Interventions for preventing hypothermia during caesarean delivery under regional anaesthesia
Abstract
This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:
To assess the interventions used for prevention of hypothermia in women undergoing caesarean delivery under regional anaesthesia.
Background
Caesarean delivery is a commonly‐performed surgical procedure for the delivery of a newborn infant. The procedure is frequently performed under regional (spinal or epidural) anaesthesia, although general anaesthesia may also be used. Whilst caesarean deliveries may be performed electively, in more than half of cases they are required as an emergency procedure for a woman in labour, where there is perceived to be a threat to maternal or fetal well‐being (Bragg 2010).
Body temperature is closely regulated in humans to maintain a core temperature around 37 degrees Celsius (°C). Thermoreceptors in the skin, deep abdominal viscera and brain/spinal cord provide temperature information to the anterior hypothalamus which triggers a response. Responses can be behavioural or physical. Behavioural responses may include adding or removing clothing or increasing or decreasing the temperature of the environment. Various physiological responses to hypothermia can be mounted, and may include shivering, vasoconstriction of the skin and piloerection of hair follicles. Responses to hyperthermia include sweating and vasodilation (Sessler 1997).
Description of the condition
Anaesthesia interferes with the normal mechanisms of thermoregulation, and as a result, hypothermia is a common consequence of many types of surgery (Arkilic 2000). Conceptually, the reduction in body temperature occurs in several phases. Initially, peripheral vasodilation (a feature of both regional and general anaesthesia) allows a phase of rapid redistribution of body heat from the body’s core to the cooler periphery. Secondly, this heat is lost to the environment (through radiation, conduction and convection) until a third phase of equilibrium is reached (Carpenter 2012; Sessler 1997).
Hypothermia is typically defined as a core body temperature of less than 36 °C (Sultan 2015). Maternal hypothermia can occur during caesarean delivery under either regional or general anaesthesia. This has multiple potential adverse consequences for maternal and neonatal well‐being.
Adverse effects of even mild to moderate hypothermia can include maternal distress caused by shivering and thermal discomfort, increased rates of wound infection (Kurz 1996; Melling 2001) and coagulopathy. As a result, maternal hypothermia has been associated with increased blood loss and higher transfusion requirements (Rajagopalan 2008). Although less likely in the obstetric population, perioperative hypothermia has also been shown to increase myocardial ischaemia (Frank 1997; Leslie 2003; Sessler 1997) and impair drug metabolism (Leslie 1995). Studies have shown that neonatal hypothermia occurs rapidly and can lead to several adverse outcomes, which include lower Apgar scores observed in neonates born to hypothermic mothers (Paris 2014).
Description of the intervention
Commonly‐employed techniques to prevent hypothermia include administration of warmed intravenous fluids (Campbell 2015; Oshvandi 2014) and the use of forced air devices, which blow warmed air over the woman by means of a perforated blanket (Butwick 2007; Forbes 2009; Kurz 1993). Other strategies may include warming mattresses and blankets containing chemicals that produce warmth through an exothermic reaction (Chakladar 2014). Previously‐published Cochrane Reviews in non‐obstetric surgery have assessed the efficacy of warmed fluids (Campbell 2015), forced air warming blankets (Madrid 2016) and thermal insulation (Alderson 2014).
Pre‐warming is the application of heat in the period immediately prior to surgery. This aims to warm the woman’s periphery and thereby reduce the initial phase of thermal redistribution. Whilst pre‐warming can theoretically use any of the techniques used for intra‐operative warming, forced air warming is the most common technique.
National Institute of Health and Care Excellence (NICE) guidelines recognise management of temperature as an important aspect of perioperative care (Harper 2008) and evidence‐based guidelines have been published (Forbes 2009).
There are several reasons why common strategies for warming may be difficult to use during caesarean delivery. Forced air warming blankets are cumbersome and difficult to use on the upper body in awake women, especially in women who wish to bond by skin‐to‐skin contact with their newborn baby. Lower body forced air warming is limited by the need for exposure of the entire abdomen to perform the caesarean delivery, and therefore may be ineffective (Butwick 2007). Pre‐warming of women has been shown to be effective (Chung 2012), but is unlikely to be possible in emergency situations prior to surgery.
How the intervention might work
Forced air warming
Forced air warming devices consist of a base unit, a length of conducting hose and a disposable blanket. The base unit contains an electric motor and fan, electric heating element, thermostat and air filter. The hosing is connected to the blanket and the fan draws air through the filter, the heating element heats the air to the set temperature, which is controlled by the thermostat. The contact surface of the blanket is permeable to air, and the warm air leaves the blanket and moves over the woman. The heat is transferred through convection (Cleves 2010b), and the blanket prevents convective and radiant heat loss from exposed skin (John 2014). NICE guidelines suggest that there is stronger evidence to support the use of forced air warming over other warming methods.
The risk of thermal injury with forced air warming devices is very low, if used according to manufacturers' guidelines; for example, the hosing should not be used to direct warmed air under a non‐compatible blanket, which can result in burns. These devices should not be used over wet skin, as evaporative cooling may result (Cleves 2010b).
Intravenous fluid warming systems
Intravenous fluid warming systems consist of a fluid bag, a filter if blood products are being administered, the warming device’s heat exchanger, an air trap or detector, and tubing carrying the warmed fluid to the woman’s intravenous cannula. The air trap or detector is required, as air may bubble out of solution when the fluid is warmed, so any bubbles should be removed before the fluid passes to the woman’s cannula. Warming devices within this system can consist of a plate warmer, where one or more large metal plates are used to heat the fluid. The next option is a drum warmer, where the fluid tubing is wrapped around grooves in the drum, which warms the fluid. A counter current warmer consists of a recirculating fluid that is warmed, and runs in the opposite direction to the intravenous fluid which passes in channels next to the recirculating fluid. Induction warmers use an electromagnetic field to induce heat in a metal component of the fluid administration set, which warms the intravenous fluid. Halogen lamps in an infrared warmer are used to heat fluid by infrared radiation. Forced air warmers use an air warmer device to heat the fluid passing in a tube within the warmer. The sleeve on patient line technique uses a warmed sleeve around the fluid line, in which the sleeve can be electrically heated or a heated recirculating fluid is used (Cleves 2010a).
Safety considerations when using fluid warmers include temperature control, which is guided by sensors. Air detection and removal systems such as bubble traps prevent air entering the fluid to be administered. Flow control prevents errors in pressure delivery, either by roller clamps in the fluid heating system or by using a separate fluid pump in addition to the fluid warmer (Cleves 2010a). There is a low risk of infection or electrolyte disturbances with counter current warming systems, if there is a leak in the coaxial tubing (John 2014).
An alternative to intravenous fluid warmers is the use of warming cabinets. Fluid bags are pre‐warmed in the cabinet, and the fluid is administered through a conventional giving set. This is a cheaper and simpler option which can achieve fluid temperatures similar to fluid warming devices, especially if the pre‐warmed bag is insulated. The main disadvantage of this method is the potential cooling effect from slow fluid delivery rates through long thing tubing, which may decrease the delivered fluid temperature (John 2014).
Resistive heating
Resistive heating uses electric current through semiconductor material in a mattress or blanket. Heat transfer occurs by conduction, and this technique has been shown to have similar efficacy to forced air warming blankets. The benefits include greater body surface area availability for warming when using a mattress, as compared with a forced air blanket, which may only cover the upper or lower part of the body. The efficacy can be influenced by the degree of tissue perfusion to dependent areas of the woman. Caution needs to be used to avoid excessive temperatures, and burns have occurred in children (John 2014).
Pre‐warming of women
Pre‐warming of women has been shown to be effective (Chung 2012), but is unlikely to be possible in emergency situations prior to surgery. Pre‐warming consists of the application of peripheral or cutaneous warming prior to induction of anaesthesia (De Brito 2013). The warming technique often consists of a forced air blanket prior to surgery. Administration of vasodilatory medication such as nifedipine allows a short period of pre‐warming to be more efficacious. Vasodilatation also counteracts the redistribution hypothermia effect of general or regional anaesthesia (Sessler 1997).
Why it is important to do this review
Whilst systematic reviews have been previously published on this subject (Munday 2014; Sultan 2015), none has been subject to Cochrane methodology and this topic has not been previously published in the Cochrane Library. There are several possible confounders which may result in bias in studies in this area, including maternal, anaesthetic, surgical and environmental factors. Maternal confounders may include obstructed labour and epidural anaesthesia, both of which have been associated with maternal fever (Goetzl 2012; Goetzl 2014). The mechanism of this fever is uncertain. Also, vasodilation is a common consequence of regional anaesthesia. It is likely that this vasodilation increases heat loss from the peripheries. Several different medications and other strategies are used to treat this vasodilation. It is possible that different strategies (for example, metaraminol or phenylephrine) could have differing effects on heat loss by way of their different effects on vasodilation. Surgical factors such as surgical duration, exteriorisation of the uterus and peritoneal washings may also potentially confound the results, as may environmental factors such as ambient temperature of the operating room (as well as the pre‐operative area) (Duryea 2016).
Objectives
To assess the interventions used for prevention of hypothermia in women undergoing caesarean delivery under regional anaesthesia.
Methods
Criteria for considering studies for this review
Types of studies
We will include randomised controlled trials (RCTs). There may be cluster‐randomised trials relevant to this review (for example, where the intervention is operating theatre ambient temperature). We will include these studies. We will exclude quasi‐randomised and cross‐over trials. When studies are published in abstract form we will list the study as ‘awaiting classification’ and attempt to contact the authors with a view to either obtaining the raw study data or acquiring the full study publication when available.
Types of participants
Women undergoing caesarean delivery, either elective or emergency, and under regional anaesthesia.
Types of interventions
Any intervention specifically for the prevention of hypothermia during or following caesarean delivery, including (but not limited to):
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'forced‐air warming' devices (upper body or lower body);
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'self‐warming' blankets using exothermic chemical reactions;
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warming mattresses (warming from underneath the woman);
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pre‐warmed intravenous fluids (e.g. from a ‘warming cabinet’);
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co‐warmed intravenous fluids (e.g. by a Ranger ® device);
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'pre‐warming' of women by any means administered prior to surgery.
Types of outcome measures
Primary outcomes
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Change in maternal core body temperature from pre‐operative/beginning of surgery to postoperative/end of surgery
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Incidence (proportion) of women with hypothermia (core temperature < 36 °C)
Secondary outcomes
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Incidence of shivering (% of participants, if reported, severity of shivering)
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Thermal comfort (verbal or numeric rating score)
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Wound infection (proportion (%) of participants with wound infection
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Estimated perioperative blood loss
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Neonatal outcomes including Apgar scores and umbilical artery/vein pH scores, incidence of neonatal hypothermia
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Incidence of adverse effects, including maternal or neonatal excessive warming/hyperthermia
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Maternal acceptability or satisfaction, or both
Search methods for identification of studies
The following methods section of this protocol is based on a standard template used by Cochrane Pregnancy and Childbirth.
Electronic searches
We will search Cochrane Pregnancy and Childbirth’s Trials Register by contacting their Information Specialist.
The Register is a database containing over 23,000 reports of controlled trials in the field of pregnancy and childbirth. For full search methods used to populate Cochrane Pregnancy and Childbirth’s Trials Register including the detailed search strategies for CENTRAL, MEDLINE, Embase and CINAHL; the list of handsearched journals and conference proceedings, and the list of journals reviewed through the current awareness service, please follow this link to the editorial information about Cochrane Pregnancy and Childbirth in the Cochrane Library and select the ‘Specialized Register ’ section from the options on the left side of the screen.
Briefly, the Cochrane Pregnancy and Childbirth’s Trials Register is maintained by their Information Specialist and contains trials identified from:
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monthly searches of the Cochrane Central Register of Controlled Trials (CENTRAL);
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weekly searches of MEDLINE (Ovid);
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weekly searches of Embase (Ovid);
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monthly searches of CINAHL (EBSCO);
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handsearches of 30 journals and the proceedings of major conferences;
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weekly current awareness alerts for a further 44 journals plus monthly BioMed Central email alerts.
Two people screen the search results and review the full text of all relevant trial reports identified through the searching activities described above. Based on the intervention described, each trial report is assigned a number that corresponds to a specific Pregnancy and Childbirth review topic (or topics), and is then added to the Register. The Information Specialist searches the Register for each review using this topic number rather than keywords. This results in a more specific search set that will be fully accounted for in the relevant review sections (Included, Excluded, Awaiting Classification or Ongoing).
In addition, we will search ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform (ICTRP) for unpublished, planned and ongoing trial reports (see: Appendix 1 for search terms).
Searching other resources
We will search the reference lists of retrieved studies.
We will not apply any language or date restrictions.
Data collection and analysis
Selection of studies
Two review authors will independently assess for inclusion all the potential studies we identify as a result of the search strategy. We will resolve any disagreement through discussion or, if required, we will consult the third review author.
We will create a study flow diagram to map out the number of records identified, included and excluded.
Data extraction and management
We will design a form to extract data. For eligible studies, at least two review authors will extract the data using the agreed form. We will extract the data relevant to our primary and secondary outcomes. We will also extract other data including the setting of the study, the dates of participant recruitment, any sources of funding and other declarations of interest by the authors.
We will resolve discrepancies through discussion or, if required, we will consult the third review author. We will enter data into Review Manager 5 software (RevMan 2014) and check them for accuracy. When information about any of the above is unclear, we will try to contact authors of the original reports to provide further details.
Assessment of risk of bias in included studies
Two review authors will independently assess risks of bias for each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We will resolve any disagreement by discussion or by involving a third assessor.
(1) Random sequence generation (checking for possible selection bias)
We will describe for each included study the method used to generate the allocation sequence in sufficient detail to allow an assessment of whether it should produce comparable groups.
We will assess the method as:
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low risk of bias (any truly random process, e.g. random‐number table; computer random‐number generator);
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high risk of bias (any non‐random process, e.g. odd or even date of birth; hospital or clinic record number); or
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unclear risk of bias.
(2) Allocation concealment (checking for possible selection bias)
We will describe for each included study the method used to conceal allocation to interventions prior to assignment and will assess whether intervention allocation could have been foreseen in advance of, or during recruitment, or changed after assignment.
We will assess the methods as:
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low risk of bias (e.g. telephone or central randomisation; consecutively‐numbered sealed opaque envelopes);
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high risk of bias (open random allocation; unsealed or non‐opaque envelopes, alternation; date of birth);
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unclear risk of bias.
(3.1) Blinding of participants and personnel (checking for possible performance bias)
We will describe for each included study the methods used, if any, to blind study participants and personnel from knowledge of which intervention a participant received. We will consider that studies are at low risk of bias if they were blinded, or if we judge that the lack of blinding would be unlikely to affect results. We will assess blinding separately for different outcomes or classes of outcomes.
We will assess the methods as:
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low, high or unclear risk of bias for participants;
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low, high or unclear risk of bias for personnel.
(3.2) Blinding of outcome assessment (checking for possible detection bias)
We will describe for each included study the methods used, if any, to blind outcome assessors from knowledge of which intervention a participant received. We will assess blinding separately for different outcomes or classes of outcomes.
We will assess methods used to blind outcome assessment as:
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low, high or unclear risk of bias.
(4) Incomplete outcome data (checking for possible attrition bias due to the amount, nature and handling of incomplete outcome data)
We will describe for each included study, and for each outcome or class of outcomes, the completeness of data including attrition and exclusions from the analysis. We will state whether attrition and exclusions were reported and the numbers included in the analysis at each stage (compared with the total randomised participants), reasons for attrition or exclusion where reported, and whether missing data were balanced across groups or were related to outcomes. Where sufficient information is reported, or can be supplied by the trial authors, we will re‐include missing data in the analyses which we undertake.
We will assess methods as:
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low risk of bias (e.g. no missing outcome data; missing outcome data balanced across groups);
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high risk of bias (e.g. numbers or reasons for missing data imbalanced across groups; ‘as treated’ analysis done with substantial departure of intervention received from that assigned at randomisation);
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unclear risk of bias.
(5) Selective reporting (checking for reporting bias)
We will describe for each included study how we investigated the possibility of selective outcome reporting bias and what we found.
We will assess the methods as:
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low risk of bias (where it is clear that all of the study’s prespecified outcomes and all expected outcomes of interest to the review have been reported);
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high risk of bias (where not all the study’s prespecified outcomes have been reported; one or more reported primary outcomes were not prespecified; outcomes of interest are reported incompletely and so cannot be used; study fails to include results of a key outcome that would have been expected to have been reported);
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unclear risk of bias.
(6) Other bias (checking for bias due to problems not covered by (1) to (5) above)
We will describe for each included study any important concerns we have about other possible sources of bias.
We will assess whether each study was free of other problems that could put it at risk of bias:
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low risk of other bias;
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high risk of other bias;
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unclear whether there is risk of other bias.
(7) Overall risk of bias
We will make explicit judgements about whether studies are at high risk of bias, according to the criteria given in the Handbook (Higgins 2011). With reference to (1) to (6) above, we will assess the likely magnitude and direction of the bias and whether we consider it likely to impact on the findings. We will explore the impact of the level of bias through undertaking sensitivity analyses (see Sensitivity analysis).
Assessing the quality of the evidence using GRADE
We will assess the quality of the evidence using the GRADE approach as outlined in the GRADE handbook, in order to assess the quality of the body of evidence relating to the following outcomes for the main comparisons:
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Change in maternal core body temperature from pre‐operative/beginning of surgery to postoperative/end of surgery
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Incidence (proportion) of women with hypothermia (core temperature < 36 °C)
We will use the GRADEpro Guideline Development Tool to import data from Review Manager 5 (RevMan 2014) in order to create ’Summary of findings’ tables. We will produce a summary of the intervention effect and a measure of quality for each of the above outcomes using the GRADE approach. The GRADE approach uses five considerations (study limitations, consistency of effect, imprecision, indirectness and publication bias) to assess the quality of the body of evidence for each outcome. The evidence can be downgraded from 'high quality' by one level for serious (or by two levels for very serious) limitations, depending on assessments for risk of bias, indirectness of evidence, serious inconsistency, imprecision of effect estimates or potential publication bias.
Measures of treatment effect
Dichotomous data
For dichotomous data, we will present results as a summary risk ratio with a 95% confidence interval.
Continuous data
For continuous data, we will use the mean difference if outcomes are measured in the same way between trials. We will use the standardised mean difference to combine trials that measure the same outcome, but use different methods.
Unit of analysis issues
Cluster‐randomised trials
We will include cluster‐randomised trials in the analyses along with individually‐randomised trials. We will adjust their sample sizes using the methods described in the Handbook (Section 16.3.4 or 16.3.6), using an estimate of the intracluster correlation co‐efficient (ICC) derived from the trial if possible, from a similar trial or from a study of a similar population. If we use ICCs from other sources, we will report this and will conduct sensitivity analyses to investigate the effect of variation in the ICC. If we identify both cluster‐randomised trials and individually‐randomised trials, we plan to synthesise the relevant information. We will consider it reasonable to combine the results from both if there is little heterogeneity between the study designs and if we consider the interaction between the effect of intervention and the choice of randomisation unit to be unlikely.
We will also acknowledge heterogeneity in the randomisation unit and perform a sensitivity analysis to investigate the effects of the randomisation unit.
Cross‐over trials
Cross‐over trials will not be eligible for inclusion in this review.
Dealing with missing data
For included studies, we will note levels of attrition. We will explore the impact of including studies with high levels of missing data in the overall assessment of treatment effect by using sensitivity analysis.
For all outcomes, we will carry out analyses as far as possible on an intention‐to‐treat basis, i.e. we will attempt to include all participants randomised to each group in the analyses, and will analyse all participants in the group to which they were allocated, regardless of whether or not they received the allocated intervention. The denominator for each outcome in each trial will be the number randomised minus any participants whose outcomes are known to be missing.
Assessment of heterogeneity
We will assess statistical heterogeneity in each meta‐analysis using the Tau2, I2 and Chi2 statistics. We will regard heterogeneity as substantial if I2 is greater than 30% and either Tau2 is greater than zero, or there is a low P value (less than 0.10) in the Chi2 test for heterogeneity.
Assessment of reporting biases
If there are 10 or more studies in the meta‐analysis we will investigate reporting biases (such as publication bias) using funnel plots. We will assess funnel plot asymmetry visually. If asymmetry is suggested by a visual assessment, we will perform exploratory analyses to investigate it.
Data synthesis
We will carry out statistical analysis using Review Manager 5 software (RevMan 2014). We will use a fixed‐effect meta‐analysis for combining data where it is reasonable to assume that studies are estimating the same underlying treatment effect, i.e. where trials are examining the same intervention, and we judge the trials’ populations and methods to be sufficiently similar. If there is clinical heterogeneity sufficient to expect that the underlying treatment effects differ between trials, or if we find substantial statistical heterogeneity, we will use a random‐effects meta‐analysis to produce an overall summary if an average treatment effect across trials is considered clinically meaningful. The random‐effects summary will be treated as the average of the range of possible treatment effects, and we will discuss the clinical implications of treatment effects differing between trials. If the average treatment effect is not clinically meaningful we will not combine trials.
If we use random‐effects analyses, we will present the results as the average treatment effect with 95% confidence intervals, and the estimates of Tau2 and I2.
Subgroup analysis and investigation of heterogeneity
If we identify substantial heterogeneity, we will investigate it using subgroup analyses and sensitivity analyses. We will consider whether an overall summary is meaningful, and if it is, will use random‐effects analysis to produce it.
We plan to carry out the following subgroup analyses:
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Elective versus emergency caesarean section
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Pre‐warming versus intra‐operative warming strategies
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Epidural versus spinal anaesthesia
We will use the following outcomes in subgroup analysis:
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Change in maternal core body temperature from pre‐operative/beginning of surgery to postoperative/end of surgery
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Incidence (proportion) of women with hypothermia (core temperature < 36 °C)
We will assess subgroup differences by interaction tests available within RevMan (RevMan 2014). We will report the results of subgroup analyses quoting the Chi2 statistic and P value, and the interaction test I2 value.
Sensitivity analysis
We plan to carry out sensitivity analyses to explore the effect of trial quality assessed by concealment of allocation, high attrition rates, or both, with poor‐quality studies being excluded from the analyses in order to assess whether this makes any difference to the overall result. We will use our primary outcomes: 1. change in maternal core body temperature (°C) from pre‐operative to postoperative; and 2. proportion of women with hypothermia (% of participants).
