Troponin testing in routine primary care: observations from a dynamic cohort study in the Amsterdam metropolitan area
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Ralf E. Harskamp
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Indra M. Melessen
Abstract
Objectives
Troponin testing is indicated in the diagnostic work-up of acute coronary syndrome (ACS) and incorporated in risk stratification pathways. This study aims to gain insights on the use, outcomes, and diagnostic accuracy of troponin testing in routine primary care; a setting that is understudied.
Methods
Routine data were used from the academic primary care network in the Amsterdam metropolitan area (968,433 patient records). The study population included adult patients who underwent high-sensitivity troponin I or T (hs-TnI/T) testing between 2011 and 2021. The primary outcome was the reported diagnosis and the secondary outcome was the diagnostic accuracy measured by death or ACS at 30 days.
Results
3,184 patients underwent hs-troponin testing, either with hsTNT (n=2,333) or hsTNI (n=851). Median patients’ age was 55 (44–65) years, and 62.3 % were female. Predominant symptoms were chest pain and dyspnea (56.7 %). Additional diagnostic laboratory tests were commonly performed (CRP: 47.7 %, natriuretic peptides: 25.6 %, d-dimer: 21.5 %). Most common diagnoses were musculoskeletal symptoms (21.6 %) and coronary heart disease (7.1 %; 1.1 % ACS). Troponin testing showed sensitivity and specificity of 77.8 % (60.9–89.9) and 94.3 % (93.5–95.1), respectively. Negative and positive predictive values were 99.7 (99.5–99.9) and 13.5 (11.1–16.4), and positive and negative likelihood ratios were 13.7 (10.9–17.1) and 0.24 (0.13–0.43).
Conclusions
GPs occasionally use troponin testing in very low-risk patients, often as part of a multi-marker rule-out strategy. The diagnostic characteristics of troponin tests, while promising, warrant prospective validation and implementation to facilitate appropriate use.
Introduction
Troponin testing is part of the diagnostic work-up in patients with acute chest pain to rule out an acute myocardial infarction (AMI), and incorporated in risk stratification pathways in an emergency care setting [1, 2]. In prehospital settings, troponin testing may serve a similar purpose, but there are practical concerns, such as direct access to troponin testing, as well as possible inappropriate use and safety [3]. The introduction of point-of-care (POC) troponin testing has rekindled interest in prehospital settings, with recent studies suggesting that equipping ambulances with POC troponin (embedded in a risk stratification tool) could reliably identify low-risk patients who could be left at home safely; hereby reducing the burden on secondary care and reduce healthcare costs [4, 5]. In countries where GPs fulfill a role as first point-of-contact for urgent care, these developments are of particular interest, as a similar approach could also work in primary care. From clinical experience, we know that GPs do already order troponin tests in their patients [6]. An in-depth, systematic evaluation is warranted and we therefore set out to study troponin use in primary care using routine care data from a large GP network in the Amsterdam metropolitan area. We aimed to understand in which patients GPs order troponin tests, what diagnoses and outcomes are subsequently reported, and finally to evaluate the diagnostic accuracy of troponin testing based on these reported outcomes.
Methods
We reported this study in accordance with the ‘Standards for Reporting of Diagnostic Accuracy Studies’ (STARD) 2015 statement [7]. Moreover, since we relied on routinely-collected health data, we also used elements of the ‘Reporting of studies conducted using observational routinely-collected health data’ (RECORD) statement [8]. The study protocol was approved by our institution’s Medical Ethics Review Committee (W23_073#23.097).
Study design and setting
We performed our analyses on a cohort of patients registered with GPs affiliated with the Academic General Practice Network of the Amsterdam UMC in the Amsterdam metropolitan area, The Netherlands. In the Netherlands, virtually all inhabitants are enlisted at a local GP, who is the gatekeeper to specialist care and holds the responsibility to maintain an up-to-date electronic health record. Patients in network-affiliated practices have the option to refuse to share their data, but this is rarely noted by the network (<0.5 %). The dataset that we had at our disposal was restricted to those who underwent troponin testing and included patient encounters, demographic data, laboratory findings, a list of episodes (i.e. recurring symptoms or conditions), and vital status. Each encounter in the database is coded using International Classification of Primary Care-1 (ICPC-1) codes. Medication in the database is coded by Anatomical Therapeutic Chemical (ATC) code. Laboratory findings are coded according to Nederlands Huisartsen Genootschap (NHG) laboratory codes. Data were collected, processed and analyzed using a highly secure, digital research environment, MyDRE. More on this platform can be found at: https://www.amsterdamumc.org/en/research-support/mydre-1.htm.
Study population
For this analysis we included all patients ≥18 years in whom a troponin test was performed and recorded in the patients’ electronic health record during the observation window of January 1st 2011 through December 31st 2021. We excluded cases where the troponin test result was not adequately recorded, due to lacking the troponin subtype, the test result and/or a measurement unit. Patients with an eligible troponin test were included once, using only the first recorded troponin test on those with multiple tests during the observation window. Medical history and medication use for baseline characteristics were assessed at the time of first troponin recording.
Troponin tests
The troponin subtype (hsTNT, hsTNI) that the treating physician ordered, depended on which specific assay was available through the laboratory. Therefore, troponin type variation, to a large degree, reflects regional differences in laboratory assays, with inter-assay variability over time influenced by laboratories’ decision to switch from one assay to another. Troponin results (and 99th percentile upper-reference limits) are reported back and integrated into the patient’s primary care electronic health record.
Outcomes of interest
We reported the final diagnosis, defined as the reported diagnostic code at 30 days after the troponin test. For the evaluation of diagnostic accuracy we used a clinical reference standard, which consisted of a composite endpoint of the occurrence of either death, myocardial infarction, or unstable angina, occurring within 30 days after the troponin test.
Statistical analyses
We used descriptive statistics to characterize the study population, with median and interquartile range for continuous variables and number and percentage for categorical variables. We expressed diagnostic test characteristics for each troponin subtype at its predefined optimal threshold in terms of safety [(99th percentile) upper reference limits of the specific troponin assay], and provided sensitivity, specificity, accuracy, positive and negative likelihood ratios (LR+, LR−), positive and negative predictive values (PPV/NPV), with 95 % confidence intervals (CI). For this analysis we only included troponin measurements from assays with verifiable units. Data were analyzed using Python and MedCalc software.
Results
Baseline characteristics
During the observation period, a total of 3,184 patients underwent hs-troponin testing through routine primary care, which represents <0.5 % of enlisted patients. The tests involved hsTNT in the majority of patients (n=2,333; 73.3 %). All involved tests were analyzed at a central laboratory, and no point-of-care-testing (POCT) was recorded. Patients’ baseline characteristics are shown in Table 1. Overall, the median age was 55 (44–65) years, and 62.3 % were female. Risk factors for cardiovascular disease were common, of which hypertension had the highest prevalence. Symptomatology was diverse, with chest pain as the predominant primary symptom, followed by dyspnea. Additional tests such as d-dimer, CRP and natriuretic peptides were often performed.
Patient and symptom characteristics of patients who underwent troponin testing (n=3,184).
| Patient characteristics | hsTnT (n=2,333) | hsTnI (n=851) | All patients (n=3,184) |
|---|---|---|---|
| Age, years, median (IQR) | 54 (44–64) | 55 (45–68) | 55 (44–65) |
| Male, % (n) | 38.6 (900) | 35.4 (301) | 37.7 (1,201) |
| Prior MI, % (n) | 6.5 (151) | 3.9 (33) | 5.8 (184) |
| Atrial fibrillation, % (n) | 3.5 (81) | 3.3 (28) | 3.4 (109) |
| Valvular heart disease, % (n) | 2.5 (58) | 2.5 (21) | 2.5 (79) |
| Hypertension, % (n) | 25.5 (595) | 26.6 (226) | 25.8 (821) |
| Chronic obstructive pulmonary disease, % (n) | 5.7 (133) | 6.6 (56) | 5.9 (189) |
| Diabetes, % (n) | 11.0 (256) | 11.4 (97) | 11.1 (353) |
| Chronic kidney disease, % (n) | 3.4 (80) | 4.7 (40) | 3.8 (120) |
| Presenting symptom | |||
| Chest pain, % (n) | 45.6 (1,064) | 47.1 (401) | 46.0 (1465) |
| Dyspnea, % (n) | 10.3 (241) | 11.6 (99) | 10.7 (340) |
| Fatigue, % (n) | 6.9 (162) | 7.3 (62) | 7.0 (224) |
| Palpitations, % (n) | 5.2 (122) | 3.9 (33) | 4.9 (155) |
| Dizziness, % (n) | 1.7 (40) | 2.2 (19) | 1.9 (59) |
| Syncope, % (n) | 1.4 (32) | 1.1 (9) | 1.3 (41) |
| Edema, % (n) | 1.1 (25) | 1.2 (10) | 1.1 (35) |
| Nausea, % (n) | 0.9 (20) | 1.4 (12) | 1.0 (32) |
| Lightheadedness, % (n) | 0.4 (9) | 0.9 (8) | 0.5 (17) |
| Other, % (n) | 26.5 (618) | 23.3 (198) | 25.6 (816) |
| Other diagnostic tests | |||
| BNP/NT-proBNP, % (n) | 25.2 (588) | 26.7 (227) | 25.6 (815) |
| D-dimer, % (n) | 21.0 (490) | 22.7 (193) | 21.5 (683) |
| CRP, % (n) | 45.8 (1,069) | 52.8 (449) | 47.7 (1,518) |
Clinical outcomes and diagnoses
The composite of 30 days mortality, AMI, or unstable angina occurred in 36 patients (1.1 %). Of those patients, there was one fatal case, of probable cardiovascular causes. Table 2 lists the diagnoses in patients following troponin testing. The most common underlying cause was related to a musculoskeletal origin (21.6 %). Coronary heart disease was the second most common cause (7.1 %), of which ACS was reported in 1.1 % of cases. Pulmonary and gastrointestinal causes were also common (6.6 and 4.3 % respectively).
Diagnoses after troponin testing/contact (n=3,184).
| Diagnosis | % (n) |
|---|---|
| Chest wall/musculoskeletal symptoms | 21.6 (687) |
| Coronary heart diseasea | 7.1 (226) |
| Pulmonary cause | 6.6 (209) |
| Gastrointestinal cause | 4.3 (136) |
| Fatigue | 2.9 (92) |
| Palpitations | 3.0 (94) |
| Symptom diagnosis (arm/neck/back) | 2.7 (86) |
| Anxiety/stress/hyperventilation | 2.0 (64) |
| Hypertension | 2.0 (65) |
| Unexplained/no disease | 1.5 (49) |
| Dizziness/syncope | 1.4 (45) |
| Anemia | 0.9 (30) |
| Thyroid disorder | 0.7 (22) |
| Diabetes mellitus | 0.6 (18) |
| Costochondritis | 0.6 (18) |
| Atrial fibrillation | 0.5 (17) |
| Kidney disease | 0.5 (17) |
| Heart failure | 0.5 (16) |
| Pulmonary embolism | 0.5 (16) |
| Other diagnosisb | 39.4 (1,256) |
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aIncluding 1.1 % (n=36) cases of acute coronary syndrome; ball other diagnoses occurred less than 0.5 % of cases.
Diagnostic performance of troponin tests
The diagnostic characteristics of the troponin tests are listed in Table 3. Sensitivity and specificity of hs-troponin testing (irrespective of assay used) were 77.8 and 94.3 %, respectively. In this very low risk population, this resulted in a high negative predictive value (99.7 %) and low positive predictive value (13.5 %). Still, a positive troponin test result increased the likelihood of ACS by a factor 13–14. We found no difference in diagnostic performance between hsTNT and hsTNI assays.
Diagnostic accuracy for standardized cut-off values for troponin tests for composite of death, MI or unstable angina at 30 days follow-up.
| Sensitivity | Specificity | Accuracy, % | PPV, % | NPV, % | LR+ | LR− | |
|---|---|---|---|---|---|---|---|
| Overall (n=3,184) | 77.8 (60.9–89.9) | 94.3 (93.5–95.1) | 94.1 (93.3–94.9) | 13.5 (11.1–16.4) | 99.7 (99.5–99.9) | 13.7 (10.9–17.1) | 0.24 (0.13–0.43) |
| hsTnT (n=2,333) | 78.6 (59.1–91.7) | 94.2 (93.2–95.1) | 94.0 (93.0–94.9) | 14.1 (11.3–17.5) | 99.7 (99.4–99.9) | 13.5 (10.5–17.4) | 0.23 (0.11–0.46) |
| hsTnI (n=851) | 75.0 (34.9–96.8) | 94.7 (92.9–96.1) | 94.5 (92.7–95.9) | 11.8 (7.6–17.9) | 99.8 (99.2–99.9) | 14.1 (8.6–23.0) | 0.26 (0.08–0.88) |
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Detailed statistics with full 2×2 contingency tables per troponin subtype are displayed in Supplemental Table S1.
A random sample for in-depth analysis
To further illustrate the diagnostic use in routine primary care practice, we included a supplemental file (Table S2), which provides a detailed description of a random sample of 50 patients who underwent troponin testing in 2021. This sample illustrates, that the vast majority of patients involved those with a low a priori ACS risk, and who presented with symptoms that usually lasted for days, often of atypical or non-specific nature. In this patient sample, 30 % (n=15) was referred for secondary care evaluation, including two ACS cases (4 %). Among referred patients, were all seven patients (14 %) with an abnormal troponin result. Of these patients with a positive troponin test result, one case involved NSTEMI, the other cases involved relevant other outcomes, including HF, cardiac arrhythmias and pulmonary embolism.
Discussion
Main findings
Symptoms with a possible cardiac origin, such as chest pain, often present a clinical challenge. In acute secondary care, risk stratification tools that include routine troponin testing are standard of care in such patients. In primary care, the additional value of troponin testing is a subject of ongoing debate. On this background, our study provides a number of insights. First, our study shows that GPs occasionally use troponin testing for diagnostic purposes, and are performed in a (very) low risk patient category, as reflected by low event rates. Second, we found that troponin testing is performed for a multitude of symptoms (not restricted to acute chest pain only), often as part of a multiple rule-out strategy or multi-marker risk stratification approach, given that simultaneous measurements of d-dimer, natriuretic peptides, and CRP, were common. Finally, the diagnostic test characteristics of the current standard of high-sensitivity troponin assays are adequate in terms of safety, and an abnormal test result increased the likelihood of ACS fourteenth-fold.
Strengths and limitations
Our study relied on routine care data from a large number of patients and GPs and is hereby likely reflective (in terms of representativeness and generalizability) of current primary care practice in the Amsterdam metropolitan area. Moreover, the data are of sufficient granularity in terms of consultation and laboratory findings, structured diagnostic codes, as well as follow-up data. Important for the latter is that each specialist consultation or hospitalization (and thus each event and diagnosis) is reported back to the patient’s GP and recorded in this patient’s electronic health record. The limitations are also largely related to the nature of retrospectively collected, routine care data, which are not intended for research purposes. Whilst a retrospective study is informative for descriptive purposes on how troponin is used, there are a number of biases, most notably selection and verification bias, when it comes to the evaluation of diagnostic test characteristics, the second aim of our study. A prospective study of consecutive patients in a pre-defined cohort with detailed characteristics would be better positioned to provide definitive answers on diagnostic test characteristics. Another limitation is that we relied on diagnostic coding for clinical outcomes, and thus relied on physician reported outcomes. Finally, it is uncertain whether our findings can be generalized beyond a Dutch primary care setting. In fact, it is likely that differences in health care systems, guidelines and patient demographics affect the actual use of troponin testing in primary care, as well as the diagnostic performance.
Troponin testing in primary care: what do guidelines tell us?
What is considered appropriate use of troponin testing in primary care varies among countries. The Dutch GP guideline on ACS does not support a troponin testing strategy in the hands of GPs and propagates a low referral threshold based on clinical judgement [3]. As our study demonstrates, Dutch GPs do not abstain from troponin testing. Instead, their diagnostic management is more in line with pragmatic statements on appropriate use in primary care from other countries (i.e. Australia and the United Kingdom), which state that troponin testing in primary care could be used when restricted to low-risk patients in which ACS is considered and in whom the last episode was more than 24–72 h previously [9], [10], [11].
Prior studies on the use of troponin tests in primary care
To our knowledge, our study is the first to present these data for contemporary Dutch general practice. However, Dutch GPs are certainly not the only ones using troponin tests in Europe. Several years ago, a survey among Swiss GPs found that three-quarters of responders sometimes apply troponin testing for the evaluation of acute chest pain [12]. An audit from a central laboratory in New Zealand in 2010 showed that troponin tests were performed occasionally (total of 2,666 patients in a large urban community) and the test was abnormal in 1 out of 12 patients. They concluded that troponin served as an appropriate triage test in patients in need for admission, not only for ACS (diagnosed in half of those with positive test results) but also for other urgent causes that may cause troponin release (such as heart failure) [13]. In addition, another study from New Zealand found that when GPs made serum troponin requests, the time between initial onset of symptoms and troponin testing was distributed with peaks at 7–12 h and 3.5 days [14]. This suggests that there is a clinical need for those acute symptoms, as well as for those who present later and/or possibly with other less specific symptoms. In our study we also found considerable variability in time between symptom onset and troponin testing, as well as the type of symptom, which warrants further exploration [14]. Finally, our study illustrates that GPs often perform other diagnostic tests alongside with troponin testing. To our knowledge, this concept of a multi-marker diagnostic strategy has not been extensively studied before. There was however report of multiple rule-out testing by GPs in a study in which a POCT diagnostic device was introduced which allowed them to analyze troponin, NT-proBNP and d-dimer in the GP practice [15]. Despite the paucity of other data, it is likely that the practice of multiple testing is more common, and serves further study.
Diagnostic test characteristics of hs-troponin assays in primary care
A hallmark study is the OUT-ACS cohort, in which 1,711 patients were prospectively enrolled with acute non-specific chest pain in a large-scale primary care emergency clinic in Oslo, Norway [16]. The authors found that a diagnostic strategy using the 0/1 h algorithm of the European Society of Cardiology is safe and efficient for accelerated assessment in a low-risk primary care setting. In their study, the algorithm assigned three-quarters of patients to the rule-out group (i.e. not necessitating evaluation in secondary care) and the negative predictive value was 99.9 %. The latter is comparable with our findings, in which both hs-troponin assays had negative predictive values of 99.7–99.8 %. When looking strictly at sensitivity, the performance of hs-troponin in OUT-ACS was somewhat higher than the 75–79 % that we found, a subject that warrants further exploration. A possible explanation may be the more restricted patient population that was used in OUT-ACS, namely acute non-specific chest pain.
Future directions
The role of troponin testing in primary care is a subject of ongoing research. Currently, there are two ongoing clinical trials (POB-HELP and HEART-GP), which assess the diagnostic test characteristics and impact of troponin testing in day-time and out-of-hours primary care settings [17, 18]. The main advantage of access to troponin testing is that it helps to early identify cases of AMI that would otherwise perhaps have been missed. At the same time it also helps to rule out the possibility of AMI. This in turn may reduce the burden of unnecessary referrals to emergency departments, in a similar fashion as was recently demonstrated in an ambulance study [4]. Thus far most troponin tests were performed at a central laboratory, which presents a practical hurdle and thus selective use in primary care. Due to technological advances, we anticipate that in the near future the use of POCTs for high-sensitivity troponin will lower the threshold for performing diagnostic testing in primary care settings, and hereby result in a paradigm shift. Moreover, simulation models suggest that bringing POCT troponin tests to primary care will be cost-saving; as it will decrease the referral rate in non-ACS patients by 6.6 % (31.9 vs. 38.5 %) and reduce costs (≈€77 per patient) [19, 20]. However, improved access to troponin testing also brings about a number of fundamental questions. First, while troponin is highly sensitive for acute MI, it is not a very specific marker; troponin levels may also be elevated in other conditions, some of those conditions warrant direct medical attention (such as pulmonary embolism), while others, such as chronic kidney disease, do not. Such false-positive results can lead to an increased burden on secondary care, with unnecessary testing and procedures, which can increase healthcare costs and cause harm to patients. Another fundamental discussion is whether a single time-point measurement is sufficient, and if so, whether this requires different thresholds based on patient characteristics and symptom onset. These questions also circle back to whether we should implement troponin testing as a stand-alone tool in conjunction with clinical gestalt or instead embed troponin testing as part of a clinical risk stratification tool, as is currently being done in secondary care settings. A number of secondary care developed scores (most notably HEART and EDACS) are currently evaluated in primary care settings. In New Zealand, the use of the EDACS rule was found to be safe and effective in excluding MACEs in a mixed setting of GP practices, urgent care clinics and rural hospitals [21, 22]. For the HEART score and modified versions (incorporating the GPs ‘gut feeling’ or intuition) there are also promising initial results [23, 24]. However, it remains to be seen whether the HEART score will outperform clinical judgement plus hs-troponin testing, in terms of safety and efficiency. An exploratory analysis from OUT-ACS on this matter [25], showed neutral results, warranting further study. However, the biggest question of all is what balance of false negative and false positive results will be considered acceptable? Prior exploratory work in this field suggests that GPs and ED physicians will accept a miss rate of <1 % [15, 26]. This work requires confirmation, with future research focusing on establishing consensus among relevant stakeholders and formulating clear recommendations for the use of troponin testing in primary care, followed by consensus-based affirmation in future guidelines.
Conclusions
Our study provides a snapshot on troponin testing in an urban, routine primary care setting. Overall, troponin testing was performed by GPs in very low-risk patients presenting with various symptoms, often as part of a multi-marker rule-out strategy along with natriuretic peptides, d-dimer and CRP. An exploratory analysis on the diagnostic characteristics of troponin tests suggests that high-sensitivity assays are safe in these very low-risk patients, with high negative predictive values. These findings provide valuable insights into the use of troponin testing in primary care and support further study on exploring its role in ruling out ACS, and myocardial infarction in particular.
Funding source: Hartstichting/Dutch Heart Foundation
Award Identifier / Grant number: Dekker Sr Clinical Scientist 2022
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Research ethics: The study protocol was approved by our institution’s Medical Ethics Review Committee (Decision: W23_073#23.097).
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Informed consent: Not applicable.
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Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission. Authorship roles (according to CRediT): REH: conceptualization, funding acquisition, co-writing original draft, review&editing and supervision; IMM: conceptualization, investigation, co-writing original draft, review & editing: AM: conceptualization, review&editing; LDC: data curation, formal analysis, methodology, software, review & editing; WPJDE: methodology, validation, review&editing; JCLH: methodology, review&editing, supervision.
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Competing interests: The authors state no conflict of interest.
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Research funding: This study was funded by the Dutch Heart Foundation (Dekker Sr Clinical Scientist 2022).
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Data availability: Aggregate can be obtained on request from the corresponding author.
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/dx-2023-0183).
© 2024 the author(s), published by De Gruyter, Berlin/Boston
This work is licensed under the Creative Commons Attribution 4.0 International License.
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