Benefits of Home-Based Solutions for Diagnosis and Treatment of Acute Coronary Syndromes on Health Care Costs: A Systematic Review

sensors Review Benefits of Home-Based Solutions for Diagnosis and Treatment of Acute Coronary Syndromes on Health Care Costs: A Systematic Review Pau Redón1,2,*, Atif Shahzad 2, Talha Iqbal 2and William Wijns 1,2,3 1CÚRAM Center for Research in Medical Devices, H91 W2TY Galway, Ireland; [email protected] 2Smart Sensor Lab, School of Medicine, National University of Ireland, Galway (NUIG), H91 TK33 Galway, Ireland; [email protected] (A.S.); [email protected] (T.I.) 3Saolta University Healthcare Group, University Hospital Galway, Newcastle Road, H91 YR71 Galway, Ireland *Correspondence: [email protected] Received: 2 August 2020; Accepted: 1 September 2020; Published: 3 September 2020   Abstract: Diagnosing and treating acute coronary syndromes consumes a significant fraction of the healthcare budget worldwide. The pressure on resources is expected to increase with the continuing rise of cardiovascular disease, other chronic diseases and extended life expectancy, while expenditure is constrained. The objective of this review is to assess if home-based solutions for measuring chemical cardiac biomarkers can mitigate or reduce the continued rise in the costs of ACS treatment. A systematic review was performed considering published literature in several relevant public databases (i.e., PUBMED, Cochrane, Embase and Scopus) focusing on current biomarker practices in high-risk patients, their cost-effectiveness and the clinical evidence and feasibility of implementation. Out of 26,000 references screened, 86 met the inclusion criteria after independent full-text review. Current clinical evidence highlights that home-based solutions implemented in primary and secondary prevention reduce health care costs by earlier diagnosis, improved patient outcomes and quality of life, as well as by avoidance of unnecessary use of resources. Economical evidence suggests their potential to reduce health care costs if the incremental cost-effectiveness ratio or the willingness-to-pay does not surpass £20,000/QALY or € 50,000 limit per 20,000 patients, respectively. The cost-effectiveness of these solutions increases when applied to high-risk patients. Keywords: cardiovascular disease; acute myocardial infarction; home-based solutions; troponin; cardiac biomarkers 1. Introduction Over the past few decades, cardiovascular diseases (CVD) are in a continuous rise and currently accounting for 17.64 million deaths worldwide in the general population [ 1 ]. Moreover, CVD is the leading cause of death in patients with chronic kidney disease (CKD) and other comorbidities. In adult diabetic patients the probability of dying from heart disease is 2–4 times higher compared to their healthy peers [1]. One of the most common acute coronary syndromes (ACS) triggered by CVD are heart attacks, also known as acute myocardial infarction (AMI). These can be symptomatic or asymptomatic and are caused by a complete (ST-segment elevation MI, or STEMI) or partial blockage of coronary arteries (non-STEMI or unstable angina). The damage or injury is generated by the lack of blood and oxygen supply to the downstream myocardium and it can be largely irreversible in the absence of essential repair mechanisms, inherent to the myocardium. In healthy hearts, see Figure 1a, the regeneration rate of the heart cells decreases considerably with age [ 2 , 3 ] and equally affects males and females [ 3 ]. Sensors 2020,20, 5006; doi:10.3390/s20175006 www.mdpi.com/journal/sensors Sensors 2020,20, 5006 2 of 20 Focusing on cardiomyocytes, responsible for the contraction of the myocardium, their regeneration rate reduces from an annual rate of 5%, in the first years of life, to less than 0.5% in an elderly population. Consequently, as illustrated in Figure 1b, the number of cardiomyocytes remains approximately constant throughout the whole lifespan of males and females, without opportunity for repair in case of cell loss due to STEMI. Sensors 2020, 20, x 2 of 20 regeneration rate of the heart cells decreases considerably with age [2,3] and equally affects males and females [3]. Focusing on cardiomyocytes, responsible for the contraction of the myocardium, their regeneration rate reduces from an annual rate of 5%, in the first years of life, to less than 0.5% in an elderly population. Consequently, as illustrated in Figure 1b, the number of cardiomyocytes remains approximately constant throughout the whole lifespan of males and females, without opportunity for repair in case of cell loss due to STEMI. (a) (b) Figure 1. “Regeneration rate and number of cardiomyocytes depending on: (a) age and (b) gender” Olaf Bergmann et al. [3], licensed under the number 4772391132781. Independently from the type of AMI, the detection in the blood stream of abnormal levels of biomarkers associated with myocardial necrosis, in particular troponins, is now the standard evaluation and classification criterion according to the recently published Fourth Universal Definition of Myocardial Infarction Consensus Document [4]. This consensus document elaborated by several scientific associations (European Society of Cardiology (ESC), American Heart Association (AHA) and American College of Cardiology (ACC)) introduces several updates with respect to prior versions [5–7]. The most relevant observation in the consensus document is related to the differentiation between infarction and injury based on troponin levels. The troponin, a contractile protein, which is responsible for the heart’s contraction−relaxation movements, can be found as part of the cardiomyocyte structure in the isoforms I (cTnI) and T (cTnT). A troponin release into the circulatory system is a sign of ischemic cardiomyocytes or myocardial damage, see Figure 2. Currently, no other cardiac biomarker has shown higher diagnostic and prognostic capability than troponins [8–10]. Figure 2. Depiction of cardiac troponin and cardiac myosin-binding protein and their release during myocardial injury by Twerenbold et al . [9], licensed under open access terms. Figure 1. “Regeneration rate and number of cardiomyocytes depending on: ( a ) age and ( b ) gender” Olaf Bergmann et al. [3], licensed under the number 4772391132781. Independently from the type of AMI, the detection in the blood stream of abnormal levels of biomarkers associated with myocardial necrosis, in particular troponins, is now the standard evaluation and classification criterion according to the recently published Fourth Universal Definition of Myocardial Infarction Consensus Document [ 4 ]. This consensus document elaborated by several scientific associations (European Society of Cardiology (ESC), American Heart Association (AHA) and American College of Cardiology (ACC)) introduces several updates with respect to prior versions [ 5 – 7 ]. The most relevant observation in the consensus document is related to the differentiation between infarction and injury based on troponin levels. The troponin, a contractile protein, which is responsible for the heart’s contraction − relaxation movements, can be found as part of the cardiomyocyte structure in the isoforms I (cTnI) and T (cTnT). A troponin release into the circulatory system is a sign of ischemic cardiomyocytes or myocardial damage, see Figure 2. Currently, no other cardiac biomarker has shown higher diagnostic and prognostic capability than troponins [8–10]. Sensors 2020, 20, x 2 of 20 regeneration rate of the heart cells decreases considerably with age [2,3] and equally affects males and females [3]. Focusing on cardiomyocytes, responsible for the contraction of the myocardium, their regeneration rate reduces from an annual rate of 5%, in the first years of life, to less than 0.5% in an elderly population. Consequently, as illustrated in Figure 1b, the number of cardiomyocytes remains approximately constant throughout the whole lifespan of males and females, without opportunity for repair in case of cell loss due to STEMI. (a) (b) Figure 1. “Regeneration rate and number of cardiomyocytes depending on: (a) age and (b) gender” Olaf Bergmann et al. [3], licensed under the number 4772391132781. Independently from the type of AMI, the detection in the blood stream of abnormal levels of biomarkers associated with myocardial necrosis, in particular troponins, is now the standard evaluation and classification criterion according to the recently published Fourth Universal Definition of Myocardial Infarction Consensus Document [4]. This consensus document elaborated by several scientific associations (European Society of Cardiology (ESC), American Heart Association (AHA) and American College of Cardiology (ACC)) introduces several updates with respect to prior versions [5–7]. The most relevant observation in the consensus document is related to the differentiation between infarction and injury based on troponin levels. The troponin, a contractile protein, which is responsible for the heart’s contraction−relaxation movements, can be found as part of the cardiomyocyte structure in the isoforms I (cTnI) and T (cTnT). A troponin release into the circulatory system is a sign of ischemic cardiomyocytes or myocardial damage, see Figure 2. Currently, no other cardiac biomarker has shown higher diagnostic and prognostic capability than troponins [8–10]. Figure 2. Depiction of cardiac troponin and cardiac myosin-binding protein and their release during myocardial injury by Twerenbold et al . [9], licensed under open access terms. Figure 2. Depiction of cardiac troponin and cardiac myosin-binding protein and their release during myocardial injury by Twerenbold et al. [9], licensed under open access terms. Sensors 2020,20, 5006 3 of 20 Unfortunately, the incidence of AMI is expected to continue increasing with the rise of CVD and other chronic diseases (e.g., diabetes, hypertension and obesity) in conjunction with a rapidly aging population in the Western world. Such increase is expected to negatively impact the budget of national health care systems. Treating acute cardiac events, like AMI, consumes a significant fraction of the limited budget of the healthcare providers (UK € 1.9 billion, France € 1.3 billion, Germany €3.3 billion , Italy € 3.1 billion, Spain € 1.0 billion and US $12.1 billion), attributable to both the frequency with which it occurs and the cost associated with each acute hospitalization [ 10 , 11 ]. Even though a detailed analysis of these costs reveals that most of them are not modifiable by the care team or the health system, some potential reductions can be achieved by replacing routine-based practices with need-based practices [ 12 ]. This is especially relevant for high-risk patients (e.g., diabetic patients, elderly, heart failure and CKD) who demand quick and safe diagnostic procedures to reduce their risk of suffering recurrent events or dying. Consequently, interventions targeting these high-risk patients are more likely to yield effective results when it comes to reducing health care expenditure [13]. In this context, one potential solution worth considering is the use of home-based or telemonitoring systems, which are capable of measuring troponin levels in biological samples, easily implementable in current clinical practice and focusing on high-risk patients. The objective of this review is to explore these opportunities by assessing the available evidence in key enabling fields: sensing technologies currently available for home-based telemonitoring systems; relevance of personal data for diagnosis and prognosis of ACS including NSTEMI and STEMI; anticipated clinical benefits from implementation of telemonitoring in this context; and features that make an ambulatory troponin-based strategy potentially cost-effective. 2. Materials & Methods The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology [ 14 ] was used to synthesize the current evidence available in the published literature on home-based solutions for ACS management, see Figure 3. The major research databases, PubMed, Cochrane Library, Embase and Scopus, were scanned between the 1st of December 2019 and the 31st of January 2020. The search terms were the result of combining 3 general keywords (cardiac troponin or cTn, Emergency Department (ED), diagnosis, prognosis, myocardial injury) with a maximum of 3 specific keywords (elderly, diabetes, CKD, heart failure, cost-effectiveness, economical, clinical, home-based or wearables or biosensors). Sensors 2020,20, 5006 4 of 20 Sensors 2020, 20, x 4 of 20 Figure 3. Schematic summary of the number of papers evaluated for this review according to the PRISMA methodology [14]. The search terms were the result of combining 3 general keywords (cardiac troponin or cTn, Emergency Department (ED), diagnosis, prognosis, myocardial injury) with a maximum of 3 specific keywords (elderly, diabetes, CKD, heart failure, cost-effectiveness, economical, clinical, home-based or wearables or biosensors). A total of 26,485 papers were initially retrieved after adding up the different combinations of the search terms and 330 were selected after removing duplicates, those not available in English and those published prior to 2010. Two-hundred and fifty papers were excluded during the title and abstract screening process and deemed irrelevant to the topic of this review. The excluded papers have focused on pathophysiological and biochemical principles as well as a different population compared to the high-risk population covered in this paper. The last step prior to final inclusion was to determine the eligibility of the 80 remaining references. A full-text analysis was performed on all of the selected 80 papers with special attention to identify the study’s limitations. In those cases, where this information was not available, the authors applied specific quality assessment tools, specially AGREE-II [15,16], see Table S1 in the Supplementary Materials section (Supplementary Material 1) for the list of items reviewed by this methodology. Based on the quality assessment, an additional 10 papers were excluded due to either important limitations with respect to selection bias (e.g., patient recruitment in clinical trials not performed randomly) or outcome bias (e.g., the results of not all measured variables were published) or because they were not published in first or second quartile journals. Only when a limited number of references were available for a certain topic, these were complemented by papers published in journals of the third or fourth quartile and by others identified from the reference list of already included papers. At the end, a total of 86 references were Records identified through database searching ( n = 26485 ) Screenin g Included Eligibility Identification Records after duplicates removed and limited from 2010 onwards (n = 330) Records screened (n = 330) Records excluded (n = 250) Full-text articles assessed for eligibility ( n = 80 ) Full-text articles excluded, out of the main scope of the paper ( n = 10 ) Studies included in systematic review ( n = 86 ) Additional records identified (n = 16) Figure 3. Schematic summary of the number of papers evaluated for this review according to the PRISMA methodology [14]. A total of 26,485 papers were initially retrieved after adding up the different combinations of the search terms and 330 were selected after removing duplicates, those not available in English and those published prior to 2010. Two-hundred and fifty papers were excluded during the title and abstract screening process and deemed irrelevant to the topic of this review. The excluded papers have focused on pathophysiological and biochemical principles as well as a different population compared to the high-risk population covered in this paper. The last step prior to final inclusion was to determine the eligibility of the 80 remaining references. A full-text analysis was performed on all of the selected 80 papers with special attention to identify the study’s limitations. In those cases, where this information was not available, the authors applied specific quality assessment tools, specially AGREE-II [ 15 , 16 ], see Table S1 in the Supplementary Materials section (Supplementary Material 1) for the list of items reviewed by this methodology. Based on the quality assessment, an additional 10 papers were excluded due to either important limitations with respect to selection bias (e.g., patient recruitment in clinical trials not performed randomly) or outcome bias (e.g., the results of not all measured variables were published) or because they were not published in first or second quartile journals. Only when a limited number of references were available for a certain topic, these were complemented by papers published in journals of the third or fourth quartile and by others identified from the reference list of already included papers. At the end, a total of 86 references were included in this systematic review, see Figure S1 included in the Supplementary Materials section (Supplementary Material 1) for further details. The limitations of this review article can be potentially related to selection bias caused by three key aspects: (1) the selection of the search terms and how they are combined. Other combinations of these search terms may result in a slightly different search base; (2) the date and type of the databases scanned, including the list of journals indexed in these databases, which means some of the relevant Sensors 2020,20, 5006 5 of 20 manuscripts published in other journals or stored in other databases are expected to be omitted; and (3) only published data were considered, limiting the inclusion of more recent and updated studies pending publication. 3. Diagnosing AMI 3.1. Diagnosis and Prognosis of Cut-OffValues in Troponin-Based Assays Sensitive (s-Tn) and high-sensitive (hs-Tn) troponin-based assays coexist commercially either integrated in bulky and expensive laboratory equipment or as a bedside point of care (PoC) solution [ 17 ]. The difference between them is not restricted to the limit of detection (LOD) of the assays but more importantly with the potential strategies these assays can drive. The hs-Tn assays can contribute to improve patient outcomes by reducing the event-to-diagnosis-time through their capacity to detect smaller changes in the concentrations of troponins between two consecutive readings. A key milestone regarding the recognition of this technology has been the presentation of the 0/1 h algorithm in the recently published ESC guidelines [ 8 ]. Despite this potential benefit their clinical implementation is still restricted probably due to some identified limitations: nonspecific elevations, false-positive results, biological variability and lack of assay standardization [ 18 ]. In high-risk patient cohorts (e.g., CKD, adult diabetic patients, heart failure (HF) and elderly patients) which demand rapid and more accurate diagnosis, these and other limitations can have major health care consequences. 3.1.1. Chronic Kidney Disease Focusing on the CKD cohorts of patients with CVD, important conclusions can be extracted from several recently published review papers [ 19 , 20 ]. Michos et al. [ 19 ] examined 124 studies to evaluate how troponin levels contributed to diagnosis, patient management and prognosis of ACS patients as well as risk stratification of patients without ACS symptoms. The results revealed that elevated cTnI or cTnT are potent predictors of mortality in CKD patients with and without suspicion of ACS and independent of the condition whether the patient is receiving dialysis or not. The authors suggested that measuring troponin levels may be reasonable for additional risk stratification. Stacy et al. [ 20 ] evaluated 23 trials where troponin levels were measured in CKD cohorts. The results revealed a need to identify optimal cut-offpoints of troponins for patients with CKD and ACS for proper risk stratification. Aligned with these conclusions is the study performed by Skadberg et al. [21]. The author measured, using hs-Tn assays, troponin levels before and after hemodialysis and found that mean values decreased during this process. Consequently, the author recommends the need to determine specific cut-off points, before and after hemodialysis, when using hs-Tn assays. Even though Twerenbold et al. [ 22 ] results were in agreement with the previous studies, they emphasized that optimal cut-offvalues should be assay-specific, isoform-specific and manufacturer-specific. In a multicenter study on 2813 patients, of which 16% had renal dysfunction, the conclusions were: (i) hs-Tn assay showed slightly lower diagnosis accuracy at presentation in CKD patients versus patients without renal dysfunction; (ii) no systematic superiority was found between hs-Tn and s-Tn assays; and (iii) hs-Tn loses specificity when comparing CKD with normal renal function patients. 3.1.2. Diabetes In diabetic patients, special emphasis goes to type 2 diabetes mellitus (T2DM) patients who are more common than type 1 diabetes mellitus (T1DM) in a 10:1 ratio. The ARIC [ 23 ] and the EXAMINE trial [ 24 ], with respectively 1500 and 3808 T2DM patients, pointed out that troponin testing using hs-Tn assays could be a good biomarker for personalized medicine. The ARIC study concluded that abnormal troponin levels can predict the CVD risk of T2DM patients 10 years in advance. The EXAMINE study found that elevated troponins can help to identify patients at extreme risk for cardiac events. The extreme risk for cardiac events is a new category identified in 2017 by the Association of Clinical Endocrinologists and American College of Endocrinology (AACE) on the Comprehensive T2D Sensors 2020,20, 5006 6 of 20 Management Algorithm. Both findings can contribute to improve the management of T2DM patients with more aggressive primary or secondary preventive interventions. Nonetheless, further studies are required to confirm this complementary valuable information. Surprisingly, meta-analyses have revealed that in most clinical settings, hs-Tn has a comparable diagnostic and prognostic performance to that of s-Tn [25]. 3.1.3. Elderly The elderly population, with increasing life expectancy, is another high-risk cohort due to comorbidities and chronic diseases. Using hs-Tn in this cohort can be misleading because the pathophysiological mechanisms resulting in cardiomyocyte injury in the aging heart are still not well-understood and troponins can be elevated due to non-cardiovascular comorbidities (e.g., sepsis, myocarditis, drug toxicity, pulmonary embolism, hypoxia and global hypoperfusion) [ 26 , 27 ]. For example, in elderly NSTEMI patients, using the uniform assay-specific 99th percentile for STEMI diagnosis, troponins were shown to have limited diagnostic capability due to reduced specificity [ 28 , 29 ]. In this context, age-adjusted cut-offvalues [ 30 , 31 ] or even algorithm-specific [ 32 ] would be desirable. Nevertheless, to establish these cut-offvalues further research studies are required to determine the trade-offbetween diagnosis efficacy and prognosis capability. 3.1.4. Heart Failure The last high-risk cohort discussed in this paper is the HF patients. This life-threatening scenario can be reached due to recurrent or big injuries resulting from a prolonged delay, from event to intervention, producing massive losses of cardiomyocytes. Even though left ventricular ejection fraction contributes to the risk stratification of HF patients, the measuring of cardiac biomarkers (e.g., troponin (cTn) and brain natriuretic peptide (BNP) in biological fluids (e.g., blood, urine and saliva) are also useful in this population for diagnosis and management purposes [ 33 , 34 ] as well as to prognosticate for mortality and need for hospital readmission [ 34 , 35 ]. The ADHERE study [ 36 ] with 65,180 patients revealed that higher troponin levels were associated with higher in-hospital mortality. In the EFFECT study [ 37 ], with 2000 patients hospitalized for HF in Ontario (Canada), it was found that a troponin value greater than 0.5 µ g/L during the first 48 h of hospitalization was a predictor of increased 1-year all-cause mortality. Other small scale studies [ 38 , 39 ] have demonstrated that elevated troponin I is associated with lower ejection fraction, higher systolic pulmonary artery pressure and increased length of hospital stay. Moreover, abnormal troponin T is a predictor of increased risk of HF readmission and mortality [ 40 , 41 ]. These associations have persisted up to 3 years from the index hospitalization. Elevated troponin values at discharge predict an increased risk of HF exacerbation, cardiac death and all-cause mortality. Another interesting study, PROTECT [ 42 ], showed that increased troponin levels in serial measurements were good predictors of rehospitalization or death at 60 days. From all the previously reviewed clinical evidence, see Table 1, the value of troponin-based diagnosis and prognosis emerges in patients with ACS or even in HF patients. However, the accuracy of troponin assays can be compromised when threshold values determined from general population are applied to high-risk patient cohorts. Establishing precise cut-offvalues for each patient subset is expensive, requires large cohorts and standardization of assays from different manufacturers. Therefore, the need for personal data is key to reduce the event-to-diagnosis-time and therefore mitigate unnecessary myocardium damage. Home-based tools can play a decisive role in this context. Sensors 2020,20, 5006 7 of 20 Table 1. Summary of the review process regarding diagnosis and prognosis of troponin in high-risk patients. Patient Cohort. Studies Key Characteristics Major Outcomes Chronic Kidney Disease (CKD) Michos E.D. et al. [19]Examined 124 studies to evaluate diagnosis and prognosis of troponins. Elevated cTnI or cTnT are potent predictors of mortality in CKD patients with and without suspicion of ACS and independent of the condition whether the patient is receiving dialysis or not. Stacy S.R. et al. [20]Evaluated 23 trials where troponin levels were measured in CKD cohorts. Identify optimal cut-offpoints of troponins for patients with CKD and ACS for proper risk stratification. Skadberg O. et al. [21] Serum samples were collected from 20 patients before and after 10 consecutive HD treatments using hs-cTnT. Need to determine specific cut-offpoints, before and after hemodialysis, when using hs-Tn assays. Twerenbold R. et al. [22]Multicenter study with 2813 patients with 16% prevalence of renal dysfunction. Hs-Tn assays showed slightly lower diagnosis accuracy at presentation in CKD patients versus patients without renal dysfunction, no systematic superiority was found between hs-Tn and s-Tn assays and hs-Tn loses specificity when comparing CKD with normal renal function patients. Diabetes (T2DM) Whelton S.P. et al. [23]ARIC trial where 1500 patients with T2DM were recruited. Troponin testing using hs-Tn assays could be a good biomarker for personalized medicine. Abnormal troponin levels can predict the CVD risk of T2DM patients 10 years in advance. Ferdinand K.C. et al. [24]EXAMINE trail where 3808 patients with T2DM were recruited. Elevated troponins can help to identify patients at extreme risk for cardiac events. This is a new category identified in 2017 by the Association of Clinical Endocrinologists and American College of Endocrinology on the Comprehensive T2D Management Algorithm. Thygesen K. et al. [25] Summary of meta-analyses. Hs-Tn have comparable diagnostic and prognostic performance as s-Tn in most clinical settings. Elderly Sedighi S.M. et al. [27] 6977 medical records aged ≥ 65 years without acute coronary events were recruited. Troponin values in geriatric population is a consequence of non-cardiovascular comorbidities. These results confirm the conclusions of Park KC et al. [26]. Reiter M. et al. [28] 1098 consecutive patients with symptoms suggestive of AMI where 37% had more than 70 years old. Elderly NSTEMI patients, using the uniform assay-specific 99th percentile for STEMI diagnosis, were shown to have limited diagnostic capability due to reduced specificity. Ichise T. et al. [29] 355 consecutive patients with mean age 66 ± 16.1 years patients attending Kanazawa University Hospital. When measuring hs-cTnT careful assessment are needed in elderly subjects. Zhang S. et al. [30] 679 geriatric inpatients without ACS. Hs-cTnT elevation caused by non-ischemic acute conditions was very common in geriatric hospitalized patients. Further studies are needed to establish age-specific 99th percentile values of hs-cTnT for elderly individuals. Sensors 2020,20, 5006 8 of 20 Table 1. Cont. Patient Cohort. Studies Key Characteristics Major Outcomes Gore M.O. et al. [31] Data included from three well characterized population-based studies: the Dallas Heart Study (DHS), the Atherosclerosis Risk in Communities (ARIC) Study and the Cardiovascular Health Study (CHS). Use of a uniform 14 ng/L cutofffor the hs-cTnT assay may lead to overdiagnosis of myocardial infarction, particularly in men and the elderly. Clinical validation is needed of new ageand sex-specific cutoffvalues for this assay. Rains M.G. et al. [32] Review paper of how different biomarkers were used to diagnose ACS in elderly population evolve. Desirable to have algorithm specific. Heart Failure (HF) Fonarow G.C. et al. [36]ADHERE study where 65,180 patients were recruited. Higher troponin levels were associated with higher in-hospital mortality. You J.J et al. [37]EFFECT study where 2000 patients hospitalized in Ontario (CANADA). Troponin value greater than 0.5 µ g/L during the first 48 h of hospitalization was a predictor of increased 1-year all-cause mortality. Parenti N. et al. [38] 99 patients discharged from the department between March and December 2002 with a HF diagnosis and samples of cTnI. Patients with acute coronary syndromes, myocarditis or renal failure were excluded. Elevated troponin I is associated with lower ejection fraction, higher systolic pulmonary artery pressure and increased length of hospital stay. Vechia L.L et al. [39] Thirty-four patients were examined. Upon admission, we measured serum levels of cTnI by conventional immunoenzymatic assay. cTnI is detected in the blood of 25% to 33% of patients with severe heart failure; its presence may help to identify a high-risk sub-group who faces very poor short-term prognosis. Del Carlo C.H. et al. [40]70 patients with chronic HF worsening that needed hospitalization were studied. Abnormal troponin T is a predictor of increased risk of HF readmission and mortality. Perna E.R. et al. [41] One hundred and eighty-four consecutive patients with ADHF were enrolled in the absence of an acute coronary syndrome. Troponin T was an independent long-term prognostic marker of morbidity and mortality and it suggests a role of biochemical risk stratification in HF. O’Connor C.M et al. [42] PROTECT study. Increased troponin levels in serial measurements were good predictors of rehospitalization or death at 60 days. cTnI: cardiac troponin isoform I, cTnT: cardiac troponin isoform T, ACS: acute coronary syndrome, hs-cTnT: high sensitive cardiac troponin isoform T, hs-Tn: high sensitive troponin assays, S-Tn: sensitive troponin assay, CVD: cardiovascular disease, NSTEMI: non-ST-segment elevation myocardial infarction, STEMI: ST-segment elevation myocardial infarction. Sensors 2020,20, 5006 9 of 20 3.2. Cost-Effectiveness Analysis of Troponin-Based Strategies Despite the relevance of the LOD of the assay or the role of having appropriate cut-offvalues, it is the cost factor that is the ultimate parameter to select the best assay for clinical implementation. In this context, a pay per assay scheme is common in the clinical laboratories. Regardless of the importance of costs especially in limited budgets like the national healthcare systems, the number of available cost-effectiveness analyses focusing on troponin-based patient management strategies are scarce and heterogenous in the scientific literature, making it difficult to establish general conclusions. Nevertheless, the reviews performed by Westwood M. et al. [ 43 ], Kip MMA. et al. [ 44 ] and St. John A. et al. [ 45 ] are a good starting point. These were complemented by other sources retrieved by the authors, see Table 2. In all of them either the incremental cost-effectiveness ratio (ICER) or the willingness to pay (WTP) indicators were used. The former is an index which allows the comparison of the cost-benefits of two possible interventions and is calculated as the cost difference between them divided by the difference in their effect measured in quality adjusted life years (QALY). The latter refers to the maximum amount an individual is willing to hand over to procure a product, service or technology. Further details of health economics are available as Supplementary Material (see Supplementary Material 2). Figure S2 included in the Supplementary Material section (Supplementary Material 2) summarizes the advantages and disadvantages of the different methods available to evaluate the willingness-to-pay indicator. Sensors 2020,20, 5006 16 of 20 References 1. Cardiovascular Diseases (CVDs). Available online: https://www.who.int/news-room/fact-sheets/detail/ cardiovascular-diseases-(cvds) (accessed on 7 April 2020). 2. L á z á r, E.; Sadek, H.A.; Bergmann, O. Cardiomyocyte Renewal in the Human Heart: Insights from the Fall-Out. Eur. Heart J. 2017,38, 2333–2342. [CrossRef] 3. Bergmann, O.; Zdunek, S.; Felker, A.; Salehpour, M.; Alkass, K.; Bernard, S.; Sjostrom, S.L.; Szewczykowska, M.; Jackowska, T.; dos Remedios, C.; et al. 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