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Cochrane Database of Systematic Reviews Protocol - Intervention

Total intravenous anaesthesia versus inhalational anaesthesia for transabdominal robotic assisted laparoscopic surgery

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Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

To assess the outcomes related to the choice of anaesthesia (TIVA versus Inhalational anaesthesia) for adult patients undergoing transabdominal robotic assisted gynaecological, urological or gastroenterological surgery.

Background

Description of the condition

The introduction of robotic transabdominal surgery has resulted in a need for a re‐evaluation of the most suitable form of anaesthesia. The objective is to minimize the perioperative risk and discomfort for patients during surgery. Anaesthesia for patients undergoing robotic surgery is different from anaesthesia for patients undergoing open or laparoscopic surgery and new anaesthetic concerns accompany robotic surgery. These concerns include the physiological effects of fixed extreme positioning of the patient during a long period of time, pneumoperitoneum, restricted access to the patient during surgery and the need for carefully monitored relaxation of the patient. Regardless of the method of surgery it is universal that the three anaesthetic qualities, which include sleep, freedom from pain and muscle relaxation, can be reached by two methods:

  1. total intravenous anaesthesia (TIVA) in which the patient receives all anaesthetic drugs through an intravenous line; or

  2. inhalational anaesthesia, in which one of the drugs is delivered through the lungs.

This review addresses the advantages and disadvantages of TIVA compared to inhalational anaesthesia in transabdominal robotic surgery.

Anaesthetists advocating for TIVA might highlight the lower risks of both postoperative nausea and vomiting (PONV) and pollution of the operating room and environment compared to anaesthesia gas (Vari 2010). However, those advocating for inhalational anaesthesia might focus on easier monitoring and regulation of the delivered anaesthesia, faster emergence from the anaesthesia and, although controversial in non‐cardiac surgery, the proposed cardioprotective effect of inhalational anaesthesia (Landoni 2009). It has to be considered how these circumstances influence patients in the context of transabdominal robotic surgery.

Two issues in transabdominal surgery that might influence the outcome of the anaesthesia are positioning and pneumoperitoneum. Extreme positioning, for example steep Trendelenburg (in lower abdominal surgery) or steep anti‐Trendelenburg (in upper abdominal surgery), and insufflation of carbon dioxide in the abdominal cavity affect the patient's cardiovascular and respiratory systems as well as the intracerebral pressure. At the same time, the patient’s normal compensatory mechanisms are blunted by the anaesthesia. Absorption of carbon dioxide over the abdominal tissue membranes, as well as the upwards pressure on the diaphragm and compromised venous return, is a constant challenge to the patient's respiratory and circulatory systems. These physiological disturbances are tolerated differently by patients according to their age, body mass index (BMI), medications and comorbidity.

The restricted access to the patient during often lengthy surgery demands careful preparation of the intravenous lines and the monitoring equipment as well as a focus on avoiding nerve damage and ocular injuries (Awad 2012; Kakar 2011; Sullivan 2008; Yoo 2014).

The refinement of surgical conditions in transabdominal robotic surgery with reduced bleeding and the potential advantages of lower rates of surgical trauma due to minor incisions makes it possible to consider surgery for a broader patient population. Some of the patients subjected to robotic surgery may have been considered inoperable by traditional operating techniques, especially the growing patient population with a very high BMI (Stone 2010). This additional aspect of change in patient selection has to be considered when choosing the type of anaesthesia.

Robotic surgery is increasingly used in the treatment of cancer in gynaecology (Mettler 2008), in urology (Sohn 2013) and in gastrointestinal oncology (Mak 2014; Papanikolaou 2014).

Anaesthesia for robotic surgery in the treatment of cancer involves another aspect of the choice of aesthesic, namely a potential different effect of inhalational agents and TIVA on the immune system thereby influencing the recurrence of cancer (Fodale 2014).

The use of robotic surgery is expanding rapidly in the developed world. At present there are two manufacturers of robotic surgical systems on the market (Paranjape 2014). One is the Zeus Surgical System (Computer Motion) and the other is the da Vinci Surgical System (Intuitive Surgical). The latter manufacture claims that 2900 da Vinci robots are located throughout the world and that more than half a million robotic assisted surgeries were performed in 2013. The high cost and increasing volume of robotic assisted surgeries has implications for public health (Barbash 2010) as health services have limited budgets and there is limited evidence in terms of large multicentre randomised controlled trials (RCTs) to determine which patients may benefit from robotic surgery as opposed to conventional surgery (Gurusamy 2012; Liu 2012; Shi 2012). Outcomes such as shorter length of stay, less postoperative pain, fewer episodes of PONV, faster recovery and return to habitual functioning after anaesthesia and surgery are of great importance to public health.

This review compares two different anaesthesia techniques for transabdominal robotic surgery and focuses on postoperative patient comfort (pain, PONV, perioperative cardiovascular and respiratory conditions) and patient safety.

Description of the intervention

For maintenance of anaesthesia it is possible to use either TIVA or a halogenated inhalational agent in combination with intravenous drugs for maintaining a painless operation. The drugs used for maintaining a painless operation are mainly opioid‐based but might also be a secondary analgesic or a regional anaesthetic administered as a central nervous blockade (Gerges 2006).

This review will focus on the applicability of anaesthesia for transabdominal robotic assisted surgery with an intravenous infusion of a hypnotic and a pain killing agent compared to a halogenated inhalational agent together with an analgesic. We will not consider the level of relaxation, combination with regional anaesthesia or local infiltration in this review. Instead, we will focus on different aspects of delivering these two types of anaesthesia regimens and include measures of pain, PONV, cardiovascular and pulmonary impact, effects on cerebral autoregulation, cognitive function, practical aspects, controllability as well as environmental effects.

How the intervention might work

The difference between the two anaesthesia types that we plan to study resides in their physiological properties as well as the practical delivery of the drugs. While delivery of anaesthesia gas is easily monitored via the ventilator, the pumps and intravenous lines associated with TIVA are potentially exposed to error through accidental disconnection. It is also important to consider the cardiovascular stability with the drugs being used during anaesthesia for transabdominal robotic surgery, where patients are in unphysiologic positions such as the steep head‐down (Trendelenburg) or steep head‐up (anti‐Trendelenburg) position. Traditionally, anaesthesia gas is considered to be easier to control than TIVA‐based anaesthesia in patients with cardiovascular morbidity (Landoni 2009) and possibly to have cardioprotective properties during cardiac surgery (Hert 2003), although this might be controversial for non‐cardiac surgery (Landoni 2009). For obese patients undergoing surgery such as knee arthroscopy, transurethral resection of the prostate, minor breast or hand surgery, inhalational anaesthetics (desflurane) may have a safer profile than propofol with regards to postoperative pulmonary function. This has been measured by surrogate outcomes such as oxyhaemoglobin saturation and lung function (Zoremba 2011). The combination of extreme positioning together with pneumoperitoneum during most transabdominal robotic procedures are factors that are known to affect intracerebral pressure (Kalmar 2010). For this reason, it is important that the anaesthesia for this type of surgery preserves the cerebral autoregulatory mechanisms in order to prevent cerebral events and postoperative cognitive dysfunction. Comparative studies of the use of sevoflurane versus propofol‐remifentanil for spinal or maxillo‐facial surgery have indicated that propofol preserves cerebral autoregulation whereas this is not the case when sevoflurane is used in higher concentrations (Conti 2006). The cerebral vascular responsiveness to carbon dioxide (CO2) is impaired during sevoflurane anaesthesia but not during anaesthesia with propofol‐remifentanil (Conti 2006).

Why it is important to do this review

Robot assisted techniques are increasingly used for a wide variety of surgical specialties in the developed world (Barbash 2010). It is imperative that the outcomes of the anaesthesia for transabdominal robotic surgery are known. The advantages and disadvantages must be clear for both clinicians and patients so that the most appropriate anaesthesia technique can be chosen. At present we know of isolated RCTs (Atallah 2009; Yoo 2012) which address this clinical question in specialized areas of the field (either gynaecology, urology or gastroenterology). We expect this body of evidence to expand within the next few years as there are several ongoing trials registered at http://clinicaltrials.gov/ (NCT01402622; NCT01744262; NCT01898897; NCT00863928).

Objectives

To assess the outcomes related to the choice of anaesthesia (TIVA versus Inhalational anaesthesia) for adult patients undergoing transabdominal robotic assisted gynaecological, urological or gastroenterological surgery.

Methods

Criteria for considering studies for this review

Types of studies

We will include RCTs conducted in any clinical or research setting where the management of anaesthesia in transabdominal robotic surgery is the intervention.

Types of participants

We will include adult patients aged 18 years and older, of both genders and treated with transabdominal robotic assisted gynaecological, urological or gastroenterological surgery.

Types of interventions

We will include the following interventions during transabdominal robotic assisted surgery.

  1. TIVA (propofol and opioid‐based) versus inhalational‐based anaesthesia (isoflurane, desflurane or sevoflurane in combination with an opioid).

Types of outcome measures

Primary outcomes

  1. Postoperative pain within 24 hours (as measured by the authors of the included studies)

  2. PONV within 24 hours (as measured by the authors of the included studies)

Secondary outcomes

  1. Adverse effects (as measured by the authors of the included studies), for example cerebral oedema, stroke and ocular complications

  2. All‐cause mortality within 90 days

  3. Respiratory complications requiring treatment within 48 hours (as measured by the authors of the included studies)

  4. Circulatory complications requiring treatment within 48 hours (as measured by the authors of the included studies)

  5. Cognitive dysfunction (as measured by the authors of the included studies)

  6. Length of stay in the postoperative ward (as measured by the authors of the included studies)

  7. Costs (as measured by the authors of the included studies)

Search methods for identification of studies

Electronic searches

We will search the Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library (current issue), Ovid MEDLINE (1946 to date), EMBASE via OvidSP (1982 to date), CINAHL via EBSCOhost (1982 to date) and ISI Web of Science (1956 to date).

We will adapt our MEDLINE search strategy (Appendix 1) for searching other databases. The search terms are a combination of thesaurus‐based and free text terms for the interventions.

There will be no language restrictions or limitations because of publications status.

Searching other resources

We will search:

  1. http://www.who.int/ictrp/en/; and

  2. http://www.clinicaltrials.gov/.

Data collection and analysis

Selection of studies

Two review authors (SH and BD) will select the studies that are eligible by reviewing the titles and abstracts in order to decide if the studies fulfil the inclusion criteria. We (SH and BD) will assess the full text articles of the eligible studies to decide if they are relevant for inclusion. We (SH and BD) will resolve any disagreement by discussion with a third review author (AM), and if there is any missing information or inconsistencies in the studies we (SH or BD) will contact the authors of the studies.

Data extraction and management

We (SH and BD) will extract data from published papers or reports from the original researchers. We (SH and BD) will use a modified version of the Cochrane Anaesthesia Review Group (CARG) data extraction form (see Appendix 2). This form includes data on participants, risk of bias, methods of randomization, blinding, reporting of outcomes, results and applicability. We will record the information in the characteristics of included and excluded studies and risk of bias sections at the review stage. We (SH and BD) will resolve disagreements by discussion with a third author (AM). SH will enter extracted data into Review Manager 5 (RevMan 5.2) for the analysis and BD will check the accuracy of these data.

Assessment of risk of bias in included studies

SH and BD will independently assess the risk of bias in the studies to be included using the criteria in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We will report on the following domains:

  1. adequate sequence generation,

  2. allocation concealment,

  3. blinding of outcome assessment,

  4. incomplete outcome data,

  5. selective reporting, and

  6. other bias.

We will grade the studies as 'low risk', 'high risk' or 'unclear risk' of bias. We (SH and BD) will resolve any disagreement by discussion with a third author (AM).

We (SH and BD) will create plots of risk of bias in Review Manager (RevMan 5.2).

Measures of treatment effect

We will report results in absolute numbers, providing mean differences for the event rate of postoperative pain and PONV with 95% confidence intervals (CIs). We will report risk ratios (RR) for adverse events, mortality and complications.

Unit of analysis issues

We do not expect to encounter any unit of analysis issues as we do not expect to find any cluster‐randomized trials or cross‐over trials.

Dealing with missing data

We will conduct intention‐to‐treat (ITT) analysis for all outcomes, as far as possible. For studies with more dropouts than estimated, we will contact the trialists for additional data on those participants lost to follow up. We will perform a sensitivity analysis of best case versus worst case scenarios.

Assessment of heterogeneity

We will assess heterogeneity between studies by visual inspection of forest plots. We will then assess the statistical heterogeneity of effect sizes by means of the I2 statistic and the Chi2 test. The I2 statistic describes the percentage of total variation across trials due to sampling error (Higgins 2011) rather than to heterogeneity. We will conduct a meta‐analysis if we visually (forest plot), statistically (I2 statistic) and clinically find the heterogeneity acceptable (low enough). We will proceed with a meta‐analysis if populations, interventions, comparisons, measurements, timeframes and settings are reasonably similar, if there are three or more studies, and if the direction of effect of an intervention is consistent. All authors will discuss and agree upon when to conduct a meta‐analysis.

Assessment of reporting biases

We will assess reporting bias by a thorough search for unpublished studies and by contacting known experts, leading authors and pharmaceutical companies in the field. If we find more than 10 studies we will include a funnel plot (Egger 1997) in the review.

Data synthesis

If we identify moderate heterogeneity (I2 value 30% to 60%) we will use a fixed‐effect model. If we identify substantial heterogeneity (I2 value 50% to 90%) we will use a random‐effects model. All statistics will be performed in Review Manager (RevMan 5.2). If we identify considerable heterogeneity (I2 value 75% to 100%) we will not pool the data. If this is the case, we will summarize the studies, present the information in tables and describe them qualitatively. The evidence of heterogeneity will be considered significant based on a P < 0.05 for the Chi2 test and from the 95% confidence intervals (CI) for the I2 statistic.

Subgroup analysis and investigation of heterogeneity

It is possible that the following subgroups might obtain different outcomes than the remaining population and should undergo a subgroup analysis:

  1. patients in gynaecology;

  2. patients in urology;

  3. patients in gastroenterology;

  4. patients positioned head up;

  5. women.

Sensitivity analysis

Provided sufficient studies are identified, we plan to perform a sensitivity analysis by comparing the results with the inclusion and exclusion of the RCTs classified to have a 'low risk of bias' to decide whether our conclusions are robust (Higgins 2011).

Summary of findings

We will use the principles of the GRADE system (Guyatt 2008) to assess the quality of the body of evidence associated with the following specific outcomes.

  1. Postoperative pain within 24 hours.

  2. PONV within 24 hours.

  3. Adverse effects (as measured by the authors of the included studies), for example cerebral oedema, stroke and ocular complications.

  4. All‐cause mortality within 90 days.

  5. Respiratory complications requiring treatment within 48 hours (as measured by the included studies).

  6. Circulatory complications requiring treatment within 48 hours (as measured by the included studies).

  7. Costs (as measured by the included studies).

in our review we will construct a summary of findings (SoF) table using the GRADE software. The GRADE approach appraises the quality of a body of evidence based on the extent to which one can be confident that an estimate of effect or association reflects the item being assessed. The quality of a body of evidence takes into consideration within study risk of bias (methodologic quality), the directness of the evidence, heterogeneity of the data, precision of effect estimates and risk of publication bias (Guyatt 2008).