Gases for establishing pneumoperitoneum during laparoscopic abdominal surgery
Abstract
This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:
To assess the safety, benefits, and harms of different gases (CO2, He, Ar, N2, N2O, etc) for establishing pneumoperitoneum in patients undergoing laparoscopic abdominal surgery.
Background
Pneumoperitoneum means air or gas in the abdominal cavity (Andersen 2010). Laparoscopic surgery, also known as keyhole surgery, is a minimally invasive surgery (Ahmad 2008; Andersen 2010; Birch 2011; Harrell 2005). The operation is performed through small incision(s) with the assistance of a video camera and several thin instruments (Harrell 2005). An artificial pneumoperitoneum is deliberately established by surgeons to perform laparoscopic surgery (Ahmad 2008; Gurusamy 2008). It is achieved by insufflating the abdominal cavity with gas (Andersen 2010; Birch 2011).
Description of the condition
Laparoscopic surgery, which was originally developed in gynaecology, is now widely performed by general surgeons to treat various abdominal diseases (Ahmad 2008; Birch 2011; Harrell 2005; Magaji 2002), including the diseases of stomach, gallbladder, liver, pancreas, spleen, intestine, kidney, etc (Dasari 2011; Keus 2006; Kodera 2010; Kuhry 2008; Mirnezami 2011; Nabi 2010; Nigri 2011; Sanabria 2005; Sauerland 2010; Winslow 2003). Although the exact number of patients undergoing laparoscopic surgery each year worldwide is unknown, it is reported that more than 500,000 patients undergo laparoscopic cholecystectomy (removal of gallbladder by laparoscopic surgery) every year in the United States alone (Gurusamy 2008; NIH 1992). Laparoscopic surgery offers various advantages over conventional open surgery: less postoperative pain, smaller scars, shorter hospital stay, and quicker recovery etc (Ahmad 2008; Birch 2011; Harrell 2005). It has become the gold standard for some abdominal procedures (e.g. laparoscopic cholecystectomy) (Gurusamy 2008; Keus 2006).
Description of the intervention
Traditionally, the first step in a laparoscopic surgery is the establishment of pneumoperitoneum, including entry into the abdominal cavity and then insufflation of a gas (Ahmad 2008; Birch 2011; Gurusamy 2008; Magaji 2002). There are two common laparoscopic entry techniques: open method (all layers of the abdominal wall are incised and a trocar is then inserted under direct vision) and closed method (only skin is incised and a Veress needle is the inserted blindly) (Ahmad 2008; Magaji 2002). After entry the abdominal cavity, a gas is insufflated into the abdominal cavity through a trocar (open method) or Veress needle (closed method) to separate the abdominal wall from the internal organs (Ahmad 2008; Gurusamy 2008; Magaji 2002). The established pneumoperitoneum provide enough operating space to ensure adequate visualization of camera and manipulation of instruments in the abdominal cavity (Gurusamy 2008; Magaji 2002).
How the intervention might work
The abdominal cavity is insufflated with gas. A pneumoperitoneum of 8 to 20 mmHg is created and maintained for laparoscopic surgery (Gurusamy 2008; Karapolat 2011). An ideal gas for establishing pneumoperitoneum should be cheap, colourless, nonflammable, in explosive, easily excreted, and completely non‐toxic to patients (Menes 2000; Neuhaus 2001; Sammour 2009). Currently, carbon dioxide (CO2) is the most commonly used gas for insufflation (Karapolat 2011). CO2 is absorbed by the peritoneum and delivered directly to the lungs by the circulation (Eaton 2009; Grabowski 2009). At last, it is excreted by the lungs during respiratory exchange (Eaton 2009; Neuhaus 2001). Although CO2 meets most of the requirements (e.g. low cost, nonflammable, chemical stability, and high diffusion capacity with subsequent rapid absorption and excretion), it is not a perfect gas. The absorption of CO2 causes hypercapnia and acidosis, which has to be avoided by hyperventilation (Grabowski 2009; Gurusamy 2008). It is associated with various cardiopulmonary (heart and lung) complications such as tachycardia, cardiac arrhythmias, and pulmonary edema (Gurusamy 2008; Gutt 2004; Kwak 2010). In addition, it may cause postoperative pain due to peritoneal irritation, and its use is associated with immunological impairment (Grabowski 2009; Neuhaus 2001). Elderly patients with cardiopulmonary diseases are more likely to suffer from the adverse events (Grabowski 2009; Karapolat 2011).
Identifying an ideal insufflation gas to replace CO2 remains an active of area of research in the era of laparoscopic surgery (Menes 2000; Neuhaus 2001). Various gases, such as helium (He), argon (Ar), nitrogen (N2), and nitrous oxide (N2O), have been introduced as alternatives of CO2 to establish pneumoperitoneum (Gardner 1995; Karapolat 2011;Menes 2000; Neuhaus 2001; Rammohan 2011). However, their use is controversial. Helium and argon are inert gases which may offer some advantages over CO2 (Gutt 2004; Menes 2000; Neuhaus 2001). Nevertheless, they are less soluble than CO2, which might increase the risk of venous gas embolism (Gutt 2004; Menes 2000; Neuhaus 2001). Nitrous oxide, also known as laughing gas, is a mild anaesthetic (Aboumarzouk 2011). It may reduce postoperative pain theoretically because of anaesthetic and analgesic properties (Rammohan 2011; Tsereteli 2002). However, there have been two cases of explosion using electrocautery during laparoscopy (El‐Kady 1976; Gunatilake 1978), and the risk of explosion when using N2O insufflation remains controversial (Hunter 1995; Neuman 1993; Rammohan 2011).
Why it is important to do this review
Up to now, we have not been able to identify any systematic review or meta‐analysis assessing the different gases for establishing pneumoperitoneum during laparoscopic abdominal surgery.
Objectives
To assess the safety, benefits, and harms of different gases (CO2, He, Ar, N2, N2O, etc) for establishing pneumoperitoneum in patients undergoing laparoscopic abdominal surgery.
Methods
Criteria for considering studies for this review
Types of studies
Randomized controlled trials (RCTs) comparing different gases for establishing pneumoperitoneum in patients undergoing laparoscopic abdominal surgery. We will exclude quasi‐randomized trials (where the allocation is done on the basis of a pseudo‐random sequence, e.g. odd/even hospital number or date of birth, alternation) and non‐randomized studies.
Types of participants
We will include patients (irrespective of age, sex, and race) who are about to undergo laparoscopic abdominal surgery performed by general surgeons. We will exclude patients who are about to undergo laparoscopic pelvic surgery performed by gynaecologic surgeons.
Types of interventions
We will only include the laparoscopic abdominal surgery performed under standard pressure (12 to 16 mmHg) pneumoperitoneum with cold gas insufflation (Gurusamy 2008). We will analysis the following gases for establishing pneumoperitoneum:
-
Carbon dioxide versus nitrous oxide.
-
Carbon dioxide versus helium.
-
Carbon dioxide versus argon.
-
Carbon dioxide versus nitrogen.
-
Carbon dioxide versus any other gas.
-
Any other gas (except carbon dioxide) versus any other gas (except carbon dioxide).
Types of outcome measures
Main outcomes for ‘Summary of findings’ table
-
Complications.
-
Pneumoperitoneum‐related severe adverse events.
-
Cardiopulmonary changes.
-
Pain score (shoulder or abdominal pain).
-
Costs (costs of gases, hospital costs).
Primary outcomes
-
Complications.
-
Pneumoperitoneum‐related cardiopulmonary complications (arrhythmias, ischemias, atelectasis, hypoxaemia, pneumothorax, pulmonary edema).
-
Procedure‐related general complications.
-
-
Pneumoperitoneum‐related severe adverse events (gas embolism, abdominal explosion, port site metastasis).
Secondary outcomes
-
Cardiopulmonary changes (heart rate, blood pressure, blood pH, cardiac output, pulmonary compliance, peak airway pressure).
-
Pain score (shoulder or abdominal pain).
-
Analgesia requirements.
-
Costs (costs of gases, hospital costs).
-
Mortality.
-
Quality of life.
Search methods for identification of studies
We will design the search strategy with the help of Marija Barbateskovic (Trial Search Coordinator) before searching irrespective of language, year or publication status.
Electronic searches
We will search the following databases: The Cochrane Library; MEDLINE, EMBASE, Science Citation Index Expanded, and China Biological Medicine Database (CBM) during the review preparation (Royle 2003). We have given the preliminary search strategies for the listed databases in Appendix 1, Appendix 2, Appendix 3, and Appendix 4.
Searching other resources
We will search the following databases which include ongoing trials: The World Health Organization International Trials Registry Platform search portal (http://apps.who.int/trialsearch/), ClinicalTrials.gov (http://www.clinicaltrials.gov/), Current Controlled Trials (http://www.controlled‐trials.com/), Chinese Clinical Trial Register (http://www.chictr.org/), and EU Clinical Trials Register (https://www.clinicaltrialsregister.eu/). We will also search the references in relevant publications and meeting abstracts (via http://www.asco.org/ASCOv2/Meetings and Conference Proceedings Citation Index) to explore further relevant clinical trials. We also plan to communicate with the authors of RCTs included for more information in the review, if necessary.
Data collection and analysis
We will conduct the systematic review according to the Cochrane Handbook for Systematic Reviews of Intervention (Higgins 2011a).
Selection of studies
After completing all searches, we will merge the search results using the software package Endnote X4 (reference management software) and remove duplicate records of the same report. Two independent review authors (Lin YX, Xiong XZ) will scan the title and abstract of every record identified by the search for inclusion. We will retrieve full text for further assessment if the inclusion criteria are unclear from the abstract. We plan to detect duplicate publication by identifying common authors, centres, details of the interventions, numbers of participants, and baseline data (Higgins 2011b). We intend to correspond with the authors of the RCTs to confirm whether the trial results had been duplicated, if necessary. We will exclude papers not meeting the inclusion criteria and list the reasons for the exclusion. A third review author (Cheng Y) will resolve any discrepancy between the two authors by discussion, and if required, by consultation with the review group's editors.
Data extraction and management
Two authors (Wu SJ, Lin YX) will independently extract the data, check and enter the data into an electronic data collection form (Microsoft Word) (Figure 1; Figure 2). We will resolve any discrepancy between the two authors by consensus.
Data collection form= Figure 1 + Figure 2
Data collection form= Figure 1 + Figure 2
Assessment of risk of bias in included studies
Two review authors (Xiong XZ, Cheng NS) will assess the methodological quality of the included trails independently. We plan to use the quality checklist recommended by the Cochrane Handbook, version 5.1.0 (Table 1) (Higgins 2011c). We will resolve any disagreements by discussion and referral to a third author (Wu TX) for adjudication. We intend to present the results of risk of bias by two figures (a 'Risk of bias graph' figure and a 'Risk of bias summary' figure) generated using Review Manager 5 (RevMan 2011).
| Domain | Support for judgement | Review authors’ judgement |
| Random sequence generation. | Describe the method used to generate the allocation sequence in sufficient detail to allow an assessment of whether it should produce comparable groups. | Selection bias (biased allocation to interventions) due to inadequate generation of a randomized sequence: High risk/Low risk/Unclear risk? |
| Allocation concealment. | Describe the method used to conceal the allocation sequence in sufficient detail to determine whether intervention allocations could have been foreseen in advance of, or during, enrolment. | Selection bias (biased allocation to interventions) due to inadequate concealment of allocations prior to assignment: High risk/Low risk/Unclear risk? |
| Blinding of participants and personnel. | Describe all measures used, if any, to blind study participants and personnel from knowledge of which intervention a participant received. Provide any information relating to whether the intended blinding was effective. | Performance bias due to knowledge of the allocated interventions by participants and personnel during the study: High risk/Low risk/Unclear risk? |
| Blinding of outcome assessment. | Describe all measures used, if any, to blind outcome assessors from knowledge of which intervention a participant received. Provide any information relating to whether the intended blinding was effective. | Detection bias due to knowledge of the allocated interventions by outcome assessors: High risk/Low risk/Unclear risk? |
| Incomplete outcome data. | Describe the completeness of outcome data for each main outcome, including attrition and exclusions from the analysis. State whether attrition and exclusions were reported, the numbers in each intervention group (compared with total randomized participants), reasons for attrition/exclusions where reported, and any re‐inclusions in analyses performed by the review authors. | Attrition bias due to amount, nature or handling of incomplete outcome data: High risk/Low risk/Unclear risk? |
| Selective reporting. | State how the possibility of selective outcome reporting was examined by the review authors, and what was found. | Reporting bias due to selective outcome reporting: High risk/Low risk/Unclear risk? |
| Other sources of bias. | State any important concerns about bias not addressed in the other domains in the tool. | Bias due to problems not covered elsewhere in the table: High risk/Low risk/Unclear risk? |
Measures of treatment effect
We will perform the meta‐analyses using the software package Review Manager 5 (RevMan 2011). For dichotomous outcomes, we will calculate the risk ratio (RR) with 95% confidence interval (Deeks 2011). In case of rare events, we plan to calculate the Peto odds ratio (Peto OR) (Deeks 2011). For continuous outcomes, we will calculate mean difference (MD) with 95% confidence interval (Deeks 2011). For continuous outcomes with different measurement scales in different randomized clinical trials, we will calculate standardized mean differences (SMD) with 95% confidence interval (Deeks 2011).
Unit of analysis issues
The unit of analysis is each patient. We will analyze data using the generic inverse‐variance method in RevMan for cluster‐randomized trials (Higgins 2011d). We will analyze only data from the first period of treatment for cross‐over trials (Higgins 2011d). We will combine groups to create a single pair‐wise comparison for trials with multiple intervention groups (Higgins 2011d).
Dealing with missing data
We will contact the original investigators to request further information in case of missing data. If there is no reply, we will perform the analysis on an 'intention‐to‐treat' (ITT) principle, if applicable (Newell 1992). Otherwise, we will use only the available data in the analysis.
Assessment of heterogeneity
We plan to describe the heterogeneity by using the Chi2 test (Deeks 2011). The P value less than 0.10 is considered to be significant heterogeneity (Deeks 2011). We also plan to use the I2 statistic to measure the quantity of heterogeneity. In case of heterogeneity, we will perform the meta‐analysis and interpret the result cautiously. We will explore the clinical heterogeneity by comparing the characteristics of participants, interventions, controls, outcome measures and study designs in the included studies. We plan to undertake the following approaches for explanation and solution: (1) Check again that the data are correct; (2) Change the effect measure; (3) analysis using the random‐effects model; (4) sensitivity analysis by excluding potentially biased trails; (5) subgroup analysis or meta‐regression; (6) present all trails and provide a narrative discussion (Deeks 2011).
Assessment of reporting biases
If meta‐analysis is possible, we plan to use funnel plots to assess reporting biases (Sterne 2011). Visual asymmetry in funnel plots will be used to determine the reporting biases (Sterne 2011). We also plan to perform linear regression approach to determine the funnel plots asymmetry (Egger 1997). We will not perform funnel plots if the number of trails included is less than ten (Sterne 2011).
Data synthesis
We will perform the meta‐analyses using Review Manager 5 software provided by The Cochrane Collaboration (RevMan 2011). Two review authors (Wu SJ, Xiong XZ) will check and enter all data into Review Manager independently. We will resolve any disagreement by consensus. For all analyses, we will employ both fixed‐effect and random‐effects models. We will only report the fixed‐effect model results when there is no discrepancy between the two models. In case of discrepancy between the two models, we will report both results.
Subgroup analysis and investigation of heterogeneity
If there is a significant heterogeneity among the RCTs, we plan the following subgroup analyses:
-
Trials with low risk of bias versus trials with high risk of bias.
-
The type of operation (laparoscopic surgery of stomach, gallbladder, liver, pancreas, spleen, intestine, kidney, etc).
-
High risk patients (e.g. patients with cardiopulmonary disease; American Society of Anesthesiologists (ASA) Ⅲ or Ⅳ) versus low risk patients (e.g. patients without cardiopulmonary disease; American Society of Anesthesiologists (ASA) Ⅰ or Ⅱ).
Sensitivity analysis
We will perform sensitivity analyses to see whether conclusions are robust to decisions made during the review process following the method as follows:
-
Changing statistics among risk ratio (RR), risk differences (RD) and odds ratios (OR) for dichotomous outcomes.
-
Changing statistics between mean difference (MD) and standardized mean differences (SMD) for continuous outcomes.
-
Excluding RCTs with low quality.
-
Excluding RCTs with either small or large sample sizes.
-
Excluding non‐English literatures.
If the results do not change, they are considered to have low sensitivity. If the results change, they are considered to have high sensitivity.
Data collection form= Figure 1 + Figure 2
Data collection form= Figure 1 + Figure 2
| Domain | Support for judgement | Review authors’ judgement |
| Random sequence generation. | Describe the method used to generate the allocation sequence in sufficient detail to allow an assessment of whether it should produce comparable groups. | Selection bias (biased allocation to interventions) due to inadequate generation of a randomized sequence: High risk/Low risk/Unclear risk? |
| Allocation concealment. | Describe the method used to conceal the allocation sequence in sufficient detail to determine whether intervention allocations could have been foreseen in advance of, or during, enrolment. | Selection bias (biased allocation to interventions) due to inadequate concealment of allocations prior to assignment: High risk/Low risk/Unclear risk? |
| Blinding of participants and personnel. | Describe all measures used, if any, to blind study participants and personnel from knowledge of which intervention a participant received. Provide any information relating to whether the intended blinding was effective. | Performance bias due to knowledge of the allocated interventions by participants and personnel during the study: High risk/Low risk/Unclear risk? |
| Blinding of outcome assessment. | Describe all measures used, if any, to blind outcome assessors from knowledge of which intervention a participant received. Provide any information relating to whether the intended blinding was effective. | Detection bias due to knowledge of the allocated interventions by outcome assessors: High risk/Low risk/Unclear risk? |
| Incomplete outcome data. | Describe the completeness of outcome data for each main outcome, including attrition and exclusions from the analysis. State whether attrition and exclusions were reported, the numbers in each intervention group (compared with total randomized participants), reasons for attrition/exclusions where reported, and any re‐inclusions in analyses performed by the review authors. | Attrition bias due to amount, nature or handling of incomplete outcome data: High risk/Low risk/Unclear risk? |
| Selective reporting. | State how the possibility of selective outcome reporting was examined by the review authors, and what was found. | Reporting bias due to selective outcome reporting: High risk/Low risk/Unclear risk? |
| Other sources of bias. | State any important concerns about bias not addressed in the other domains in the tool. | Bias due to problems not covered elsewhere in the table: High risk/Low risk/Unclear risk? |
