Advance care planning for heart failure
Abstract
This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:
To assess the effects of advance care planning (ACP) in people with heart failure compared to usual care strategies that do not have any components promoting ACP.
Background
Description of the condition
Heart failure is a complex clinical syndrome that is associated with various symptoms including dyspnoea, fatigue, peripheral oedema and depression (Falk 2013; Ponikowski 2016). The condition is caused by any structural cardiac disorder, functional cardiac disorder, or both, affecting the ability of the ventricle to pump blood (Yancy 2013). Coronary heart disease, heart valve disease, arrhythmias, familial cardiomyopathy, toxin‐induced cardiomyopathy and hypertension are all linked to heart failure (Ponikowski 2016; Yancy 2013). Heart failure is classified using the American College of Cardiology Foundation/American Heart Association (ACCF/AHA) stages or the New York Heart Association (NYHA) functional classification system (Ponikowski 2016; Yancy 2013). The ACCF/AHA stages are based on structural heart changes, and focus on the development and progression of disease (Ponikowski 2016; Yancy 2013). In contrast, the NYHA functional classification describes the severity of symptoms and exercise capacity (Ponikowski 2016; Yancy 2013).
Incidence of heart failure is more common with increasing age (Redfield 2003; Yancy 2013), and is a worldwide public health problem. In 2015, the worldwide prevalence of heart failure was estimated to be approximately 40 million people (GBD 2016). In 2013, approximately 17.3 million people died from cardiovascular disease globally (Benjamin 2017). People with heart failure are often linked to a trajectory of periodic exacerbations and recoveries, where each exacerbation event may lead to death (Lynn 2001). The mortality rate is high for such people, however, and estimating a prognosis is challenging. When a person's medical condition worsens, in many cases, they require urgent and intensive management (Allen 2012). In this situation, people with heart failure and their families might not be able to contemplate treatment and care options that take into account the person's values and care preferences. Therefore, the AHA has emphasised the importance of discussing with patients advance care planning (ACP) to plan for future care according to the patient's values and preferences, as well as current clinical status such as symptom burden and quality of life, potential treatment options and prognosis, as an annual heart failure review (Allen 2012). Currently, the 2013 ACCF/AHA Guideline for the Management of Heart Failure recommends palliative and supportive care for people with advanced heart failure to improve quality of life (Class I recommendation; Level of Evidence B) (Yancy 2013). Some systematic reviews have collectively shown that ACP may lead to improvement of communication between patients and healthcare providers, satisfaction with care, and concordance between a patient's preferences of care and received care (Houben 2014; Martin 2016; Weathers 2016).
Description of the intervention
ACP is the process of discussing an individual's future care plan between the person, their family members, surrogate decision‐makers and healthcare providers while considering the person's values, concerns, wishes, life goals and preferences for future medical care (NCPC 2007; Rietjens 2017; Sudore 2017). This generally occurs while the person is still able to communicate their wishes independently and is in a stable clinical condition (Stevenson 2015). In hospital, ACP may start when individuals are diagnosed with heart failure or make an outpatient visit (Mullick 2013; Stevenson 2015). Additionally, the topic of ACP can be broached when patients undergo repeat hospitalisations for exacerbated comorbidities and move into extended care facilities (Stevenson 2015). The discussion component of ACP may include an individual's family members, surrogate decision‐makers, such as friends and neighbours, and key people who are involved in their care (NCPC 2007; Sudore 2017), since they best understand the person's values, goals, and care preferences (Sudore 2017). In the event that the person loses their capacity to make informed decisions, it becomes the responsibility of the surrogate decision‐makers to direct medical care in keeping with the person's wishes, and with an understanding of their illness and prognosis (NCPC 2007; Sudore 2010; Sudore 2017). The aim of ACP, therefore, is to ensure that the care a person receives is consistent with their goals, values and preferences (Sudore 2017).
In 1990, the Patient Self‐Determination Act was enacted in the USA, and highlighted the rights of patients in the shared decision making of their own medical treatment (Allen 2012; Prendergast 2001; Stevenson 2015). In 2005, the Mental Capacity Act was enacted in the UK, and it also emphasised the importance of patients' rights in decision making (Hayhoe 2011; NCPC 2007). Discussion about ACP has since been facilitated worldwide. Initially, ACP focused on specific treatment decisions (Prendergast 2001), as well as formal documents. For example, advance directives, shared decision making, living wills, power of attorney, physician orders for life‐sustaining treatment, and do‐not‐resuscitate orders are commonly used to legally appoint a spokesperson for the patient and record their wishes about future medical treatment. Although these documents continue to be a part of ACP, the process has evolved to emphasise the importance of communication and understanding between the patient, their family members and healthcare providers regarding the individual's values, wishes and preferences for future care (Prendergast 2001; Rietjens 2017; Sudore 2017).
Although the clinical condition of heart failure is sometimes stable for a long time, it may change suddenly (Mullick 2013). It is, therefore, important to discuss ACP not only when a person's clinical condition is exacerbated, but early in the disease process (Mullick 2013). As well, because a person's values and preferences can change over time, it is also important to regularly review advance care plans (Sudore 2010).
How the intervention might work
People with heart failure report various symptoms, however, they often have a poor understanding of their disease, and they rarely realise the terminal nature of their condition (Browne 2014). An ACP approach that involves communicating and understanding an individual's values, life goals and wishes can lead to agreement between patients and their surrogate decision‐makers concerning future care preferences (Lorenz 2008). As well, supportive physician behaviours and shared decision making are associated with patient and family satisfaction with care (Fine 2010). ACP can also help to resolve differences of opinion among family members (Rhee 2013), assist families to face end‐of‐life scenarios, and reduce their psychological and physical distress (Rhee 2013). In cancer patients and their families, ACP is associated with fewer patients receiving aggressive medical interventions as end‐of‐life treatment (Wright 2008). Such interventions can result in lower quality of life for patients in end‐of‐life care and can intensify depressive disorders among distressed family members (Wright 2008). Therefore, implementation of ACP and effective communication among patients, family members, and healthcare providers might lead to or contribute to positive outcomes.
Why it is important to do this review
Healthcare providers can play a vital role in the care of patients with advanced heart failure by discussing a patient's values, preferences and planning for future care (Allen 2012). As mentioned above, current guideline from the ACCF/AHA recommends the implementation of palliative and supportive care in advanced HF (Class I recommendation; Level of Evidence B) (Yancy 2013). The European Society of Cardiology (ESC) guideline recommends that, as a key component of palliative and end‐of‐life care, healthcare providers should focus on improving or maintaining quality of life of patients and their carers until death (Ponikowski 2016). Despite both the USA and European guidelines' recommendations of ACP, many heart failure patients do not have documented ACP (Butler 2015).
Barriers to ACP for healthcare providers include the unpredictable trajectory of heart failure, the difficulty in determining when to initiate ACP, and patients' poor understanding of their disease (Browne 2014; De Vleminck 2014; Hjelmfors 2014). However, despite the unpredictable prognosis of disease, healthcare providers need to understand and discuss with patients the patients' own values and preferences for future care, while revising their expectations of the disease course (Allen 2012). Moreover, patients and their families emphasise that effective communication, in particular focusing on the patient's treatments and future care options, are important elements (Virdun 2015).
An existing Cochrane Review explores the effects of ACP for participants receiving haemodialysis (Lim 2016). This review suggested that in‐depth discussion regarding end‐of‐life care did not lead to unnecessary discomfort or anxiety (Lim 2016). The review's included studies also reported that the surrogate decision‐makers' understanding of the patient's goals and preferences for future medical treatment increased after the implementation of ACP. Additionally, ACP intervention has been shown to improve the proportion of patients completing advance directives (Lim 2016). Two recent reviews, one on people aged 65 years of age and older (Weathers 2016), and another on adult patients with different diseases (Houben 2014), suggested that ACP interventions might improve documentation of end‐of‐life care preferences, and increase discussion about end‐of‐life care between patients and healthcare providers.
Although a few systematic reviews have been conducted on ACP, none have studied the effects of ACP in people with heart failure. Little is known about the impact of ACP on the physical and psychological condition, quality of life, and care satisfaction of people with heart failure, their families and carers. Therefore, a review aiming to reveal the effects of ACP for people with heart failure is warranted.
Objectives
To assess the effects of advance care planning (ACP) in people with heart failure compared to usual care strategies that do not have any components promoting ACP.
Methods
Criteria for considering studies for this review
Types of studies
We will include randomised controlled trials (RCTs) including randomised parallel group trials and cluster‐randomised trials. For cross‐over studies, we will use only the first‐phase treatment data. We will include studies reported as full‐text, those published as abstract only, and unpublished data, published in any language.
Types of participants
We will include adults (≥ 18 years of age) with a clinical diagnosis of heart failure. We will include participants of all types of heart failure (e.g. preserved ejection fraction (diastolic heart failure) or reduced ejection fraction (systolic heart failure)), who were recruited to the trials without a carer, as well as participants who were enrolled with their surrogate decision‐makers/carers by study investigators. If participants of various diagnoses (i.e. besides heart failure) are included, we will contact authors and extract the data of only heart failure participants. If we are not able to obtain the data of only heart failure participants, we will include studies if the majority of participants have a diagnosis of heart failure and we will pursue a sensitivity analysis to assess the impact of mixed diagnoses on the effectiveness of ACP (Sensitivity analysis).
Types of interventions
We will include trials that implement ACP practices, such as discussing and considering participants' values, wishes, and life goals; understanding participants' illness and prognosis, and their preferences about future medical care. We will compare the ACP intervention with usual care that does not involve any components to promote ACP. We will include trials that aim to assess the effectiveness of interventions to promote, improve, or strengthen ACP. We will include interventions that involve video or websites to promote ACP. These tools may provide information required for ACP such as resuscitation measures, and may educate patients and their family members about the importance of communication about a patient's own values, life goals, and preferences about future medical care between patients, their families, surrogate decision‐makers and healthcare providers. The eligibility criterion is any study that describes an ACP intervention as defined by the trial investigators.
Types of outcome measures
Primary outcomes
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Concordance between participants' preferences and end‐of‐life care (measurement defined by trial author, e.g. comparing end‐of‐life care that participants received with participant‐stated preferences) (yes/no).
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Participants' quality of life (e.g. Minnesota Living with Heart Failure Questionnaire (MLHFQ), the Kansas City Cardiomyopathy Questionnaire (KCCQ), the 36‐Item Short Form Health Survey (SF‐36), or other measurement scales, as defined by trial authors).
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Participants' satisfaction with care/treatment (measurement defined by trial author) (yes/no).
Secondary outcomes
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Completion of documentation by medical staff regarding discussions with participants about ACP processes (yes/no).
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Participants' depressive state (measurement defined by trial authors, e.g. Hospital Anxiety and Depression Scale (HADS), the Patient Health Questionnaire (PHQ‐9)).
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Caregivers' satisfaction with care/treatment (measurement defined by trial authors) (yes/no).
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Quality of communication (measurement defined by trial authors, e.g. Quality of Communication (QOC) questionnaire).
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Use of life‐sustaining treatment, such as intubation (yes/no).
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Participants' decisional conflict (measurement defined by trial authors, e.g. Decisional Conflict Scale).
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Use of hospice services (yes/no).
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All‐cause mortality.
We are interested in effects of the intervention from the longest follow‐up duration; however, it is likely that numerous outcome measures are obtained at different time points in patients with serious illness, and thus we will also consider the effects of ACP at shorter follow‐up time points where possible and perform subgroup analyses accordingly (Unit of analysis issues; Subgroup analysis and investigation of heterogeneity).
We do not anticipate ACP to be associated with any adverse effects and thus we have decided not to consider adverse effects as a prespecified outcome measure of interest. We will however identify any participant‐ or physician‐reported adverse effects as described in the included studies and present our findings narratively in the 'Discussion' section.
Reporting one or more of the outcomes listed here in the trial is not an inclusion criterion for the review. If sufficient evidence is available, we will also comment on the economic costs associated with ACP in the 'Discussion' section.
Search methods for identification of studies
Electronic searches
We will identify trials through systematic searches of the following bibliographic databases.
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Cochrane Central Register of Controlled Trials (CENTRAL; latest issue), in the Cochrane Library.
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MEDLINE (Ovid, from 1946 onwards).
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Embase (Ovid, from 1980 onwards).
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Cumulative Index of Nursing and Allied Health Literature (CINAHL).
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Social Work Abstracts (Ovid).
We will adapt the preliminary search strategy for MEDLINE (Ovid) for use in the other databases (Appendix 1). We will apply the Cochrane sensitivity‐maximising RCT filter to MEDLINE (Ovid) and adapt it to the other databases (Lefebvre 2011), except CENTRAL.
We will conduct a search of the following trial registers for ongoing or unpublished trials.
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USA National Institutes of Health Ongoing Trials Register ClinicalTrials.gov (www.clinicaltrials.gov; to date of search).
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WHO ICTRP (World Health Organization International Clinical Trials Registry Platform; www.who.int/ictrp; to date of search).
We will search all databases from their inception to the present, and we will impose no restriction on language of publication or publication status.
We do not anticipate this type of intervention to be associated with any adverse effects and thus will not perform a separate search for adverse effects of ACP; however, we will extract any participant‐ or physician‐reported adverse effects as described in the included studies and present our findings narratively.
Searching other resources
We will check reference lists of all included studies and any relevant systematic reviews identified for additional references to trials. We will also examine any relevant retraction statements and errata for included studies.
In the case of unpublished or incomplete data, we will contact the original study authors for further information.
Data collection and analysis
Selection of studies
Five review authors (YN, EO, AM, MM, NH) will independently screen titles and abstracts for inclusion of all the potential studies we identify as a result of the search, and code them as 'retrieve' (eligible or potentially eligible/unclear) or 'do not retrieve'. If there are any disagreements, a third author (HF) will be asked to arbitrate. We will retrieve the full‐text study reports/publication and five review authors (YN, EO, AM, MM, NH) will independently screen the full‐text and identify studies for inclusion, and identify and record reasons for exclusion of the ineligible studies. We will resolve any disagreement through discussion or, if required, we will consult a third review author (HF). We will identify and exclude duplicates and collate multiple reports of the same study so that each study rather than each report is the unit of interest in the review. We will record the selection process in sufficient detail to complete a PRISMA flow diagram and 'Characteristics of excluded studies' table (Liberati 2009).
Data extraction and management
We will design a data extraction form specifically for this Cochrane Review in order to extract relevant information regarding study and population characteristics as well as outcome data. For consistency during the review development process and to reduce bias and improve validity and reliability, five review authors (YN, EO, AM, MM, NH) will first pilot the data extraction form by extracting data from a random sample of six studies. We will refine/amend the form according to comments or suggestions that arise from the pilot stage before finalising the data extraction form for the full review development process. The five review authors (YN, EO, AM, MM, NH) will then independently extract study characteristics and outcome data from the remaining included studies.
We will extract the following study characteristics.
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Methods: study design, total duration of study, number of study centres and location, study setting (community centres, hospices, hospitals, etc.), and date of study.
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Participants: N randomised, N lost to follow‐up/withdrawn from studies, N analysed, mean age, age range, gender, severity of condition (such as the commonly used classification system, the NYHA Functional Classification; or the ACC/AHA stages of heart failure) and diagnostic criteria (e.g. according to the ESC guideline diagnostic algorithm for diagnosis of heart failure (Ponikowski 2016)), study inclusion and exclusion criteria.
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Interventions: intervention and comparison.
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Outcomes: primary and secondary outcomes specified and collected, and time points reported. Although adverse effects are not our outcome measure of interest, for completeness we will also extract any participant‐ or physician‐reported adverse outcomes in the study publications (Types of outcome measures).
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Notes: funding for trial, and notable conflicts of interest of trial authors.
We will resolve disagreements by consensus or by involving a third person (HF). One review author (YN) will transfer data into the Review Manager 5 file (Review Manager 2014). We will double‐check that data are entered correctly by comparing the data presented in the systematic review with the study reports. A second review author (NH) will spot‐check study characteristics for accuracy against the trial report.
Assessment of risk of bias in included studies
Five review authors (YN, EO, AM, MM, NH) will independently assess risk of bias for each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We will resolve any disagreements by discussion or by involving another review author (HF). We will assess the risk of bias of the included RCTs and cluster‐RCTs according to the following domains.
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Random sequence generation.
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Allocation concealment.
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Blinding of participants and personnel.
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Blinding of outcome assessment.
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Incomplete outcome data.
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Selective outcome reporting.
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Other bias (e.g. industry funding, lack of individual randomisation).
We will grade each potential source of bias as high, low or unclear and provide a quote from the study report together with a justification for our judgment in the 'Risk of bias' table. We will summarise the risk of bias judgements across different studies for each of the domains listed. Where information on risk of bias relates to unpublished data or correspondence with a trialist, we will note this in the 'Risk of bias' table.
For cluster‐randomised trials, we will pay particular attention to the following sources of bias: (i) recruitment bias; (ii) baseline imbalance; (iii) loss of clusters; (iv) incorrect analysis; and (v) comparability with individually randomised trials (Higgins 2011).
We will report results of our 'Risk of bias' assessment using a 'Risk of bias' summary and a 'Risk of bias' graph, with detailed descriptions of our observations in the 'Characteristics of included studies' tables in the full review.
When considering treatment effects, we will take into account the risk of bias for the studies that contribute to that outcome.
Assessment of bias in conducting the systematic review
We will conduct the review according to this published protocol and report any deviations from it in the 'Differences between protocol and review' section of the systematic review.
Measures of treatment effect
For dichotomous outcome measures (completion of documentation by medical staff regarding discussions with participants about ACP processes, use of life‐sustaining treatment such as intubation, use of hospice services, all‐cause mortality) we will use risk ratios (RRs) with 95% confidence intervals (CIs). For continuous endpoints (concordance between participants' preferences and end‐of‐life care, quality of life, participants and caregivers' satisfaction with care/treatment, depressive state, quality of communication, participants' decisional conflict) we will use mean differences (MDs) (or standardised mean differences (SMDs) if different measuring scales were used, such as in the case of quality of life scores) with 95% CIs. We will stratify analyses by pooling data from measuring scales/scoring systems with a consistent direction of effect (e.g. two separate analyses for quality of life data obtained from measuring scales where a reduced score favours ACP, and for data from scales where an increased score favours the ACP intervention, respectively).
We will narratively describe skewed data reported as medians and interquartile ranges.
Unit of analysis issues
For studies with repeated outcome measurements at different follow‐up durations, we will include data from the longest follow‐up available. If the outcomes at the short term follow‐up data are extracted, we will conduct a subgroup analysis for other follow‐up time points.
Since we plan to include cluster‐randomised trials, we will analyse data reported in them along with those from individually randomised trials. If adjustment for the cluster design effects are not performed by the eligible cluster‐randomised trialists, we will adjust the relevant summary statistics (such as sample sizes and standard deviations) using the methods described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011), using an estimate of the intraclass correlation coefficient (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 clearly report this and perform sensitivity analyses to test the effects of variation in the ICC.
Dealing with missing data
We will contact investigators or study sponsors in order to verify key study characteristics and obtain missing numerical outcome data where possible (e.g. when a study is identified as abstract only). Where this is not possible, and the missing data are thought to introduce serious bias, we will explore the impact of including such studies in the overall assessment of results by a sensitivity analysis.
Assessment of heterogeneity
We will use the Chi2 test and the I2 statistic to measure heterogeneity among the trials in each analysis. We will use a P value of 0.10 for the Chi2 test for statistical significance and interpret the I2 statistic according to the following guidance in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011).
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0% to 40%: might not be important.
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30% to 60%: may represent moderate heterogeneity.
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50% to 90%: may represent substantial heterogeneity.
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75% to 100%: considerable heterogeneity.
If we identify substantial heterogeneity (I2 > 50%), we will report it and explore possible causes by prespecified subgroup analysis.
We will also assess the degree of heterogeneity by visually inspecting forest plots.
Assessment of reporting biases
If we are able to pool more than 10 trials, we will create and examine a funnel plot to explore possible small study biases for the primary outcomes. We will examine the funnel plot visually for symmetry.
Data synthesis
We will undertake meta‐analyses only if the treatments, participants and the underlying clinical question are similar enough for data pooling. We will use a fixed‐effect model for data synthesis based on the assumption that studies are of sufficient homogeneity in terms of study populations, method of delivering/implementing ACP, and study methodology. We will, however, also analyse data using a random‐effects model as a means to test the robustness of the fixed‐effect model, if we judge clinical heterogeneity to be substantial or if we find substantial statistical heterogeneity (Assessment of heterogeneity).
'Summary of findings' table
We will create a 'Summary of findings' table for the following seven primary and secondary outcomes (Types of outcome measures).
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Concordance between participants' preferences and end‐of‐life care.
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Participants' quality of life.
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Participants' satisfaction with care/treatment.
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Completion of documentation by medical staff regarding discussions with participants about ACP processes.
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Participants' depressive state;
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Caregivers' satisfaction with care/treatment;
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Quality of communication.
We will follow the GRADE approach to evaluate the overall quality of evidence and use the five GRADE considerations (study limitations, consistency of effect, imprecision, indirectness and publication bias) to assess the quality of a body of evidence as it relates to the studies which contribute data to the meta‐analyses for the prespecified outcomes. We will use methods and recommendations described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011), using GRADEpro GDT software (GRADEpro GDT 2015). We will justify all decisions to downgrade the quality of studies using footnotes and we will make comments to aid the reader's understanding of the review where necessary.
Five review authors (YN, EO, AM, MM, NH) will make judgements about evidence quality by working independently, with disagreements resolved by discussion or involving a third review author (HF). We will justify, document and incorporate judgements into the reporting of results for each outcome.
We plan to extract study data, format our comparisons in data tables and prepare a 'Summary of findings' table before writing the results and conclusions of our review. A template 'Summary of findings' table is included as Table 1.
| Advanced care planning compared with usual care for patients with heart failure | |||||
| Patient or population: heart failure patients with or without their surrogate decision‐makers/carers Settings: in‐patient and out‐patient hospitals and clinics Intervention: advanced care planning Comparison: usual care | |||||
| Outcomes | Illustrative comparative risks* (95% CI) | Relative effect | No. of Participants | Quality of the evidence | |
| Assumed risk | Corresponding risk | ||||
| Usual care | ACP | ||||
| Concordance between participants' preferences and end‐of‐life care (yes/no) | [value] per 1000 | [value] per 1000 | RR [value] ([value] to [value]) | [value] | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ |
| Participants' quality of life | The mean quality of life score ranged across control groups from [value][measure] | The mean quality of life score in the intervention groups was | MD [value] ([value] to [value]) or SMD [value] ([value] to [value]) | [value] | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ |
| Participants' satisfaction with care/treatment (yes/no) | [value] per 1000 | [value] per 1000 | RR [value] ([value] to [value]) | [value] | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ |
| Completion of documentation by medical staff regarding discussions with participants about ACP processes (yes/no) | [value] per 1000 | [value] per 1000 | RR [value] ([value] to [value]) | [value] | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ |
| Participants' depressive state | The mean quality of life score ranged across control groups from [value][measure] | The mean quality of life score in the intervention groups was | MD [value] ([value] to [value]) or SMD [value] ([value] to [value]) | [value] | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ |
| Caregivers' satisfaction with care/treatment (yes/no) | [value] per 1000 | [value] per 1000 | RR [value] ([value] to [value]) | [value] | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ |
| Quality of communication | The mean quality of communication domain score ranged across control groups from [value][measure] | The mean quality of communication domain score in the intervention groups was [value] [lower/higher] | MD [value] ([value] to [value]) or SMD [value] ([value] to [value]) | [value] | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ |
| *The basis for the assumed risk (e.g. the median control group risk across studies) is provided in footnotes. The corresponding risk (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | |||||
| GRADE Working Group grades of evidence | |||||
Subgroup analysis and investigation of heterogeneity
We plan to carry out the following subgroup analyses for our primary outcomes, if sufficient (stratified) data from included studies allow for such analyses (Types of outcome measures).
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Mean age ≥ 70 years versus under the age of 70 years.
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Gender.
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Trial registration status (preregistered in a clinical trial registry, had a published protocol and/or provided ethics approval): trials with the above compared to trials without.
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Study design (cluster‐RCTs versus parallel RCTs).
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Follow‐up periods (defined by trial authors).
We will use the formal test for subgroup interactions in Review Manager 5 (Review Manager 2014).
Sensitivity analysis
Given that it is likely for studies to include mixed populations of varied diagnoses, of which only a subset have the diagnosis of interest, in addition to the main analysis where we will include all participants, we will also conduct a sensitivity analysis in which we will analyse data from studies that enrolled only participants with the diagnosis of interest, in order to examine the influence of such baseline clinical characteristics on the overall effectiveness of ACP.
We also plan to carry out a sensitivity analysis by including only studies with a low risk of bias (we define low risk of bias for studies in which we judge at least four domains to be "low"). Moreover, we will repeat our analyses by excluding unpublished studies and by excluding studies with missing data.
Reaching conclusions
We will base our conclusions only on findings from the quantitative or narrative synthesis of included studies for this review. We will avoid making recommendations for practice and our implications for research will suggest priorities for future research and outline what the remaining uncertainties are in the area.
| Advanced care planning compared with usual care for patients with heart failure | |||||
| Patient or population: heart failure patients with or without their surrogate decision‐makers/carers Settings: in‐patient and out‐patient hospitals and clinics Intervention: advanced care planning Comparison: usual care | |||||
| Outcomes | Illustrative comparative risks* (95% CI) | Relative effect | No. of Participants | Quality of the evidence | |
| Assumed risk | Corresponding risk | ||||
| Usual care | ACP | ||||
| Concordance between participants' preferences and end‐of‐life care (yes/no) | [value] per 1000 | [value] per 1000 | RR [value] ([value] to [value]) | [value] | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ |
| Participants' quality of life | The mean quality of life score ranged across control groups from [value][measure] | The mean quality of life score in the intervention groups was | MD [value] ([value] to [value]) or SMD [value] ([value] to [value]) | [value] | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ |
| Participants' satisfaction with care/treatment (yes/no) | [value] per 1000 | [value] per 1000 | RR [value] ([value] to [value]) | [value] | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ |
| Completion of documentation by medical staff regarding discussions with participants about ACP processes (yes/no) | [value] per 1000 | [value] per 1000 | RR [value] ([value] to [value]) | [value] | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ |
| Participants' depressive state | The mean quality of life score ranged across control groups from [value][measure] | The mean quality of life score in the intervention groups was | MD [value] ([value] to [value]) or SMD [value] ([value] to [value]) | [value] | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ |
| Caregivers' satisfaction with care/treatment (yes/no) | [value] per 1000 | [value] per 1000 | RR [value] ([value] to [value]) | [value] | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ |
| Quality of communication | The mean quality of communication domain score ranged across control groups from [value][measure] | The mean quality of communication domain score in the intervention groups was [value] [lower/higher] | MD [value] ([value] to [value]) or SMD [value] ([value] to [value]) | [value] | ⊕⊝⊝⊝ ⊕⊕⊝⊝ ⊕⊕⊕⊝ ⊕⊕⊕⊕ |
| *The basis for the assumed risk (e.g. the median control group risk across studies) is provided in footnotes. The corresponding risk (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | |||||
| GRADE Working Group grades of evidence | |||||
