a b s t r a c t

Aim: We aimed to determine the predictors of early death in the course of Acute pulmonary embolism . Materials and methods: We included 206 patients who had been admitted to our hospital between January 2011 and April 2013 with the diagnosis of APE. We derived a new model including Corrected QT interval dispersion (QTcd) and P wave dispersion (Pd), echocardiographic findings, laboratory markers, and blood cell count indices to predict early death in patients with APE.

Results: Thirty patients (14.5%) died; 176 patients (85.5%) lived after diagnosis of APE. Logistic regression (LR) analysis found that troponin I (odds ratio [OR], 1.084 [95% confidence interval {CI}, 1.009-1.165]), creatinine (OR, 4.153 [95% CI, 1.375-12.541]), mean platelet volume (OR, 1.991 [95% CI, 1.230-3.223]), neutrophil to

lymphocyte ratio (NLR) (OR, 1.079 [95% CI, 1.005-1.160]), QTcd (OR, 1.084 [95% CI, 1.043-1.127]), Pd (OR,

1.049 [95% CI, 1.004-1.096]) were associated with early death in APE. New LR model (area under the curve [AUC], 0.970) performed better than the simplified pulmonary embolism severity index (sPESI) score (AUC, 0.859) in predicting early death in APE (P = .021).

The predictivity of the sPESI score significantly improved after its single combination with creatinine, QTcd, or troponin I. When the combined model was constructed together with these 6 independent variables and sPESI score, stepwise LR model automatically excluded Pd and NLR, and the AUC from the rest of the combined model was 0.976, which is significantly different from the AUC of sPESI (0.859) (P = .0031).

Conclusions: Creatinine, troponin I, and QTcd significantly improves sPESI score. A new model with troponin I, creatinine, mean platelet volume, NLR, QTcd, and Pd seems to have greater prognostic power than the sPESI scoring system.

(C) 2014

Introduction

Acute pulmonary embolism remains associated with high Morbidity and mortality rates despite advanced therapeutic options. This may be rooted partially in deficient initial Prognostic assessment of patients. Both European and US guidelines suggest more aggressive treatment, such as administration of thrombolytic agents, for those at high risk for early mortality [1]. Moreover, some studies indicate that thrombolytic therapy may have a place in the management of some moderate-risk patients [2]. Risk stratification of patients with APE is mandatory to allow assessment of the individual prognosis and guide therapeutic decision making. Interestingly, Clinical scores have been developed and validated to predict short-term prognosis after APE [3-5]. The simplified pulmonary embolism severity index (sPESI) is the most extensively studied clinical score to date [3]. It includes 6

? This report was neither previously submitted elsewhere nor under Review process.

* Corresponding author. Adnan Menderes Universitesi, Tip Fakultesi, Kardiyoloji Anabilim Dali, 090100, Aytepe, Aydin, Turkey. Tel.: +90 256 444 12 56 2215; fax: +90

256 213 60 64.

E-mail address: [email protected] (C. Akgullu).

equally weighted variables: older than 80 years, history of cancer, history of chronic cardiopulmonary disease, heart rate greater than 110 beat per minute, systolic blood pressure less than 100 mm Hg, and arterial oxyhemoglobin saturation less than 90%. Other than these useful Clinical scores, there is no clear consensus on the use of thrombolytic therapy, especially in intermediate-risk patients, defined as those without shock or hypotension but with adverse event predictors, such as elevated serum markers or right ventricular dysfunction by diagnosed by Transthoracic echocardiography .

To highlight the problem, some studies have suggested that laboratory biomarkers, particularly cardiac troponins but also electrocardiographic and echocardiographic parameters and some complete blood cell count indices, could be useful in identifying patients with an elevated risk of death and complications during the acute phase of pulmonary embolism (PE) [6-10]. In addition, data indicate that serum Creatinine levels may have Prognostic importance in PE [11]. A positive characteristic of these Prognostic markers is that all can be achieved easily in the emergency department (ED).

To the author’s best knowledge, there are no data in the literature about combined use of these prognostic markers in the course of APE. We aimed to determine the predictive abilities of ECG, TTE, laboratory

http://dx.doi.org/10.1016/j.ajem.2014.11.022

0735-6757/(C) 2014

markers, blood cell count indices, and associated clinical conditions regarding early death in the course of APE. In addition, we used logistic regression (LR) analyses of independent variables to derive a valuable model to predict those at high risk. We also tested the additive prognos- tic determination values of these independent variables when combin- ing them to the sPESI score.

Materials and methods

Patients

This study was conducted in Adnan Menderes University Faculty of Medicine in Aydin, Turkey. We retrospectively reviewed archived data of 288 patients who had been hospitalized in Faculty Hospital between January 2011 and April 2013 with the diagnosis of PE and who received final diagnoses after exact demonstration of thrombus in pulmonary arteries via computed tomography (CT). The study included 206 patients who were in sinus rhythm, suitable for QT and P wave analyses, and who had accessible TTE data and Laboratory test results. Eighty-two patients were excluded from the study (36 had incomplete TTE data, TTE was not performed on 12 of them, 11 had atrial fibrillation in the ECG, 9 had excessive noise in the ECG, and 14 patients had missing laboratory data) (Fig. 1).

We recorded patients’ baseline characteristics (sex, ages, etc), comorbidities, symptoms, hemodynamic conditions, all-cause mortality rates during hospitalization, total hospitalization times, radiographic test results, and laboratory findings, and we evaluated ECGs and TTEs obtained during admission (Table 1). Using collected baseline data at the time of PE diagnosis and the outcome data of this cohort, we retrospectively assessed sPESI scores for all patients. We excluded

patients with atrial fibrillation during admission, excessive noise in ECG, or incomplete TTE data. The study protocol was approved by the Ethics Committee of the University of Adnan Menderes, and we follow- ed all procedures in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2008.

Diagnosis of PE

We diagnosed PE by spiral CT pulmonary angiography with the direct visualization of an intraluminal filling defect in the course of acute symptoms and signs suggesting PE.

Definitions

We defined early death as Inhospital mortality. We defined major bleeding as (1) a fall in hemoglobin of 2 g/dL, (2) transfusion of 2 U or more of red blood cells, (3) symptoms in a critical organ (intracranial, intraspinal, intraocular, retroperitoneal, intraarticular or pericardial, or intramuscular with compartment syndrome), or (4) fatal bleeding. Otherwise, we defined bleeding as minor bleeding.

We defined the appropriate ECG to have at least 10 analyzable leads for the needed measurements. Otherwise, ECG was defined to have excessive noise.

If the TTE data included all needed measurements (such as RV and left ventricular [LV] diameters, ejection fraction, or pulmonary artery pressure), then we defined it to be complete; otherwise, we defined it to be incomplete data.

We defined hemodynamic instability as (1) PE causing hypotension (systolic blood pressure <=90 mm Hg or a reduction of at least 40 mm Hg

Fig. 1. A diagram depicting the inclusion phase of the patients. Abbreviation: AF, atrial fibrillation.

Table 1

Baseline characteristics of the study population and their comparison between the deceased and survivors in the course of APE

	All patients	Deaths (n = 30)	Survivors (n = 176)	P
Age (y)	61.8 +- 11.8	61.8 +- 2.16	59.06 +- 1.04	.310
Sex
Female	109 (53%)	7 (23.3%)	102 (58%)	.001
Male	97 (47%)	23 (76.7%)	74 (42%)
Deep venous thrombosis	35 (17%)	7 (23.3%)	28 (15.9%)	.461
Diabetes mellitus	61 (30%)	9 (30%)	52 (29.5%)	1.000
Hypertension	124 (60%)	18 (60%)	106 (49.4%)	1.000
Chronic obstructive pulmonary disease	58 (28%)	7 (23.3%)	51 (29%)	.678
Malignancy	43 (21%)	15 (50%)	28 (15.9%)	b.001
Smoking	89 (43.2%)	17 (56.7%)	72 (40.9%)	.158
Hemodynamic instability	57 (27.7%)	18 (60%)	39 (22.2%)	b.001
Thrombolytic therapy	25 (12.1%)	8 (26.7%)	17 (9.7%)	.015
Minor bleeding	14 (6.79%)	3 (10.0%)	11 (6.3%)	.435
QTcd (milliseconds)	79 (73.5-95.13)	104 (97.37-118.85)	78 (68.12-84)	b.001
Pd (milliseconds)	49.5 (37-58)	72.5 (53.75-78.5)	48 (35.25-55.5)	b.001
P pulmonale	8 (3.9%)	4 (13.3%)	4 (2.3%)	.017
T-wave abnormalities	86 (41.7%)	20 (66.7%)	66 (37.5%)	.005
ST-segment depression	46 (22.3%)	10 (33.3%)	36 (20.5%)	.184
S1Q3T3	10 (4.9%)	6 (20%)	4 (2.3%)	.001
Incomplete RBBB	12 (5.8%)	6 (20%)	6 (3.4%)	.003
Complete RBBB	14 (6.8%)	5 (16.7%)	9 (5.1%)	.036
Right axis deviation	16 (7.8%)	6 (20%)	10 (5.7%)	.016
Left axis deviation	20 (9.7%)	6 (20%)	14 (8%)	.086
Precordial low voltage	8 (3.9%)	2 (6.7%)	6 (3.4%)	.329
Tachycardia	112 (54.4%)	17 (56.7%)	95 (54%)	.940
RV hypertrophy	8 (3.9%)	2 (6.7%)	6 (3.4%)	.329
Hemoglobin (g/dL)	12.12 +- 1.75	11.71 +- 2.02	12.19 +- 1.69	.162
MCV (fl)	84.9 +- 8.49	85 (81.23-88.93)	85.6 (79.8-90.08)	.833
RDW (%)	15.5 (14.2-16.6)	15.6 (14.8-17.2)	15.5 (14.2-16.6)	.477
Platelet count (per mm3)	283000 (214250-336250)	227000 (162000-338250)	284000 (229000-336750)	.051
MPV (fl)	8.8 (8.2-9.8)	10.2 (8.75-11.2)	8.8 (8.2-9.5)	b.001
PDW (%)	50.75 (46.1-56.17)	52.8 (50.02-64.4)	49.75 (45.42-54.4)	.001
NLR	5 (2.70-8.90)	12.2 (8.37-21.02)	3.9 (2.6-7.3)	b.001
Troponin I (mg/dL)	0.10 (0-2.12)	5.6 (2.5-13.15)	0 (0.0-1.2)	b.001
D-Dimer (ug/dL)	3200 (1700-5125)	4450 (3200-5900)	2700 (1450-4500)	b.001
Creatinine (mg/dL)	0.81 (0.70-1.20)	1.7 (0.9-2.32)	0.8 (0.69-1.0)	b.001
Ejection fraction (%)	66 (62-68)	64 (59.5-66.5)	66 (63-68)	.015
Estimated PAP	36 (33-42)	45.5 (36-56.5)	36 (33-39.75)	b.001
LV end-diastolic diameter	48 (46-51)	49 (47-51.25)	48 (46-50.75)	.240
RV end-diastolic diameter	46 (43.75-48)	49 (45.75-51.25)	46 (43-48)	b.001
RV/LV ratio	0.96 (0.91-1)	1.01 (0.95-1.06)	0.95 (0.90-1.0)	.003
D-shaped septum	77 (37.4%)	22 (73.3%)	55 (31.3%)	b.001
sPESI score	2 (1-2)	3 (2-4)	2 (1-2)	b.001

Abbreviations: PDW, platelet distribution width; MCV, mean corpuscular volume; PAP, Pulmonary arterial pressure.

for at least 15 minutes); (2) tachycardia (pulse rate >= 110/min);

(3) hypoxemia (PaO2 b 60 mm Hg); (4) blurred consciousness; or (5) syncope associated with hypotension; oliguria; or cool, clammy extremities.

We used the definition of “cool and clammy extremities” as a result of the physical examination notes of the physicians who had first con- tact in the ED.

Transthoracic echocardiography

In this study, we used recorded data from comprehensive TTEs performed on admission on subjects in the Left lateral decubitus position (Philips HD11XE and Envisor HD; Phillips USA, Andover, MA). We acquired images from standard echocardiographic views in accordance with the recommendations of the American Society of Echocardiography [12].

To calculate the RV/LV ratio, we used archived measurements of the midcavitary end-diastolic diameters recorded from the standard, Apical 4-chamber view. In addition, we used archived data about pulmonary artery systolic pressure, which was derived as the sum of the tricuspid regurgitant gradient obtained from continuous wave Doppler and the right atrial pressure as estimated from the inferior vena cava [12]. A great deal of data pertaining to RV tricuspid annular plane systolic ex- cursion measurements was missing from the archives. In addition, the

study did not have access to the equipment to perform off-line analyses from digitally stored prior images and, thus, did not use this useful echo- cardiographic parameter, which has become accepted as a good predic- tor of RV longitudinal function.

Analyses of ECG, corrected QT interval dispersion, and P wave dispersion measurements

To the best of our knowledge, there are no data in the literature to support the usefulness of P wave dispersion (Pd) in the determination of prognosis of APE. However, both Pd and corrected QT interval disper- sion (QTcd) were previously shown to be increased in the setting of pul- monary hypertension [13,14]. Moreover, recently, QTcd was shown to be useful in the prognostic determination of APE [15]. To make the analysis, we followed similar ECG measurement techniques.

We analyzed ECGs that had been recorded on admission using a supine, standard 12-lead ECG tracing at 25 mm/s paper speed at 10 mm/mV amplitude. We performed measurements manually with the help of a magnifying glass by 2 experienced cardiologists who were blind to clinical data of the patients. We used 3 consecu- tive beats for the analyses where at least 10 leads were analyzable in ECGs.

We measured QT intervals from the onset of the QRS to the end of the T wave, defined as the return to the T-P isoelectric baseline. Besides,

we accepted only monophasic, well-defined T waves for measurement. When U waves were present, we measured the QT interval to the nadir of the curve between the T and the U waves. We defined QTcd as the difference between the maximum and minimum QT values. Bazett’s formula (QT corrected [QTc] = QT/?RR) was used for the QTc and QTcd analyses [16].

We measured P wave duration from the point of junction between the isoelectric line and the beginning of P wave deflection to the point of junction between the end of P wave deflection and the isoelectric line. We defined Pd as the difference between the maximum (Pmax) and minimum (Pmin) P wave durations occurring in any of the 12 leads. To estimate intraobserver and Interobserver variability, we reanalyzed 33 randomized ECGs, and we repeated the measurements by 2 cardiologists. To determine intraobserver variability, we evaluated 93 ECG tracings by the same investigator on 2 occasions. To assess inter- observer variation, all ECG tracings were analyzed by a second, indepen-

dent investigator who was blind to the results obtained by the first.

Statistical analyses

We used the Kolmogorov-Smirnov test to assess the normality of numeric variables. For those that were normally distributed, we made comparison between 2 groups by independent-sample t test, and we present descriptive statistics as mean +- SD. For numeric variables that were not normally distributed, we made comparison between 2 groups by Mann-Whitney U test, and we present descriptive statistics as medi- an (25-75 percentiles). To analyze categorical data, we used a ?² test, and we present descriptive statistics as frequency (percentages). To de- termine the reliability and reproducibility of ECG parameters, we used the Spearman’s ? correlation analysis to evaluate their interobserver and intraobserver variability.

The study used LR with a forward stepwise variable selection to pre- dict the probability of early death in APE. We assessed fit by ?² statistics proposed by a Hosmer-Lemeshow goodness-of-Fit test. Furthermore, we used the receiver operating characteristic (ROC) curve to determine the cutoff point, the area under the curve (AUC) of sPESI, and predictors in the best LR model. In addition, the study tested the statistical signifi- cance of the difference between the areas under 2 ROC curves, the best LR model, and sPESI score, using the method proposed by Hanley and McNeil. In conclusion, we considered the P values less than .05 statisti- cally significant.

Results

We excluded 1 patient who had died because of a malignancy and 2 patients who had had pneumonia, as their baseline ECGs were not appropriate for further analyses. In addition, we excluded 2 patients who had died of sepsis because they had had atrial fibrillation. In addi- tion, we excluded 1 patient who had died of PE and 2 patients who had died because of major bleeding from the study because they lacked ini- tial echocardiographic evaluations. After excluding these inappropriate deaths, all deaths included in the study were related to PE.

Among the study population, 30 patients (14.5%) died, and 176 patients (85.5%) lived after diagnosis of APE. Table 1 shows baseline characteristics of the study population. Mean age was

61.8 +- 11.8 years. Frequency of females in the population was 53% (n = 109), and 47% were male (n = 97). Frequency of hyper- tension was 60% (n = 124), diabetes mellitus was 30% (n = 61), chronic obstructive pulmonary disease was 28% (n = 58), deep ve- nous thrombosis was 17% (n = 35), and history of malignancy was 21% (n = 43). In addition, 43% (n = 89) were smokers. Mean total hospitalization time was 7.0 (4.0-9.0) days, and mean hospitaliza- tion to death time was 3.0 (2.0-5.0) days.

Mean hemoglobin of the population was 12.12 +- 1.75 g/dL, mean troponin I was 0.10 (0-2.12), and mean D-dimer was 3200 (1700-5125). Mean QTcd was 83.59 +- 20.01 milliseconds, and mean

Pd was 49.50 (37-58) milliseconds. The mean longest P wave duration was 101 (87-112) milliseconds, and the mean shortest was 47 (42-60) milliseconds. In addition, 27.7% (n = 57) of patients were hemodynamically unstable, and 12.1% (n = 25) had had thrombolytic therapy. There was no major bleeding, and minor bleeding occurred in 6.8% (n = 14) of patients. Mean total hospitalization time was 7.00 (4.00-9.00) days, and mean hospitalization to time of death was 3.00 (2.00-5.00) days (Table 1).

Table 1 also shows a comparison of baseline characteristics of the deceased and survivors in the course of APE. There was no difference between survivors and deceased in age; smoking habits; and accompanying diseases, such as diabetes, hypertension, chronic obstructive pulmonary disease, and deep venous thrombo- sis (P N .05) (Table 1). However, there was a significant difference in sex, with more males dying (76.7% vs 23.3%; P = .001). Malignancy was more frequent in the deceased (50%; n = 15) than in survivors (15.9%; n = 28) (P b .001). Hemodynamic insta- bility was a significant factor, with those having it who died being 60% (n = 18) and those having it who lived being 22% (n = 39) (P b .001). Frequency of thrombolytic therapy was higher among those who died (26.7%; n = 8) than among those who lived (9.7%; n = 17) (P = .015). Total hospitalization time, at 3 days (2-5.25), was less among those who died than the 7 days (5-9.75) among those who survived (P b .001). The sPESI scores of those who died, at 3 (2-4), were higher than those of the survivors, at 2 (1-2) (P b .001).

D-dimer levels of those who died were higher, at 4450 ug/dL

(3200-5900), than D-dimer levels of survivors, at 2700 ug/dL (1450-4500) (P <= .001). In addition, troponin I serum levels were higher, at 5.6 mg/dL (2.5-13.15), in those who died than in those who lived, in which they were 0 mg/dL (0.0-1.2) (P b .001). Creati- nine levels were also higher among those who died (1.70 mg/dL [0.90-2.32] vs 0.80 mg/dL [0.69-1.00]; P b .001).

There was no significant difference between the groups in hemato- logical parameters, such as hemoglobin, mean corpuscular volume, and Red blood cell distribution width levels. However, platelet distribution width (P = .001), Mean platelet volume (P b .001), and Neutrophil to lymphocyte ratio (P b .001) were significantly higher in those who died (Table 2).

There was no difference between the groups in ECG findings, such as left axis deviation, ST-segment depression, low voltage, findings of RV hypertrophy, and tachycardia (Table 1). However, the incidence on ECGs of complete and incomplete right bundle-branch block (RBBB) was higher in those who died (P = .036 and P = .003, respectively). electrocardiographic findings of nonspecific T-wave abnormalities (P = .005), right axis deviation (P = .016), P pulmonale (P = .017), and S1Q3T3 (P = .001) were higher in those who died (Table 1).

P wave dispersion values of those who died were higher than they were in those who survived: 52.80 (50.02-64.40) milliseconds and

49.75 (45.42-54.40) milliseconds, respectively (P b .001). In addition, QTcd values of those who died were higher than those of survivors:

104.00 (97.37-118.85) milliseconds and 78.00 (68.12-84.00) millisec- onds, respectively (P b .001).

Reproducibility of the determination of QTcd and Pd was high in both intraobserver and interobserver comparisons. To estimate

Table 2

Multivariable LR analysis model to predict early death in APE

Variables	OR	95% CI	P
Troponin	1.084	1.009-1165	.027
Creatinine	4.153	1.375-12.541	.012
MPV	1.991	1.230-3.223	.005
NLR	1.079	1.005-1.160	.037
QTcd	1.084	1.043-1.127	b.001
Pd	1.049	1.004-1.096	.031

Odds ratios with respective 95% CIs for early mortality were calculated by LR analysis.

intraobserver and interobserver variability, we reanalyzed 93 randomized ECGs, and measurements were repeated by both cardiologists. Intraobserver variability for QTcd (r = 0.976; P b .001) and for Pd (r = 0.988; P b .001) was not significant. Interobserver variability between the 2 cardiologists estimating QTcd (r = 0.982; P b .001) and Pd (r = 0.994; P b .001) was not significant.

Among TTE parameters, there was no difference between the groups in LV end-diastolic diameter (P = .240). However, RV end-diastolic diameter, pulmonary artery systolic pressure, presence of D-shaped septum (P b .001), and RV/LV ratio (P = .003) were higher among those who died. Ejection fraction was lower in those who died (P =

.015) (Table 1).

Using independent predictors, we used LR analysis with a forward stepwise variable selection to predict the probability of early death in APE. We assessed fit by ?² statistics proposed by the Hosmer- Lemeshow goodness-of-fit test. The LR model showed a good fit based on the ?² of Hosmer-Lemeshow goodness-of-fit statistics (P N .05). Re- sults of LR analysis showed that troponin I (odds ratio [OR], 1.084 [95% confidence interval {CI}, 1.009-1.165]), creatinine (OR, 4.153 [95% CI,

1.375-12.541]), MPV (OR, 1.991 [95% CI, 1.230-3.223]), NLR (OR, 1.079

[95% CI, 1.005-1.160]), QTcd (OR, 1.084 [95% CI, 1.043-1.127]), and Pd

(OR, 1.049 [95% CI, 1.004-1.096]) were associated with early death in acute PE. The study found the best model by LR analysis (Table 2).

P (early death)

1

= 1 + e-(-9.894+0.081*troponin+1.424*creatinine+0.689*MPV+0.076*NLR+0.081*QTcd+0.048*Pd)

Table 3 shows a comparison of the cutoff value, AUC, 95% CIs of AUC, sensitivity, and specificity for predictors in the best LR model. Troponin I, creatinine, MPV, NLR, QTcd, and Pd all had AUCs, sensitivities, and specificities in the ranges of 0.719 to 0.895, 60.00% to 96.67%, and 77.84% to 95.45%, respectively. As Fig. 2 shows, the LR model (AUC, 0.970) performed better than sPESI scores (AUC, 0.859) in predicting early death in APE (P = .021).

We created LR models to determine the predictive abilities of 6 var- iables together with sPESI. We added our new independent variables one by one to the sPESI score to derive a new LR model each time to demonstrate the contribution values of each variable to the sPESI. Then, ROC analyses were performed using the predictive probabilities of these 6 LR models (Table 4). The most valuable contributions came from creatinine, QTcd, troponin I, and MPV, whereas Pd and NLR seemed to have less valuable contributions to the predictivity of the sPESI (Fig. 3).

We also checked whether the difference between the ROC analyses of each new LR model and the sPESI score had any statistical signifi- cance. We demonstrated that the predictive value of the ROC analyses of the LR models, sPESI + creatinine (P = .0317), sPESI + QTcd (P =

.0132), and sPESI + troponin (P = .0245), were different from the pre- dictive value of the ROC analyses of the sPESI, where sPESI + MPV (P =

.0587) had borderline P value and sPESI + Pd (P = .2846) and sPESI + NLR (P = .0793) had no difference.

We added all 6 variables of our model together to the sPESI to dem- onstrate their combined predictive value. When we ran a stepwise LR

Table 3

receiver operating characteristic curve analysis of variables that significantly predict early death

Variables and cutoff values AUC P Sensitivity Specificity

Troponin N 2.3	0.879	0.827-0.920	b.0001	83.33	88.07
Creatinine N 1.35	0.823	0.764-0.873	b.0001	66.67	88.64
MPV N 9.7	0.719	0.653-0.779	.0001	63.33	81.25
NLR N 8.4	0.825	0.766-0.875	b.0001	76.67	81.82
QTcd N 86	0.895	0.845-0.933	b.0001	96.67	77.84
Pd N 64.5	0.795	0.733-0.848	b.0001	60.0	95.45
sPESI N 2	0.859	0.804-0.903	b.0001	73.33	87.5

model for the combined 6 variables and sPESI together, Pd and NLR were excluded automatically from the analysis model. The AUC of the combined model was 0.976 (creatinine, MPV, QTcd, troponin I, and sPESI score together) (Table 4) (Fig. 2). The difference between the AUC of the sPESI score and the combined model was significant (P =

.0031). The difference between the AUC of our new LR model (6 vari- ables together) and combined model was not significant (P = .8020). We have demonstrated that our model increased the predictivity of the sPESI score, but the sPESI score did not improve the predictivity in our model.

Discussion

With a unicenter cohort of 206 patients with APE, we demonstrated that ECG findings of QTc and Pd values, serum creatinine and Troponin I levels, and hematological parameters of the MPV and NLR, all of which are easily detected in the ED, constitute a useful model to predict early death in the course of APE. In addition, we demonstrated that this model is significantly more powerful than the sPESI scoring system in predicting high-risk patients with APE.

Clinical presentation of APE varies from a small, asymptomatic pulmonary embolus with low mortality to a massive PE resulting in RV heart failure, shock, and/or death. Incidence of mortality is directly related to Management strategy, which, in turn, is related to accurate risk stratification of patients. The crucial importance of identifying patients who are at high risk has given rise to studies focusing on detec- tion of powerful, new Predictive tools. Interestingly, some studies have demonstrated that Laboratory markers, such as cardiac troponins, D-dimer, Natriuretic peptides, heart-type fatty acids, and serum homo- cysteine levels, can be useful Prediction tools [17-22]. In addition, some parameters among imaging modalities, especially focusing on the assessment of RV and right atrial size and function, have been shown to be useful [23-25]. In addition, reports indicate that renal failure may play a crucial role in the risk stratification of patients with APE [11,26]. Some reports evaluate the usefulness of complete blood count indices, such as NLR, MPV, and RDW, in predicting patients with high risk [27-30]. Finally, reports evaluate the QT dispersion parameter of the surface ECG as a useful predictive tool in the course of APE [15,10].

Several classical ECG abnormalities are associated with APE, but none are highly specific or sensitive. In patients with RV failure, the ECG may show sinus tachycardia, signs of RV strain, Repolarization abnormalities, ischemia including complete or incomplete RBBB, a rightward axis greater than 90?, an S1Q3T3 pattern, a Qr in lead V₁, ST elevation in V₁, or precordial T-wave inversions. However, approxi- mately two-thirds of patients with massive or submassive PEs exhibit no such classical changes on ECG [31].

Another parameter of the surface ECG, QTcd, has been shown to have an important role in predicting mortality in APE [15,10]. Corrected QT interval dispersion is suggested as a good marker for detection of inhomogeneity of ventricular Recovery times. The rationale for this close relation of QTcd and prognosis of PE may be explained partly by acute repolarization changes of the overloaded RV. In the context of acute RV failure, advanced heterogeneity of repolarization may lead to increased QTcd that can be detected easily on a surface ECG [32]. Inter- estingly, Ermis et al [15] suggested that the sensitivity of QTcd greater than 71.5 milliseconds for prediction of mortality was 71%, with a spec- ificity of 73% in patients with APE [15]. Thus, it is not surprising that this study found that QTcd had significant importance in the LR analyses.

Another parameter of the surface ECG is Pd. This ECG parameter, to the author’s best knowledge, has not been studied previously as a prog- nostic marker in the context of APE. P wave dispersion is regarded as a marker of atrial depolarization heterogeneity and has been suggested as reflecting abnormalities of atrial size and structure [33,34]. During acute RV failure, as RV end-diastolic volumes and pressures increase, RV wall stress increases, leading to reduced RV stroke volume. In addi- tion, elevated RV end-diastolic volumes promote tricuspid annular

Fig. 2. Comparison of ROC curves of the new model, sPESI score, and combined model in predicting early mortality in APE. Variables of logistic regression model: troponin I, creatinine, MPV, NLR, QTcd, and Pd. Variables of sPESI: older than 80 years, history of cancer, history of chronic cardiopulmonary disease, heart rate greater than 110 beats per minute, systolic blood pressure less than 100 mm Hg, and arterial oxyhemoglobin saturation less than 90%. Variables of the combined model: troponin I, creatinine, MPV, QTcd, older than 80 years, history of cancer, history of chronic cardiopulmonary disease, heart rate greater than 110 beats per minute, systolic blood pressure less than 100 mm Hg, and arterial oxyhemoglobin saturation less than 90%.

dilatation, which worsens Tricuspid valve insufficiency and increases right atrial pressure and atrial wall tension. Previously, Barra et al [35] demonstrated that, in the course of APE, atrial fibrillation is a predictor of bad prognosis. In addition, it has been shown recently that Pd is a pre- dictor of atrial fibrillation [36]. Thus, in this study, we sought to deter- mine Pd’s prognostic power in APE and demonstrated that Pd can be a useful ECG predictor in APE.

In addition, we showed the myocardial injury marker troponin I to be a significantly important prognostic marker in our LR analysis

model. Its importance to risk stratification has been shown previously in APE [19,37]. Moreover, recent studies have also demonstrated that the use of new, highly sensitive cardiac troponins improves diagnostic sensitivity in APE [38]. Interestingly, Lankeit et al [39] have shown that a combination of highly sensitive troponin T and sPESI score im- proved risk stratification of normotensive patients with APE.

We have shown that serum creatinine levels play a significant role in detecting patients at high risk. Interestingly, Kostrubiec et al [11] have shown that rapid improvement of renal function in patients with APE

Table 4

Receiver operating characteristic curve analysis of variables combined with sPESI score to predict early death

LR models	Sensitivity	Specificity	AUC	95% CI for AUC	P
sPESI	73.33	87.5	0.859	0.804-0.903	b.001
LR model (Cr + MPV + NLR + QTcd + Pd + troponin I)	90.0	93.7	0.970	0.937-0.989	b.001
Combined model (sPESI + Cr + troponin I + QTcd + MPV)	96.7	92.6	0.976	0.945-0.992	b.001
sPESI + Cr	90.00	92.05	0.933	0.890-0.963	b.001
sPESI + MPV	86.67	85.23	0.909	0.861-0.944	b.001
sPESI + NLR	90	79.55	0.906	0.858-0.942	b.001
sPESI + Pd	80	86.36	0.892	0.842-0.931	b.001
sPESI + QTcd	96.67	73.3	0.928	0.883-0.959	b.001
sPESI + troponin I	93.33	82.39	0.921	0.875-0.954	b.001

Abbreviation: Cr, creatinine.

Fig. 3. Comparison of ROC curves of the independent variables when combined with sPESI score in predicting early mortality in APE.

may indicate a favorable short-term prognosis. In another study, they showed that impaired kidney function is related to all-cause mortality in APE. They found that, in initially normotensive patients, a glomerular filtration rate (GFR) less than 35 mL/min predicts 30-day mortality. They concluded that GFR assessment improved troponin-based risk stratification of APE [26]. In this study, we did not use GFR; however, we found that serum creatinine levels can be used as a good Prognostic tool in APE.

Lastly, we found that complete blood count indices, such as MPV and NLR, play a significant role in prediction of prognosis in APE. The balance between neutrophils and lymphocytes has been regarded as a marker of systemic inflammation [40]. Kayrak et al [27] previously suggested that NLR may play an important role in predicting high-risk patients. On the other hand, MPV, which is accepted as an indicator of platelet activation, has been shown to have prognostic value in APE [29,41]. We suggest that both indices, which can be derived from a simple complete blood count test, can be good Prognostic tools in the context of APE.

In this study, analyses of QTcd and Pd were performed manually by 2 experienced cardiologists. We demonstrated that reproducibility of the determination of QTcd and Pd was high in both intraobserver and interobserver comparisons. However, in real life, it may be a lit- tle time consuming to perform this analysis manually, especially in emergency situations. Of interest, it was previously shown that auto- matic QTcd measurements may be as reliable as manual QTcd measure- ment techniques [42-44]. There are no data in the literature about automatic Pd measurement techniques or comparison of automatic vs

manual analyses. However, it may be possible in the future after the essential studies.

Current guidelines recommend prognostic evaluation to stratify pa- tients into risk groups after a diagnosis of APE. Among the recommend- ed evaluation systems are sPESI, Geneva, and Wells [4]. However, none of these scoring systems take into account the troponins, creatinine levels, MPV, NLR, QTcd, or Pd. In this study, we concluded that combined use of these predictors may have greater prognostic power than the sPESI scoring system.

The most prominent limitation of our study was relatively small number of outcome of interest (death number) among the study popu- lation. The power of our analysis might have been affected from the relatively small number.

Large, randomized studies are needed to assess the importance of these markers. In addition, in future studies, it would be valuable to as- sess the probable improvement power of these prognostic markers when combined with TTE or CT parameters, such as tricuspid annular plane systolic excursion or CT obstruction indices, or with laboratory markers, such as heart-type fatty acids, binding proteins, or natriuretics.

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