A new way of stratifying acute chest pain: the clinical – chemistry score

Milocco M., Colella N., Corbi D., De Matteis N., Pedroni G.

Emergency Department, Policlinico Umberto I, “Sapienza” University, Rome


In our study, carried out in the Emergency Department of the Policlinico Umberto I in Rome, we tested a new diagnostic score: The Clinical – Chemistry Score (CCS) (2018).
We selected 143 patients with acute chest pain without signs of STEMI, analyzing the data acquired from the first value of high sensitivity cardiac troponin, from the result obtained from the scores that we selected and from the diagnosis and outcome data. We took the HEART score as a reference and comparison to the CCS.
Comparing the two scores, we have demonstrated the validity of the CCS (76% concordance index), the non-inferiority in the “rule-in” and the superiority of the CCS in the “rule-out”.
In our study we have for the first time highlighted the capability of CCS compared to the HEART score to reduce patients in the so-called gray zone, bringing patients to the “extremes” of the risk classification.


Clinical – Chemistry Score (CCS) – Acute Chest Pain – Stratification of Risk


Acute chest pain management is one of the greatest challenges of the Emergency Departments (ED) worldwide. [1]
Chest pain is one of the most common and complex symptoms for which patients approach to the Emergency Departments; according to some published studies, it causes 5-9% [2] of the total accesses.
Several documents in literature, both at national and international level, have deal over years with the problem of risk stratification in patients that show up to ED with chest pain, proposing a series of implementation strategies. [3,4,5,6,7,8,9,10]
However, this doesn’t lead to data that allow us to have in 100% of cases a correct diagnosis and a short time of observation of the patients “rule-out” for ACS (Acute Coronary Syndrome).
This situation leads to inappropriate hospitalizations, up to 25-50% of patients presenting with chest pain and to inappropriate discharges of 2-8% of patients, with important forensic implications [11] (the erroneous discharge of patients with MI (Myocardial Infarction) accounts for 20% of the forensic expenses against the doctors in the USA Emergency Departments [ 12]). Also give rise to a prolongation of the examination times with a consequent increase in the number of patients under observation and the reduction of the reception capacity of the ED.
For these reasons, the research has focused on new strategies employing both the use of increasingly faster biochemical markers (hs-cTn, High-sensitivity Cardiac Troponin) and the use of diagnostic algorithms and their implementation with scores that define the probability of risk.
The essential concept that drives the medical research to compare the value of troponin with other elements is that troponins do not express only the damage from MI but, in general, they express myocardial damage, even as from different causes. The diagnostic scores rise to support the clinical picture, the EKG and the troponins so to be helpful for a correct classification of the patient.
The Clinical – Chemistry Score is a diagnostic score develop by a Canadian medical team in collaboration with German, Australian and New Zealand doctors and whose primary results were published on 20 August 2018. [13]
The score was studied on 4245 patients in the ED of Hamilton (Canada), Hamburg (Germany), Brisbane (Australia) and Christchurch (New Zealand) and the first results showed a greater sensitivity and specificity in the stratification “rule-in / rule- out”, compared to the use of the only ultrasensitive troponins.
In this study we examine the CCS as a new score to be tested in the ED of Policlinico Umberto I in Rome, make a comparison with the HEART score and test its validity.
The data collected in this study constitute the first experimentation in Italy of this new score.

Case Report

This study was born in the context of the clinical investigation promoted by the Istituto Superiore di Sanità ” “Valutazione clinica e farmaco-economica delle metodiche di dosaggio per la TROponina CARdiaca per la diagnosi di NSTEMI nel setting della pratica clinica della Medicina di Pronto Soccorso nel territorio nazionale – TROCAR 2017””, which takes place across the country in 12 centers.
Our study was carried out at the ED of Policlinico Umberto I in Rome.
The interval of the study was from 23 March 2018 to 31 December 2018; the study was approved by the Ethics Committee of the Policlinico on March 19, 2018, ref. EC 4877.
Patients admitted to the ED of the Policlinico Umberto I of Rome were selected with a symptom of “chest pain” which, at the entrance examinations, showed the characteristics of a thoracic pain of suspected cardiac origin (or anginal equivalent).
A fundamental element in admission is the negativity of the electrocardiographic examination for ACS-STE (elevation of the ST segment; new-onset of left or right branch block).
The inclusion and exclusion criteria for the admission of patients and the evaluation of the scores are those of the TROCAR study protocol:
Inclusion criteria: 
  • Both sexes
  • Age³18 years
  • At least one determination of cardiac troponin
  • Informed and written consent
  • Chest pain (or angina pain) of suspected cardiac origin and negative EKG for ACS – STE as normal EKG, non-diagnostic / nonspecific EKG or ECG with other ischemic changes (negative T-waves or ST-segment depression).
Exclusion criteria:
  • Refusal to provide informed consent;
  • ST segment elevation to the EKG;
  • Pregnancy or breastfeeding;
  • Any other clinical condition not judged by the investigator compatible with participation in the TROCAR study.
Once we had obtained the informed and written consent and received from the laboratory the first data of the blood exams (troponins, glycaemia, creatinine), we calculated the diagnostic scores (HEART score and CCS).
The observation of the patients continued according to the guidelines currently in force, with the 0-3H or 0-6H algorithm in relation to the stratification risk of the patient and to his/her clinical conditions.
In latter times, were collected data regarding the outcomes, from the ED files or from wards of admission files.
Subsequently, through a retrospective analysis, was compared the stratification of the risk with whether or not hospitalization.
After obtaining all the data concerning the patient, especially patient’s outcome both as regards diagnostic and operation, was carried out the division of the patients into several groups, in relation to the CCS-outcomes value and then CCS-HEART comparison score-outcomes.
In each group, and in each category, were evaluated the real positive and true negative patients and the percentages of false positive and false negative.
The first group was created to understand the validity of the CCS score and the patients were divided into: patients with CCS 4-5 score (HIGH risk); patients with CCS 3 score (INTERMEDIATE risk); patients with CCS 1-2 score (LOW risk). 
The second group was created on the stratification given by the HEART score: patients with HEART score 7-10 (HIGH risk); patients with a HEART score 4-6 score (INTERMEDIATE risk); Patients with a HEART score 0-3 score (LOW risk).
The third group placed the ACS + / ACS – diagnosis in relation to the calculation of the CCS and the HEART score.
The patients were divided into:
  1. HIGH risk patients to CCS (4-5 pt.) and HEART score (7-10 pt.) and ACS +;
  2. HIGH risk patients to CCS and HEART score and ACS -;
  3. HIGH risk patients to CCS and LOW / INTERMEDIATE risk to HEART score and ACS +;
  4. LOW/ INTERMEDIATE risk patients to CCS and HIGH risk to HEART score and ACS +;
  5. LOW/ INTERMEDIATE risk patients to CCS and HEART score and ACS +;
  6. LOW/ INTERMEDIATE risk patients risk to CCS and HEART score and ACS -.                      
In this investigation, were considered “rule-in” patient anyone who the clinical suspicion of ACS was confirmed by outcome in relation to the diagnosis, the value of all the instruments (CCS, HEART score) and, in a retrospective manner, by the outcomes of angiography and files from hospitalization departments.
Were considered “rule-out” all those patients who, for clinic and test exams:
  • discharged at home, at affiliated and / or ambulatory facilities for further investigations;
  • hospitalized with ACS – diagnosis;
  • performed coronarography that excluded the diagnosis of ACS.
Patients were re-contacted at 30±10 days and asked to return to the DEA clinics for a follow-up visit to assess the reliability of risk stratification with the scores that we used. If it wasn’t possible to visit the patient, it has been done a telephone follow-up.
In all patients was assessed the incidence of adverse cardiovascular events (death, ACS, other major event).


Were recruited 143 patients from 23 March 2018 to 31 December 2018 with thoracic pain of suspected cardiac origin (or anginal equivalent).
The analysis of the data began comparing the patients with the score obtained with the CCS, with the HEART score and finally with the outcome in relation to the diagnosis (ACS + / ACS-).
Starting from this first element we obtained data concerning the outcomes of the patients compared to the diagnosis: 39 patients with ACS + diagnosis; 40 patients with ACS – diagnosis and hospitalized; 57 patients with ACS – diagnosis and discharged; 7 patients whose data concerning the diagnosis are unavailable.
The population recruited was subdivided into patients with troponin above or below the cut-off value according to benchmark values of ED laboratory of Policlinico Umberto I of Rome (0.014 mg / L): 53 patients with troponin at T0 above the cut-off value; 90 patients with troponin at T0 below the cut-off value.
Starting from these two categories examined was evaluated the relationship between troponin and diagnosis of ACS to assess the diagnostic power of troponin.
The positive or negative value of troponin at T0 was correlated with the ACS + / ACS – diagnosis: 31 patients had ACS + with hs-cTn +; 8 patients had ACS + with hs-cTn -; 22 patients had ACS – with hs-cTn +; 75 patients had ACS – with hs-cTn -.
These data show how the value of troponin alone lead to: 22 patients false positives; 8 false negatives.
We proceeded to relate the value of the HEART score with the outcomes in relation to the diagnosis (fig.1): 
  • 40 patients with LOW risk to HEART score and ACS -;
  • 2 patients with LOW risk to HEART score and ACS +;
  • 48 patients with INTERMEDIATE to HEART score and ACS -;
  • 14 patients with INTERMEDIATE to HEART score and ACS +;
  • 23 patients with HIGH risk to HEART score and ACS +;
  • 9 patients with HIGH risk to HEART score and ACS -.

Figure 1 – Comparison between HEART score and outcome related to diagnosis

Thereafter was evaluated the Clinical – Chemistry Score.We initially proceeded analyzing the stratification risk according to CCS for patients diagnosed with ACS.The data point out (fig. 2): 
  • 69 patients with LOW risk to CCS and ACS -;
  • 4 patients with LOW risk to CCS and ACS +;
  • 17 patients with INTERMEDIATE to CCS and ACS -;
  • 9 patients with INTERMEDIATE to CCS and ACS +;
  • 26 patients with HIGH risk to CCS and ACS +;
  • 11 patients with HIGH risk to CCS and ACS -.

Figure 1 – Comparison between CCS and outcome related to diagnosis

Then was evaluated the true and false positives in relation to the HIGH risk to CCS, so in 37 patients there was: 26 patients with CCS + and ACS +; 3 patients with a score of 5 (CCS +) and ACS-; 8 patients with a score of 4 (CCS +) and ACS -. A further analysis was performed on patients with a score of 3 to CCS (INTERMEDIATE risk): 9 patients were ACS +; 17 patients were ACS -.
Finally, we proceeded to analyze the “rule-out” data, by relating patients at LOW risk to CCS (0-2 pt.) with diagnosis and possible hospitalization regimens:
  • 14 patients with a score of 0 to CCS, which 12 discharged and 2 hospitalized (chest pain of unknow cause);
  • 29 patients with score of 1 to CCS, which 22 discharged and 7 hospitalized (chest pain of unknow cause);
  • 30 patients with a score of 2 to CCS, including 15 discharges, 11 hospitalizations (chest pain of unknow cause) and 4 patients diagnosed with ACS +.
Then we analyzed the data with the double entry table to observe the statistical results: we considered the patient CCS + the patient who had a score of 3-4-5 to CCS while was considered patient CCS – who had a CCS score of 0-1-2.
So, analyzing the data of all patients we had: 35 ACS + /CCS +; 4 ACS + /CCS -; 28 ACS – /CCS +; 69 ACS – /CCS -.
The consequential results are:
  • CCS sensitivity: 0.9 (IC95% 0.82-0.98);
  • CCS specificity: 0.71 (IC95% 0.62-0.79);
  • Positive predictive Value (PPV): 0.56 (IC95% 0.438-0.682);
  • Negative predictive value (NPV): 0.95 (IC95% 0.902-0.998);
  • Validity of the test: 0.76.
Within these first data, patients with a score of 3 (INTERMEDIATE risk) were considered CCS +, as occurs within the HEART score protocol for patients with a score of 4-6.However, considering the INTERMEDIATE risk as a gray area, we wanted to observe the variations in the results if we leave out patients with a score of 3 to CCS. Therefore, the double entry table show this data: 26 ACS + /CCS +; 4 ACS + /CCS-; 11 ACS – /CCS +; 69 ACS – / CCS-
The consequential results are:
  • Sensitivity: 0.86 (IC95% 0.736-0.984);
  • Specificity: 0.86 (IC95% 0.799-0.921);
  • Positive Predictive Value (PPV): 0.7 (IC95% 0.562-0.838);
  • Negative Predictive Value (NPV: 0.95 (IC95% 0.902-0.998).
  • Validity of the test: 0.86.


The data in our results allow for further consideration on the questions agreed upon and can also be useful for observations concern health economics. The use of tools such as scores allows stratification of the risk that can direct the ED doctor to select the patient who needs in-depth diagnostic procedures in hospital and who needs it in the outpatient setting. [14].
This can be an important resource to avoid overcrowding of the ED or wards.
We have first observed how the troponin alone cannot be a parameter to diagnose. [15, 16]
Currently, the results of troponin within the evaluation of acute chest pain are overrated and we tend to use them as unique discrimination: instead the data obtained show us that troponin alone cannot make ACS + / ACS – diagnosis.
In fact, observing the only value of troponin, we found the presence of 22 false positive and 8 false negative.
The first consideration concerns the 8 patients whose initial value was below the cut-off: the troponin result alone could have generated an important error in their evaluation in fact, of these, 5 required stents via percutaneous coronary intervention and 2 underwent on cardiac surgery for major coronary stenosis.
Could be made considerations on health economics for the 22 patients with an initial value of troponin above the cut-off, but whose diagnosis was ACS -. If we are going to evaluate retrospectively medical records and any treatments or hospitalizations which these patients have undergo, we will see that there has been an overestimation of the risk.
All this validates the premise that troponin alone cannot be diagnostic and must be supported by other instruments.
The next observation was on the diagnostic scores.
According to the literature the HEART score is able to realize the stratification of risk [17,18,19,20] better than other scores.
Because it’s also being already validated and used in the common clinical practice, it was the guide for stratification of risk within our study and, subsequently, term of report to test the new CCS score.
Comparing the scores obtained by the HEART score we can observe how the number of false negatives (patient with LOW risk stratification but with diagnosis of ACS +) is reduced (2 false negative for HEART score against 8 false negatives with the only troponin).
These results confirm the usefulness of the scores.          
Then we focused on the Clinical-Chemistry-Score. This is an innovation in medical practice because the first results were published only in August 2018. This score correlates the highly sensitive troponin at 0h (the first troponin sample at the time of the patient’s visit) the estimated renal clearance (through the CKD-EPI formula) [21] and the value of blood glucose [22,23,24], assigning a score to each of these values, until reaching a maximum total score of 5. Risk stratification within CCS is: 0-2 points LOW-risk patients; 3 points INTERMEDIATE risk; 4-5 points HIGH risk. Furthermore, has never been carried out in Italy the testing of this score. For this reason, in addition to its validation in practice, we also wanted to see if this score was applicable to the evaluation in our healthcare situation.  
The results show that the CCS has indicated as patients with HIGH / INTERMEDIATE risk 35 subjects of the 39 with ACS +. 
False positive data indicate that only 11 patients out of 143 were wrongly indicated as HIGH risk; as regards false negatives, even here the percentage was low with 4 patients out of 143. 
It should be considered that patients with LOW risk and positive diagnosis for ACS presented a clinical picture difficult to interpret, so much so that applying other scores of common practices were framed as patients at risk LOW / INTERMEDIATE. 
We identified that patients with a score of 3 to CCS (INTERMEDIATE risk) are placed in a gray area in which we do not have a relationship between ACS + / ACS- patients to define it as a “rule-in” or “rule-out” category (17 patients with a negative diagnosis for ACS versus 9 with a positive diagnosis). In data analysis, however, it was decided to consider patients at INTERMEDIATE risk as equivalent to a HIGH risk (CCS +), as is the case for patients with 4-6 points in the HEART score protocol. That’s because we are faced with patients who do not have a low / zero risk of developing an acute event. In fact, they present a lower probability than patients at HIGH risk, but not tending towards zero as for LOW-risk patients.
The subsequent analysis of the data made excluding the patients with score 3 shows even more this gray area, in fact despite the sensitivity decreases (from 0.9 to 0.86) both specificity and positive predictive value increase (specificity from 0.71 to 0.86; PPV from 0.56 to 0.7). The impact on the negative predictive value (0.95) is indifferent. 
The gray area remains subject of discussion in the context of risk stratification [25,26,27] but plays a minimal role within our population (26 out of 143 patients). The most important data on CCS remain its ability to reduce the number of patients in the gray zone and to increase extremizations, which is a valuable aid in decision-making in the ED. 
In order to obtain more data on this new score, was made a comparison with the HEART score.
The first important data concerns the correlation index between the two tests, namely the degree of agreement between a new test and a test of common use in practice: this index takes into consideration the patients positive for both tests, negative for both tests and variations in the positive between the two tests. In case of CCS-HEART score this index is 76%, which is a positive result as it allows us to use CCS in clinical practice. 
Analyzing the data of the “rule-in” (Fig.4) we observe as of the 39 patients with ACS + diagnosis: 16 patients HIGH risk to both scores; 10 patients HIGH risk to CCS and LOW / INTERMEDIATE to HEART score; 7 patients HIGH risk to HEART score and LOW / INTERMEDIATE to the CCS; 6 patients at LOW risk to both scores. Comparing the data obtained in the study from the two scores we can observe the validity of the CCS in relation to the HEART score.

Figure 3. Comparison of HEART score – CCS. Correlation between risk in relation to positive diagnosis for ACS

Figure 4. Comparison of HEART score – CCS. Correlation between low risk patients in relation to negative diagnosis for ACS


The capability of Clinical – Chemistry Score to reduce the numbers of patients in the gray area and to bring them to the “extremes” of stratification is the most important data of our study.
Often the gray areas are the weak point of the scores, which make the case of difficult interpretation and, therefore, the reliability of the score in the medical evaluation.
Moreover, it is quite the gray area that limits the direction to make the choice about “rule-out” patients.
In our experience the CCS as compared to HEART has the ability to reduce the number of patients in the gray area by directing them mainly towards “rule-out” and this is an important strength of this new score. Regarding “rule-in” the data of the CCS are similar to the HEART.
The judgment on this score will be validated by expanding the case study, but our preliminary results allow us to see a greater accuracy of this new score.


  1. Filippo Ottani, Nicola Binetti, Ivo Casagranda, Matteo Cassin, Mario Cavazza, Stefano Grifoni, Tiziano Lenzi, Roberto Lorenzoni, Rodolfo Sbrojavacca, Pietro Tanzi, Giuseppe Vergara – Percorso di valutazione del dolore toracico – Valutazione dei requisiti di base per l’implementazione negli ospedali italiani – G Ital Cardiol 2009; 10 (1): 46-63
  2. Tanzi P., Pelliccia F. – La gestione del dolore toracico acuto in Pronto Soccorso. La realtà attuale, le prospettive future, i punti controversi. – G Ital Cardiol 2006; 7 (3): 165-175
  3. Aktürk E. Akn L. Taolar M.H. Türkmen S. Kaya H.
Comparison of the Predictive Roles of Risk Scores of In-Hospital Major Adverse Cardiovascular Events in Patients with Non-ST-Elevation Myocardial Infarction Undergoing Percutaneous Coronary Intervention – Med Princ Pract. 2018;27(5):459-465.
  4. Mahler SA, Miller CD, Hollander JE, Nagurney JT, Birkhahn R, Singer AJ, Shapiro NI, Glynn T, Nowak R, Safdar B, Peberdy M, Counselman FL, Chandra A, Kosowsky J, Neuenschwander J, Schrock JW, Plantholt S, Diercks DB, Peacock WF. Identifying patients for early discharge: performance of decision rules among patients with acute chest pain. Int J Cardiol. 2013; 168(2): 795–802. [pubmed: 23117012] 
  5. Fanaroff AC, Rymer JA, Goldstein SA, et al. Does this patient with chest pain have acute coronary syndrome? The rational clinical examination systematic review. JAMA 2015;314:1955-65. 
  6. Bueno H. The ACCA Clinical Decision Making Toolkit – Second Edition, 2015. ACCA. 
  7. Kontos MC, Diercks DB, Kirk JD. – Emergency department and office-based evaluation of patients with chest pain. –  Mayo Clin Proc 2010;85:284-99. 
  8. Body R, Cook G, Burrows G, Carley S, Lewis PS. – Can emergency physicians ‘rule in’ and ‘rule out’ acute myocardial infarction with clinical judgement? – Emerg Med J 2014;31:872-6. 
  9. Casagranda I, Cavazza M, Clerico A, et al. – Proposta per l’utilizzo in PS delle troponine cardiache misurate con metodi di ultima generazione in pazienti con sospetta di sindrome coronarica acuta senza sopraslivellamento del tratto – ST. Ligand Assay 2012;17:350-60.

  10. Leite L, Baptista R, Leitao J, et al. – Chest pain in the emergency department: risk stratification with Manchester triage system and HEART score. – BMC Cardiovasc Disord 2015;15:48. 
  11. Guerrino Zuin, Vito Maurizio Parato, Paolo Groff, Michele Massimo Gulizia, Andrea Di Lenarda, Matteo Cassin, Gian Alfonso Cibinel, Maurizio Del Pinto, Giuseppe Di Tano, Federico Nardi, Roberta Rossini, Maria Pia Ruggieri, Enrico Ruggiero, Fortunato Scotto Di Uccio, Serafina Valente – Documento di consenso ANMCO/SIMEU: Gestione intraospedaliera dei pazienti che si presentano con dolore toracico – Giorn Ital di Cardiologia 2016; 17(9); 416-446 
  12. Mccarthy BD –  Missed diagnoses of acute myocardial infarction in the emergency department: results from a multicenter study. – Ann Emerg Med 1993 Mar;22(3):579-82
  13. Peter A. Kavsak phd, Johannes T. Neumann MD, Louise Cullen MBBS phd, Martin Than MBBS, Colleen Shortt phd, Jaimi H. Greenslade phd, John W. Pickering phd, Francisco Ojeda phd, Jinhui Ma phd, Natasha Clayton CRA RA, Jonathan Sherbino MD, Stephen A. Hill phd, Matthew mcqueen mbchb phd, Dirk Westermann MD, Nils A. Sörensen MD, William A. Parsonage MBBS DM, Lauren Griffith phd, Shamir R. Mehta MD msc, P.J. Devereaux MD phd, Mark Richards mbchb phd, Richard Troughton mbchb phd, Chris Pemberton phd, Sally Aldous mbchb MD, Stefan Blankenberg MD, Andrew Worster MD msc –  Clinical chemistry score versus high-sensitivity cardiac troponin I and T tests alone to identify patients at low or high risk for myocardial infarction or death at presentation to the emergency department – CMAJ 2018 August 20;190:E974-84.
  14. Linee guida ESC 2015 per il trattamento delle sindromi coronariche acute nei pazienti senza sopraslivellamento persistente del tratto ST alla presentazione – Eur Heart J 2016;37:267-315
  15. Thygesen K, Mair J, Giannitsis E, et al. –  How to use high-sensitivity cardiac tro- ponins in acute cardiac care. –  Eur Heart J 2012;123:169-72. 
  16. Body R, Mueller C, Giannitsis E, Christ M, Ordonez-Llanos J, de Filippi CR, Nowak R, Panteghini M, Jernberg T, Plebani M, Verschuren F, French JK, Christenson R, Weiser S, Bendig G, Dilba P, Lindahl B. T.-A. Investigators. – The Use of Very Low Concentrations of High-sensitivity Troponin T to Rule Out Acute Myocardial Infarction Using a Single Blood Test. Acad Emerg Med. 2016; 23(9): 1004–1013. 
  17. Poldervaart, Langedijk, Backus, Dekker, Six, Doevendans, Hoes, Reitsma – Comparison of the GRACE, HEART and TIMI score to predict major adverse cardiac events in chest pain patients at the emergency department. – Int J Cardiol. 2017 Jan 15;227:656-661
  18. Six AJ, Backus BE, Kelder JC. – Chest pain in the emergency room: value of the HEART score. – Neth Heart J. 2008; 16(6):191–196. 
  19. Backus BE, Six AJ, Kelder JC, Mast TP, van den Akker F, Mast EG, Monnink SH, van Tooren RM, Doevendans PA.-  Chest pain in the emergency room: a multicenter validation of the HEART Score. – Crit Pathw Cardiol. 2010; 9(3):164–169. 
  20. Six AJ, Cullen L, Backus BE, Greenslade J, Parsonage W, Aldous S, Doevendans PA, Than M. – The HEART score for the assessment of patients with chest pain in the emergency department: a multinational validation study. – Crit Pathw Cardiol. 2013; 12(3):121–126. 
  21. Jaimi H. Greenslade, phd; Louise Cullen, MBBS; Lauren Kalinowski, MBBS; William Parsonage, DM; Suetonia Palmer, phd; Sally Aldous, MD; Mark Richards, phd; Kevin Chu, MBBS; Anthony F. T. Brown, MB CHB; Richard Troughton, phd; Chris Pemberton, phd; Martin Than, MBBS – Examining Renal Impairment as a Risk Factor for Acute Coronary Syndrome: A Prospective Observational Study  – Ann Emerg Med. 2013 Jul;62(1):38-46
  22. Colleen Shortt, Jinhui Ma, Natasha Clayton, Jonathan Sherbino, Richard Whitlock, Guillaume Pare, Stephen A. Hill, Matthew mcqueen, Shamir R. Mehta, P.J. Devereaux, Andrew Worster, and Peter A. Kavsak – Rule-In and Rule-Out of Myocardial Infarction Using Cardiac Troponin and Glycemic Biomarkers in Patients with Symptoms Suggestive of Acute Coronary Syndrome – Clin Chem. 2017 Jan;63(1):403-414.
  23. Rosalinda Madonna, Maria Elena Colella, Raffaele De Caterina – Il controllo glicemico in unità coronarica: valore prognostico e nuove strategie terapeutiche. – G Ital Cardiol 2008; 9 (9): 603-614
  24. G. Mathieu – Il Controllo Glicemico Nel Paziente Con Infarto Miocardico Acuto. – Tigullocardio 12-2008 69-73
  25. Erhardt L, Herlitz J, Bossaert L, et al. – Task force on the management of chest pain. – Eur Heart J 2002;23:1153-76.

  26. Lee TH, Cook EF, Weisberg M, Sargent RK, Wilson C, Goldman L. – Acute chest pain in the emergency room: identification and examination of low-risk patients. – Arch Intern Med 1985;145:65-9. 
  27. Hollander JE. – The continuing search to identify the very-low-risk chest pain patient. – Acad Emerg Med. 1999;6:979-981.