PAPP-A protein diagnostic and prognostic significance in acute coronary syndromes without persistent ST-T-segment elevation.

PAPP-A protein diagnostic and prognostic significance in acute coronary syndromes without persistent ST-T-segment elevation. | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article PAPP-A protein diagnostic and prognostic significance in acute coronary syndromes without persistent ST-T-segment elevation. Monika Różycka-Kosmalska, Rafał Frankowski, Anna Pękala-Wojciechowska, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5342541/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract There are ongoing attempts to find a reliable, highly sensitive and specific early indicator of myocardial ischemia. Recently, a potential new function for the “non-pregnancy” related PAPP-A protein has been reported in many papers, including that the protein could be used in diagnosing heart conditions. Hence, our study aimed to determine the diagnostic and prognostic significance of PAPP-A protein in individuals diagnosed with Non ST-Elevation Acute Coronary Syndromes (NSTE-ACS). The study comprised a 100 consecutive patients (68 males and 32 females), aged from 42 to 83 years (mean age: 64.2 years). We assessed PAPP-A protein levels, anthropometric measurements, basic laboratory tests, ECG recordings, and coronary angiography for each patient. The participants were subsequently divided into two groups: Non ST Elevation Myocardial Infarction (NSTEMI, n = 74) or Unstable Angina (UA, n = 25). The levels of PAPP-A protein in patients with NSTEMI were slightly higher than those in patients with UA, but the difference was not statistically significant (7.93 ± 6.35mIU/l vs. 6.52 ± 5.45mIU/l, p = 0.253). Higher levels of PAPP-A protein (≥ 5.83mIU/l) were found to be linked to a greater risk of NSTEMI (OR = 1.37; 95%CI: 0.56–3.36), although with less accuracy compared to the initial measurement of troponin T (cTnT) in the identification of cases. After 12 months, there was a significant correlation between the amount of labeled PAPP-A protein and the likelihood of experiencing acute myocardial infarction, cardiovascular death, and the necessity for unplanned coronary angiography (UCA). The diagnostic utility of PAPP-A protein in NSTE-ACS is limited, both in the NSTEMI and UA patient groups. However, its measurement can be used to estimate the annual risk for these groups of patients. Biological sciences/Biochemistry/Peptides Health sciences/Cardiology/Interventional cardiology Health sciences/Diseases/Cardiovascular diseases Health sciences/Biomarkers/Diagnostic markers Acute coronary syndrome. PAPP-A. ACS. Cardiology. Cardiovascular disease Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Cardiovascular diseases (CVD) are the primary cause of mortality, as well as illness and disability, with 80% of deaths related to CVD observed in low- and middle-income countries. It is known that those with high income have more risk factors of CVD death, however, in comparison to other countries, the decline in CVD-related deaths is faster there [ 1 ]. According to the European Society of Cardiology, CVDs are the primary cause of mortality which contributes to 45% of all deaths in Europe and 37% in the European Union. Nevertheless, CVD mortality is currently reduced in practically all European nations [ 2 ]. The initial 12-lead electrocardiogram (ECG) is used as the basis for categorizing patients with chest pain into two groups: those with ST-segment elevation ACS (ST Elevation Acute Coronary Syndromes, STE-ACS) and those with non-ST elevation ACS (NSTE-ACS). The second aspect of stratification entails assessing myocardial necrosis markers, primarily by determination of cardiac troponins (cTn). Pregnancy-associated plasma protein A (PAPP-A) is a glycoprotein with a high molecular weight of approximately 200 kDa. It is known as a zinc-binding metalloproteinase and belongs to the family of metalloproteins [ 3 ]. The presence of this substance was initially detected in the plasma of pregnant women in the 1970s by Lin et al [ 4 ]. For several years, reports concerning a novel and distinct function of the "non-pregnancy" PAPP-A protein have been published. Bayes-Genis et al. [ 5 ] utilized immunohistochemical analyses to confirm the existence of PAPP-A protein in ruptured and eroded atherosclerotic plaques. They also observed higher levels of this marker in patients with acute coronary syndrome (ACS) compared to those with stable ischemic heart disease (IHD). Sangorini et al. [ 6 ] used RT-PCR to illustrate an elevation in PAPP-A levels within atherosclerotic carotid artery plaques. Significantly, the level of this marker was markedly increased in unstable and ruptured plaques compared to stable ones. PAPP-A is elevated 2 to 30 hours after the beginning of chest pain [ 7 ]. Furthermore, PAPP-A seems to be a predictive and evaluative factor of heart failure after AMI [ 8 ]. In the cardiovascular system, PAPP-A protein is produced in the vascular endothelium and in arterial smooth muscle cells [ 9 , 10 ]. Researchers have observed that the PAPP-A protein in ACS patients differs from the PAPP-A protein in pregnancy, existing as a homodimer consisting of two distinct subunits unrelated to proMBP [ 11 , 12 ]. Glerup et al. [ 13 ] and Stocker et al. [ 14 ] demonstrated that the formation of the PAPP-A protein molecule is a complex process that depends on many external factors. The presence of oxidative compounds in the surrounding environment limits the above-mentioned process. The oxidative stress that exists in an unstable atherosclerotic plaque stops proMBP and PAPP-A protein from forming a covalent bond, which then leads to the formation of a homodimer. The PAPP-A protein plays various pathophysiological roles. One concept is that the PAPP-A protein acts as a metalloproteinase, causing atherosclerotic plaque destabilization through degradation of the extracellular matrix [ 15 , 16 ]. A recent work presents that serum levels of PAPP-A were markedly elevated in diabetics relative to healthy individuals and exhibited a correlation with aortic augmentation index and coronary calcification, which may indicate its correlation with subclinical atherosclerosis in diabetics [ 17 ]. There is also a thesis that PAPP-A protein has a direct or indirect (IGF-1-mediated) effect on the inflammatory component of atherogenesis, which may contribute to atherosclerotic plaque destabilization [ 9 , 18 – 20 ]. The concepts of Crea et al. [ 21 ] and Conti et al. [ 22 ] contradict these theories, assuming that the increase in PAPP-A protein levels observed in ACS is the result of repair processes mediated by released IGF-1, which stimulates cells to proliferate and differentiate. A number of studies evaluating the diagnostic and prognostic role of the PAPP-A protein in ACS indicate its significant importance [ 9 , 23 – 27 ]. The aim of the study The purpose of this study was to determine the diagnostic and prognostic value of PAPP-A protein in patients with Non ST- Elevation Acute Coronary Syndromes (NSTE-ACS) and to answer the question of whether PAPP-A determination can be used in risk stratification in patients with NSTE-ACS. The specific objectives were as follows: To assess whether PAPP-A protein determination has diagnostic significance in the diagnosis of acute myocardial infarction (AMI). To compare the sensitivity, specificity, predictive value of PAPP-A protein against the classic marker of myocardial necrosis-cardiac troponin T (cTnT). To assess whether PAPP-A protein determination is significantly predictive of the occurrence of adverse cardiovascular events and the composite endpoint (including death and AMI) at early follow-up (30 days). To assess whether PAPP-A protein determination has prognostic significance for the incidence of adverse cardiovascular events and the composite endpoint (including cardiovascular death and AMI) at long-term follow-up (3, 6 and 12 months). To assess whether PAPP-A protein determination has prognostic significance with respect to the occurrence of restenosis. 2. Materials and methods The Bioethics Committee of the Medical University of Lodz approved the study protocol (RNN/2/08/KE). The study included 100 patients with an initial diagnosis of non-ST segment elevation acute coronary syndrome (Non ST Elevation Acute Coronary Syndromes, NSTE-ACS) treated in the Department of Cardiology, Medical University of Lodz, in 2008–2009. The inclusion criteria for the study were as follows: clinical diagnosis of ACS up to the 12th hour from the onset of pain, electrocardiographic features of NSTE-ASC: onset of transient ST-segment elevation, new horizontal or downward sloping ST-segment depression of at least ≥ 0.5mV in 2 adjacent leads, T-wave inversion ≥ 0.1mV or “pseudo-normalization” of T-waves, or absence of ischemic changes on resting ECG, informed consent to participate in the study signed by the patient. The disqualification criteria included a diagnosis of ACS with persistent ST-segment elevation (STE-ACS), a diagnosis of NSTE-ACS more than 12 hours from the onset of pain, unfractionated or low-molecular-weight heparin therapy, renal failure (creatinine > 1.6 mg/dL), an illness or a severe skeletal muscle injury within the past few days, acute or chronic infectious diseases, pregnancy. In all patients, an additional blood sample of 5ml was collected for quantification of PAPP-A protein. The PAPP-A US (ultrasensitive) ELISA reagent from DRG (DRG Instruments GmbH, Germany) based on the Enzyme-Linked Immunosorbent Assay (ELISA) method was used for this determination. It is used to detect specific proteins in the test material using mono- or polyclonal antibodies configured with the appropriate enzyme [ 28 – 30 ]. The reagent used is based on one variation of the classic ELISA - the so-called “sandwich method” (Sandwich ELISA). The subjects then underwent a twelve-month clinical follow-up. They were interviewed four times (after 1, 3, 6, 12 months of follow-up) about their current health status. We collected information over the phone, during potential follow-up visits, and during in-person visits to the patients' homes. We paid special attention to the need to repeat hospitalization for cardiovascular causes, the need for follow-up coronary angiography, the occurrence of another AMI, the stroke, and the death from cardiovascular causes. Statistical Research Methodology. Quantitative (measurable) variables are presented with basic descriptive statistics: the value of the arithmetic mean and standard deviation (SD), as well as the smallest and largest value, and positional measures - median and quartiles Q25 - quartile I and Q75 - quartile III. For qualitative (nominal) variables, we provide the number of observations for each variant of the variable (N) along with the corresponding percentage (%). The choice of statistical methods for the analysis of measurable variables depended mainly on the distribution of these variables, hence, the hypotheses of normality of distribution were verified using the Shapiro-Wilk normality test. Since the distribution of most variables is not a normal distribution, the non-parametric Mann-Whitney U test was used to compare the analyzed groups from the point of view of measurable variables (if the distribution of a variable in at least one group was not normal). The study groups were compared using the Student's t-test if there was no reason to reject the hypothesis of normal distribution. We used the chi-square test of independence to compare the studied groups in relation to non-measurable variables. The ROC operating-characteristic curve, a graphical representation of changes in sensitivity and specificity of a particular factor, also described the usefulness of the measurable variable PAPP-A in differentiating between NSTEMI and UA patients and predicting adverse events at 12-month follow-up. The higher the ROC curve (larger AUC area under the curve), the better the predictive value of the analyzed factor: AUC ≤ 0.5 - the factor does not differentiate patients, 0.5 < AUC < 0.6 - the factor differentiates individuals very poorly, 0.6 ≤ AUC < 0.7 - the factor differentiates patients sufficiently, 0.7 ≤ AUC < 0.8 - the factor differentiates individuals satisfactorily, 0.8 ≤ AUC < 0.9 - the factor differentiates individuals very well, AUC ≥ 0.9 - the factor differentiates patients perfectly. We determined certain threshold values of the PAPP-A variable using this curve to predict the occurrence of MI and adverse events. We also analyzed the basic measures that determine the usefulness of a particular diagnostic test, such as sensitivity, specificity, chance of a false positive result, chance of a false negative result, positive predictive value, and negative predictive value (percentage of patients with a negative test result who did not have a pk). The predictive value of a positive result of a particular diagnostic test for the occurrence of PCP was also determined by the odds ratio – OR. We assessed correlations between quantitative variables using the Spearman's rank correlation coefficient (R). A significance level of p = 0.05 was adopted for all statistical tests used. We performed the statistical analysis using the STATISTICA PL 7.1 software package. 3. Results The study included 100 patients aged 42 to 83 years (mean 64.2 ± 10.5) with a diagnosis of ACS [68 men (M) aged 42 to 83 years (mean 63.4 ± 10.3) and 32 women (K) aged 44 to 82 years (mean 66 ± 11.03); p = 0.252]. The study included 100 patients with an ACS diagnosis, 74 of whom were eventually diagnosed with NSTEMI and the remaining 26 received a UA diagnosis. We performed further statistical analysis by dividing patients with NSTEMI and UA. Those with NSTEMI and UA did not differ significantly in the presence of coronary risk factors [Table 1 ]. Table 1 Risk factors for ischemic heart disease in patients with NSTEMI and UA. Risk factor Patients with NSTEMI (n = 74) Patients with UA (n = 26) p * Age (years) 63.39 ± 10.52 66.50 ± 10.27 0.196 Male sex 48 [64.86%] 20 [76.92%] 0.591 Dyslipidemia 74 [100.0%] 26 [100.0%] 1.0 Hypertension 69 [93.20%] 23 [88.46%] 0.439 Smoking 61 [82.43%] 21 [80.77%] 0.849 Obesity Overweight 29 [39.19%] 32 [43.24%] 9 [34.62%] 10 [38.46%] 0.679 0,672 T2DM Impaired fasting blood glucose 30 [40.54%] 20 [27.03%] 11 [42.31%] 8 [30.77%] 0.874 0.715 Familial occurrence of atherosclerotic diseases 14 [18.92%] 5 [19.23%] 0.972 NSTEMI – Non ST Elevation Myocardial Infarction; T2DM – type 2 diabetes mellitus, UA – unstable angina. The data are expressed as the number of observations with a given variable variant (N) and its corresponding percentage (%), except age where the data is given as the mean value and standard deviation (SD). * p-value assessed using the chi-square test, except for the age variables in which the Mann-Whitney U test was used. Angiographic characteristics. Selective coronary angiography was performed from access through the radial artery in 83 patients, and from access through the femoral artery in 17 patients, including 5 patients coronary artery bypass grafting (CABG). Significant coronary artery stenosis at coronary angiography was more common in patients with NSTEMI (93.3%) than in pts with UA (76.9%) (p = 0.022). The two groups did not differ in the presence of stenosis in 1, 2 or 3 coronary arteries. Nearly ¼ of patients with UA had only marginal irregularities (vs 6.7% of patients with NSTEMI; p = 0.022) [Table 2 ]. Table 2 Coronary artery stenosis at coronary angiography in pts with NSTEMI and UA. Changes in the coronary arteries Patients with NSTEMI (n = 74) Patients with UA (n = 26) p ** Marginal irregularities 5 [6.76%] 6 [23.07%] 0.022 Critical stenoses in the coronary arteries 69 [93.24%] 20 [76.91%] 0.022 Critical stenoses in 1 coronary artery 29 [39.19%] 6 [23.07%] 0.138 2 coronary arteries 15 [20.27%] 7 [26.92%] 0.481 ≥ 3 coronary arteries 25 [33.78%] 7 [26.92%] 0.519 NSTEMI – Non ST Elevation Myocardial Infarction; UA – unstable angina. The data are expressed as the number of observations with a given variable variant (N) and its corresponding percentage (%). **p-value assessed using the chi-square test. The bolded results indicate statistically significant differences. Based on the nature of coronary artery lesions on angiography, the patients were qualified for conservative treatment (17%) or surgical treatment (83%). The patients with UA were significantly more often qualified for conservative treatment (30.8% vs 12.2%; p = 0.029). Characteristics of selected laboratory parameters, atherogenicity indices, renal function and PAPP-A protein. Table 3 displays the results of laboratory tests that patients with NSTEMI and UA underwent on admission. Since the distribution of most measurable variables does not show a normal distribution, the mean and standard deviation may not be reliable assessments of the variable's mean level and variation. In these cases, we should focus more on the median and interquartile range (Q25-Q75 interval). Table 3 Comparison of laboratory tests in patients with NSTEMI and UA. Laboratory tests Patients with NSTEMI (n = 74) Patients with UA (n = 26) P Glycemia [mg/dl] 141.97 [78.06] 125.19 [77.23] 0.187* TC [mg/dl] 201.92 [45.17] 188.12 [43.37] 0.179** LDL[mg/dl] 123.97 [41.89] 112.38 [38.32] 0.218** HDL[mg/dl] 50.54 [20.70] 47.85 [19.76] 0.207* TG [mg/dl] 135.47 [75.06] 149.62 [76.74] 0.301* Creatinine [mg/dl] 0.89 [0.24] 0.90 [0.22] 0.396* Uric acid [mg/dl] 6.44 [1.09] 6.48 [1.86] 0.934** CRP [mg/l] 7.54 [7.56] 7.40 [10.15] 0.359* Fibrinogen [g/l] 4.69 [2.11] 5.13 [2.40] 0.376* Leukocytes [10 3 /mm 3 ] 8.89 [2.83] 8.03 [2.48] 0.132* Neutrophils [%] 61.79 [10.50] 61.37 [8.37] 0.857* CRP – C reactive protein; HDL – high density lipoproteins; LDL – low density lipoproteins; NSTEMI – Non ST Elevation Myocardial Infarction; TC – total cholesterol; TG – triglycerides; UA – unstable angina. The data are expressed presented as mean value and standard deviation (SD). * p-value assessed using the the Mann-Whitney U test. ** p-value assessed using the Student’s T-Test. Echography characteristics of patients with NSTEMI and UA. The results of echography measurements of patients with NSTEMI and UA are presented in Table 4 . Table 4 Echography characteristics of patients with NSTEMI and UA. EF% Patients with NSTEMI (n = 74) Patients with UA (n = 26) p * 56.85 ± 10.15 57.73 ± 13.81 0.374 % of patients with EF EF ≥ 55% 68.9% 73.1% 40%≤EF < 55% 25.7% 15.4% EF < 40% 5.4% 11.5% EF – ejection fraction; NSTEMI – Non ST Elevation Myocardial Infarction; UA – unstable angina. The data are expressed as the percentage (%) of observations, except EF value where the data is given as the mean value ± standard deviation (SD). * p -value assessed using the chi-square test. The role of PAPP-A protein in predicting myocardial infarction. We observed slightly higher mean and median PAPP-A protein concentrations in patients with NSTEMI compared to those with UA, but these differences were not statistically significant [Table 5 ]. Despite this, the ROC curve, a graphical presentation of changes in the sensitivity and specificity of a given factor, described the usefulness of PAPP-A protein concentration in distinguishing patients with NSTEMI from those with UA. The ROC curve and basic statistics, which describe the area under the curve (AUC) for PAPP-A protein concentration as a factor differentiating both study groups are presented in Fig. 1 and Table 6 . Table 5 Comparison of PAPP-A protein levels in patients with NSTEMI and UA. PAPP-A protein concentration [mIU/l] Patients with NSTEMI (n = 74) Patients with UA (n = 26) p * Mean 7.93 6.52 0.253 Median 6.31 5.26 Min 1.44 0.60 Max 35.84 27.60 Q25 3.62 3.04 Q75 9.58 7.60 SD 6.35 5.45 NSTEMI – Non ST Elevation Myocardial Infarction; PAPP-A- Pregnancy-associated plasma protein A; UA – unstable angina. The data are expressed as mean, median, minimum, maximum, IQR (Quartile 1; Quartile 3) and standard deviation (SD). * p -value assessed using the Mann-Whitney U test. Table 6 Basic descriptive statistics of the ROC curve describing the usefulness of PAPP-A concentration in differentiating PTS with NSTEMI and UA. AUC SE p * 95%CI Lower limit Upper limit 0.576 0.065 0.253 0.449 0.703 The data are expressed as area under the curve (AUC), standard error (SE) mean and confidence level (cl) with lower and upper limit. * p -value assessed using the chi-square test. As it can be seen from Table 6 , the area under the ROC curve is: AUC = 0.576. This value is not statistically significant, which means that the PAPP-A protein concentration weakly differentiates patients with NSTEMI and patients with UA. Further analysis of the above curve also determined the threshold value of PAPP-A protein concentration, allowing for prediction of NSTEMI occurrence. The cut-off point for the PAPP-A protein value turned out to be 5.83 mIU/l [Figure 2 ]. For this PAPP-A protein concentration, the odds ratio (OR) was then calculated. The results are presented in Table 7 (OR and 95% CI for OR are given). The OR was 1.37, which means that patients with PAPP-A concentration ≥ 5.83 mIU/l had a 1.37-fold higher risk of NSTEMI than those with PAPP-A < 5.83 mIU/l. Table 7 OR and 95% confidence interval for OR for PAPP-A concentration ≥ 5.83mIU/l. Diagnostic test OR -95%CI + 95%CI PAPP-A ≥ 5,83mIU/l 1.37 0.56 3.36 PAPP-A- Pregnancy-associated plasma protein A. The data are expressed as odds ratio (OR) and confidence level (Cl). Comparison of sensitivity, specificity and predictive values ​​of PAPP-A protein versus the classic marker of myocardial necrosis cTnT. For the PAPP-A protein concentration determined during the ROC curve analysis, which allows for the prediction of NSTEMI (5.83 mIU/l) and for the classic marker of myocardial necrosis, i.e. cTnT, the following measures were calculated to determine the usefulness of the diagnostic test: sensitivity, specificity, chance of a false positive result, chance of a false negative result, positive predictive value (PPV), negative predictive value (NPV) [Table 8 ]. Table 8 Comparison of sensitivity, specificity and predictive values ​​of cTnT and PAPP-A protein. Diagnostic test Sensitivity Specificity PPV NPV Chance of results false positive false negative cTnT- 1 positive 58.11% 100.00% 100.00% 45.61% 0.00% 41.89% cTnT- 2 positive 100.00% 100.00% 100.00% 100.00% 0.00% 0.00% PAPP-A ≥ 5,83mIU/l 54.05% 53.85% 76.92% 29.17% 46.15% 45.95% cTnT - cardiac Troponin T, NPV - negative predictive value, PAPP-A- Pregnancy-associated plasma protein A, PPV - positive predictive value. The data are expressed as percentage (%) of observations. The second cTnT test (cTnT-2) provides the best results in predicting myocardial infarction (NSTEMI). The PAPP-A protein with the optimal cut-off point turns out to be a worse indicator even than the first cTnT test. The sensitivity and specificity of the PAPP-A protein test approximates 54%. The positive predictive value is quite high (PPV = 76.92%), which means that in the group of patients with PAPP-A protein concentration ≥ 5.83 mIU/l the percentage of patients with myocardial infarction (NSTEMI) was 76.92%. Assessment of the association of PAPP-A protein with adverse cardiovascular events. Because of the relatively small number of adverse cardiovascular events, these data were considered together for both groups. We also constructed a composite endpoint (CE) that included acute myocardial infarction (AMI) and cardiovascular death (CD). 1-month observation period. In patients with the above-defined CE in the first month of follow-up, the PAPP-A protein concentration determined in the ACS was significantly higher (p < 0.001) than in patients without CE [Table 9 ]. Table 9 Relationship between PAPP-A protein concentration and the risk of CE in 1 month of observation. CE (AMI + CD) 1-month observation period PAPP-A (mIU/l) p * n Mean Median Min Max Q25 Q75 SD NO 94 6.73 5.70 0.60 26.29 3.36 8.56 4.69 0.0008 YES 6 20.59 20.77 6.82 35.84 11.73 27.60 10.85 AMI – acute myocardial infarction; CD – cardiovascular death; CE – composite endpoint. The data are expressed as as the number (n) of observations, mean, median, minimum, maximum, IQR (Quartile 1; Quartile 3) and standard deviation (SD). * p -value assessed using the Mann—Whitney U test The bolded results indicate statistically significant differences. The ROC curve [Figure 3 ] and basic statistics describing the area under the curve (AUC) [Table 10 ] for PAPP-A protein concentration as a factor differentiating patients with or without CE are presented below: Table 10 Basic descriptive statistics of the ROC curve - tested variable: PAPP-A protein concentration in patients with and without CE in the 1st month of observation. AUC SE p * 95%CI Lower limit Upper limit Adverse event CE 0.908 0.057 0.001 0.797 1.019 CE – composite endpoint. The data are expressed as area under the curve (AUC), standard error (SE) mean and confidence level (cl) with lower and upper limit. * p -value assessed using the chi-square test. The bolded results indicate statistically significant differences. The analysis shows that the PAPP-A protein concentration determined on admission to hospital is a variable that differentiates patients at risk of AMI or CD in an excellent way (AUC ≥ 0.9). Further analysis of the ROC curve revealed a PAPP-A protein concentration cut-off point that significantly correlated with the risk of occurrence of the above-defined CE. The optimal cut-off point turned out to be 11.44 mIU/l. Then, the variable of PAPP-A protein concentration together with the mentioned cut-off point was treated as a diagnostic test that allows for prediction of the occurrence of CE. We obtained the results presented in Table 11 by analyzing the basic measures determining the usefulness of a given diagnostic test (sensitivity, specificity, positive and negative predictive value). Table 11 Sensitivity, specificity, PPV, NPV for PAPP-A concentration ≥ 11.44 mIU/l (1 month of observation). Diagnostic test Sensitivity Specificity PPV NPV PAPP-A protein concentration ≥ 11.44mIU/l. 83.33% 88.30% 31.25% 98.81% NPV - negative predictive value, PAPP-A- Pregnancy-associated plasma protein A, PPV - positive predictive value. The presented analysis shows that this value was characterized by high sensitivity (83.33%) and specificity (88.30%). The probability that CE will not occur at a PAPP-A protein concentration of < 11.44 mIU/l is also very high (NPV- 98.81%). The predictive value of a positive result of a given diagnostic test for the occurrence of CE was also determined based on the odds ratio - OR. For this cut-off point, the OR was 37.73, which means that if the PAPP-A protein concentration ≥ 11.44 mIU/l, the risk of CE is almost 38 times higher than in the case when the PAPP-A protein concentration is < 11.44 mIU/l, with a 95% confidence interval for OR [95%CI: 8.14–74.83]. Period between 1 and 3 months of observation. In 3-month follow-up, a statistically significant association between PAPP-A protein concentration and the risk of AMI (14.59 ± 9.17mIU/l vs 6.73 ± 4.92mIU/l; p = 0.042) and the need for unplanned coronary angiography (UCA) (11.64 ± 6.65mIU/l vs 6.62 ± 5.08mIU/l; p = 0.004) was observed. Table 12 presents basic descriptive statistics of ROC curves (Fig. 4 ) that describe the usefulness of PAPP-A protein in predicting the aforementioned adverse events. Table 12 Basic descriptive statistics of the ROC curve - test variable: PAPP-A protein concentration in predicting AMI or the need for UCA (from 1 to 3 months of follow-up). AUC SE p * 95%CI Lower limit Upper limit Adverse event AMI 0.771 0.116 0.042 0.544 0.999 UCA 0.777 0.070 0.004 0.641 0.914 AMI – acute myocardial infarction; UCA – unplanned coronary angiography. The data are expressed as area under the curve (AUC), standard error (SE) mean and confidence level (cl) with lower and upper limit. * p -value assessed using the chi-square test. The bolded results indicate statistically significant differences. In the case of both aforementioned adverse events, the value of 0.7≤AUC < 0.8 indicates that PAPP-A protein differentiates patients in a satisfactory manner. The optimal cut-off points (PAPP-A protein concentration), determined during further analysis of the ROC curve, turned out to be values ​​≥16.34 mIU/l for AMI and ≥ 10.7 mIU/l for the need to perform UCA. The determined threshold values ​​of PAPP-A protein concentration are characterized by moderate sensitivity (60%) and PPV (42.86%), with high specificity (> 90%) and NPV (> 95%) [Table 13 ]. Table 13 Sensitivity, specificity, PPV, NPV for the selected diagnostic test (PAPP-A protein concentration ≥ 16.34 mIU/l for AMI and ≥ 10.7 mIU/l for the need to perform UCA) (from 1 to 3 months of observation). Diagnostic test Sensitivity Specificity PPV NPV PAPP-A protein concentration ≥ 16.34mIU/l 60.00% 95.60% 42.86% 97.75% PAPP-A protein concentration -A ≥ 10.7mIU/l 60.00% 90.70% 42.86% 95.12% NPV - negative predictive value, PAPP-A- Pregnancy-associated plasma protein A, PPV - positive predictive value. Particularly high probability of AMI occurrence was found in pts with PAPP-A protein concentration ≥ 16.34 mIU/l. In this group of patients the risk is almost 33 times higher compared to patients with PAPP-A protein concentration below this value [OR = 32.63; 95%CI: 7.52- 141.48] In pts with PAPP-A protein concentration ≥ 10.7 mIU/l the risk of UCA was almost 15 times higher [OR = 14.63; 95%CI: 4.30-49.69]. Period between 3 and 6 months of observation. During the next 3-month observation period, a relationship between PAPP-A protein concentration and the risk of CE (14.93 ± 7.85mIU/l vs 6.80 ± 5.10mIU/l; p = 0.017) and the need for UCA (8.86 ± 4.63mIU/l vs 6.77 ± 5.25mIU/l; p = 0.044) was observed. Table 14 presents basic descriptive statistics of ROC curves [Figure 5 ], which describe the usefulness of PAPP-A protein testing in predicting the aforementioned adverse events. Table 14 Basic descriptive statistics of the ROC curve - tested variable: PAPP-A protein concentration in predicting the occurrence of CE or the need for UCA (from 3 to 6 months of observation). AUC SE p * 95%CI Lower limit Upper limit Adverse event CE 0.853 0.078 0.017 0.700 1.006 UCA 0.716 0.083 0.044 0.554 0.879 CE – composite endpoint; UCA – unplanned coronarography angiography. The data are expressed as area under the curve (AUC), standard error (SE) mean and confidence level (cl) with lower and upper limit. * p -value assessed using the chi-square test. The bolded results indicate statistically significant differences. The analysis shows that the PAPP-A protein concentration determined on admission is a variable differentiating in a satisfactory manner patients in whom UCA will be required (0.7(AUC < 0.8), while this differentiation was very good in those at risk of AMI or cardiovascular death (0.8(AUC < 0.9). The best cut-off points (PAPP-A protein concentration) were found by looking more closely at the ROC curve. They were ≥ 10.14 mIU/l for CE and ≥ 6.47 mIU/l for NK. The level of PAPP-A protein concentration that was found to be the threshold for CE had a high level of specificity (> 85%) and sensitivity (75%). The optimal cut-off point for PAPP-A protein level ≥ 6.47 mIU/l was characterized by only moderate sensitivity and specificity (approx. 60%). High NPV values indicate a very high probability of no occurrence of a specific adverse event. At PAPP-A protein concentration < 10.14 mIU/l the probability of not having CE is almost 99%, while at PAPP-A protein concentration < 6.47 mIU/l the probability of no necessity to perform UCA is almost 99% [Table 15 ]. Table 15 Sensitivity, specificity, PPV, NPV for the selected diagnostic test (PAPP-A protein concentration ≥ 10.14 mIU/l for CE and ≥ 6.47 mIU/l for the need to perform UCA) (from 3 to 6 months of observation). Diagnostic test Sensitivity Specificity PPV NPV PAPP-A protein concentration ≥ 10.14mIU/l 75.00% 86.96% 20.00% 98.77% PAPP-A protein concentration ≥ 6.47mIU/l 66.67% 61.63% 15.38% 94.64% NPV - negative predictive value, PAPP-A- Pregnancy-associated plasma protein A, PPV - positive predictive value. The risk of CE in patients with PAPP-A protein concentration ≥ 10.14 mIU/l was 20 times higher [OR = 20; 95%CI: 3.45-115.96]. In patients with PAPP-A protein concentration ≥ 6.47 mIU/l the risk of UCA was more than 3 times higher [OR = 3.21; 95%CI: 0.80-12.94]. Period between 6 and 12 months of observation. During the next 6 months of observation, a relationship was found between PAPP-A protein concentration and the risk of CE (6.40 ± 4.13mIU/l vs. 24.53 ± 4.23mIU/l; p = 0.004). Basic descriptive statistics of ROC curves [Figure 6 ] describing the usefulness of PAPP-A protein concentration in predicting the aforementioned adverse events are presented in Table 16 . Table 16 Basic descriptive statistics of the ROC curve - tested variable: PAPP-A protein concentration in patients with CE between 6 and 12 months of observation. AUC SE p * 95%CI Lower limit Upper limit Adverse event CE 0.996 0.006 0.004 0.986 1.007 CE – composite endpoint. The data are expressed as area under the curve (AUC), standard error (SE) mean and confidence level (cl) with lower and upper limit. * p -value assessed using the chi-square test. The bolded results indicate statistically significant differences. The analysis clearly shows that the PAPP-A protein concentration determined on admission is a variable that differentiates patients at risk of AMI or CD in a perfect way (AUC ≥ 0.9). AUC equal to 1 means perfect discrimination between the groups. After looking more closely at the ROC curve, we found that the best cut-off points for CE were values greater than or equal to 19.43 mIU/l for PAPP-A protein concentration. The PAPP-A protein level determined as the threshold value for the occurrence of CE was characterized by 100% sensitivity and almost 100% specificity [Table 17 ]. Table 17 Sensitivity, specificity, PPV, NPV for PAPP-A concentration ≥ 19.43 mIU/l for CE (from 6 to 12 months of observation). Diagnostic test Sensitivity Specificity PPV NPV PAPP-A protein concentration ≥ 19.43mIU/l 100% 98.91% 75.00% 100% NPV - negative predictive value, PAPP-A- Pregnancy-associated plasma protein A, PPV - positive predictive value. Association between PAPP-A protein concentration and the occurrence of restenosis. A statistically significant difference in PAPP-A protein concentration was observed between patients with restenosis and those without restenosis (11.89 ± 6.13mIU/l vs 6.92 ± 5.90mIU/l; p = 0.0005). Table 18 presents the basic descriptive statistics of ROC curves [Figure 7 ], which describe the usefulness of PAPP-A protein concentration in predicting restenosis. Table 18 Basic descriptive statistics of the ROC curve - tested variable: PAPP-A protein concentration in predicting restenosis during 12 months of follow-up. AUC SE p * 95%CI Lower limit Upper limit Restenosis 0.802 0.055 0.0005 0.694 0.910 The data are expressed as area under the curve (AUC), standard error (SE) mean and confidence level (cl) with lower and upper limit. * p -value assessed using the chi-square test. The bolded results indicate statistically significant differences. As it results from the above analysis, the PAPP-A protein concentration determined on admission is a variable differentiating patients at risk of restenosis in a very good way (0.8(AUC < 0.9). The optimal cut-off point turned out to be the PAPP-A protein concentration of ≥ 8.17 mIU/l. This value was characterized by quite good sensitivity (76.92%) and specificity (75.86%) as well as high NPV value (95.65%) [Table 19 ]. Table 19 Sensitivity, specificity, PPV, NPV for PAPP-A concentration ≥ 8.17mIU/l in predicting restenosis in 12-month follow-up. Diagnostic test Sensitivity Specificity PPV NPV PAPP-A protein concentration ≥ 8.17mIU/l 76.92% 75.86% 32.25% 96.65% NPV - negative predictive value, PAPP-A- Pregnancy-associated plasma protein A, PPV - positive predictive value. In patients with PAPP-A protein concentration ≥ 8.17 mIU/l the risk of restenosis was more than 10-fold higher [OR = 10.48; 95%CI: 3.16–34.77]. 4. Discussion Every year, over 7 million individuals worldwide suffer from ACS [ 31 ]. In 2019 in Poland, circa 100,000 patients were treated for ACS, and NSTE-ACS accounted for approximately 75% of cases [ 32 ]. NSTE-ACS is the most common type of ACS, constituting the main cause of hospitalization due to ACS [ 33 ]. Observations show a decreasing proportion of STEMI cases in high-income countries [ 34 ]. Considering the large number of patients, the variety of symptoms, and the different prognosis in individual groups of patients with NSTE-ACS, early risk stratification, aimed at identifying both patients at high risk of death or adverse cardiovascular events and "low risk" patients, in whom expensive and potentially dangerous invasive treatment methods bring little benefit, is extremely important. The ECG continues to play a fundamental role in assessing patients with ACS. Biochemical tests have been part of the diagnostic toolkit since the 1950s. The basis for establishing the dominant role of cTn in the diagnosis of patients with ACS was the announcement in 2000 by the European Society of Cardiology (ESC) and the American College of Cardiology (ACC) announced a new definition of AMI [ 35 ]. Currently, the latest guidelines refer to the fourth universal definition of myocardial infarction [ 36 ]. In our own studies, elevated cTnT concentration on admission was more common, affecting 57% of patients, which also included 77% of patients with a final diagnosis of NSTEMI. This may be related to the relatively long time elapsed from the onset of pain to the moment the patient was admitted to the hospital. For the entire group, it was 8.5 hours (± 3.5) on the average and was slightly shorter for patients with NSTEMI (8 ± 3.6 hours) compared to those with UA (9.5 ± 2.7 hours), but this difference did not reach statistical significance (p = 0.09). Despite its indisputable advantages, cTn concentration determination in the diagnosis of ACS is not free from limitations. Therefore, an ideal marker of necrosis/ischemia, characterized by high sensitivity, specificity, and specificity, is still sought. Acceptance of the analysis costs is also important [ 37 ]. PAPP-A protein is considered to be a “promising” marker. Researchers observed that in ACS, the PAPP-A marker of plaque instability is significantly elevated [ 38 ]. What is more, serum PAPP-A level elevations may occur before or even in the absence of myocardial necrosis [ 39 ]. In our own studies, no significant difference in PAPP-A protein concentrations was found between patients with NSTEMI and UA (7.93 ± 6.35mIU/l vs 6.52 ± 5.45mIU/l; p = 0.253). Similar observations were reported by You et al. (2.42 ± 2.98mIU/l vs 2.33 ± 2.68mIU/l; p > 0.05) [ 40 ] and Bayes-Genis et al. (14.9mIU/l in patients with UA vs 20.6mIU/l in patients with AMI; p = 0.5) [ 5 ]. In contrast, a statistically significant difference between PAPP-A protein concentrations between patients with STEMI and NSTEMI and patients with UA (PAPP-A protein concentrations were 30.3 ± 30.11mIU/l in STEMI, 21.13 ± 24.71mIU/l in NSTEMI, 19.73 ± 19.78mIU/l in UA, respectively, p = 0.045) was demonstrated by Hájek et al. [ 41 ]. It is in line with the observations of Mehrpooya et al.. In their study, PAPP-A protein concentrations were significantly lower in subjects with UA compared to those with STEMI [Median (IQR): 12.8 (73.3) vs 116.0 (220.0); p < 0.001] or NSTEMI [Median (IQR): 12.8 (73.3) vs 108.0 (128.0); p = 0.003] [ 42 ]. A study by Schaub et al. also revealed that individuals with AMI have higher concentrations of PAPP-A than those with other diagnoses, including UA [PAPP-A 4.6 (4.0 − 9.3) vs 4.0 (4.0 − 5.6) mIU/L, p < 0.001]. On the other hand, no significant differences were observed in PAPP-A levels between STEMI and NSTEMI [ 43 ]. Different conclusions are drawn from the work of Spanish researchers. Dominguez-Rodriguez et al. [ 44 ] did not note a significant difference in PAPP-A protein concentration between patients with AMI and the control group consisting of people without a previous history of CAD (1.24 ± 0.07mIU/l vs 1.29 ± 0.02mIU/l; p = 0.54), which can be explained primarily by the type of diagnostic test used. Initially, PAPP-A protein was determined using tests commonly used in gynecology for screening for Down syndrome [ 45 ]. However, it was noticed that the concentration of PAPP-A protein in pregnant women is many times higher than in men and non-pregnant women [ 5 , 46 ] and can even reach 3655 mIU/l [ 47 ]. Therefore, it became necessary to create tests capable of detecting low concentrations of PAPP-A protein (so-called "ultra sensitive" tests). The commonly available tests may contain both antibodies reacting with both the PAPP-A protein molecule and proMBP, or antibodies specific only for the PAPP-A protein molecule. Thus, the former detect the PAPP-A protein in the form of a tetramer (2 PAPP-A protein molecules bound to 2 proMBP molecules). A direct consequence of the aforementioned properties is therefore the detection of PAPP-A protein originating from cells of the female reproductive system, kidneys, large intestine and bone marrow [ 48 – 50 ] and the possibility of failure to detect the ACS-specific PAPP-A homodimer [ 12 , 51 ]. Currently, the use of the second type of diagnostic tests, which contain antibodies that react only with the PAPP-A protein molecule, is increasing significantly. Due to the possibility of changing the structure of the PAPP-A protein (in the absence of the proMBP molecule), antibodies contained in such tests may also fail to detect the PAPP-A protein associated with ACS [ 12 , 51 ]. There are also tests specially prepared to detect PAPP-A protein molecules specific for ACS (taking into account specific epitopes), but they are not commercially available [ 11 , 51 , 52 ]. Therefore, it is not surprising that we observed the aforementioned discrepancy in PAPP-A protein concentrations. The higher the PAPP-A protein concentration (5.83 mIU/l) that we found in our own study during further analysis, the lower the risk of NSTEMI was found to be (OR = 1.37; 95%CI: 8.14–74.83). In fact, the PAPP-A protein with the higher cut-off point was even less useful for diagnosing NSTEMI than the first cTnT test. The sensitivity and specificity of the PAPP-A protein test was approximately 54% (respectively, these measures for the above cTnT test were: specificity − 100%, sensitivity − 58.1%). Given that PAPP-A protein has a pretty high positive predictive value (PPV = 76.9%), NSTEMI was found in more than 75% of patients whose PAPP-A protein concentration was at least 5.83 mIU/l. For comparison, Bayes-Genis et al. [ 5 ] in a study published in 2001 in The New England Journal of Medicine, including 69 individuals (including 17 with AMI, 20 with UA, 19 with stable CAD, and 13 without a previous history of CAD) indicated that PAPP-A protein concentration > 10 mIU/l allows for the identification of patients with ACS with a sensitivity close to 90% and specificity over 80%. Czech study showed the significant increase of PAPP-A levels in ACS heparin-naive individuals with high positive (95.7%) and lower negative predictive values (47.7%), furthermore in NSTE-ACS no differences were shown in AUC compared to TnI [ 53 ]. On the other hand, a study by Schaub et al. considers PAPP-A to be of little value in the diagnosis of ACS with an AUC of 0.61, which was inferior to troponin [ 43 ]. Slightly higher PAPP-A protein concentration values ​​allowing for identification of patients with ACS with the highest sensitivity and specificity were reported by Hájek et al. [ 41 ]. For individual types of ACS, these values ​​were in the range of 10.65–14.75 mIU/l (with AUC values ​​from 0.613 to 0.919). The time from the onset of symptoms to the moment of blood collection for the determination of PAPP-A protein concentration varied in individual studies. In our own studies, blood was collected after the patients were admitted to the hospital (it was 8 ± 3.6 hours from the onset of pain in patients with NSTEMI, and among pts UA − 9.5 ± 2.7 hours). It was pretty much the same as the time it took to collect blood in the study by Bayes-Genis et al. (8.4 ± 3 hours for patients with AMI and 9.4 ± 3.9 hours for the UA group) [ 5 ], but different from that in the Czech-German studies (in STEMI − 4 ± 3.3 hours; in NSTEMI − 9.1 ± 2.1 hours, in UA − 15.5 ± 9.5 hours) [ 41 ]. However, the data on the kinetics of PAPP-A protein concentrations are rather modest, although it appears that in the case of STEMI the concentrations normalize rapidly [ 54 – 56 ], while in NSTE-ACS the elevated concentrations remain at a similar level for 24–36 hours [ 56 – 58 ]. The noted variation in PAPP-A protein levels may potentially be affected by other variables, such as heparin, often used in ACS treatment. The capacity of the PAPP-A protein to bind heparin has been recognized for an extended period [ 59 ], and the precise binding site was delineated in 2004 by Weyer et al. [ 60 ]. In vitro, heparin and PAPP-A protein are known to compete for binding on the cell surface [ 61 ]. Subsequent research has unequivocally shown an elevation in PAPP-A protein levels due to the effects of both unfractionated heparin and low-molecular-weight heparins [ 62 – 64 ]. The precise mechanism of this phenomena remains unidentified. One hypothesis posits that the fast elevation in PAPP-A protein concentration upon heparin administration, regardless of the type, results from the release of PAPP-A protein from the endothelial cell surface in arteries with very high blood flow. In our research, one of the exclusion criteria was the administration of unfractionated or low-molecular-weight heparin treatment. This criteria was excluded from the research conducted by Bayes-Genis et al. [ 5 ] and the investigations of Hájek et al. [ 41 ]. Troponins are not only critical in diagnosing individuals with ACS, but they also serve as an exceptional prognostic tool. Extensive data supporting the efficacy of their determination in risk assessment for patients with NSTE-ACS has established cTn as the foundation for risk classification in this cohort [ 31 , 65 – 67 ]. In view of a number of reports on the significance of PAPP-A protein as a prognostic factor in patients with ACS [ 23 , 38 , 68 – 71 ], our own studies assessed its association with adverse events in a 12-month follow-up. Given the small number of adverse cardiovascular events observed, they were considered in the entire NSTE-ACS group. A CE including AMI and CD was also constructed. In the 1st month of observation (taking into account also the people who died during hospitalization), a relationship was observed between the concentration of PAPP-A protein determined in ACS and the risk of the occurrence of CE (20.59 ± 10.85mIU/l vs. 6.73 ± 4.69mIU/l; p = 0.0008). The cut-off point of the concentration of PAPP-A protein (≥ 11.44mIU/l) determined during further analysis was associated with a nearly 38-fold higher risk of CE [OR = 37.73; 95%CI: 8.14–74.83]. It was also characterized by very high sensitivity (83.33%) and specificity (88.30%), while the probability that at the concentration of PAPP-A protein < 11.44mIU/l CE would not occur was almost 99% (NPV- 98.81%). A similar cut-off point, with the same endpoint, was determined by Heeschen et al. [ 72 ], whereby in the case of PAPP-A protein concentration ≥ 12.6 mIU/l the risk of CD or AMI was only more than twice as high [OR = 2.32; 95%CI: 1.32–4.26]. Such a significant difference may be due primarily to the different numbers and characteristics of the study groups. Only 323 patients in the Heeschen et al. group of 644 patients admitted to the hospital with chest pain received a final diagnosis of ACS, while the remaining 105 patients received a diagnosis of stable IHD, 19 patients experienced an exacerbation of heart failure, and 197 patients had a non-cardiac cause of chest pain [ 72 ]. In Bonaca et al. [ 73 ] study at presentation, PAPP-A levels exceeding 6.0 µIU/ml were associated with increased rates of CD or AMI at 30 days (7.4% vs. 3.7%, hazard ratio [HR]: 2.01; 95% confidence interval [CI]: 1.43 to 2.82; p < 0.001) and at 1 year (14.9% vs. 9.7%, HR: 1.63; 95% CI: 1.29 to 2.05; p < 0.001). At 30 days, PAPP-A was also associated with increased incidences of AMI (HR: 1.82; 95% CI: 1.22 to 2.71, p = 0.003) and CD (HR: 1.94; 95% CI: 1.07 to 3.52, p = 0.027). In the same observation period, Laterza et al. [ 74 ] also noticed a relationship between PAPP-A protein concentration and the risk of a complex endpoint including: CD, AMI and the need for revascularization. However, the threshold concentration value determined was much lower (0.22 mIU/l), and was also characterized by lower sensitivity and specificity (66.7% and 51.1%, respectively), while the risk of the endpoint defined above increased 2-fold [OR = 1.9; 95%CI: 0.9–4.1]. Such a large discrepancy in PAPP-A protein concentration should be associated with the use of a different test (American company DSL) for the determination. In our own studies, a statistically significant relationship was observed in the 3-month follow-up between the PAPP-A protein concentration and the risk of AMI (14.59 ± 9.17mIU/l vs 6.73 ± 4.92mIU/l; p = 0.042) and the need for unplanned coronary angiography (UCA) (11.64 ± 6.65mIU/l vs 6.62 ± 5.08mIU/l; p = 0.004). The determined threshold values ​​of PAPP-A protein concentration (≥ 16.34mIU/l for AMI and ≥ 10.7mIU/l for the need for NA) were characterized by high specificity (> 90%) with moderate sensitivity of the test (60%). Among patients with PAPP-A protein concentration ≥ 16.34mIU/l, the risk of AMI was almost 33 times higher [OR = 32.63; 95%CI: 7.52-141.48], and the risk of NK was almost 15 times higher in the case of PAPP-A protein concentration ≥ 10.7mIU/l [OR = 14.63; 95%CI: 4.30-49.69]. Similarly, a relationship between PAPP-A protein level and the risk of adverse events (AMI or death) during a 3-month follow-up was found by Iversen et al. [ 58 ] who evaluated 415 patients with low-risk NSTE-ACS (no ECG changes and negative cTn test result). Danish investigators found that in the case of PAPP-A protein level > 12.4 mIU/l (evaluated in the vast majority of patients from 2 or 3 blood samples) the risk of AMI or death was 3.7 times higher. Additionally, when comparing patients with levels 12.4 mIU/l, the risk of death in the latter was almost 12 times higher (11% vs 1%; p < 0.01; RR = 11.9). During the next observation period (up to 6 months), our own studies found a relationship between PAPP-A protein concentration and the risk of CE (14.93 ± 7.85mIU/l vs 6.80 ± 5.10mIU/l; p = 0.017) and the need for UCA (8.86 ± 4.63mIU/l vs 6.77 ± 5.25mIU/l; p = 0.044). For CE, the optimal cut-off point was ≥ 10.14mIU/l. After exceeding it, the risk of PE was 20 times higher [OR = 20; 95%CI: 3.45-115.96]. This value was characterized by quite high sensitivity (75%) and specificity (> 85%). What is particularly interesting, at PAPP-A protein concentration < 10.14 mIU/l the probability of not developing CE was almost 99%. In the case of PAPP-A protein concentration < 6.47 mIU/l, the probability of not having to perform UCA was 99%, and after exceeding this value the risk increased more than 3-fold [OR = 3.21; 95%CI: 0.80-12.94]. The optimal cut-off point was characterized by moderate sensitivity and specificity (approx. 60%). Heeschen et al. [ 72 ] and Lund et al. [ 75 ] also assessed the risk of adverse events during a 6-month follow-up. One study found that PAPP-A protein levels above 12.6 mIU/l increased the risk of developing a CNS or AMI by more than 2.5 times [OR = 2.44; 95%CI: 1.43–4.15]. The latter indicated that the concentration of PAPP-A protein > 2.9 mIU/l was associated with a more than 4.5-fold increase in the risk of the endpoint including CD, AMI, and the need for revascularization [OR = 4.6; 95%CI: 1.8–11.8]. However, the methodology for determining the PAPP-A protein concentration used in the studies by Lund et al. [ 75 ] (immunofluorometric method) and Heeschen et al. [ 72 ] (immunoenzymatic method - using a reagent manufactured by Roche) differed from that used in our own studies. In our own studies, during the observation of patients in the period of 6–12 months after ACS, a relationship between the concentration of PAPP-A protein and the risk of the occurrence of CE was found again (6.40 ± 4.13mIU/l vs. 24.53 ± 4.23mIU/l; p = 0.004). The value of the concentration of PAPP-A protein ≥ 19.43mIU/l was characterized by 100% sensitivity and almost 100% specificity. Similarly, analyzing the factors influencing the prognosis of patients with STEMI during a 12-month follow-up period, Lund et al. [ 54 ] found that PAPP-A protein concentration above 10 mIU/l was associated with an increased risk of CD and AMI, while Iversen et al. [ 58 ] found a 2.4-fold increase in the risk of AMI or death among patients at low risk of NSTE-ACS in the case of PAPP-A protein concentration > 12.4 mIU/l (24% vs. 10%; p = 0.01). Both Lund et al. [ 54 ] and Danish researchers [ 58 ] took into account the average PAPP-A protein concentration from several measurements. In our studies, a single PAPP-A protein concentration was determined (from a single blood sample taken at admission) using the immunoenzymatic method (Sandwich ELISA). In several years of observation, there have also been reports on the prognostic significance of PAPP-A protein in individuals [ 76 ]. When analyzing adverse events in the observation of patients after ACS, it is impossible not to take restenosis into account. Restenosis is one of the main limitations of PCI. PCI is a method that is not only safe [ 77 ], but also effectively reduces early and late mortality [ 78 – 82 ] and is currently the reference method of treatment for patients with ACS. Angiographically significant restenosis is defined as significant (≥ 50%) narrowing of the vessel lumen at the site of the previous PCI procedure [ 83 ]. According to estimates, up to 50% of patients may experience restenosis, [ 84 – 86 ]. Restenosis may manifest as recurrence or exacerbation of exertional angina and/or ischemic changes in the resting or exercise ECG [ 87 , 88 ]. This usually occurs between 1 and 6 months after PCI. According to some authors, restenosis most often occurs in the 3th to 6th month after PCI [ 89 ]. The above data is in line with our own studies, where clinical indications for control coronary angiography occurred most often between the 3rd and 6th month of observation. During this period, we confirmed restenosis angiographically in every case of clinical suspicion of recurrent stenosis. Out of the total number of 13 restenoses in the entire observation period, 10 (76.9%) manifested within the period of up to 6 months of observation. Reports on the clinical course of restenosis are contradictory. Many authors state that in most patients it manifests as ACS [ 90 , 91 ]. In our own studies, ACS was a clinical manifestation of restenosis in 85% of cases [in over half of the patients (54.55%) AMI, in the remaining - UA]. These data are comparable with the observations of Bainey et al. [ 92 ] (ACS was a clinical manifestation of restenosis in 70.7%, of which NSTE-ACS constituted 52.2%, and STEMI − 18.5%), but different from the observations from the Cleveland Clinic registry [ 93 ] (ACS was a clinical manifestation in 35.9% of restenoses, of which AMI constituted 9.5%, and UA − 26.4%). In our own studies, a statistically significant difference in PAPP-A protein concentration was found in patients with and without restenosis (11.89 ± 6.13mIU/l vs 6.92 ± 5.90mIU/l; p = 0.0005). PAPP-A protein concentration determined on admission turned out to be a variable differentiating patients at a very high risk of restenosis (0.8 ≤ AUC < 0.9). The risk of restenosis was more than 10-fold higher [OR = 10.48; 95%CI: 3.16–34.77] when PAPP-A protein concentration was ≥ 8.17mIU/l. There are no comparative data in the available literature. 5. Limitations The type of test we used to determine the PAPP-A protein represents a significant limitation of our own research. We used a commercially available test with high sensitivity, enabling the detection of low PAPP-A protein concentrations. However, it contains antibodies that react with both the PAPP-A protein molecule and proMBP. The choice of the test was dictated primarily by promising literature data on the usefulness of "ultra sensitive" tests in assessing PAPP-A protein concentrations in patients with ACS [ 74 , 94 ]. Furthermore, as previously mentioned, tests dedicated to detecting the specific epitopes present in the PAPP-A protein homodimer are not commercially available. The study included a relatively small number of patients, specifically only 26 in the UA group, which led to a decrease in the power of the diagnostic tests. This was because univariate analyses failed to confirm the influence of specific individual factors on adverse events. Multivariate analysis was not performed. Additionally, the number of adverse cardiovascular events during 12-month follow-up decreased. However, we jointly analyzed these events in both subgroups and created composite endpoints. 6. Conclusions 1. Elevated PAPP-A protein concentration (≥ 5.83mIU/l) in patients with acute coronary syndrome without persistent ST-segment elevation has limited diagnostic significance (it has lower sensitivity and specificity than Troponin T). 2. Elevated PAPP-A protein concentration (≥ 8.17mIU/l) in patients with acute coronary syndrome without persistent ST-segment elevation increases the risk of coronary restenosis 10-fold in a 12-month follow-up. 3. Elevated PAPP-A protein concentration (≥ 16.34mIU/l) in patients with acute coronary syndrome without persistent ST-segment elevation increases the risk of myocardial infarction almost 33-fold in a 3-month follow-up. 4. Elevated PAPP-A protein concentration in patients with acute coronary syndrome without persistent ST-segment elevation increases the risk of a composite endpoint (myocardial infarction + cardiovascular death) by more than 20-fold (at concentrations: ≥11.44mIU/l in 1-month follow-up, ≥ 10.14mIU/l in 6-month follow-up and ≥ 19.43mIU/l in 12-month follow-up). 5. Elevated PAPP-A protein concentration in patients with acute coronary syndrome without persistent ST-segment elevation increases the risk of exacerbation of coronary artery disease requiring control coronary angiography: by more than 14-fold at a concentration of ≥ 10.7mIU/l in 3-month follow-up and 3-fold at a concentration of ≥ 6.47mIU/l in 6-month follow-up. Declarations Author Contributions: Conceptualization, M.R-K. and M.K.; methodology, M.R-K and M.K; software, M.R-K.; validation, M.R-K..; formal analysis, M.K and A.P-W.; investigation, M.K.; resources, M.R-K.; data curation, M.K. and K.S.; writing—original draft preparation R.F; writing—review and editing, M.R-K. and M.K.; visualization, R.F.; supervision, M.K.; project administration, M.R-K.; funding acquisition, T.P. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the Medical University of Lodz, institutional grant no. 503/1-151-07/ 503-11-001-18. Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Local Ethics Committee (Agreement no. RNN/2/08/KE) of the Medical University of Lodz. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5342541","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":374276125,"identity":"64e088bd-b92a-4c33-9dad-8df9ef69cba9","order_by":0,"name":"Monika Różycka-Kosmalska","email":"","orcid":"","institution":"Medical University of Lodz","correspondingAuthor":false,"prefix":"","firstName":"Monika","middleName":"","lastName":"Różycka-Kosmalska","suffix":""},{"id":374276126,"identity":"7835b2db-46d8-4f95-b236-01ec3d9e8a66","order_by":1,"name":"Rafał Frankowski","email":"","orcid":"","institution":"Medical University of Lodz","correspondingAuthor":false,"prefix":"","firstName":"Rafał","middleName":"","lastName":"Frankowski","suffix":""},{"id":374276127,"identity":"aaf1ed16-2c9f-4b5a-bc5a-7425a52c4880","order_by":2,"name":"Anna Pękala-Wojciechowska","email":"","orcid":"","institution":"Medical University of Lodz","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Pękala-Wojciechowska","suffix":""},{"id":374276128,"identity":"2729c9e3-3dcf-4c36-a902-cc41b10c699f","order_by":3,"name":"Kasper Sipowicz","email":"","orcid":"","institution":"The Maria Grzegorzewska University in Warsaw","correspondingAuthor":false,"prefix":"","firstName":"Kasper","middleName":"","lastName":"Sipowicz","suffix":""},{"id":374276129,"identity":"67901c26-bc87-433c-b427-72508574ed45","order_by":4,"name":"Tadeusz Pietras","email":"","orcid":"","institution":"Medical University of Lodz","correspondingAuthor":false,"prefix":"","firstName":"Tadeusz","middleName":"","lastName":"Pietras","suffix":""},{"id":374276130,"identity":"0aae6052-5604-4cbf-8071-5fa05f5c5ea6","order_by":5,"name":"Marcin Kosmalski","email":"data:image/png;base64,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","orcid":"","institution":"Medical University of Lodz","correspondingAuthor":true,"prefix":"","firstName":"Marcin","middleName":"","lastName":"Kosmalski","suffix":""}],"badges":[],"createdAt":"2024-10-27 18:53:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5342541/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5342541/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":69359873,"identity":"1e713f7a-4a45-4dde-a999-a5f354093f8e","added_by":"auto","created_at":"2024-11-19 14:11:01","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":158882,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve - tested variable: PAPP-A protein concentration in differentiating patients with NSTEMI and UA.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5342541/v1/b96ba2e119cd9c53d5ba2f9f.jpeg"},{"id":69356165,"identity":"6bd000f7-5231-4c05-aeb2-3c26f6b78c21","added_by":"auto","created_at":"2024-11-19 13:47:00","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":350554,"visible":true,"origin":"","legend":"\u003cp\u003eCurves estimating the sensitivity and specificity of PAPP-A protein concentrations.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5342541/v1/8c435ae6169be9d8f5740b89.jpeg"},{"id":69356162,"identity":"f524b512-7732-414d-8d00-0bc502e4ec47","added_by":"auto","created_at":"2024-11-19 13:47:00","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":187943,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve - tested variable: PAPP-A protein concentration in differentiating patients with CE in 1 month of observation.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5342541/v1/2f08a15b95421220b8298dcf.jpeg"},{"id":69357959,"identity":"91060d0b-37a6-45e1-aa86-f7212bf58077","added_by":"auto","created_at":"2024-11-19 13:55:00","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":262776,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve - tested variable: PAPP-A protein concentration in differentiating patients with AMI (A) or the need to perform UCA (B) between 1 and 3 months of CE observation.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5342541/v1/a15aad0b4c3ed46e0a35ff12.jpeg"},{"id":69358338,"identity":"4760b173-e9f8-4293-8db3-db0fb37ab27c","added_by":"auto","created_at":"2024-11-19 14:03:00","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":264607,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve - tested variable: PAPP-A protein concentration in differentiating patients with CE (A) or the need to perform UCA (B) between 3 and 6 months of observation.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5342541/v1/c8dc561e00a333ffbc7896f8.jpeg"},{"id":69356161,"identity":"f12a4ff0-312a-4366-b230-c142945c608c","added_by":"auto","created_at":"2024-11-19 13:47:00","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":147646,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve - tested variable: PAPP-A protein concentration in differentiating patients in whom CE occurred between 6 and 12 months of observation.\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5342541/v1/5d97f4761445c2325e14b020.jpeg"},{"id":69357961,"identity":"b8a0db70-0276-4451-b1be-31f4008c7761","added_by":"auto","created_at":"2024-11-19 13:55:00","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":152642,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve - tested variable: PAPP-A protein concentration in differentiating patients who developed restenosis.\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5342541/v1/af1ae2f02dbafd30b57b94ad.jpeg"},{"id":96892112,"identity":"54f18ce7-872c-4e3c-8e29-8dbdaee83272","added_by":"auto","created_at":"2025-11-27 09:24:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3261831,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5342541/v1/0c8ac4f9-a458-43ae-aa38-bd04df42cd34.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"PAPP-A protein diagnostic and prognostic significance in acute coronary syndromes without persistent ST-T-segment elevation.","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCardiovascular diseases (CVD) are the primary cause of mortality, as well as illness and disability, with 80% of deaths related to CVD observed in low- and middle-income countries. It is known that those with high income have more risk factors of CVD death, however, in comparison to other countries, the decline in CVD-related deaths is faster there [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. According to the European Society of Cardiology, CVDs are the primary cause of mortality which contributes to 45% of all deaths in Europe and 37% in the European Union. Nevertheless, CVD mortality is currently reduced in practically all European nations [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe initial 12-lead electrocardiogram (ECG) is used as the basis for categorizing patients with chest pain into two groups: those with ST-segment elevation ACS (ST Elevation Acute Coronary Syndromes, STE-ACS) and those with non-ST elevation ACS (NSTE-ACS). The second aspect of stratification entails assessing myocardial necrosis markers, primarily by determination of cardiac troponins (cTn).\u003c/p\u003e \u003cp\u003ePregnancy-associated plasma protein A (PAPP-A) is a glycoprotein with a high molecular weight of approximately 200 kDa. It is known as a zinc-binding metalloproteinase and belongs to the family of metalloproteins [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The presence of this substance was initially detected in the plasma of pregnant women in the 1970s by Lin et al [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor several years, reports concerning a novel and distinct function of the \"non-pregnancy\" PAPP-A protein have been published. Bayes-Genis et al. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] utilized immunohistochemical analyses to confirm the existence of PAPP-A protein in ruptured and eroded atherosclerotic plaques. They also observed higher levels of this marker in patients with acute coronary syndrome (ACS) compared to those with stable ischemic heart disease (IHD). Sangorini et al. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] used RT-PCR to illustrate an elevation in PAPP-A levels within atherosclerotic carotid artery plaques. Significantly, the level of this marker was markedly increased in unstable and ruptured plaques compared to stable ones. PAPP-A is elevated 2 to 30 hours after the beginning of chest pain [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Furthermore, PAPP-A seems to be a predictive and evaluative factor of heart failure after AMI [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the cardiovascular system, PAPP-A protein is produced in the vascular endothelium and in arterial smooth muscle cells [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Researchers have observed that the PAPP-A protein in ACS patients differs from the PAPP-A protein in pregnancy, existing as a homodimer consisting of two distinct subunits unrelated to proMBP [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Glerup et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and Stocker et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] demonstrated that the formation of the PAPP-A protein molecule is a complex process that depends on many external factors. The presence of oxidative compounds in the surrounding environment limits the above-mentioned process. The oxidative stress that exists in an unstable atherosclerotic plaque stops proMBP and PAPP-A protein from forming a covalent bond, which then leads to the formation of a homodimer.\u003c/p\u003e \u003cp\u003eThe PAPP-A protein plays various pathophysiological roles. One concept is that the PAPP-A protein acts as a metalloproteinase, causing atherosclerotic plaque destabilization through degradation of the extracellular matrix [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. A recent work presents that serum levels of PAPP-A were markedly elevated in diabetics relative to healthy individuals and exhibited a correlation with aortic augmentation index and coronary calcification, which may indicate its correlation with subclinical atherosclerosis in diabetics [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere is also a thesis that PAPP-A protein has a direct or indirect (IGF-1-mediated) effect on the inflammatory component of atherogenesis, which may contribute to atherosclerotic plaque destabilization [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The concepts of Crea et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and Conti et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] contradict these theories, assuming that the increase in PAPP-A protein levels observed in ACS is the result of repair processes mediated by released IGF-1, which stimulates cells to proliferate and differentiate.\u003c/p\u003e \u003cp\u003eA number of studies evaluating the diagnostic and prognostic role of the PAPP-A protein in ACS indicate its significant importance [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR24 CR25 CR26\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe aim of the study\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe purpose of this study was to determine the diagnostic and prognostic value of PAPP-A protein in patients with Non ST- Elevation Acute Coronary Syndromes (NSTE-ACS) and to answer the question of whether PAPP-A determination can be used in risk stratification in patients with NSTE-ACS.\u003c/p\u003e \u003cp\u003eThe specific objectives were as follows:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eTo assess whether PAPP-A protein determination has diagnostic significance in the diagnosis of acute myocardial infarction (AMI).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTo compare the sensitivity, specificity, predictive value of PAPP-A protein against the classic marker of myocardial necrosis-cardiac troponin T (cTnT).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTo assess whether PAPP-A protein determination is significantly predictive of the occurrence of adverse cardiovascular events and the composite endpoint (including death and AMI) at early follow-up (30 days).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTo assess whether PAPP-A protein determination has prognostic significance for the incidence of adverse cardiovascular events and the composite endpoint (including cardiovascular death and AMI) at long-term follow-up (3, 6 and 12 months).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTo assess whether PAPP-A protein determination has prognostic significance with respect to the occurrence of restenosis.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cp\u003e The Bioethics Committee of the Medical University of Lodz approved the study protocol (RNN/2/08/KE). The study included 100 patients with an initial diagnosis of non-ST segment elevation acute coronary syndrome (Non ST Elevation Acute Coronary Syndromes, NSTE-ACS) treated in the Department of Cardiology, Medical University of Lodz, in 2008\u0026ndash;2009. The inclusion criteria for the study were as follows: clinical diagnosis of ACS up to the 12th hour from the onset of pain, electrocardiographic features of NSTE-ASC: onset of transient ST-segment elevation, new horizontal or downward sloping ST-segment depression of at least\u0026thinsp;\u0026ge;\u0026thinsp;0.5mV in 2 adjacent leads, T-wave inversion\u0026thinsp;\u0026ge;\u0026thinsp;0.1mV or \u0026ldquo;pseudo-normalization\u0026rdquo; of T-waves, or absence of ischemic changes on resting ECG, informed consent to participate in the study signed by the patient. The disqualification criteria included a diagnosis of ACS with persistent ST-segment elevation (STE-ACS), a diagnosis of NSTE-ACS more than 12 hours from the onset of pain, unfractionated or low-molecular-weight heparin therapy, renal failure (creatinine\u0026thinsp;\u0026gt;\u0026thinsp;1.6 mg/dL), an illness or a severe skeletal muscle injury within the past few days, acute or chronic infectious diseases, pregnancy.\u003c/p\u003e \u003cp\u003eIn all patients, an additional blood sample of 5ml was collected for quantification of PAPP-A protein. The PAPP-A US (ultrasensitive) ELISA reagent from DRG (DRG Instruments GmbH, Germany) based on the Enzyme-Linked Immunosorbent Assay (ELISA) method was used for this determination. It is used to detect specific proteins in the test material using mono- or polyclonal antibodies configured with the appropriate enzyme [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The reagent used is based on one variation of the classic ELISA - the so-called \u0026ldquo;sandwich method\u0026rdquo; (Sandwich ELISA).\u003c/p\u003e \u003cp\u003eThe subjects then underwent a twelve-month clinical follow-up. They were interviewed four times (after 1, 3, 6, 12 months of follow-up) about their current health status. We collected information over the phone, during potential follow-up visits, and during in-person visits to the patients' homes. We paid special attention to the need to repeat hospitalization for cardiovascular causes, the need for follow-up coronary angiography, the occurrence of another AMI, the stroke, and the death from cardiovascular causes.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStatistical Research Methodology.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eQuantitative (measurable) variables are presented with basic descriptive statistics: the value of the arithmetic mean and standard deviation (SD), as well as the smallest and largest value, and positional measures - median and quartiles Q25 - quartile I and Q75 - quartile III. For qualitative (nominal) variables, we provide the number of observations for each variant of the variable (N) along with the corresponding percentage (%). The choice of statistical methods for the analysis of measurable variables depended mainly on the distribution of these variables, hence, the hypotheses of normality of distribution were verified using the Shapiro-Wilk normality test. Since the distribution of most variables is not a normal distribution, the non-parametric Mann-Whitney U test was used to compare the analyzed groups from the point of view of measurable variables (if the distribution of a variable in at least one group was not normal). The study groups were compared using the Student's t-test if there was no reason to reject the hypothesis of normal distribution. We used the chi-square test of independence to compare the studied groups in relation to non-measurable variables. The ROC operating-characteristic curve, a graphical representation of changes in sensitivity and specificity of a particular factor, also described the usefulness of the measurable variable PAPP-A in differentiating between NSTEMI and UA patients and predicting adverse events at 12-month follow-up. The higher the ROC curve (larger AUC area under the curve), the better the predictive value of the analyzed factor: AUC\u0026thinsp;\u0026le;\u0026thinsp;0.5 - the factor does not differentiate patients, 0.5\u0026thinsp;\u0026lt;\u0026thinsp;AUC\u0026thinsp;\u0026lt;\u0026thinsp;0.6 - the factor differentiates individuals very poorly, 0.6\u0026thinsp;\u0026le;\u0026thinsp;AUC\u0026thinsp;\u0026lt;\u0026thinsp;0.7 - the factor differentiates patients sufficiently, 0.7\u0026thinsp;\u0026le;\u0026thinsp;AUC\u0026thinsp;\u0026lt;\u0026thinsp;0.8 - the factor differentiates individuals satisfactorily, 0.8\u0026thinsp;\u0026le;\u0026thinsp;AUC\u0026thinsp;\u0026lt;\u0026thinsp;0.9 - the factor differentiates individuals very well, AUC\u0026thinsp;\u0026ge;\u0026thinsp;0.9 - the factor differentiates patients perfectly. We determined certain threshold values of the PAPP-A variable using this curve to predict the occurrence of MI and adverse events.\u003c/p\u003e \u003cp\u003eWe also analyzed the basic measures that determine the usefulness of a particular diagnostic test, such as sensitivity, specificity, chance of a false positive result, chance of a false negative result, positive predictive value, and negative predictive value (percentage of patients with a negative test result who did not have a pk). The predictive value of a positive result of a particular diagnostic test for the occurrence of PCP was also determined by the odds ratio \u0026ndash; OR. We assessed correlations between quantitative variables using the Spearman's rank correlation coefficient (R).\u003c/p\u003e \u003cp\u003eA significance level of p\u0026thinsp;=\u0026thinsp;0.05 was adopted for all statistical tests used. We performed the statistical analysis using the STATISTICA PL 7.1 software package.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe study included 100 patients aged 42 to 83 years (mean 64.2\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5) with a diagnosis of ACS [68 men (M) aged 42 to 83 years (mean 63.4\u0026thinsp;\u0026plusmn;\u0026thinsp;10.3) and 32 women (K) aged 44 to 82 years (mean 66\u0026thinsp;\u0026plusmn;\u0026thinsp;11.03); p\u0026thinsp;=\u0026thinsp;0.252].\u003c/p\u003e \u003cp\u003eThe study included 100 patients with an ACS diagnosis, 74 of whom were eventually diagnosed with NSTEMI and the remaining 26 received a UA diagnosis. We performed further statistical analysis by dividing patients with NSTEMI and UA. Those with NSTEMI and UA did not differ significantly in the presence of coronary risk factors [Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRisk factors for ischemic heart disease in patients with NSTEMI and UA.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk factor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePatients with NSTEMI\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;74)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatients with UA\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63.39\u0026thinsp;\u0026plusmn;\u0026thinsp;10.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.50\u0026thinsp;\u0026plusmn;\u0026thinsp;10.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 [64.86%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 [76.92%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.591\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74 [100.0%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 [100.0%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69 [93.20%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 [88.46%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.439\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 [82.43%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 [80.77%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.849\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 [39.19%]\u003c/p\u003e \u003cp\u003e32 [43.24%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 [34.62%]\u003c/p\u003e \u003cp\u003e10 [38.46%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.679\u003c/p\u003e \u003cp\u003e0,672\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2DM\u003c/p\u003e \u003cp\u003eImpaired fasting blood glucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 [40.54%]\u003c/p\u003e \u003cp\u003e20 [27.03%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 [42.31%]\u003c/p\u003e \u003cp\u003e8 [30.77%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.874\u003c/p\u003e \u003cp\u003e0.715\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamilial occurrence of atherosclerotic diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 [18.92%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 [19.23%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNSTEMI \u0026ndash; Non ST Elevation Myocardial Infarction; T2DM \u0026ndash; type 2 diabetes mellitus, UA \u0026ndash; unstable angina.\u003c/p\u003e \u003cp\u003eThe data are expressed as the number of observations with a given variable variant (N) and its corresponding percentage (%), except age where the data is given as the mean value and standard deviation (SD).\u003c/p\u003e \u003cp\u003e* p-value assessed using the chi-square test, except for the age variables in which the Mann-Whitney U test was used.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAngiographic characteristics.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSelective coronary angiography was performed from access through the radial artery in 83 patients, and from access through the femoral artery in 17 patients, including 5 patients coronary artery bypass grafting (CABG). Significant coronary artery stenosis at coronary angiography was more common in patients with NSTEMI (93.3%) than in pts with UA (76.9%) (p\u0026thinsp;=\u0026thinsp;0.022). The two groups did not differ in the presence of stenosis in 1, 2 or 3 coronary arteries. Nearly \u0026frac14; of patients with UA had only marginal irregularities (vs 6.7% of patients with NSTEMI; p\u0026thinsp;=\u0026thinsp;0.022) [Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCoronary artery stenosis at coronary angiography in pts with NSTEMI and UA.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eChanges in the coronary arteries\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatients with NSTEMI\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;74)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePatients with UA\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e**\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMarginal irregularities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 [6.76%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6 [23.07%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCritical stenoses in the coronary arteries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 [93.24%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20 [76.91%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCritical stenoses in\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 coronary artery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29 [39.19%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6 [23.07%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 coronary arteries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15 [20.27%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7 [26.92%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.481\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3 coronary arteries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25 [33.78%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7 [26.92%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.519\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNSTEMI \u0026ndash; Non ST Elevation Myocardial Infarction; UA \u0026ndash; unstable angina.\u003c/p\u003e \u003cp\u003eThe data are expressed as the number of observations with a given variable variant (N) and its corresponding percentage (%).\u003c/p\u003e \u003cp\u003e**p-value assessed using the chi-square test.\u003c/p\u003e \u003cp\u003eThe bolded results indicate statistically significant differences.\u003c/p\u003e \u003cp\u003eBased on the nature of coronary artery lesions on angiography, the patients were qualified for conservative treatment (17%) or surgical treatment (83%). The patients with UA were significantly more often qualified for conservative treatment (30.8% vs 12.2%; p\u0026thinsp;=\u0026thinsp;0.029).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCharacteristics of selected laboratory parameters, atherogenicity indices, renal function and PAPP-A protein.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e displays the results of laboratory tests that patients with NSTEMI and UA underwent on admission. Since the distribution of most measurable variables does not show a normal distribution, the mean and standard deviation may not be reliable assessments of the variable's mean level and variation. In these cases, we should focus more on the median and interquartile range (Q25-Q75 interval).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of laboratory tests in patients with NSTEMI and UA.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaboratory tests\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePatients with NSTEMI\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;74)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003ePatients with UA\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlycemia [mg/dl]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e141.97 [78.06]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e125.19 [77.23]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.187*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC [mg/dl]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e201.92 [45.17]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e188.12 [43.37]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.179**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL[mg/dl]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e123.97 [41.89]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e112.38 [38.32]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.218**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL[mg/dl]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e50.54 [20.70]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e47.85 [19.76]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.207*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG [mg/dl]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e135.47 [75.06]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e149.62 [76.74]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.301*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine [mg/dl]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0.89 [0.24]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.90 [0.22]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.396*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUric acid [mg/dl]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6.44 [1.09]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.48 [1.86]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.934**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP [mg/l]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.54 [7.56]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.40 [10.15]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.359*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFibrinogen [g/l]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e4.69 [2.11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.13 [2.40]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.376*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeukocytes [10\u003csup\u003e3\u003c/sup\u003e/mm\u003csup\u003e3\u003c/sup\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e8.89 [2.83]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e8.03 [2.48]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.132*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophils [%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e61.79 [10.50]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e61.37 [8.37]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.857*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCRP \u0026ndash; C reactive protein; HDL \u0026ndash; high density lipoproteins; LDL \u0026ndash; low density lipoproteins; NSTEMI \u0026ndash; Non ST Elevation Myocardial Infarction; TC \u0026ndash; total cholesterol; TG \u0026ndash; triglycerides; UA \u0026ndash; unstable angina.\u003c/p\u003e \u003cp\u003eThe data are expressed presented as mean value and standard deviation (SD).\u003c/p\u003e \u003cp\u003e* p-value assessed using the the Mann-Whitney U test.\u003c/p\u003e \u003cp\u003e** p-value assessed using the Student\u0026rsquo;s T-Test.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEchography characteristics of patients with NSTEMI and UA.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe results of echography measurements of patients with NSTEMI and UA are presented in Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEchography characteristics of patients with NSTEMI and UA.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eEF%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatients with NSTEMI\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePatients with UA\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56.85\u0026thinsp;\u0026plusmn;\u0026thinsp;10.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.73\u0026thinsp;\u0026plusmn;\u0026thinsp;13.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.374\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e% of patients with EF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEF\u0026thinsp;\u0026ge;\u0026thinsp;55%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40%\u0026le;EF\u0026thinsp;\u0026lt;\u0026thinsp;55%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEF\u0026thinsp;\u0026lt;\u0026thinsp;40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eEF \u0026ndash; ejection fraction; NSTEMI \u0026ndash; Non ST Elevation Myocardial Infarction; UA \u0026ndash; unstable angina.\u003c/p\u003e \u003cp\u003eThe data are expressed as the percentage (%) of observations, except EF value where the data is given as the mean value\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD).\u003c/p\u003e \u003cp\u003e* \u003cem\u003ep\u003c/em\u003e-value assessed using the chi-square test.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe role of PAPP-A protein in predicting myocardial infarction.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe observed slightly higher mean and median PAPP-A protein concentrations in patients with NSTEMI compared to those with UA, but these differences were not statistically significant [Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e]. Despite this, the ROC curve, a graphical presentation of changes in the sensitivity and specificity of a given factor, described the usefulness of PAPP-A protein concentration in distinguishing patients with NSTEMI from those with UA. The ROC curve and basic statistics, which describe the area under the curve (AUC) for PAPP-A protein concentration as a factor differentiating both study groups are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of PAPP-A protein levels in patients with NSTEMI and UA.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAPP-A protein concentration [mIU/l]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePatients with NSTEMI\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;74)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatients with UA\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e0.253\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNSTEMI \u0026ndash; Non ST Elevation Myocardial Infarction; PAPP-A- Pregnancy-associated plasma protein A; UA \u0026ndash; unstable angina.\u003c/p\u003e \u003cp\u003eThe data are expressed as mean, median, minimum, maximum, IQR (Quartile 1; Quartile 3) and standard deviation (SD).\u003c/p\u003e \u003cp\u003e* \u003cem\u003ep\u003c/em\u003e-value assessed using the Mann-Whitney U test.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic descriptive statistics of the ROC curve describing the usefulness of PAPP-A concentration in differentiating PTS with NSTEMI and UA.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLower limit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpper limit\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.576\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.703\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe data are expressed as area under the curve (AUC), standard error (SE) mean and confidence level (cl) with lower and upper limit.\u003c/p\u003e \u003cp\u003e*\u003cem\u003ep\u003c/em\u003e-value assessed using the chi-square test.\u003c/p\u003e \u003cp\u003eAs it can be seen from Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, the area under the ROC curve is: AUC\u0026thinsp;=\u0026thinsp;0.576. This value is not statistically significant, which means that the PAPP-A protein concentration weakly differentiates patients with NSTEMI and patients with UA.\u003c/p\u003e \u003cp\u003eFurther analysis of the above curve also determined the threshold value of PAPP-A protein concentration, allowing for prediction of NSTEMI occurrence. The cut-off point for the PAPP-A protein value turned out to be 5.83 mIU/l [Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor this PAPP-A protein concentration, the odds ratio (OR) was then calculated. The results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e (OR and 95% CI for OR are given). The OR was 1.37, which means that patients with PAPP-A concentration\u0026thinsp;\u0026ge;\u0026thinsp;5.83 mIU/l had a 1.37-fold higher risk of NSTEMI than those with PAPP-A\u0026thinsp;\u0026lt;\u0026thinsp;5.83 mIU/l.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOR and 95% confidence interval for OR for PAPP-A concentration\u0026thinsp;\u0026ge;\u0026thinsp;5.83mIU/l.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnostic test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-95%CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;95%CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAPP-A\u0026thinsp;\u0026ge;\u0026thinsp;5,83mIU/l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePAPP-A- Pregnancy-associated plasma protein A.\u003c/p\u003e \u003cp\u003eThe data are expressed as odds ratio (OR) and confidence level (Cl).\u003c/p\u003e \u003cp\u003e \u003cb\u003eComparison of sensitivity, specificity and predictive values ​​of PAPP-A protein versus the classic marker of myocardial necrosis cTnT.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFor the PAPP-A protein concentration determined during the ROC curve analysis, which allows for the prediction of NSTEMI (5.83 mIU/l) and for the classic marker of myocardial necrosis, i.e. cTnT, the following measures were calculated to determine the usefulness of the diagnostic test: sensitivity, specificity, chance of a false positive result, chance of a false negative result, positive predictive value (PPV), negative predictive value (NPV) [Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of sensitivity, specificity and predictive values ​​of cTnT and PAPP-A protein.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDiagnostic test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eChance of results\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003efalse\u003c/p\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003efalse\u003c/p\u003e \u003cp\u003enegative\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecTnT- 1 positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.11%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.61%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.89%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecTnT- 2 positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAPP-A\u0026thinsp;\u0026ge;\u0026thinsp;5,83mIU/l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.05%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.85%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76.92%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.17%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e46.15%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45.95%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ecTnT - cardiac Troponin T, NPV - negative predictive value, PAPP-A- Pregnancy-associated plasma protein A, PPV - positive predictive value.\u003c/p\u003e \u003cp\u003eThe data are expressed as percentage (%) of observations.\u003c/p\u003e \u003cp\u003eThe second cTnT test (cTnT-2) provides the best results in predicting myocardial infarction (NSTEMI). The PAPP-A protein with the optimal cut-off point turns out to be a worse indicator even than the first cTnT test. The sensitivity and specificity of the PAPP-A protein test approximates 54%. The positive predictive value is quite high (PPV\u0026thinsp;=\u0026thinsp;76.92%), which means that in the group of patients with PAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;5.83 mIU/l the percentage of patients with myocardial infarction (NSTEMI) was 76.92%.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAssessment of the association of PAPP-A protein with adverse cardiovascular events.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eBecause of the relatively small number of adverse cardiovascular events, these data were considered together for both groups. We also constructed a composite endpoint (CE) that included acute myocardial infarction (AMI) and cardiovascular death (CD).\u003c/p\u003e\n\u003ch3\u003e1-month observation period.\u003c/h3\u003e\n\u003cp\u003eIn patients with the above-defined CE in the first month of follow-up, the PAPP-A protein concentration determined in the ACS was significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than in patients without CE [Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelationship between PAPP-A protein concentration and the risk of CE in 1 month of observation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCE (AMI\u0026thinsp;+\u0026thinsp;CD)\u003c/p\u003e \u003cp\u003e1-month observation period\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c9\" namest=\"c2\"\u003e \u003cp\u003ePAPP-A (mIU/l)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eQ75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.0008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAMI \u0026ndash; acute myocardial infarction; CD \u0026ndash; cardiovascular death; CE \u0026ndash; composite endpoint.\u003c/p\u003e \u003cp\u003eThe data are expressed as as the number (n) of observations, mean, median, minimum, maximum, IQR (Quartile 1; Quartile 3) and standard deviation (SD).\u003c/p\u003e \u003cp\u003e*\u003cem\u003ep\u003c/em\u003e-value assessed using the Mann\u0026mdash;Whitney U test\u003c/p\u003e \u003cp\u003eThe bolded results indicate statistically significant differences.\u003c/p\u003e \u003cp\u003eThe ROC curve [Figure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e] and basic statistics describing the area under the curve (AUC) [Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e] for PAPP-A protein concentration as a factor differentiating patients with or without CE are presented below:\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic descriptive statistics of the ROC curve - tested variable: PAPP-A protein concentration in patients with and without CE in the 1st month of observation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLower limit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUpper limit\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdverse event\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCE \u0026ndash; composite endpoint.\u003c/p\u003e \u003cp\u003eThe data are expressed as area under the curve (AUC), standard error (SE) mean and confidence level (cl) with lower and upper limit.\u003c/p\u003e \u003cp\u003e*\u003cem\u003ep\u003c/em\u003e-value assessed using the chi-square test.\u003c/p\u003e \u003cp\u003eThe bolded results indicate statistically significant differences.\u003c/p\u003e \u003cp\u003eThe analysis shows that the PAPP-A protein concentration determined on admission to hospital is a variable that differentiates patients at risk of AMI or CD in an excellent way (AUC\u0026thinsp;\u0026ge;\u0026thinsp;0.9). Further analysis of the ROC curve revealed a PAPP-A protein concentration cut-off point that significantly correlated with the risk of occurrence of the above-defined CE. The optimal cut-off point turned out to be 11.44 mIU/l. Then, the variable of PAPP-A protein concentration together with the mentioned cut-off point was treated as a diagnostic test that allows for prediction of the occurrence of CE. We obtained the results presented in Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e by analyzing the basic measures determining the usefulness of a given diagnostic test (sensitivity, specificity, positive and negative predictive value).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSensitivity, specificity, PPV, NPV for PAPP-A concentration\u0026thinsp;\u0026ge;\u0026thinsp;11.44 mIU/l (1 month of observation).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnostic test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNPV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;11.44mIU/l.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83.33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e98.81%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNPV - negative predictive value, PAPP-A- Pregnancy-associated plasma protein A, PPV - positive predictive value.\u003c/p\u003e \u003cp\u003eThe presented analysis shows that this value was characterized by high sensitivity (83.33%) and specificity (88.30%). The probability that CE will not occur at a PAPP-A protein concentration of \u0026lt;\u0026thinsp;11.44 mIU/l is also very high (NPV- 98.81%). The predictive value of a positive result of a given diagnostic test for the occurrence of CE was also determined based on the odds ratio - OR. For this cut-off point, the OR was 37.73, which means that if the PAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;11.44 mIU/l, the risk of CE is almost 38 times higher than in the case when the PAPP-A protein concentration is \u0026lt;\u0026thinsp;11.44 mIU/l, with a 95% confidence interval for OR [95%CI: 8.14\u0026ndash;74.83].\u003c/p\u003e \u003cp\u003e \u003cb\u003ePeriod between 1 and 3 months of observation.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn 3-month follow-up, a statistically significant association between PAPP-A protein concentration and the risk of AMI (14.59\u0026thinsp;\u0026plusmn;\u0026thinsp;9.17mIU/l vs 6.73\u0026thinsp;\u0026plusmn;\u0026thinsp;4.92mIU/l; p\u0026thinsp;=\u0026thinsp;0.042) and the need for unplanned coronary angiography (UCA) (11.64\u0026thinsp;\u0026plusmn;\u0026thinsp;6.65mIU/l vs 6.62\u0026thinsp;\u0026plusmn;\u0026thinsp;5.08mIU/l; p\u0026thinsp;=\u0026thinsp;0.004) was observed. Table\u0026nbsp;\u003cspan refid=\"Tab12\" class=\"InternalRef\"\u003e12\u003c/span\u003e presents basic descriptive statistics of ROC curves (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) that describe the usefulness of PAPP-A protein in predicting the aforementioned adverse events.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab12\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 12\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic descriptive statistics of the ROC curve - test variable: PAPP-A protein concentration in predicting AMI or the need for UCA (from 1 to 3 months of follow-up).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLower limit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUpper limit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdverse event\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.042\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.914\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAMI \u0026ndash; acute myocardial infarction; UCA \u0026ndash; unplanned coronary angiography.\u003c/p\u003e \u003cp\u003eThe data are expressed as area under the curve (AUC), standard error (SE) mean and confidence level (cl) with lower and upper limit.\u003c/p\u003e \u003cp\u003e*\u003cem\u003ep\u003c/em\u003e-value assessed using the chi-square test.\u003c/p\u003e \u003cp\u003eThe bolded results indicate statistically significant differences.\u003c/p\u003e \u003cp\u003eIn the case of both aforementioned adverse events, the value of 0.7\u0026le;AUC\u0026thinsp;\u0026lt;\u0026thinsp;0.8 indicates that PAPP-A protein differentiates patients in a satisfactory manner. The optimal cut-off points (PAPP-A protein concentration), determined during further analysis of the ROC curve, turned out to be values ​​\u0026ge;16.34 mIU/l for AMI and \u0026ge;\u0026thinsp;10.7 mIU/l for the need to perform UCA. The determined threshold values ​​of PAPP-A protein concentration are characterized by moderate sensitivity (60%) and PPV (42.86%), with high specificity (\u0026gt;\u0026thinsp;90%) and NPV (\u0026gt;\u0026thinsp;95%) [Table\u0026nbsp;\u003cspan refid=\"Tab13\" class=\"InternalRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab13\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 13\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSensitivity, specificity, PPV, NPV for the selected diagnostic test (PAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;16.34 mIU/l for AMI and \u0026ge;\u0026thinsp;10.7 mIU/l for the need to perform UCA) (from 1 to 3 months of observation).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnostic test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNPV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;16.34mIU/l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.86%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e97.75%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAPP-A protein concentration -A\u0026thinsp;\u0026ge;\u0026thinsp;10.7mIU/l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.86%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95.12%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNPV - negative predictive value, PAPP-A- Pregnancy-associated plasma protein A, PPV - positive predictive value.\u003c/p\u003e \u003cp\u003eParticularly high probability of AMI occurrence was found in pts with PAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;16.34 mIU/l. In this group of patients the risk is almost 33 times higher compared to patients with PAPP-A protein concentration below this value [OR\u0026thinsp;=\u0026thinsp;32.63; 95%CI: 7.52- 141.48]\u003c/p\u003e \u003cp\u003eIn pts with PAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;10.7 mIU/l the risk of UCA was almost 15 times higher [OR\u0026thinsp;=\u0026thinsp;14.63; 95%CI: 4.30-49.69].\u003c/p\u003e \u003cp\u003e \u003cb\u003ePeriod between 3 and 6 months of observation.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eDuring the next 3-month observation period, a relationship between PAPP-A protein concentration and the risk of CE (14.93\u0026thinsp;\u0026plusmn;\u0026thinsp;7.85mIU/l vs 6.80\u0026thinsp;\u0026plusmn;\u0026thinsp;5.10mIU/l; p\u0026thinsp;=\u0026thinsp;0.017) and the need for UCA (8.86\u0026thinsp;\u0026plusmn;\u0026thinsp;4.63mIU/l vs 6.77\u0026thinsp;\u0026plusmn;\u0026thinsp;5.25mIU/l; p\u0026thinsp;=\u0026thinsp;0.044) was observed. Table\u0026nbsp;\u003cspan refid=\"Tab14\" class=\"InternalRef\"\u003e14\u003c/span\u003e presents basic descriptive statistics of ROC curves [Figure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e], which describe the usefulness of PAPP-A protein testing in predicting the aforementioned adverse events.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab14\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 14\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic descriptive statistics of the ROC curve - tested variable: PAPP-A protein concentration in predicting the occurrence of CE or the need for UCA (from 3 to 6 months of observation).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLower limit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUpper limit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdverse event\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.044\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.879\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCE \u0026ndash; composite endpoint; UCA \u0026ndash; unplanned coronarography angiography.\u003c/p\u003e \u003cp\u003eThe data are expressed as area under the curve (AUC), standard error (SE) mean and confidence level (cl) with lower and upper limit.\u003c/p\u003e \u003cp\u003e*\u003cem\u003ep\u003c/em\u003e-value assessed using the chi-square test.\u003c/p\u003e \u003cp\u003eThe bolded results indicate statistically significant differences.\u003c/p\u003e \u003cp\u003eThe analysis shows that the PAPP-A protein concentration determined on admission is a variable differentiating in a satisfactory manner patients in whom UCA will be required (0.7(AUC\u0026thinsp;\u0026lt;\u0026thinsp;0.8), while this differentiation was very good in those at risk of AMI or cardiovascular death (0.8(AUC\u0026thinsp;\u0026lt;\u0026thinsp;0.9). The best cut-off points (PAPP-A protein concentration) were found by looking more closely at the ROC curve. They were \u0026ge;\u0026thinsp;10.14 mIU/l for CE and \u0026ge;\u0026thinsp;6.47 mIU/l for NK. The level of PAPP-A protein concentration that was found to be the threshold for CE had a high level of specificity (\u0026gt;\u0026thinsp;85%) and sensitivity (75%). The optimal cut-off point for PAPP-A protein level\u0026thinsp;\u0026ge;\u0026thinsp;6.47 mIU/l was characterized by only moderate sensitivity and specificity (approx. 60%). High NPV values indicate a very high probability of no occurrence of a specific adverse event. At PAPP-A protein concentration\u0026thinsp;\u0026lt;\u0026thinsp;10.14 mIU/l the probability of not having CE is almost 99%, while at PAPP-A protein concentration\u0026thinsp;\u0026lt;\u0026thinsp;6.47 mIU/l the probability of no necessity to perform UCA is almost 99% [Table\u0026nbsp;\u003cspan refid=\"Tab15\" class=\"InternalRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab15\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 15\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSensitivity, specificity, PPV, NPV for the selected diagnostic test (PAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;10.14 mIU/l for CE and \u0026ge;\u0026thinsp;6.47 mIU/l for the need to perform UCA) (from 3 to 6 months of observation).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnostic test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNPV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;10.14mIU/l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86.96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e98.77%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;6.47mIU/l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.67%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.63%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.38%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e94.64%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNPV - negative predictive value, PAPP-A- Pregnancy-associated plasma protein A, PPV - positive predictive value.\u003c/p\u003e \u003cp\u003eThe risk of CE in patients with PAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;10.14 mIU/l was 20 times higher [OR\u0026thinsp;=\u0026thinsp;20; 95%CI: 3.45-115.96]. In patients with PAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;6.47 mIU/l the risk of UCA was more than 3 times higher [OR\u0026thinsp;=\u0026thinsp;3.21; 95%CI: 0.80-12.94].\u003c/p\u003e \u003cp\u003e \u003cb\u003ePeriod between 6 and 12 months of observation.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eDuring the next 6 months of observation, a relationship was found between PAPP-A protein concentration and the risk of CE (6.40\u0026thinsp;\u0026plusmn;\u0026thinsp;4.13mIU/l vs. 24.53\u0026thinsp;\u0026plusmn;\u0026thinsp;4.23mIU/l; p\u0026thinsp;=\u0026thinsp;0.004). Basic descriptive statistics of ROC curves [Figure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e] describing the usefulness of PAPP-A protein concentration in predicting the aforementioned adverse events are presented in Table\u0026nbsp;\u003cspan refid=\"Tab16\" class=\"InternalRef\"\u003e16\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab16\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 16\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic descriptive statistics of the ROC curve - tested variable: PAPP-A protein concentration in patients with CE between 6 and 12 months of observation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLower limit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUpper limit\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdverse event\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCE \u0026ndash; composite endpoint.\u003c/p\u003e \u003cp\u003eThe data are expressed as area under the curve (AUC), standard error (SE) mean and confidence level (cl) with lower and upper limit.\u003c/p\u003e \u003cp\u003e*\u003cem\u003ep\u003c/em\u003e-value assessed using the chi-square test.\u003c/p\u003e \u003cp\u003eThe bolded results indicate statistically significant differences.\u003c/p\u003e \u003cp\u003eThe analysis clearly shows that the PAPP-A protein concentration determined on admission is a variable that differentiates patients at risk of AMI or CD in a perfect way (AUC\u0026thinsp;\u0026ge;\u0026thinsp;0.9). AUC equal to 1 means perfect discrimination between the groups. After looking more closely at the ROC curve, we found that the best cut-off points for CE were values greater than or equal to 19.43 mIU/l for PAPP-A protein concentration. The PAPP-A protein level determined as the threshold value for the occurrence of CE was characterized by 100% sensitivity and almost 100% specificity [Table\u0026nbsp;\u003cspan refid=\"Tab17\" class=\"InternalRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab17\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 17\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSensitivity, specificity, PPV, NPV for PAPP-A concentration\u0026thinsp;\u0026ge;\u0026thinsp;19.43 mIU/l for CE (from 6 to 12 months of observation).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnostic test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNPV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;19.43mIU/l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98.91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNPV - negative predictive value, PAPP-A- Pregnancy-associated plasma protein A, PPV - positive predictive value.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cb\u003eAssociation between PAPP-A protein concentration and the occurrence of restenosis.\u003c/b\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eA statistically significant difference in PAPP-A protein concentration was observed between patients with restenosis and those without restenosis (11.89\u0026thinsp;\u0026plusmn;\u0026thinsp;6.13mIU/l vs 6.92\u0026thinsp;\u0026plusmn;\u0026thinsp;5.90mIU/l; p\u0026thinsp;=\u0026thinsp;0.0005). Table\u0026nbsp;\u003cspan refid=\"Tab18\" class=\"InternalRef\"\u003e18\u003c/span\u003e presents the basic descriptive statistics of ROC curves [Figure \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e], which describe the usefulness of PAPP-A protein concentration in predicting restenosis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab18\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 18\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic descriptive statistics of the ROC curve - tested variable: PAPP-A protein concentration in predicting restenosis during 12 months of follow-up.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLower limit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUpper limit\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRestenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.802\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.910\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe data are expressed as area under the curve (AUC), standard error (SE) mean and confidence level (cl) with lower and upper limit.\u003c/p\u003e \u003cp\u003e*\u003cem\u003ep\u003c/em\u003e-value assessed using the chi-square test.\u003c/p\u003e \u003cp\u003eThe bolded results indicate statistically significant differences.\u003c/p\u003e \u003cp\u003eAs it results from the above analysis, the PAPP-A protein concentration determined on admission is a variable differentiating patients at risk of restenosis in a very good way (0.8(AUC\u0026thinsp;\u0026lt;\u0026thinsp;0.9). The optimal cut-off point turned out to be the PAPP-A protein concentration of \u0026ge;\u0026thinsp;8.17 mIU/l. This value was characterized by quite good sensitivity (76.92%) and specificity (75.86%) as well as high NPV value (95.65%) [Table\u0026nbsp;\u003cspan refid=\"Tab19\" class=\"InternalRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab19\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 19\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSensitivity, specificity, PPV, NPV for PAPP-A concentration\u0026thinsp;\u0026ge;\u0026thinsp;8.17mIU/l in predicting restenosis in 12-month follow-up.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnostic test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNPV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;8.17mIU/l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.92%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.86%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e96.65%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNPV - negative predictive value, PAPP-A- Pregnancy-associated plasma protein A, PPV - positive predictive value.\u003c/p\u003e \u003cp\u003eIn patients with PAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;8.17 mIU/l the risk of restenosis was more than 10-fold higher [OR\u0026thinsp;=\u0026thinsp;10.48; 95%CI: 3.16\u0026ndash;34.77].\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eEvery year, over 7\u0026nbsp;million individuals worldwide suffer from ACS [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In 2019 in Poland, circa 100,000 patients were treated for ACS, and NSTE-ACS accounted for approximately 75% of cases [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. NSTE-ACS is the most common type of ACS, constituting the main cause of hospitalization due to ACS [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Observations show a decreasing proportion of STEMI cases in high-income countries [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConsidering the large number of patients, the variety of symptoms, and the different prognosis in individual groups of patients with NSTE-ACS, early risk stratification, aimed at identifying both patients at high risk of death or adverse cardiovascular events and \"low risk\" patients, in whom expensive and potentially dangerous invasive treatment methods bring little benefit, is extremely important.\u003c/p\u003e \u003cp\u003eThe ECG continues to play a fundamental role in assessing patients with ACS. Biochemical tests have been part of the diagnostic toolkit since the 1950s. The basis for establishing the dominant role of cTn in the diagnosis of patients with ACS was the announcement in 2000 by the European Society of Cardiology (ESC) and the American College of Cardiology (ACC) announced a new definition of AMI [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Currently, the latest guidelines refer to the fourth universal definition of myocardial infarction [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our own studies, elevated cTnT concentration on admission was more common, affecting 57% of patients, which also included 77% of patients with a final diagnosis of NSTEMI. This may be related to the relatively long time elapsed from the onset of pain to the moment the patient was admitted to the hospital. For the entire group, it was 8.5 hours (\u0026plusmn;\u0026thinsp;3.5) on the average and was slightly shorter for patients with NSTEMI (8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6 hours) compared to those with UA (9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7 hours), but this difference did not reach statistical significance (p\u0026thinsp;=\u0026thinsp;0.09). Despite its indisputable advantages, cTn concentration determination in the diagnosis of ACS is not free from limitations. Therefore, an ideal marker of necrosis/ischemia, characterized by high sensitivity, specificity, and specificity, is still sought. Acceptance of the analysis costs is also important [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePAPP-A protein is considered to be a \u0026ldquo;promising\u0026rdquo; marker. Researchers observed that in ACS, the PAPP-A marker of plaque instability is significantly elevated [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. What is more, serum PAPP-A level elevations may occur before or even in the absence of myocardial necrosis [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our own studies, no significant difference in PAPP-A protein concentrations was found between patients with NSTEMI and UA (7.93\u0026thinsp;\u0026plusmn;\u0026thinsp;6.35mIU/l vs 6.52\u0026thinsp;\u0026plusmn;\u0026thinsp;5.45mIU/l; p\u0026thinsp;=\u0026thinsp;0.253). Similar observations were reported by You et al. (2.42\u0026thinsp;\u0026plusmn;\u0026thinsp;2.98mIU/l vs 2.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.68mIU/l; p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] and Bayes-Genis et al. (14.9mIU/l in patients with UA vs 20.6mIU/l in patients with AMI; p\u0026thinsp;=\u0026thinsp;0.5) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn contrast, a statistically significant difference between PAPP-A protein concentrations between patients with STEMI and NSTEMI and patients with UA (PAPP-A protein concentrations were 30.3\u0026thinsp;\u0026plusmn;\u0026thinsp;30.11mIU/l in STEMI, 21.13\u0026thinsp;\u0026plusmn;\u0026thinsp;24.71mIU/l in NSTEMI, 19.73\u0026thinsp;\u0026plusmn;\u0026thinsp;19.78mIU/l in UA, respectively, p\u0026thinsp;=\u0026thinsp;0.045) was demonstrated by H\u0026aacute;jek et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. It is in line with the observations of Mehrpooya et al.. In their study, PAPP-A protein concentrations were significantly lower in subjects with UA compared to those with STEMI [Median (IQR): 12.8 (73.3) vs 116.0 (220.0); p\u0026thinsp;\u0026lt;\u0026thinsp;0.001] or NSTEMI [Median (IQR): 12.8 (73.3) vs 108.0 (128.0); p\u0026thinsp;=\u0026thinsp;0.003] [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. A study by Schaub et al. also revealed that individuals with AMI have higher concentrations of PAPP-A than those with other diagnoses, including UA [PAPP-A 4.6 (4.0 \u0026minus;\u0026thinsp;9.3) vs 4.0 (4.0 \u0026minus;\u0026thinsp;5.6) mIU/L, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001]. On the other hand, no significant differences were observed in PAPP-A levels between STEMI and NSTEMI [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDifferent conclusions are drawn from the work of Spanish researchers. Dominguez-Rodriguez et al. [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] did not note a significant difference in PAPP-A protein concentration between patients with AMI and the control group consisting of people without a previous history of CAD (1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07mIU/l vs 1.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02mIU/l; p\u0026thinsp;=\u0026thinsp;0.54), which can be explained primarily by the type of diagnostic test used.\u003c/p\u003e \u003cp\u003eInitially, PAPP-A protein was determined using tests commonly used in gynecology for screening for Down syndrome [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. However, it was noticed that the concentration of PAPP-A protein in pregnant women is many times higher than in men and non-pregnant women [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] and can even reach 3655 mIU/l [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Therefore, it became necessary to create tests capable of detecting low concentrations of PAPP-A protein (so-called \"ultra sensitive\" tests). The commonly available tests may contain both antibodies reacting with both the PAPP-A protein molecule and proMBP, or antibodies specific only for the PAPP-A protein molecule. Thus, the former detect the PAPP-A protein in the form of a tetramer (2 PAPP-A protein molecules bound to 2 proMBP molecules). A direct consequence of the aforementioned properties is therefore the detection of PAPP-A protein originating from cells of the female reproductive system, kidneys, large intestine and bone marrow [\u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] and the possibility of failure to detect the ACS-specific PAPP-A homodimer [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Currently, the use of the second type of diagnostic tests, which contain antibodies that react only with the PAPP-A protein molecule, is increasing significantly. Due to the possibility of changing the structure of the PAPP-A protein (in the absence of the proMBP molecule), antibodies contained in such tests may also fail to detect the PAPP-A protein associated with ACS [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. There are also tests specially prepared to detect PAPP-A protein molecules specific for ACS (taking into account specific epitopes), but they are not commercially available [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTherefore, it is not surprising that we observed the aforementioned discrepancy in PAPP-A protein concentrations. The higher the PAPP-A protein concentration (5.83 mIU/l) that we found in our own study during further analysis, the lower the risk of NSTEMI was found to be (OR\u0026thinsp;=\u0026thinsp;1.37; 95%CI: 8.14\u0026ndash;74.83). In fact, the PAPP-A protein with the higher cut-off point was even less useful for diagnosing NSTEMI than the first cTnT test. The sensitivity and specificity of the PAPP-A protein test was approximately 54% (respectively, these measures for the above cTnT test were: specificity \u0026minus;\u0026thinsp;100%, sensitivity \u0026minus;\u0026thinsp;58.1%). Given that PAPP-A protein has a pretty high positive predictive value (PPV\u0026thinsp;=\u0026thinsp;76.9%), NSTEMI was found in more than 75% of patients whose PAPP-A protein concentration was at least 5.83 mIU/l. For comparison, Bayes-Genis et al. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] in a study published in 2001 in The New England Journal of Medicine, including 69 individuals (including 17 with AMI, 20 with UA, 19 with stable CAD, and 13 without a previous history of CAD) indicated that PAPP-A protein concentration\u0026thinsp;\u0026gt;\u0026thinsp;10 mIU/l allows for the identification of patients with ACS with a sensitivity close to 90% and specificity over 80%. Czech study showed the significant increase of PAPP-A levels in ACS heparin-naive individuals with high positive (95.7%) and lower negative predictive values (47.7%), furthermore in NSTE-ACS no differences were shown in AUC compared to TnI [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. On the other hand, a study by Schaub et al. considers PAPP-A to be of little value in the diagnosis of ACS with an AUC of 0.61, which was inferior to troponin [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSlightly higher PAPP-A protein concentration values ​​allowing for identification of patients with ACS with the highest sensitivity and specificity were reported by H\u0026aacute;jek et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. For individual types of ACS, these values ​​were in the range of 10.65\u0026ndash;14.75 mIU/l (with AUC values ​​from 0.613 to 0.919). The time from the onset of symptoms to the moment of blood collection for the determination of PAPP-A protein concentration varied in individual studies. In our own studies, blood was collected after the patients were admitted to the hospital (it was 8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6 hours from the onset of pain in patients with NSTEMI, and among pts UA \u0026minus;\u0026thinsp;9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7 hours). It was pretty much the same as the time it took to collect blood in the study by Bayes-Genis et al. (8.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3 hours for patients with AMI and 9.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9 hours for the UA group) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], but different from that in the Czech-German studies (in STEMI \u0026minus;\u0026thinsp;4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3 hours; in NSTEMI \u0026minus;\u0026thinsp;9.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1 hours, in UA \u0026minus;\u0026thinsp;15.5\u0026thinsp;\u0026plusmn;\u0026thinsp;9.5 hours) [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. However, the data on the kinetics of PAPP-A protein concentrations are rather modest, although it appears that in the case of STEMI the concentrations normalize rapidly [\u003cspan additionalcitationids=\"CR55\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], while in NSTE-ACS the elevated concentrations remain at a similar level for 24\u0026ndash;36 hours [\u003cspan additionalcitationids=\"CR57\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe noted variation in PAPP-A protein levels may potentially be affected by other variables, such as heparin, often used in ACS treatment. The capacity of the PAPP-A protein to bind heparin has been recognized for an extended period [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e], and the precise binding site was delineated in 2004 by Weyer et al. [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. In vitro, heparin and PAPP-A protein are known to compete for binding on the cell surface [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Subsequent research has unequivocally shown an elevation in PAPP-A protein levels due to the effects of both unfractionated heparin and low-molecular-weight heparins [\u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. The precise mechanism of this phenomena remains unidentified. One hypothesis posits that the fast elevation in PAPP-A protein concentration upon heparin administration, regardless of the type, results from the release of PAPP-A protein from the endothelial cell surface in arteries with very high blood flow. In our research, one of the exclusion criteria was the administration of unfractionated or low-molecular-weight heparin treatment. This criteria was excluded from the research conducted by Bayes-Genis et al. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] and the investigations of H\u0026aacute;jek et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTroponins are not only critical in diagnosing individuals with ACS, but they also serve as an exceptional prognostic tool. Extensive data supporting the efficacy of their determination in risk assessment for patients with NSTE-ACS has established cTn as the foundation for risk classification in this cohort [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan additionalcitationids=\"CR66\" citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn view of a number of reports on the significance of PAPP-A protein as a prognostic factor in patients with ACS [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan additionalcitationids=\"CR69 CR70\" citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e], our own studies assessed its association with adverse events in a 12-month follow-up. Given the small number of adverse cardiovascular events observed, they were considered in the entire NSTE-ACS group. A CE including AMI and CD was also constructed.\u003c/p\u003e \u003cp\u003eIn the 1st month of observation (taking into account also the people who died during hospitalization), a relationship was observed between the concentration of PAPP-A protein determined in ACS and the risk of the occurrence of CE (20.59\u0026thinsp;\u0026plusmn;\u0026thinsp;10.85mIU/l vs. 6.73\u0026thinsp;\u0026plusmn;\u0026thinsp;4.69mIU/l; p\u0026thinsp;=\u0026thinsp;0.0008). The cut-off point of the concentration of PAPP-A protein (\u0026ge;\u0026thinsp;11.44mIU/l) determined during further analysis was associated with a nearly 38-fold higher risk of CE [OR\u0026thinsp;=\u0026thinsp;37.73; 95%CI: 8.14\u0026ndash;74.83]. It was also characterized by very high sensitivity (83.33%) and specificity (88.30%), while the probability that at the concentration of PAPP-A protein\u0026thinsp;\u0026lt;\u0026thinsp;11.44mIU/l CE would not occur was almost 99% (NPV- 98.81%).\u003c/p\u003e \u003cp\u003eA similar cut-off point, with the same endpoint, was determined by Heeschen et al. [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e], whereby in the case of PAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;12.6 mIU/l the risk of CD or AMI was only more than twice as high [OR\u0026thinsp;=\u0026thinsp;2.32; 95%CI: 1.32\u0026ndash;4.26]. Such a significant difference may be due primarily to the different numbers and characteristics of the study groups. Only 323 patients in the Heeschen et al. group of 644 patients admitted to the hospital with chest pain received a final diagnosis of ACS, while the remaining 105 patients received a diagnosis of stable IHD, 19 patients experienced an exacerbation of heart failure, and 197 patients had a non-cardiac cause of chest pain [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. In Bonaca et al. [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e] study at presentation, PAPP-A levels exceeding 6.0 \u0026micro;IU/ml were associated with increased rates of CD or AMI at 30 days (7.4% vs. 3.7%, hazard ratio [HR]: 2.01; 95% confidence interval [CI]: 1.43 to 2.82; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and at 1 year (14.9% vs. 9.7%, HR: 1.63; 95% CI: 1.29 to 2.05; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). At 30 days, PAPP-A was also associated with increased incidences of AMI (HR: 1.82; 95% CI: 1.22 to 2.71, p\u0026thinsp;=\u0026thinsp;0.003) and CD (HR: 1.94; 95% CI: 1.07 to 3.52, p\u0026thinsp;=\u0026thinsp;0.027).\u003c/p\u003e \u003cp\u003eIn the same observation period, Laterza et al. [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e] also noticed a relationship between PAPP-A protein concentration and the risk of a complex endpoint including: CD, AMI and the need for revascularization. However, the threshold concentration value determined was much lower (0.22 mIU/l), and was also characterized by lower sensitivity and specificity (66.7% and 51.1%, respectively), while the risk of the endpoint defined above increased 2-fold [OR\u0026thinsp;=\u0026thinsp;1.9; 95%CI: 0.9\u0026ndash;4.1]. Such a large discrepancy in PAPP-A protein concentration should be associated with the use of a different test (American company DSL) for the determination.\u003c/p\u003e \u003cp\u003eIn our own studies, a statistically significant relationship was observed in the 3-month follow-up between the PAPP-A protein concentration and the risk of AMI (14.59\u0026thinsp;\u0026plusmn;\u0026thinsp;9.17mIU/l vs 6.73\u0026thinsp;\u0026plusmn;\u0026thinsp;4.92mIU/l; p\u0026thinsp;=\u0026thinsp;0.042) and the need for unplanned coronary angiography (UCA) (11.64\u0026thinsp;\u0026plusmn;\u0026thinsp;6.65mIU/l vs 6.62\u0026thinsp;\u0026plusmn;\u0026thinsp;5.08mIU/l; p\u0026thinsp;=\u0026thinsp;0.004).\u003c/p\u003e \u003cp\u003eThe determined threshold values ​​of PAPP-A protein concentration (\u0026ge;\u0026thinsp;16.34mIU/l for AMI and \u0026ge;\u0026thinsp;10.7mIU/l for the need for NA) were characterized by high specificity (\u0026gt;\u0026thinsp;90%) with moderate sensitivity of the test (60%). Among patients with PAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;16.34mIU/l, the risk of AMI was almost 33 times higher [OR\u0026thinsp;=\u0026thinsp;32.63; 95%CI: 7.52-141.48], and the risk of NK was almost 15 times higher in the case of PAPP-A protein concentration\u0026thinsp;\u0026ge;\u0026thinsp;10.7mIU/l [OR\u0026thinsp;=\u0026thinsp;14.63; 95%CI: 4.30-49.69].\u003c/p\u003e \u003cp\u003eSimilarly, a relationship between PAPP-A protein level and the risk of adverse events (AMI or death) during a 3-month follow-up was found by Iversen et al. [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] who evaluated 415 patients with low-risk NSTE-ACS (no ECG changes and negative cTn test result). Danish investigators found that in the case of PAPP-A protein level\u0026thinsp;\u0026gt;\u0026thinsp;12.4 mIU/l (evaluated in the vast majority of patients from 2 or 3 blood samples) the risk of AMI or death was 3.7 times higher. Additionally, when comparing patients with levels\u0026thinsp;\u0026lt;\u0026thinsp;4 mIU/l and \u0026gt;\u0026thinsp;12.4 mIU/l, the risk of death in the latter was almost 12 times higher (11% vs 1%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; RR\u0026thinsp;=\u0026thinsp;11.9).\u003c/p\u003e \u003cp\u003eDuring the next observation period (up to 6 months), our own studies found a relationship between PAPP-A protein concentration and the risk of CE (14.93\u0026thinsp;\u0026plusmn;\u0026thinsp;7.85mIU/l vs 6.80\u0026thinsp;\u0026plusmn;\u0026thinsp;5.10mIU/l; p\u0026thinsp;=\u0026thinsp;0.017) and the need for UCA (8.86\u0026thinsp;\u0026plusmn;\u0026thinsp;4.63mIU/l vs 6.77\u0026thinsp;\u0026plusmn;\u0026thinsp;5.25mIU/l; p\u0026thinsp;=\u0026thinsp;0.044). For CE, the optimal cut-off point was \u0026ge;\u0026thinsp;10.14mIU/l. After exceeding it, the risk of PE was 20 times higher [OR\u0026thinsp;=\u0026thinsp;20; 95%CI: 3.45-115.96]. This value was characterized by quite high sensitivity (75%) and specificity (\u0026gt;\u0026thinsp;85%). What is particularly interesting, at PAPP-A protein concentration\u0026thinsp;\u0026lt;\u0026thinsp;10.14 mIU/l the probability of not developing CE was almost 99%.\u003c/p\u003e \u003cp\u003eIn the case of PAPP-A protein concentration\u0026thinsp;\u0026lt;\u0026thinsp;6.47 mIU/l, the probability of not having to perform UCA was 99%, and after exceeding this value the risk increased more than 3-fold [OR\u0026thinsp;=\u0026thinsp;3.21; 95%CI: 0.80-12.94]. The optimal cut-off point was characterized by moderate sensitivity and specificity (approx. 60%).\u003c/p\u003e \u003cp\u003eHeeschen et al. [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e] and Lund et al. [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e] also assessed the risk of adverse events during a 6-month follow-up. One study found that PAPP-A protein levels above 12.6 mIU/l increased the risk of developing a CNS or AMI by more than 2.5 times [OR\u0026thinsp;=\u0026thinsp;2.44; 95%CI: 1.43\u0026ndash;4.15]. The latter indicated that the concentration of PAPP-A protein\u0026thinsp;\u0026gt;\u0026thinsp;2.9 mIU/l was associated with a more than 4.5-fold increase in the risk of the endpoint including CD, AMI, and the need for revascularization [OR\u0026thinsp;=\u0026thinsp;4.6; 95%CI: 1.8\u0026ndash;11.8]. However, the methodology for determining the PAPP-A protein concentration used in the studies by Lund et al. [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e] (immunofluorometric method) and Heeschen et al. [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e] (immunoenzymatic method - using a reagent manufactured by Roche) differed from that used in our own studies.\u003c/p\u003e \u003cp\u003eIn our own studies, during the observation of patients in the period of 6\u0026ndash;12 months after ACS, a relationship between the concentration of PAPP-A protein and the risk of the occurrence of CE was found again (6.40\u0026thinsp;\u0026plusmn;\u0026thinsp;4.13mIU/l vs. 24.53\u0026thinsp;\u0026plusmn;\u0026thinsp;4.23mIU/l; p\u0026thinsp;=\u0026thinsp;0.004). The value of the concentration of PAPP-A protein\u0026thinsp;\u0026ge;\u0026thinsp;19.43mIU/l was characterized by 100% sensitivity and almost 100% specificity. Similarly, analyzing the factors influencing the prognosis of patients with STEMI during a 12-month follow-up period, Lund et al. [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] found that PAPP-A protein concentration above 10 mIU/l was associated with an increased risk of CD and AMI, while Iversen et al. [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] found a 2.4-fold increase in the risk of AMI or death among patients at low risk of NSTE-ACS in the case of PAPP-A protein concentration\u0026thinsp;\u0026gt;\u0026thinsp;12.4 mIU/l (24% vs. 10%; p\u0026thinsp;=\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003eBoth Lund et al. [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] and Danish researchers [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] took into account the average PAPP-A protein concentration from several measurements. In our studies, a single PAPP-A protein concentration was determined (from a single blood sample taken at admission) using the immunoenzymatic method (Sandwich ELISA).\u003c/p\u003e \u003cp\u003eIn several years of observation, there have also been reports on the prognostic significance of PAPP-A protein in individuals [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. When analyzing adverse events in the observation of patients after ACS, it is impossible not to take restenosis into account. Restenosis is one of the main limitations of PCI. PCI is a method that is not only safe [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e], but also effectively reduces early and late mortality [\u003cspan additionalcitationids=\"CR79 CR80 CR81\" citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e] and is currently the reference method of treatment for patients with ACS. Angiographically significant restenosis is defined as significant (\u0026ge;\u0026thinsp;50%) narrowing of the vessel lumen at the site of the previous PCI procedure [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. According to estimates, up to 50% of patients may experience restenosis, [\u003cspan additionalcitationids=\"CR85\" citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. Restenosis may manifest as recurrence or exacerbation of exertional angina and/or ischemic changes in the resting or exercise ECG [\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis usually occurs between 1 and 6 months after PCI. According to some authors, restenosis most often occurs in the 3th to 6th month after PCI [\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. The above data is in line with our own studies, where clinical indications for control coronary angiography occurred most often between the 3rd and 6th month of observation. During this period, we confirmed restenosis angiographically in every case of clinical suspicion of recurrent stenosis. Out of the total number of 13 restenoses in the entire observation period, 10 (76.9%) manifested within the period of up to 6 months of observation.\u003c/p\u003e \u003cp\u003eReports on the clinical course of restenosis are contradictory. Many authors state that in most patients it manifests as ACS [\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e, \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our own studies, ACS was a clinical manifestation of restenosis in 85% of cases [in over half of the patients (54.55%) AMI, in the remaining - UA]. These data are comparable with the observations of Bainey et al. [\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e] (ACS was a clinical manifestation of restenosis in 70.7%, of which NSTE-ACS constituted 52.2%, and STEMI \u0026minus;\u0026thinsp;18.5%), but different from the observations from the Cleveland Clinic registry [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e] (ACS was a clinical manifestation in 35.9% of restenoses, of which AMI constituted 9.5%, and UA \u0026minus;\u0026thinsp;26.4%). In our own studies, a statistically significant difference in PAPP-A protein concentration was found in patients with and without restenosis (11.89\u0026thinsp;\u0026plusmn;\u0026thinsp;6.13mIU/l vs 6.92\u0026thinsp;\u0026plusmn;\u0026thinsp;5.90mIU/l; p\u0026thinsp;=\u0026thinsp;0.0005). PAPP-A protein concentration determined on admission turned out to be a variable differentiating patients at a very high risk of restenosis (0.8\u0026thinsp;\u0026le;\u0026thinsp;AUC\u0026thinsp;\u0026lt;\u0026thinsp;0.9). The risk of restenosis was more than 10-fold higher [OR\u0026thinsp;=\u0026thinsp;10.48; 95%CI: 3.16\u0026ndash;34.77] when PAPP-A protein concentration was \u0026ge;\u0026thinsp;8.17mIU/l. There are no comparative data in the available literature.\u003c/p\u003e"},{"header":"5. Limitations","content":"\u003cp\u003eThe type of test we used to determine the PAPP-A protein represents a significant limitation of our own research. We used a commercially available test with high sensitivity, enabling the detection of low PAPP-A protein concentrations. However, it contains antibodies that react with both the PAPP-A protein molecule and proMBP. The choice of the test was dictated primarily by promising literature data on the usefulness of \"ultra sensitive\" tests in assessing PAPP-A protein concentrations in patients with ACS [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e]. Furthermore, as previously mentioned, tests dedicated to detecting the specific epitopes present in the PAPP-A protein homodimer are not commercially available. The study included a relatively small number of patients, specifically only 26 in the UA group, which led to a decrease in the power of the diagnostic tests. This was because univariate analyses failed to confirm the influence of specific individual factors on adverse events. Multivariate analysis was not performed. Additionally, the number of adverse cardiovascular events during 12-month follow-up decreased. However, we jointly analyzed these events in both subgroups and created composite endpoints.\u003c/p\u003e"},{"header":"6. Conclusions","content":"\u003cp\u003e1. Elevated PAPP-A protein concentration (\u0026ge;\u0026thinsp;5.83mIU/l) in patients with acute coronary syndrome without persistent ST-segment elevation has limited diagnostic significance (it has lower sensitivity and specificity than Troponin T).\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e2. Elevated PAPP-A protein concentration (\u0026ge;\u0026thinsp;8.17mIU/l) in patients with acute coronary syndrome without persistent ST-segment elevation increases the risk of coronary restenosis 10-fold in a 12-month follow-up.\u003c/p\u003e\n\u003c/span\u003e\u003cspan\u003e\n \u003cp\u003e3. Elevated PAPP-A protein concentration (\u0026ge;\u0026thinsp;16.34mIU/l) in patients with acute coronary syndrome without persistent ST-segment elevation increases the risk of myocardial infarction almost 33-fold in a 3-month follow-up.\u003c/p\u003e\n\u003c/span\u003e\u003cspan\u003e\n \u003cp\u003e4. Elevated PAPP-A protein concentration in patients with acute coronary syndrome without persistent ST-segment elevation increases the risk of a composite endpoint (myocardial infarction\u0026thinsp;+\u0026thinsp;cardiovascular death) by more than 20-fold (at concentrations: \u0026ge;11.44mIU/l in 1-month follow-up, \u0026ge;\u0026thinsp;10.14mIU/l in 6-month follow-up and \u0026ge;\u0026thinsp;19.43mIU/l in 12-month follow-up).\u003c/p\u003e\n\u003c/span\u003e\u003cspan\u003e\n \u003cp\u003e5. Elevated PAPP-A protein concentration in patients with acute coronary syndrome without persistent ST-segment elevation increases the risk of exacerbation of coronary artery disease requiring control coronary angiography: by more than 14-fold at a concentration of \u0026ge;\u0026thinsp;10.7mIU/l in 3-month follow-up and 3-fold at a concentration of \u0026ge;\u0026thinsp;6.47mIU/l in 6-month follow-up.\u003c/p\u003e\n\u003c/span\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Conceptualization, M.R-K. and M.K.; methodology, M.R-K and M.K; software, M.R-K.; validation, M.R-K..; formal analysis, M.K and A.P-W.; investigation, M.K.; resources, M.R-K.; data curation, M.K. and K.S.; writing\u0026mdash;original draft preparation R.F; writing\u0026mdash;review and editing, M.R-K. and M.K.; visualization, R.F.; supervision, M.K.; project administration, M.R-K.; funding acquisition, T.P. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research was funded by the Medical University of Lodz, institutional grant no. 503/1-151-07/ 503-11-001-18.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u0026nbsp;\u003c/strong\u003eThe study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Local Ethics Committee (Agreement no.\u0026nbsp;RNN/2/08/KE) of the Medical University of Lodz.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u0026nbsp;\u003c/strong\u003eInformed consent was obtained from all subjects involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e The authors declare no conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDi Cesare, M. et al. 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Pregnancy Associated Plasma Protein-A and Risk Stratification of Patients Presenting with Chest Pain in the Emergency Department. \u003cem\u003eInt. J. Cardiol.\u003c/em\u003e \u003cb\u003e117\u003c/b\u003e, 365\u0026ndash;369. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ijcard.2006.05.021\u003c/span\u003e\u003cspan address=\"10.1016/j.ijcard.2006.05.021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2007).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Acute coronary syndrome. PAPP-A. ACS. Cardiology. Cardiovascular disease","lastPublishedDoi":"10.21203/rs.3.rs-5342541/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5342541/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThere are ongoing attempts to find a reliable, highly sensitive and specific early indicator of myocardial ischemia. Recently, a potential new function for the \u0026ldquo;non-pregnancy\u0026rdquo; related PAPP-A protein has been reported in many papers, including that the protein could be used in diagnosing heart conditions. Hence, our study aimed to determine the diagnostic and prognostic significance of PAPP-A protein in individuals diagnosed with Non ST-Elevation Acute Coronary Syndromes (NSTE-ACS). The study comprised a 100 consecutive patients (68 males and 32 females), aged from 42 to 83 years (mean age: 64.2 years). We assessed PAPP-A protein levels, anthropometric measurements, basic laboratory tests, ECG recordings, and coronary angiography for each patient. The participants were subsequently divided into two groups: Non ST Elevation Myocardial Infarction (NSTEMI, n\u0026thinsp;=\u0026thinsp;74) or Unstable Angina (UA, n\u0026thinsp;=\u0026thinsp;25). The levels of PAPP-A protein in patients with NSTEMI were slightly higher than those in patients with UA, but the difference was not statistically significant (7.93\u0026thinsp;\u0026plusmn;\u0026thinsp;6.35mIU/l vs. 6.52\u0026thinsp;\u0026plusmn;\u0026thinsp;5.45mIU/l, p\u0026thinsp;=\u0026thinsp;0.253). Higher levels of PAPP-A protein (\u0026ge;\u0026thinsp;5.83mIU/l) were found to be linked to a greater risk of NSTEMI (OR\u0026thinsp;=\u0026thinsp;1.37; 95%CI: 0.56\u0026ndash;3.36), although with less accuracy compared to the initial measurement of troponin T (cTnT) in the identification of cases. After 12 months, there was a significant correlation between the amount of labeled PAPP-A protein and the likelihood of experiencing acute myocardial infarction, cardiovascular death, and the necessity for unplanned coronary angiography (UCA). The diagnostic utility of PAPP-A protein in NSTE-ACS is limited, both in the NSTEMI and UA patient groups. However, its measurement can be used to estimate the annual risk for these groups of patients.\u003c/p\u003e","manuscriptTitle":"PAPP-A protein diagnostic and prognostic significance in acute coronary syndromes without persistent ST-T-segment elevation.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-19 13:46:55","doi":"10.21203/rs.3.rs-5342541/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2061dfae-ae3b-4e43-9c5a-050f0062461b","owner":[],"postedDate":"November 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":39834965,"name":"Biological sciences/Biochemistry/Peptides"},{"id":39834966,"name":"Health sciences/Cardiology/Interventional cardiology"},{"id":39834967,"name":"Health sciences/Diseases/Cardiovascular diseases"},{"id":39834968,"name":"Health sciences/Biomarkers/Diagnostic markers"}],"tags":[],"updatedAt":"2025-11-27T09:24:01+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-19 13:46:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5342541","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5342541","identity":"rs-5342541","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}