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Research Protocol – Jun. 13, 2013

Troponin Cardiac Marker Interpretation During Renal Function Impairment

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Background and Objectives

Troponin is a protein complex of three subunits— T (TnT), I (TnI), and C (TnC)—that is involved in the contractile process of skeletal and cardiac muscle. TnC is expressed in both cardiac and skeletal muscle; under normal conditions, cardiomyocytes express cardiac-specific forms of TnT and TnI (cTnI and cTnT). Due to the cardiac specificity of cTnT and cTnI, they have the potential to be specific markers of cardiac damage and, indeed, are currently recommended by various international societies as a diagnostic indicator for acute myocardial infarction (AMI).1-3

Blood from healthy individuals with no evidence of cardiac disease contains very low, but detectable, amounts of cTn.4 Upon cardiac injury resulting from ischemia or various other causes, cTn is released from cardiomyocytes into the blood in proportion to the degree of damage.5 Troponin levels increase within 3 to 4 hours after the onset of damage and remain high for up to 4 to 7 days (cTnI) or 10 to 14 days (cTnT). A clinically relevant increase is defined as a level that exceeds the 99th percentile of a normal reference population.6 In patients with clinical symptoms of acute coronary syndrome (ACS) and without other causes for an elevated troponin, the Third Universal Definition of Myocardial Infarction1 endorses a rising/falling pattern of cardiac biomarkers (preferably cTn) with at least one value above the 99th percentile to diagnose an AMI in conjunction with at least one clinical feature (symptoms; electrocardiographic, imaging, or pathological findings) supportive of ischemia.

Currently, there is no universally adopted 99th percentile value because there is no reference standard preparation of either cTnT or cTnI, and each diagnostic manufacturer independently develops its own assays. There is no consensus on how to define a reference population for the assays (in terms of age, gender, race/ethnicity, comorbidities, or number of participants), and many of the 99th percentile values are taken from diverse and poorly defined study participants.7 When 19 cTnI and cTnT assays were compared in the same presumably healthy population, there was substantial variability between assays regarding troponin concentrations at the 99th percentile. The high-sensitivity assays detected measurable troponin levels in a larger percentage of these presumably healthy people.7 Precision recommendations state that cTn assays should be able to achieve ≤10 percent total imprecision (i.e., 10% coefficient of variation) at the 99th percentile cutpoint); however, many current assays have a coefficient of variation between 10 and 20 percent at the 99th percentile.8 Furthermore, newer high-sensitivity troponin assays have a detection limit 10-fold to 100-fold lower than currently available commercial troponin assays, which challenges this precision guideline.9

Patients with chronic kidney disease (CKD) (including those with end-stage renal disease [ESRD]) have a greater prevalence of persistently elevated cTn when compared with patients who do not have the disease. Although the mechanism is not known for certain, kidney disease-related subclinical cardiac damage is likely the cause, possibly exacerbated by reduced clearance.10 Ellis et al.11 did not observe a statistically significant difference in the half-life and the elimination rate constant of cTnI in patients with AMI and ESRD when compared with patients with AMI and normal kidney function. Increased troponin levels in patients with kidney disease may be due to cardiac injury associated with chronic structural heart disease (e.g., coronary artery disease, heart failure, etc.), rather than acute ischemia, especially when the levels do not change rapidly over time.12 Furthermore, the previous reviews have not provided a link between the degree of kidney failure and cTn elevation. Whether baseline troponin elevation reduces the ability to diagnose ACS only in patients with ESRD and not with milder forms of CKD is also unclear. Given that the prevalence of CKD in the United States reached 15 percent in 2008, how to interpret troponin levels in this population is an important issue.13,14

Discerning Acute Coronary Syndrome From Other Heart Conditions in Symptomatic Patients With Chronic Kidney Disease

Patients presenting with symptoms suspicious of ACS must be rapidly and accurately assessed because of serious clinical consequences. Recommended diagnostic strategies include clinical evaluation, 12-lead electrocardiography (ECG), and measurement of cardiac biomarkers.15 Patients with characteristic ST-elevation myocardial infarction (STEMI) can be evaluated for emergent reperfusion therapy. In situations where there is no definitive ST elevation, a decision is made between ACS (non-STEMI [NSTEMI]/unstable angina [UA]) and non-ACS conditions. The Third Universal Definition of Myocardial Infarction1 distinguishes between spontaneous myocardial infarction (MI) due to atherosclerotic plaque rupture (type 1 MI) from an MI resultant from supply/demand ischemic imbalance (type 2 MI).

In the spectrum of ACS, both UA and NSTEMI (type 1 MI) share a similar pathogenesis and are diagnosed by electrocardiographic evidence of ischemia and/or positive biomarkers of necrosis (e.g., cTn) in an appropriate clinical setting (chest discomfort or other symptoms that may occur with myocardial ischemia).16 Most patients who die from UA/NSTEMI do so from sudden cardiac death or MI. Thus, it is imperative to recognize ACS so that prompt and appropriate treatment can be implemented. In the absence of clear ECG findings, troponin levels are often a key factor in making the correct diagnosis.

On the other hand, elevations of cTn also occur in individuals with non-ACS conditions, such as kidney disease, sepsis, congestive heart failure, myocarditis, and pulmonary embolism.17 Non-ACS conditions can include noncoronary causes (hypoxia; global hypoperfusion) and coronary causes from ischemic imbalance (i.e., increased demand in the setting of stable coronary artery disease [CAD] lesions) classified as type 2 MI. Many symptoms associated with non-ACS conditions may overlap with symptoms of ACS (e.g., chest pain or dyspnea).This presents a diagnostic dilemma to the clinician and often requires an extended evaluation before an accurate diagnosis can be made. Appropriate diagnosis is critical, as ACS and non-ACS conditions are managed quite differently. For example, therapy for type 2 MIs is most often directed at treating the underlying medical condition that led to the supply/demand mismatch rather than urgent revascularization.

In addition to the harm that occurs in missing a diagnosis of ACS, harm may result from erroneously diagnosing ACS when a non-ACS condition is present. This may subject patients to unnecessary coronary angiography and its potential risks (i.e., contrast dye, radiation exposure, bleeding, MI, stroke, emergent coronary artery bypass grafting [CABG], or death) and potentially unnecessary revascularization/stenting.

The diagnosis of ACS among patients with CKD (including those with ESRD) can be particularly challenging. ECGs are frequently abnormal in patients with ESRD due to a higher prevalence of left ventricular hypertrophy and electrolyte imbalances. Furthermore, there is a higher prevalence of persistent elevation of cTn in patients with reduced kidney function, which may reduce the specificity of troponin for diagnosing AMI. To manage this uncertainty around the interpretation of cTn, additional indicators are sometimes used to help diagnose ACS in patients with CKD. Baseline troponin levels are often not known in patients with CKD on initial presentation, but elevated troponin levels are considered along with symptoms and other clinical factors in diagnosing ACS. Whether an alternative threshold other than the 99th percentile of cTn elevation should be used in patients with CKD is unknown. Patterns of troponin change (rise, fall, and magnitude of troponin change) can be very helpful for clinicians in distinguishing ACS from non-ACS in symptomatic patients. However, no consensus exists about whether the diagnostic criteria for MI using the troponin assay should be approached differently for patients with CKD and those without the disease. The National Academy of Clinical Biochemistry18 has recommended that for patients with ESRD and suspected ACS a dynamic change in troponin levels of greater than 20 percent within 9 hours should be required for a diagnosis of AMI; however, some evidence suggests that each individual assay should be evaluated to establish its own specific delta value.19

Currently, diagnostic guidelines for MI using cTn are the same for patients with and without CKD. Thus, given the higher prevalence of baseline elevated troponin levels among individuals with CKD, this population may have a higher risk of having false-positive diagnoses of MI. An evidence-based cutoff or change-from-baseline measure for the diagnosis of ACS in patients with CKD might allow clinicians to better diagnose and treat ACS in this population.

Using Troponin Level as a Management Strategy for Patients With Chronic Kidney Disease and Acute Coronary Syndrome

Cardiac biomarkers, such as cTn, also play a role in differentiating UA from NSTEMI in patients with ACS. Frequently, clinicians use troponin levels, along with clinical factors, to stratify patients according to risk when the diagnosis of NSTEMI/UA is likely. Patients at high risk for ACS generally are treated with an “early invasive” strategy (i.e., diagnostic angiography with the intent of revascularization), while patients with low to intermediate risk of ACS may be treated with an “initially conservative” (i.e., selectively invasive) management strategy.2 As with the initial diagnosis of ACS, there is a concern that elevated background troponin levels in patients with CKD may limit the applicability of treatment algorithms that are based on troponin levels in non-CKD populations. Whether troponin results in patients with CKD and suspected ACS are associated with differences in the comparative effectiveness of interventions or management strategies is unknown.

Using Troponin Level as a Prognostic Indicator in Patients With Chronic Kidney Disease Following Acute Coronary Syndrome

In addition to their use in diagnosing and managing ACS, the troponin subunits T and I and the high-sensitivity troponin assays have also been investigated as independent risk predictors of morbidity and mortality in populations following an acute ischemic event. Previous reviews and meta-analyses have investigated the prognostic performance of troponin testing in patients with kidney failure but frequently excluded studies on patients with ACS.20,21 Therefore, the prognostic significance of cTn elevation with regard to short-term and long-term major adverse cardiovascular events (MACEs) for patients with both CKD and ACS remains uncertain.

Measuring Troponins in Adults With Chronic Kidney Disease Who Do Not Have Symptoms of Acute Coronary Syndrome: A Role for Risk Stratification

Among asymptomatic patients without suspected ACS, chronic elevation of cTn identifies patients with CKD who are at increased risk for cardiovascular morbidity and mortality.21-24 However, it is unknown whether measuring troponins improves risk prediction when compared with or supplementing existing models. Furthermore, whether asymptomatic patients with CKD and chronically elevated cTn levels should be managed differently from patients with CKD who have normal cTn levels is unclear. In the absence of myocardial ischemia, there are no specific interventions recommended to reduce cardiovascular disease risk in patients with CKD based solely on a troponin elevation. Without evidence-based guidelines, clinicians will be uncertain about the role of screening asymptomatic individuals, the interpretation of elevated cTn results, and how that affects patient management and outcomes in the context of kidney disease.

Types of Troponin Assays and Special Subgroups of Patients With Chronic Kidney Disease

As mentioned previously, there are multiple commercially available troponin assays including cTnT, cTnI, high-sensitivity cTnT, and high-sensitivity cTnI. Whether all of these troponin assays have equal ability to distinguish ACS from non-ACS conditions and equal utility for prognostication and risk stratification of CKD patients with and without ACS is unclear. Furthermore, whether troponin testing leads to changes in management and outcomes among certain subgroups of patients with CKD is also unknown.

The purpose of this comparative effectiveness review will be to present information for the appropriate use of troponin levels to guide evidence-based management decisions for patients with kidney disease.

Key Questions

The Key Questions (KQs) were posted on the Agency for Healthcare Research and Quality’s Effective Health Care Program Web site between February 29 and March 28, 2012, for public comment. We present below the revised KQs based on feedback received.

Key Question 1: Diagnosis of Acute Coronary Syndrome

What is the diagnostic performance of a troponin elevation (troponin I, troponin T, high-sensitivity troponin T, or high-sensitivity troponin I) > the 99th percentile (when compared with no elevation) for the detection of ACS* in adult patients with CKD (including those with ESRD)?

* ACS will be defined by a gold standard outcome (e.g., clinically diagnosed ACS adjudicated by formal criteria such as the Third Universal Definition of Myocardial Infarction1 or the American College of Cardiology [ACC]/American Heart Association Guidelines2).

  1. What are the operating characteristics of a troponin elevation (when compared with no elevation) in distinguishing between ACS and non-ACS, including sensitivity, specificity, and positive and negative predictive values?
    1. How do the positive predictive value and the negative predictive value vary with the population’s pretest probability for ACS?
    2. Does a significant delta of change (such as greater than 20% within 9 hours) better discriminate between ACS and non-ACS when compared with a single troponin elevation?
  2. What are the operating characteristics of troponin elevation for distinguishing ACS from non-ACS among the following subgroups?
    1. Sex
    2. Age
    3. Ethnicity
    4. Stage of kidney disease (CKD stages 1–4 or ESRD requiring dialysis)
    5. Status after renal transplant
    6. Presence of baseline or previously elevated troponins
    7. Presence of ischemic ECG changes
    8. Comorbidities (e.g., diabetes, hypertension)
    9. Smoking status
    10. 10-year coronary heart disease (CHD) risk
    11. History of CAD
  3. What are the harms associated with a false-positive diagnosis of ACS based on an elevated troponin level?
  4. Among studies that directly compared one type of troponin assay (troponin I, troponin T, high-sensitivity troponin T, or high-sensitivity troponin I) against another type of troponin assay, do the operating characteristics of a certain type of troponin test perform better for diagnosis of ACS?
  5. Among studies that directly compared troponin testing in patients with CKD versus patients with normal renal function, do the operating characteristics of a troponin elevation perform similarly?

Key Question 2: Management of Acute Coronary Syndrome

In adults with CKD (including ESRD), do troponin levels improve management of ACS?

  1. Does a troponin elevation modify the comparative effectiveness of interventions or management strategies for ACS (e.g., is an aggressive strategy better than an initially conservative strategy for high troponin levels, but not for low/normal troponin levels)?
  2. Among adults with CKD with suspected ACS, how does a troponin elevation change the effects of interventions or management strategies according to the following characteristics?
    1. Sex
    2. Age
    3. Ethnicity
    4. Stage of kidney disease (CKD stages 1–4 or ESRD requiring dialysis)
    5. Status after renal transplant
    6. Presence of baseline or previously elevated troponins
    7. Presence of ischemic ECG changes
    8. Comorbidities (e.g., diabetes, hypertension)
    9. Smoking status
    10. 10-year CHD risk
    11. History of CAD

Key Question 3: Prognosis of Acute Coronary Syndrome

In adult patients with CKD (including those with ESRD) and suspected ACS, does an elevated troponin level help to estimate prognosis?

  1. Do troponin results relate to:
    1. Long-term outcomes (all-cause mortality and MACEs such as subsequent MI, stroke, or cardiovascular death over at least 1 year of followup)?
    2. Short-term outcomes (all-cause mortality and MACE during the initial hospitalization or within 1 year of followup)?
  2. Does a troponin elevation help to estimate prognosis after ACS in the following subgroups?
    1. Sex
    2. Age
    3. Ethnicity
    4. Stage of kidney disease (CKD stages 1–4 or ESRD requiring dialysis)
    5. Status after renal transplant
    6. Presence of baseline or previously elevated troponins
    7. Presence of ischemic ECG changes
    8. Comorbidities (e.g., diabetes, hypertension)
    9. Smoking status
    10. 10-year CHD risk
    11. History of CAD
  3. Among studies that directly compared one type of troponin assay (troponin I, troponin T, high-sensitivity troponin T, or high-sensitivity troponin I) against another type of troponin assay, does a certain type of troponin test estimate prognosis better after ACS?

Key Question 4: Risk Stratification Among Patients Without Acute Coronary Syndrome

Does an elevated troponin level (when compared with no elevation) help with risk stratification in adults with CKD (including those with ESRD) who do not have symptoms of ACS?

  1. In clinically stable adults with CKD (including those with ESRD) who do not have symptoms of ACS, what is the distribution of troponin values?
    1. What is the distribution by CKD stages 1–4 and in ESRD?
  2. Do troponin threshold levels or patterns of troponin change in this population improve prediction for MACE or all-cause mortality, compared with or supplementing existing models?
  3. Does troponin elevation improve CHD risk prediction for the following subgroups:
    1. Sex
    2. Age
    3. Ethnicity
    4. Stage of kidney disease (CKD stages 1–4 or ESRD requiring dialysis)
    5. Status after renal transplant
    6. Presence of baseline or previously elevated troponins
    7. Presence of ischemic ECG changes
    8. Comorbidities (e.g., diabetes, hypertension)
    9. Smoking status
    10. 10-year CHD risk
    11. History of CAD
  4. Among studies that directly compared one type of troponin assay (troponin I, troponin T, high-sensitivity troponin T, or high-sensitivity troponin I) against another type of troponin assay, does a certain type of troponin test predict risk better?

PICOTS Criteria

The PICOTS (patients, interventions, comparators, outcomes, timing, and setting) criteria for the comparative effectiveness review are as follows:

Population(s)

For all KQs, the population of interest is adult patients with CKD (including those with ESRD).

  • For KQs 1, 2, and 3, we will focus on patients with clinically suspected ACS.
  • For KQ 4, we will focus on the general population of adult patients with CKD (including those with ESRD) without suspected ACS.
  • The subgroups of interest are listed in KQs 1.2, 2.2, 3.2, and 4.3. One subgroup of particular interest is patients with ESRD who are on dialysis.
  • For KQ 1.5, we will focus on studies that directly compare patients with CKD and patients with normal renal function.
Interventions

The test of interest is troponin testing, including troponin T, troponin I, high-sensitivity troponin T, and high-sensitivity troponin I.

Comparators

For all KQs, the comparisons of interest are troponin elevation (generally > the 99th percentile) versus no elevation.

  • If there are studies that directly compared different types of troponin assays with each other, we will report these findings (KQs 1.4, 3.3, and 4.4); however, we will not study this indirectly in our methodological approach.
  • If there are studies that directly compared the utility of troponin elevation for diagnosing ACS in patients with CKD versus those without CKD, we will report these findings (KQ 1.5); however, we will not study this indirectly in our methodological approach.
  • Note that for the population with suspected ACS (KQs 1, 2, and 3), biomarker testing is done so routinely as part of standard care that “no testing” is not a realistic comparator.
  • In our subgroup analysis (KQs 1.2, 2.2, 3.2, and 4.3), we will stratify results by milder forms of CKD (stages 1–4) versus ESRD requiring dialysis.
  • In KQ 4, one comparator of interest would be “no testing” beyond the use of a standard risk-predictor model using traditional risk factors such as the Framingham Risk Score.25

The comparisons of interest for each KQ are outlined in Table 1.

Outcomes for Each Question
  • Key Question 1:
    • The outcomes of interest are sensitivity, specificity, and positive and negative predictive value against a clinical diagnosis of ACS as the reference standard. ACS is largely a clinical diagnosis, which can lend itself to some subjectivity. As defined by the ACC/AHA Guidelines,2 ACS has three major components: (1) chest pain or an anginal equivalent, (2) ischemic ECG changes, and/or (3) positive biomarkers of cardiac injury.
    • Positive biomarkers can include creatine kinase or creatine kinase-myocardial band but most often it is troponin. Therefore, troponin is not only the diagnostic assay but considered as one clinical factor for defining ACS in KQ 1. However, by itself, troponin is neither required nor sufficient for a diagnosis of ACS. Furthermore, a patient can have negative biomarkers and still be diagnosed with ACS (i.e., troponin-negative ACS), a situation where a negative troponin value represents a false-negative finding for ACS.
    • We will likely find that patients with ACS—for the purposes of the studies included in our review—will be selected based on billing records with ACS diagnostic codes. As stated in our method plan below, we will scrutinize the studies to determine how rigorously the outcome of ACS/MI was diagnosed. Our primary results will focus on studies that used a formal adjudication process for diagnosing ACS using strict criteria as established by the Third Universal Definition of Myocardial Infarction1 consensus or the ACC/AHA Guidelines.2
    • Harms of interest are associated with overdiagnosing ACS.
  • Key Question 2
    • The outcome is differences in the effects of patient management strategies, interventions, or treatments for ACS by troponin level thresholds.
    • However, based on our preliminary literature search, we think it is unlikely that there are studies that have tested this question as the primary study hypothesis. If there is limited information on studies that address KQ 2, the subquestions on subgroups and on types of troponin assays will be impossible to answer.
  • Key Questions 3 and 4

    The outcomes of interest are:

    • Long-term outcomes (all-cause mortality and MACE over at least 1 year of followup)
    • Short-term outcomes (all-cause mortality and MACE during the initial hospitalization or within 1 year of followup)
Timing
  • We will consider studies with any length of followup.
    • For KQs 1 and 2, which considers ACS, the included studies will likely involve a length of followup appropriate for the diagnosis and treatment of ACS (i.e., hours to days).
    • For KQs 3 and 4, which involve short-term and long-term outcomes, the length of followup might vary but could be weeks, months, or years.
  • Because troponin started to be used as a cardiac marker in the early 1990s, we will consider studies published after 1990.
Settings

We will consider all settings.

Table 1. Comparisons of interest for each Key Question
Key Question Outcome Elevated troponin level vs. normal troponin level Troponin T vs. troponin I vs. hs troponin T vs. hs troponin I Troponin testing in CKD vs. non-CKD Troponin testing vs. other risk- prediction models No comparison
Abbreviations: ACS = acute coronary syndrome; CKD = chronic kidney disease; hs = high sensitivity; KQ = key question; MACE = major adverse cardiovascular event
KQ 1.1 Diagnosis of ACS X        
KQ 1.2 Diagnosis of ACS X (by subgroups)        
KQ 1.3 Diagnosis of ACS X (regarding harms)        
KQ 1.4 Diagnosis of ACS   X      
KQ 1.5 Diagnosis of ACS     X    
KQ 2.1 Management of ACS X (interaction with intervention and management strategies)        
KQ 2.2 Management of ACS X (by subgroups)        
KQs 3.1a & 3.1b MACE after ACS X        
KQ 3.2 MACE after ACS X (by subgroups)        
KQ 3.3 MACE after ACS   X      
KQ 4.1 Prevalence troponin elevation         X
KQ 4.2 MACE in non-ACS       X  
KQ 4.3 MACE in non-ACS X (by subgroups)     X  
KQ 4.4 MACE in non-ACS   X      

Analytic Frameworks

Figure 1. Analytic framework for interpreting troponin as a cardiac marker among patients with chronic kidney disease and suspected acute coronary syndrome

Analytic framework of the interpretation of troponin as a cardiac marker among patients with chronic kidney disease (including those with end-stage renal disease) and suspected acute coronary syndrome. The figure is an analytic framework of the key questions one through three.  From left to right, it begins with patients with CKD, which points to symptoms, concerns for ACS and below has high pretest probability and low pretest probability.  There is also an arrow pointing to the symptoms, concerns for ACS to indicate Subgroups for key question 1.2, 2.2, and 3.2.  Then, there is an arrow labeled Troponin assay and has two arrows pointing to it and three pointing from it.  The two pointing to it are labeled KQ1.5 CKD versus non-CKD and KQ1.4, KQ3.3 specific troponin assays.  One of the arrows pointing away from Troponin assay is a wavy arrow pointing to a circle that has Harms of over-diagnosing ACS KQ1.3 inside.  Then, there is another arrow pointing from Troponin assay over to KQ3 prognosis in suspected ACS.  The third arrow from Troponin assay is straight to a rounded-edge box labeled KQ1 diagnosis with Diagnostic accuracy ACS, no ACS inside.  Then a dotted straight arrow points to another rounded-edge box to the right labeled KQ2 management of patients with ACS that has Patient management, early invasive strategy, early conservative strategy inside.  Then, a straight, dotted arrow points from that box to a straight-edge box labeled KQ3 prognosis in suspected ACS that has long term, greater than a year outcomes of MACE and all-cause mortality, and short term, less than a year outcomes of MACE and all-cause mortality.

Abbreviations: ACS = acute coronary syndrome; CKD = chronic kidney disease; ESRD = end-stage renal disease; KQ = key question; MACE = major adverse cardiovascular event

Figure 2. Analytic framework for interpreting troponin as a cardiac marker during renal function impairment among patients with chronic kidney disease without symptoms of acute coronary syndrome

Figure two is the analytic framework for the interpretation of troponin as a cardiac marker during renal function impairment among patients with chronic kidney disease, including those with end stage renal disease, without symptoms of acute coronary syndrome.  From left to right, it begins with patients with CKD, then a straight arrow to no symptoms of ACS, which is pointed to by a straight arrow from below labeled KQ4.3 subgroups.  Then there is an arrow to the right labeled Troponin assay, which is pointed to by two arrows above and below.  The above arrow that points to Troponin assay is labeled KQ4.4 specific troponin assays and the arrow below is labeled KQ4.1 prevalence of troponin elevation.  Troponin assay has a arrow to the right pointing to a rounded edge box with high risk and low risk in it, then an arrow to another rounded edge box to the right with patient management inside.  Then to the right of that box is a dotted arrow pointed to a straight-edged box with long term more than a year outcomes MACE and all-cause mortality and short term, less than a year, outcomes MACE and all-cause mortality.  Above the last three boxes is a line which is labeled KQ4.2, prognosis in stable population.

Abbreviations: ACS = acute coronary syndrome; CKD = chronic kidney disease; ESRD = end-stage renal disease; KQ = key question; MACE = major adverse cardiovascular event

Methods

Criteria for Inclusion/Exclusion of Studies in the Review

We present the inclusion/exclusion criteria in Table 2.

Table 2. Inclusion and exclusion criteria
PICOTS Inclusion criteria Exclusion criteria
Abbreviations: ACS = acute coronary syndrome; CAD = coronary artery disease; CHD = coronary heart disease; CKD = chronic kidney disease; ECG = electrocardiogram; ESRD = end-stage renal disease; MACE = major adverse cardiovascular event
Population and condition of interest
  • All studies will include human subjects exclusively.
  • We will include studies of adult patients with CKD including ESRD.
    • For KQs 1, 2, and 3, we will include patients who also are clinically suspected of having ACS
    • For KQ 1.5, we will only include patients with normal renal function if the studies made a direct comparison with CKD.
    • For KQ 4, we will include patients who are clinically stable and asymptomatic for ACS.
    • In KQs 1.2, 2.2, 3.2, and 4.3, we will evaluate subgroups of patients based on:
      • Sex
      • Age
      • Ethnicity
      • Stage of kidney disease (CKD 1–4 or ESRD requiring dialysis)
      • Status after renal transplant
      • Presence of baseline or previously elevated troponins
      • Presence of ischemic ECG changes (for patients with clinically suspected ACS only)
      • Comorbidities (e.g., diabetes, hypertension)
      • Smoking status
      • 10-year CHD risk
      • History of CAD
 
Interventions We will include studies that evaluate troponin I, troponin T, high-sensitivity troponin T, or high-sensitivity troponin I.  
Comparisons of interest
  • The comparisons of interest for each KQ are outlined in Table 1.
  • For all KQs, the comparisons of interest will compare troponin elevation (generally > the 99th percentile) versus no elevation.
  • If there are studies that directly compared different types of troponin assays with each other, we will report these findings (KQs 1.4, 3.3, and 4.4); however, we will not study this indirectly in our methodological approach.
  • If there are studies that directly compared the utility of troponin elevation for diagnosing ACS in patients with or without CKD, we will report these findings (KQ 1.5); however, we will not study this indirectly in our methodological approach.
  • For the population with suspected ACS (KQs 1–3), biomarker testing is done so routinely as part of a standard workup that “no testing” is not a realistic comparator and thus will not be evaluated.
  • In our subgroup analysis (KQs 1.2, 2.2, 3.2, and 4.3), we will stratify results by milder forms of CKD (stages 1–4) versus ESRD.
  • In KQ4, one comparator of interest is “no testing” beyond the use of a standard risk predictor model using traditional risk factors such as the Framingham Risk Score.
We will exclude studies that do not have a comparison group.
Outcomes
  • For KQ 1, the outcomes of interest are sensitivity, specificity, and positive and negative predictive values compared with clinical diagnosis of ACS (adjudicated using strict criteria according to guidelines).
  • For KQ 2a, the outcome is differences in the effects of patient management strategies, interventions, or treatments for ACS by troponin level thresholds.
  • For KQs 3 and 4, the outcomes of interest are:
    • Short-term outcomes
      • All-cause mortality
      • MACE rate at < 1 year
    • Long-term outcomes
      • All-cause mortality
      • MACE rates at ≥ 1 year
 
Type of study
  • We will include randomized controlled trials and observational studies with a comparison group.
  • We will not place any restrictions based on sample size or language.
  • We will exclude articles with no original data (reviews, editorials, and commentaries).
  • We will exclude studies published before 1990 because troponin started being used a cardiac marker in the early 1990s.
Timing and setting
  • We will include studies regardless of the length of followup.
  • We will include all study settings.
 

Searching for the Evidence: Literature Search Strategies for Identification of Relevant Studies To Answer the Key Questions

We will search the following databases for primary studies: MEDLINE®, EMBASE®, and the Cochrane Central Register of Controlled Trials from January 1, 1990, through January 31, 2013, and we will update the search during peer review. We will develop a search strategy for MEDLINE, accessed via PubMed®, based on an analysis of medical subject headings (MeSH®) and text words of key articles identified a priori. Our search strategy for MEDLINE is presented in Table 3. The search will be updated during the peer review process. We will handsearch the reference lists of all included articles and other relevant systematic reviews.

Additionally, the team will search ClinicalTrials.gov to identify relevant registered trials. We will review the Scientific Information Packets provided by the troponin assay manufacturers.

Two independent reviewers will conduct title scans. For a title to be eliminated at this level, both reviewers will need to indicate that the study was ineligible. If the reviewers disagree, the article will be advanced to the next level, which is abstract review.

The abstract review phase will be designed to identify studies reporting the effects of troponin testing. Abstracts will be reviewed independently by two investigators and will be excluded if both investigators agree that the article meets one or more of the exclusion criteria (see the inclusion and exclusion criteria listed in Table 2). Differences between investigators regarding the inclusion or exclusion of abstracts will be tracked and resolved through consensus adjudication.

Articles promoted on the basis of the abstract review will undergo another independent parallel review to determine if they should be included in the final qualitative and quantitative systematic review and meta-analysis. The differences regarding article inclusion will be tracked and resolved through consensus adjudication.

Data Abstraction and Data Management

We will use a systematic approach to extract all data to minimize the risk of bias in this process. We will create standardized forms for data extraction, which will be pilot tested. By creating standardized forms for data extraction, we seek to maximize consistency in identifying all pertinent data available for synthesis.

Each article will undergo double review by the study investigators for data abstraction. The second reviewer will confirm the first reviewer’s abstracted data for completeness and accuracy. Reviewer pairs will be formed to include personnel with both clinical and methodological expertise. A third reviewer will audit a random sample of articles to ensure consistency in the data abstraction of the articles. Reviewers will not be masked to the authors of the articles, their respective institutions, nor the journals in which their articles were published.

For all articles, the reviewers will extract information on general study characteristics (e.g., study design, study period, and followup), study participants (e.g., age, sex, dialysis status, smoking status), interventions (including type of troponin assay and cutoffs used), comparisons, outcome measures, definitions, and the results of each outcome, including measures of variability.

For all articles, we will pay attention to the troponin assay used and the troponin cutoff value used. There is a concern that in some of the older studies, very high cutoff values were used and not the 99th percentile. Furthermore, many assays do not have clinical studies associated with it to establish the 99-percent upper reference limit. We will be sensitive to this issue when synthesizing the data and may need to report results separately for studies not using the 99th percentile. If there is ambiguity in the cutoff used for the troponin assay, we will attempt to contact the manufacturer of the assay or the study authors to get more details.

For KQs 1, 2, and 3, we will collect information on how the ACS outcome was defined in the studies. While troponin is one factor often considered in evaluating MI/ACS, troponin alone is neither necessary nor sufficient for diagnosis. We are using a clinical diagnosis of ACS for our gold standard outcome for KQ 1; however, there is a concern that the literature varies greatly in the definitions of ACS. In some papers, the outcome of ACS versus non-ACS may be defined by billing or diagnostic codes rather than by using the strict criteria as established by the Third Universal Definition of Myocardial Infarction1 consensus and/or a formal adjudication process. This may lead to misclassification and reduce the utility of the diagnostic test. While we plan to include all relevant papers in the initial literature search, primary results will be limited to only studies were ACS was defined by rigorous criteria and adjudicated.

We will collect data on subgroups of interest, including sex, age, ethnicity, stage of kidney disease, dialysis status, pre/post dialysis (in patients receiving dialysis), status after renal transplant, presence of baseline or previously elevated troponins, presence of ischemic ECG changes (for patients with clinically suspected ACS only), comorbidities (e.g., diabetes, hypertension), smoking status, 10-year CHD risk, and history of CAD.

All information from the article review process will be entered into a DistillerSR database (Evidence Partners Inc., Ottawa, Canada) by the individual completing the review. Reviewers will enter comments into the system whenever applicable. The DistillerSR database will be used to maintain the data and to create detailed evidence tables and summary tables. We may contact the authors of the included studies for additional data, if necessary.

Assessment of Methodological Risk of Bias of Individual Studies

Article quality will be assessed independently by two reviewers. We will use separate quality assessment tools for studies evaluating diagnostic performance and for studies evaluating prognostication and risk stratification. For studies evaluating diagnostic performance, we will use the closed-ended questions from the QUADAS-2 quality assessment tool.26 For studies evaluating prognostication or risk stratification, we will use the Downs and Black quality assessment tool.27 We will supplement these tools with additional quality-assessment questions based on recommendations in the Methods Guide for Medical Test Reviews28 and the Methods Guide for Effectiveness and Comparative Effectiveness Reviews.29

For all studies, the overall study quality will be assessed as indicated below, and differences between reviewers will be resolved through consensus adjudication.

Data Synthesis

For KQs 1, 2, and 3, we will focus our main analysis on the studies that provided a rigorous definition of ACS (i.e., studies that adjudicated ACS as an outcome).

We will conduct meta-analyses when there are sufficient data and studies are sufficiently homogenous with respect to key variables (population characteristics, study duration, and treatment). For KQ 1, we will follow the meta-analytic methods for studies that had an imperfect reference standard.30 We will construct 2 × 2 tables and calculate sensitivity, specificity, and positive and negative predictive values where possible. If we find at least five studies that are sufficiently homogenous, we will conduct a hierarchical summary receiver operator curve meta-analysis to analyze sensitivity and specificity. For comparing studies that used different troponin assays from different manufacturers, we will use an index reference such as the 99th percentile for that assay rather than the absolute troponin value. If studies did not use the standardized cutoff of the 99th percentile, these results likely will need to be presented separately as they may not be directly comparable with studies that did use the 99th percentile.

Given the nature of the topic, we anticipate the studies to be predominantly observational in nature, including post-hoc analyses of randomized controlled trials that studied ACS interventions. In addition to including studies that compare threshold levels of cTn elevation in comparison with no elevation (for diagnosis and prognosis), we will also search for studies that directly compared elevated cTn in patients with CKD and elevated cTn in non-CKD populations for ACS diagnosis.

For continuous outcomes, we will calculate a weighted mean difference by using a random-effects model with the DerSimonian and Laird formula.31 For dichotomous outcomes, we will calculate a pooled effect estimate of the relative risk—with each study weighted by the inverse variance—by using a random-effects model with the DerSimonian and Laird formula for calculating between-study variance.31

Heterogeneity among the trials in all the meta-analyses will be tested by using a standard chi-squared test with a significance level of alpha ≤ 0.10. Heterogeneity will also be examined among studies by using an I2 statistic, which describes the variability in effect estimates that is due to heterogeneity rather than random chance.32 A value greater than 50 percent may be considered to connote substantial variability. If we find substantial heterogeneity, we will attempt to determine potential reasons for this by conducting meta-regression analyses using study-level variables.

Publication bias will be examined by using Begg’s test33 and Egger’s test34 including evaluation of the asymmetry of funnel plots for each comparison of interest for the outcomes for which meta-analyses are conducted.

STATA statistical software (Intercooled, Version 12.1, StataCorp, College Station, TX) will be used for all meta-analyses.

Studies that are not amenable to pooling will be summarized qualitatively.

Grading the Strength of Evidence for Individual Comparisons and Outcomes

At the completion of our review, at least two reviewers will independently assign evidence grades. Conflicts will be resolved through consensus or third-party adjudication. We will grade the strength of evidence based on the quantity, quality, and consistency of the best available evidence, addressing KQs 1, 2, 3, and 4 by adapting an evidence grading scheme recommended in the Methods Guide for Medical Test Reviews29 and the Methods Guide for Effectiveness and Comparative Effectiveness Reviews.30 We will apply evidence grades to the bodies of evidence about each intervention comparison for each outcome. We will assess the risk of bias of individual studies according to study design characteristics, such as confounding and selection and information biases. We will assess the strength of the best available evidence by assessing the limitations to individual study quality (using individual quality scores), consistency, directness, precision, publication bias, and the magnitude of the effect.

We will classify evidence pertaining to the KQs into four basic categories: (1) “high” grade (indicating high confidence that the evidence reflects the true effect and that further research is very unlikely to change our confidence in the estimate of the effect); (2) “moderate” grade (indicating moderate confidence that the evidence reflects the true effect and that further research may change our confidence in the estimate of the effect and may change the estimate); (3) “low” grade (indicating low confidence that the evidence reflects the true effect and that further research is likely to change our confidence in the estimate of the effect and is likely to change the estimate); and (4) “insufficient” grade (evidence is unavailable or does not permit a conclusion).

Assessing Applicability

We will assess the applicability of studies in terms of the degree to which the study population, interventions, outcomes, and settings are typical for adult patients with CKD or ESRD. Factors that may limit applicability include sex, age, ethnicity, stage of kidney disease, dialysis status, status after renal transplant, presence of baseline or previously elevated troponins, presence of ischemic ECG changes (for patients with suspected ACS only), comorbidity, smoking status, 10-year CHD risk, and history of CAD.

  • Good (low risk of bias). These studies had the least bias, and the results were considered valid. These studies adhered to the commonly held concepts of high quality, including the following: a clear description of the population, setting, interventions, and comparison groups; appropriate measurement of outcomes; appropriate statistical and analytic methods and reporting; no reporting errors; a low dropout rate; and clear reporting of dropouts.
  • Fair. These studies were susceptible to some bias, but not enough to invalidate the results. They did not meet all the criteria required for a rating of good quality because they had some deficiencies, but no flaw was likely to cause major bias. The study may have been missing information, making it difficult to assess limitations and potential problems.
  • Poor (high risk of bias). These studies had significant flaws that might have invalidated the results. They had serious errors in design, analysis, or reporting; large amounts of missing information; or discrepancies in reporting.
Table 3. Search string to capture studies on troponin
Search String
#1 "kidney failure, chronic"[mh]
#2 Renal[tiab]
#3 Kidney[tiab]
#4 Dialysis[tiab]
#5 Hemodialysis[tiab]
#6 Haemodialysis[tiab]
#7 #1 OR #2 OR #3 OR #4 OR #5 OR #6
#8 "acute coronary syndrome"[mh]
#9 “acute coronary syndrome”[tiab] OR “acute coronary syndromes”[tiab]
#10 "angina, unstable"[mh]
#11 “unstable angina”[tiab]
#12 “myocardial infarction”[tiab]
#13 “Non-ST-segment elevation”[tiab] OR “non-ST-elevation”[tiab] OR “non-ST elevation”[tiab] OR “ST-segment elevation”[tiab] OR “ST-elevation”[tiab] OR “ST elevation”[tiab] OR (elevation[tiab] AND (ST[tiab] OR “S-T”[tiab] OR “ST-segment”[tiab]))
#14 Acute[tiab]
#15 #12 AND (#13 OR #14)
#16 #8 OR #9 OR #10 OR #11 OR #15
#17 “Troponin I”[mh] OR “Troponin T”[mh]
#18 Troponin*[tiab]
#19 #17 OR #18
#20 (#7 AND #16) OR (#7 AND #9)
#21 (animal[mh] NOT human [mh])
#22 Addresses[pt] OR Autobiography[pt] OR Bibliography[pt] OR Biography[pt] OR “Case Reports”[pt] OR “Classical Article”[pt] OR “Clinical Conference”[pt] OR “Collected Works”[pt] OR Comment[pt] OR Congresses[pt] OR “Consensus Development Conference”[pt] OR “Consensus Development Conference, NIH”[pt] OR Dictionary[pt] OR Directory[pt] OR Editorial[pt] OR “Legal Cases”[pt] OR Legislation[pt] OR News[pt] OR “Newspaper Article”[pt] OR Portraits[pt]
#23 #20 NOT #21 NOT #22
  Publication date from 1990/01/01

References

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Definition of Terms

ACS = acute coronary syndrome
AMI = acute myocardial infarction
CAD = coronary artery disease
CHD = coronary heart disease
CKD = chronic kidney disease
cTn = cardiac-specific troponin
ECG = electrocardiogram
ESRD = end-stage renal disease
KQ = key question
MACE = major adverse cardiovascular event
MI = myocardial infarction
NSTEMI = non-ST elevation myocardial infarction
STEMI = ST elevation myocardial infarction
Tn = troponin
UA = unstable angina

Summary of Protocol Amendments

In the event of protocol amendments, the date of each amendment will be accompanied by a description of the change and the rationale.

Review of Key Questions

For all Evidence-based Practice Center (EPC) reviews, Key Questions were reviewed and refined as needed by the EPC with input from Key Informants and the Technical Expert Panel (TEP) to assure that the questions are specific and explicit about what information is being reviewed. In addition, the Key Questions were posted for public comment and finalized by the EPC after review of the comments.

Key Informants

Key Informants are the end-users of research, including patients and caregivers, practicing clinicians, relevant professional and consumer organizations, purchasers of health care, and others with experience in making health care decisions. Within the EPC program, the Key Informant role is to provide input into identifying the Key Questions for research that will inform health care decisions. The EPC solicits input from Key Informants when developing questions for systematic review or when identifying high-priority research gaps and needed new research. Key Informants are not involved in analyzing the evidence or writing the report and have not reviewed the report, except as given the opportunity to do so through the peer or public review mechanism.

Key Informants must disclose any financial conflicts of interest greater than $10,000 and any other relevant business or professional conflicts of interest. Because of their role as end-users, individuals are invited to serve as Key Informants and those who present with potential conflicts may be retained. The Task Order Officer and the EPC work to balance, manage, or mitigate any potential conflicts of interest identified.

Technical Experts

Technical Experts comprise a multidisciplinary group of clinical, content, and methodological experts who provide input in defining populations, interventions, comparisons, or outcomes, as well as identifying particular studies or databases to search. They are selected to provide broad expertise and perspectives specific to the topic under development. Divergent and conflicted opinions are common and perceived as healthy scientific discourse that results in a thoughtful, relevant systematic review. Therefore study questions, design, and/or methodological approaches do not necessarily represent the views of individual technical and content experts. Technical Experts provide information to the EPC to identify literature search strategies and recommend approaches to specific issues as requested by the EPC. Technical Experts do not do analysis of any kind nor contribute to the writing of the report and have not reviewed the report, except as given the opportunity to do so through the peer or public review mechanism.

Technical Experts must disclose any financial conflicts of interest greater than $10,000 and any other relevant business or professional conflicts of interest. Because of their unique clinical or content expertise, individuals are invited to serve as Technical Experts and those who present with potential conflicts may be retained. The TOO and the EPC work to balance, manage, or mitigate any potential conflicts of interest identified.

Peer Reviewers

Peer reviewers are invited to provide written comments on the draft report based on their clinical, content, or methodological expertise. Peer review comments on the preliminary draft of the report are considered by the EPC in preparation of the final draft of the report. Peer reviewers do not participate in writing or editing of the final report or other products. The synthesis of the scientific literature presented in the final report does not necessarily represent the views of individual reviewers. The dispositions of the peer review comments are documented and will, for CERs and Technical Briefs, be published 3 months after the publication of the Evidence Report.

Potential Reviewers must disclose any financial conflicts of interest greater than $10,000 and any other relevant business or professional conflicts of interest. Invited Peer Reviewers may not have any financial conflict of interest greater than $10,000. Peer reviewers who disclose potential business or professional conflicts of interest may submit comments on draft reports through the public comment mechanism.

EPC Team Disclosures

EPC core team members must disclose any financial conflicts of interest greater than $1,000 and any other relevant business or professional conflicts of interest. Related financial conflicts of interest that cumulatively total greater than $1,000 will usually disqualify EPC core team investigators.

Role of the Funder

This project was funded under Contract No. xxx-xxx from the Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services. The Task Order Officer reviewed contract deliverables for adherence to contract requirements and quality. The authors of this report are responsible for its content. Statements in the report should not be construed as endorsement by the Agency for Healthcare Research and Quality or the U.S. Department of Health and Human Services.

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