeby JM, Main BG. Systematic review of the introduction, early phase study and evaluation of pyrocarbon proximal interphalangeal joint arthroplasty. PLOS ONE 2021;16:e0257497. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52. Comet Initiative . https://www.comet-initiative.org/ (accessed May 2022)
  • 53. Webbe J, Sinha I, Gale C. Core outcome sets. Arch Dis Child Educ Pract Ed 2018;103:163–166 [DOI] [PubMed] [Google Scholar]
  • 54. Boutron I, Altman DG, Moher D, Schulz KF, Ravaud P, CONSORT NPT Group . CONSORT Statement for randomized trials of nonpharmacologic treatments: a 2017 update and a CONSORT extension for nonpharmacologic trial abstracts. Ann Intern Med 2017;167:40–47 [DOI] [PubMed] [Google Scholar]
  • 55. Gerullis H, Ecke TH, Barski D, Bantel C, Weyland A, Uphoff Jet al. Retrospective analysis of a surgical innovation using the IDEAL framework: radical cystectomy with epidural anaesthesia. J Int Med Res 2017;45:714–722 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56. Bilbro NA, Hirst A, Paez A, Vasey B, Pufulete M, Sedrakyan Aet al. The IDEAL reporting guidelines: A Delphi consensus statement stage specific recommendations for reporting the evaluation of surgical innovation. Ann Surg 2021;273:82–85 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

zrac116_Supplementary_Data

Data Availability Statement

We are willing to make our data, analytic methods, and study materials available to other researchers on request.


Articles from BJS Open are provided here courtesy of Oxford University Press

RESOURCES