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Cochrane Database of Systematic Reviews Protocol - Intervention

Leukodepletion for patients undergoing heart valve surgery

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Abstract

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

To assess the beneficial and harmful effects of leukodepletion on clinical, patient‐reported and economic outcomes in patients undergoing heart valve surgery.

Background

Description of the condition

Diseases of the heart valves can dramatically worsen quality of life and cause premature death if left untreated. Although the underlying causes of heart valve disease vary considerably between developed and developing countries, the burden of disease in Western economies is substantial, partly due to an ageing population and the accompanying increase in degenerative valve diseases (Soler‐Soler 2000; Vahanian 2007). Population prevalence of valvular heart disease is estimated at 2.5%, with age‐related increases rising to 13% in people over 75 years (Nkomo 2006). In the period 2000‐2010 the proportion of valve surgeries in the United States rose from 16% to 22% of all cardiac surgeries (Iung 2011). Despite recent innovations, the gold standard treatment remains open heart surgery to repair or replace the damaged valves (Iung 2003; Dunning 2011). Positive outcomes of such surgery include increased life expectancy and improved quality of life (Vahanian 2007; Brown 2009). However, there are intrinsic risks associated with heart valve operations which cannot be avoided (Grayson 2003).

Patients undergoing heart valve surgery compared with patients who undergo coronary artery surgery alone are at a higher risk of developing post‐operative end organ injury, such as kidney injury (Grayson 2003). It is estimated that around 8% of patients undergoing heart surgery experience post‐operative renal dysfunction and 1.5% require dialysis (Mangano 1998). Post‐operative length of stay in the ICU may be twice as long for patients with renal dysfunction (5x longer for dialysis) and the mortality rate is also significantly higher at 27% for post‐operative renal dysfunction compared to 0.9% for those without (Mangano 1998). Even mild acute kidney injury is associated with a twofold increase in mortality rate, longer stay in ICU (x 1.6) and increased costs of care (x 1.6), with risk and costs escalating with severity of kidney injury (Dasta 2008). This same mechanism may lead to the failure of other organs (multi‐organ dysfunction) which is a major cause of chronic ill‐health and death (Thadhani 1996). Avoiding cardiac surgery associated acute kidney injury is therefore crucial due to associated higher mortality rates, increased length of stay in ICU and elevated costs (Dasta 2008; Brown 2010).

Description of the intervention

A special device, called the leukodepletion (LG6) filter has been developed that can successfully remove activated leukocytes (white blood cells) during the bypass process. These specially engineered filters combine a depth element with a screening component in order to trap activated leucocytes. Early studies demonstrated a reduction in inflammation and lung injury using the filter during blood transfusions (Bando 1990; Bando 1991). Its effectiveness in removing the activated portion of leukocytes in circulating blood has been validated (Gourlay 1992; Alexiou 2006), though use of the filter is associated with an additional cost. It was first used during heart and lung bypass surgery during the early 1990’s (Schueler 1992; Palanzo 1993) and since then leukocyte filters have been used at different sites in the heart lung bypass circuit showing good performance and patient safety (Sawa 1994; Gu 1996; Gu 1999). 

How the intervention might work

A standard arterial line filter removes microemboli (gas, fat, aggregates) from blood passing through the coronary bypass circuit. In addition, the leukodepletion filter has been proven to remove activated circulating leukocytes (Gourlay 1992; Gourlay 1992b; Thurlow 1996; Gu 1999; Morris 2001). When a patient’s blood comes into contact with the artificial components of the heart and lung bypass circuit, the white blood cells (leukocytes) become activated, which may lead to a systemic inflammatory response and the elevated risk of multi‐organ dysfunction and death (Westaby 1987; Kirklin 1991; Butler 1993; Allen 1997). The role of activated leukocytes in the development of post‐operative complications is well documented (Hunt 2007). Laboratory evidence for kidney protection (renoprotection) using the leukodepletion filter has been demonstrated with low risk patients undergoing coronary artery surgery (Tang 2002). However, this study did not demonstrate clinical evidence of a reduction in kidney injury and the authors suggested that benefits may be more discernible in patients with moderate to high risk of developing kidney injury, for example, patients undergoing heart valve surgery. This cohort are at a higher risk of end‐organ failure because they face additional challenges, such as increased time spent on the heart lung machine and increased blood spillage and salvage. The sequelae of these additional challenges include an increase in leukocyte activation leading to a greater risk of morbidity and mortality. Reducing the virulence towards organ injury by reducing the number of activated leukocytes using this leukodepletion filter may reduce this elevated risk. (Tang 2002). Leukodepletion may therefore reduce post‐surgical mortality and length of stay, and improve long‐term quality of life (Conlon 1999; Antunes 2004). To our knowledge there are no known side effects or harms associated with use of the leukodepletion filter compared to a standard arterial line filter.

Why it is important to do this review

There is some evidence for the benefits of leukodepletion in patients undergoing coronary artery surgery (Bolcal 2007) but its effectiveness in higher risk patients, such as those undergoing heart valve surgery, has not previously been reviewed. Evidence for the benefit of leukodepletion in terms of overall clinical outcomes in heart surgery is currently unclear (Gott 2001; Fabbri 2001; Efstathiou 2003; Sutton 2005). Although leukodepletion during cardiopulmonary bypass has contributed to improved heart and lung function, this has not translated into better overall clinical outcomes (Efstathiou 2003). This may be partly due to studies on low risk patients, who are not expected to have frequent complications (Tang 2002). The impact of heart surgery from the patients’ perspective is an important consideration when evaluating the efficacy of an intervention. The subjective measurement of health related quality of life (HRQoL) is an established outcome measure following cardiac surgery (Caine 1991; Blumenthal 1994; Bennet 2002; Papadopoulou 2009), able to predict post‐surgical functional status (Falcoz 2003) and level of disability (Juergens 2010). In addition, post‐operative HRQoL can be predicted by the severity of pre‐operative heart failure and type of valve surgery (Falcoz 2003; Baberg 2004; Taillefer 2005). Pre‐operative HRQoL scores have recently been confirmed as independent predictors of post‐operative mortality and myocardial infarction, leading to a call for their inclusion in the standard set of assessments (Pedersen 2010). Evidence for the impact of leukodepletion on a patient’s lifestyle and well‐being has not previously been collated. A leukodepletion filter is relatively inexpensive compared to the cost of renal replacement therapy and prolonged intensive care but few studies have evaluated cost savings. However, Palanzo and colleagues reported potential savings in hospital costs of $1942 per patient arising from early discharge (Palanzo 1993). Prevention of end‐organ injury during valvular surgery could represent substantial cost savings (Mangano 1998) and it is therefore important to review the potential reduction in costs of care associated with use of the leukodepletion filter. It is the aim of this review to comprehensively evaluate the impact of leukodepletion on clinical, economic and health‐related quality of life outcomes in patients undergoing heart valve surgery.

Objectives

To assess the beneficial and harmful effects of leukodepletion on clinical, patient‐reported and economic outcomes in patients undergoing heart valve surgery.

Methods

Criteria for considering studies for this review

Types of studies

Randomised controlled trials (RCTs)

Types of participants

Included

Adult (≥18 years) patients requiring surgical intervention for heart valve disease, including single or multiple valve, first time or redo procedures. Trials considering concomitant procedures, such as coronary artery bypass graft, ascending aortic and/or root replacement, and ablation for atrial fibrillation will be included.

Excluded

Patients for whom the principal risk of perioperative end‐organ injury is related to factors other than heart valve surgery will be excluded from the review, including patients; with known pre‐existing renal disease, with impaired left ventricular function (EF <40%), with diabetes or requiring perioperative nephrotoxic medication or with deep hypothermic circulatory arrest.

Types of interventions

Use of a leukocyte‐depleting arterial line filter compared to a standard arterial line filter, at any site in the heart lung bypass circuit.

Types of outcome measures

Primary outcomes

  1. Post‐operative in‐hospital all‐cause mortality (within 3 months)

  2. Post‐operative all‐cause mortality excluding inpatient mortality <30 days

  3. Length of stay in hospital

Secondary outcomes

  1. Kidney injury (tubular or glomerular)

  2. Validated health‐related quality of life scales

  3. Validated renal injury scale, e.g. AKIN (Mehta 2007) or RIFLE (Bellomo 2004) criteria

  4. Use of continuous veno‐venous haemo‐filtration (CVVH)

  5. Length of stay in intensive care

  6. Adverse events; adverse events or serious adverse events (ICH‐GCP 1997)

  7. Costs of care; cost‐benefit, cost‐effectiveness

Search methods for identification of studies

The search strategy for OVID Medline is included in the Appendix 1 The search criteria and overall strategy for identification of studies for this review is in accordance with the Cochrane Handbook Lefebvre 2011.

Electronic searches

We will search the Cochrane Central Register of Controlled Trials (CENTRAL), the NHS Economic Evaluations Database, MEDLINE, EMBASE, CINAHL and Web of Science Conference Proceedings. We will also search the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP), (http://apps.who.int/trialsearch/), the US NIH clinical trials database (http://www.clinicaltrials.gov/) and the International Standard Randomised Controlled Trial Number Register (ISRCTN) (http://www.controlled‐trials.com/isrctn/) for ongoing studies. No language or time period restrictions will be applied.

We will also conduct a wider search for reports of adverse events in a broad range of studies e.g. quasi‐experimental, cohort studies, etc.

Searching other resources

We will examine the reference lists of all included RCT's and reviews for additional trials. We will contact authors of identified trials, and authorities in the field, in order to locate other published and unpublished studies. We will search the 'grey' literature at OpenGrey http://www.opengrey.eu/ and we will handsearch conference proceedings including the following: American Heart Association, European Society of Cardiology, International Conference on Heart & Brain, International Meeting of Intensive Cardiac Care, Pan American Heart Failure Congress and South American Congress of Cardiology.

Data collection and analysis

Selection of studies

The titles and abstracts of all retrieved trials will be independently assessed for relevance by two reviewers. Using the full text of each study, the two reviewers will then independently evaluate trials for inclusion in or exclusion from the review. Disagreements about relevance will be resolved following discussion with the third reviewer.

Data extraction and management

We will use a data collection form based on the defined outcome measures. Data for the comparison leukodepletion versus standard care will be independently extracted from included studies by two review authors. Data for the design, participants, intervention, outcomes, methods, results and study withdrawals will be recorded. Missing data in the publications will be sought from the authors by correspondence.

The same two reviewers will also evaluate methodological quality of the studies at this stage. Disagreements and clarification of published data will be resolved following discussion with the third reviewer. If necessary the third review author will help achieve consensus.

Assessment of risk of bias in included studies

We will assess the risk of bias for all included studies according to recommendations outlined in the Cochrane Handbook (Higgins 2011) for the following items:

  1. Allocation sequence generation

  2. Concealment of allocation

  3. Blinding of participants and investigators

  4. Incomplete outcome data

  5. Selective outcome reporting

Each potential source of bias will be graded as YES, NO or UNCLEAR, relating to whether the potential for bias is low, high or unknown respectively. Other sources of bias will be noted.

Measures of treatment effect

We will pool the analyses across studies using Review Manager 5.1. For continuous data the treatment effect will be estimated using a weighted mean difference (WMD) with fixed effects. For proportional outcomes, such as proportion who improve, we will compare treatment effects using risk ratios (RR) with a fixed effects model.

Unit of analysis issues

Where we identify cross‐over randomised controlled trials we will only use data from the first part of the study, in order to minimise potential bias from carry‐over effects. If we find trials with more than two arms and the variance of the difference between leukodepletion and standard care is not reported, these will be calculated from the variances of all the trial arms. Where only data for differences between treatment groups is presented, as opposed to the mean effects for each group, the data will be analysed using the generic inverse variance (GIV) function with a fixed effects model.

Dealing with missing data

We will use an intention‐to‐treat approach and missing data will not be imputed. We will use sensitivity analyses to determine the resistance of our results to the effects of missing data.

Assessment of heterogeneity

Tests for heterogeneity will be performed in Review Manager 5.1 using the I2 test; where an I2 greater than 40% is considered meaningful (Higgins 2011). Where significant heterogeneity is present we will explore sources, including checking data integrity and carrying out sub‐group analyses. Where heterogeneity cannot be explained we will incorporate it by applying a random effects model and report results from both models.

Assessment of reporting biases

We will use funnel plots to explore reporting biases and the effects of small studies. If sufficient studies are included in the meta‐analysis we will test for asymmetry in the funnel plot using Egger's method (Egger 1997).

Data synthesis

We will examine the combined effects of interventions by pooling data using meta analysis. We will use fixed effects models apriori but compare with a random effects model where substantial heterogeneity is indicated.

Subgroup analysis and investigation of heterogeneity

Where comparison group sample sizes permit, we will conduct subgroup analyses for the following variables: heart disease severity (e.g. using the New York Heart Association classification), follow‐up duration (≤1 month, >1 month), age and sex.

Sensitivity analysis

Where substantial heterogeneity is present we will examine robustness of the results by comparing fixed effects to random effects models. In addition, we will test reliability of the meta‐analyses by repeating the tests with alternate decision pathways including; methodological quality of the studies (risk of bias).