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Shock, Publish Ahead of Print
DOI : 10.1097/SHK.0000000000001027
Value of the delta neutrophil index for predicting 28-day mortality in patients with acute
pulmonary embolism in the emergency department
Taeyoung Kong 1, YooSeok Park 1, Hye Sun Lee 2, Sinae Kim2, Jong Wook Lee3,4,Gina Yu 1, Claire
Eun5, Je Sung You 1*, Hyun Soo Chung1, Incheol Park 1, Sung Phil Chung1
1
Department of Emergency Medicine, Yonsei University College of Medicine, Seoul, Republic of
Korea
2
Department of Research Affairs, Biostatistics Collaboration Unit, Yonsei University College of
Medicine, Seoul, Republic of Korea
3
Department of Laboratory Medicine, Konyang University Hospital, Daejeon, Republic of Korea
4
Research Institute of Bacterial Resistance, Yonsei University College of Medicine, Seoul, Republic of
Korea
5
Department of Neurology, University of California, San Francisco, and the San Francisco Veterans
Affairs Medical Center, San Francisco, CA, United States
Corresponding author:
Je Sung You, MD, PhD*
Department of Emergency Medicine, Yonsei University College of Medicine, 211 Eonju-Ro,
Gangnam-Gu, Seoul 135-720, Republic of Korea
E-mail: youjsmd@yuhs.ac, Tel: +82-2-2019-3030, Fax: +82-2-2019-4820
Copyright © 2017 by the Shock Society. Unauthorized reproduction of this article is prohibited.
Running head:Delta neutrophil index in acute pulmonary embolism
Word Counts: Abstract = 250, Main Text = 4640
Declaration of Interests
The authors declare no conflict of interests
Disclosure of funding
J. S. You received support from the Basic Science Research Program of the National Research
Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF2015R1C1A1A01054641), and the Yonsei University Future-leading Research Initiative for 2015
(2015-22-0096). S.P. Chung and T.Y. Kong were supported by basic Science Research Program
through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and
future Planning (2017R1A2B4012378). J.S.You received research fund from Siemens Health Care.
However, the fund did not exceed $10,000/year. The funding bodies had no role in the design,
collection, analysis, or interpretation of this study. The other authors have no financial conflicts of
interest.
Copyright © 2017 by the Shock Society. Unauthorized reproduction of this article is prohibited.
ABSTRACT
Purpose: Acute pulmonary embolism (PE), frequently seen in the emergency department (ED), is a
leading cause of cardiovascular morbidity and mortality. The delta neutrophil index (DNI) reflects the
fraction of circulating immature granulocytes as a component of the systemic inflammatory response
syndrome criteria. The pathogenesis of acute PE is significantly associated with inflammation.The aim
of the study was to investigate the clinical usefulness of the DNI as a marker of severity in patients
with acute PE admitted to the ED.
Methods: We retrospectively analysed the data of patients who were diagnosed with acute PEat a
single ED, admitted from 1 January 2011 to 30 June 2017. The diagnosis of acute pulmonary embolism
was confirmed using clinical, laboratory, and radiological findings. The DNI was determined at
presentation. The clinical outcome was all-cause mortality within 28 days of emergency
departmentadmission.
Results: We included 447 patients in this study. The multivariate Cox regression model demonstrated
that higher DNI values on EDadmission were significantly associated with short-term mortality (hazard
ratio, 1.107; 95% confidence interval, 1.042–1.177). The optimal cut-off DNI value, measured on
EDadmission, was 3.0%; this value was associated with an increased hazard of 28-day mortality
following PE(HR, 7.447; 95% CI, 4.183–13.366; p < 0.001)
Conclusion: The DNI value, obtained as part of the complete blood count analysis, can be easily
determined without additional burdens of cost or time. A high DNI is useful as a marker to predict 28day mortality in patients with acute PE.
Keywords: immature granulocyte; inflammation; mortality; prognostication; pulmonary embolism;
shock; sterile
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INTRODUCTION
Acute pulmonary embolism (PE) is a serious clinical condition and a leading cause of cardiovascular
hospitalisation, morbidity, and mortality (1-3). Although acute PE may be asymptomatic, being
incidentally diagnosed during imaging, the International Cooperative Pulmonary Embolism Registry
has reported fatality rates of approximately 15% and 58% in haemodynamically stable and unstable
patients, respectively (1). Acute PE has a high 28-day mortality rate of 9–31% (4). The severity of
acute PE is classified according to the probability of early death (2). Right ventricular (RV) dysfunction
and failure resulting from acute pressure overload are the major determinants of a patient’s early
clinical course and risk of an adverse outcome (2, 5). Although most patients with acute PE are
normotensive in the early stage, some develop shock despite receiving appropriate treatment (6). It is
important that acute PE risk stratification is optimal on admission to the emergency department (ED),
before sustained hypotension develops. In addition, early identification of patients at high risk of a poor
outcome may improve the survival rate of patients with acute PE. However, it is difficult to ascertain
risk in an emergency situation. Hence, many studies have attempted to characterize risk factors and comorbidities in patients by using a high index of suspicion for acute PE in the early stage of disease (1,
7, 8).
The Pulmonary Embolism Severity Index (PESI) is a useful, practical clinical prediction rule. It uses 11
predictors from the patient’s medical history and physical examination (9). The PESI has
discriminative power to predict short-term mortality and adverse outcomes in patients with acute PE (5,
9) and may be suitable for clinical application. However, the main limitation of the PESI is that it
requires numerous variables and is relatively complex to calculate (9). Therefore, there is a need for
new prognostic markers that can be measured rapidly and readily in the ED.
Acute PE is significantly associated with vascular inflammation in the pulmonary arteries, pulmonary
inflammation as a result of pulmonary infarction, and myocyte damage and RV dysfunction due to
cardiac inflammation (8). The sustained, exacerbated inflammatory response is strongly associated with
Copyright © 2017 by the Shock Society. Unauthorized reproduction of this article is prohibited.
increased mortality (8, 10, 11). Many studies have been conducted on the association between
predictors of severity of acute PE and inflammation-related markers (7, 8, 10-14). Immature
granulocytes have been used as a marker of inflammation, but this has been regarded as being more
important in the context of local infection, sepsis, and septic shock (15-18). There are some major
limitations to the measurement of immature granulocytes, including difficulty in obtaining a rapid
manual measurement from examination of a stained blood smear and possible inaccuracy when using
only a 200-cell manual differential count method (15, 19). The delta neutrophil index (DNI)reflects
myeloperoxidase (MPO)-reactive cells lacking nuclear lobularity as polymorphonuclear myeloidderived suppressor cells, and they may reflectthe fraction of circulating immature granulocytes,
including metamyelocytes, myelocytes, and promyelocytes as the leukocyte subfraction.(17, 19)
(Appendix 1,http://links.lww.com/SHK/A654)Nahm et al. demonstrated that the DNI correlated
strongly with manual immature granulocyte count (r = 0.75) (19). As a recent technological advance,
the specific automated blood cell analyser can rapidly and easily determine the DNI while determining
the complete blood count (CBC) (16, 17, 19). The DNI is measured by leukocyte differentials, with two
independent channels, using flow cytometric principles (17, 19). It iscalculated according to the
following formula: DNI = (neutrophil sub-fraction + eosinophil sub-fraction measured in the
myeloperoxidase channel) − (polymorphonuclear [PMN] sub-fraction measured in the nuclear
lobularity channel) (17, 19-21). A strong association has been reported between DNI and increased
mortality in patients with systemic sterile inflammation, such as those with out-of-hospital cardiac
arrest and upper gastrointestinal haemorrhage (20, 22). The aim of the present study was to evaluate
whether an increased DNI is able to predict 28-day mortality in patients with acute PE, and to
investigate the clinical usefulness of the DNI as a marker of severity in patients with acute PE admitted
to the ED.
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PATIENTS AND METHODS
Study population
This retrospective observational study was performed in the ED of Severance Hospital, a universityaffiliated, tertiary level referral hospital with an annual census of approximately 85,000 visits. The
institutional review board of Yonsei University Health System (No 3-2017-0036) reviewed and
approved the study. The requirement for written informed consent from patients was waived.
We retrospectively identified consecutive adult patients (>18 years old) with acute PE admitted to the
ED from 1 January 2011 to 30 June 2017. We retrospectively analysed the data of patients who were
diagnosed with acute PE at a single ED admission and had a final diagnosis of acute PE (according to
ICD-9 codes: I.260/ I.269) based on the findings of computed tomography (CT) performed in the ED.
The definitive CT-based diagnosis of acute PE was defined as the presence of at least one intraluminal
filling defect in an interlobar or more proximal pulmonary artery (6). We also analysed the patients’
electronic medical records. The enrolment, exclusion, and clinical outcome data for patients with acute
PE are shown in Figure 1. We excluded patients with acute myocardial infarction, those who received
chemotherapy within 7 days prior to ED admission, those with concurrent infection at the time of ED
admission, those transferred out to other hospitals, and those who self-discharged against medical
advice. Other exclusion criteria were chronic inflammatory disorders, including autoimmune diseases,
a history of previous or current haematological malignancy, and chronic PE. The primary end-point of
this study was all-cause mortality within 28 days of ED admission following acute PE. In addition, the
secondary end point was in-hospital development of hypotension or shock. To investigate in-hospital
occurrence of hypotension or shock, in additional analysis, we excluded if they had hypotension (as
defined by systolic blood pressure (SBP) <90 mmHg, shock or the need for intravenous infusion of
catecholamine) on ED admission and the need for ventilator support (n=32)(6). In-hospital occurrence
of hypotension was defined as SBP less than 90 mmHg for more than 15 min without signs of
hypovolemia (bleeding, dehydration, vomiting, diarrhea, adverse effects of drugs) or sepsis, within 24 h
Copyright © 2017 by the Shock Society. Unauthorized reproduction of this article is prohibited.
of admission and In-hospital development of shock was defined as patients with arterial hypotension
accompanied by cardiogenic shock or judged by the attending physicians to require the administration
of catecholamines(6).
Data collection
We collected data on demographic characteristics (age; sex; previous medical history, including
previous PE, previous deep vein thrombosis, and malignancy); health-related complaints;
haemodynamic parameters; laboratory results; radiological findings, including involved artery;
echocardiographic findings, including RV dilatation; in-hospital course and clinical outcome; the main
type of treatment received;and period of follow-up. The DNI for each patient was determined using
venous blood in EDTA (ethylenediaminetetraacetic) containing vacutainerson presentation to the ED
(time-0; within 15 minutesafter ED admission) andtime-24 (24 ± 6 hours after admission). To assess
the DNI, we used the same type of haematology analyser (ADVIA 2120; Siemens, Forchheim,
Germany) used for the analysis of the CBC. The PESI was measured on ED admission to evaluate the
clinical severity of each patient.
DNI measurement
The specific analysers used comprise an optical system based on a cytochemical myeloperoxidase
tungsten-halogen channel (that measures and differentiates neutrophils, eosinophils, lymphocytes,
monocytes, and large unstained cells based on size and myeloperoxidase staining intensity) and a laserdiode channel (that calculates, classifies, and counts cell types with respect to lobularity/nuclear density
and size)(15, 19, 20, 22). The DNI was then calculated by subtracting the fraction of mature PMNs
from the sum of the myeloperoxidase-reactive cells, detecting circulating immature granulocytes as the
leukocyte sub-fraction (15, 19, 20, 22). We also performed other laboratory tests, including
determination of cardiac markers, electrolytes, D-dimer, high sensitivity C-reactive protein (hs-CRP)
and creatinine at the time of ED admission.
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Statistical analysis
We presented demographic and clinical data as the median and interquartile range (IQR), mean ±
standard deviation (SD), or percentage and frequency, as appropriate. We compared continuous
variables using a two-sample t-test or the Mann–Whitney U-test and categorical variables using the χ2
test or Fisher’s exact test. A linear mixed model and repeated measures covariance pattern with
unstructured covariance within patients were estimated to assess significant differences between
survival and non-survival groups over time. Two fixed effects were assessed: A time effect (time: DNI
obtained on admission and 24-h after ED admission) and a clinical effect (level: survival and nonsurvival on 28-day). Differences in clinical effect over time were analysed in accordance with clinical
effect × time effect. In addition, we also measured significant differences between groups over time for
the development of in-hospital hypotension.We determined the area under the curve (AUC) using
receiver operating characteristic curves (ROC) to identify the effect of the DNI for predicting the
occurrence of in-hospital hypotension and 28-day mortality in patients with acute PE. Youden’s
method was used to determine the optimal DNI cut-off value. In addition, we combined the DNI on ED
admission with the PESI, using an ROC analysis.
Univariable Cox proportional hazards regression analyses were conducted to assess relationships
between demographic characteristics and clinical data. A multivariable Cox proportional hazards
regression analysis that integrated the major covariates (variables with a p< 0.05) identified in the
univariable analyses was also performed to identify promising independent factors predictive of 28-day
mortality, considering time-to-event data in patients with PE. We used the PESI as a variable in this
model because this scoring system, which was created by integrating the clinically significant variables
identified in this study, can represent various variables. The results are expressed as hazard ratios
(HRs) and 95% confidence intervals (CIs). In this study, we used the calibration plot to confirm the
suitability of the applied prediction model. We combined the variables included in the multivariable
Cox proportional hazard and calculated the probability for occurrence of an event. We created KaplanMeier survival curves using 28-day mortality data, and compared groups using the log-rank test. We
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calculated Harrell’s C-index to determine the time-dependent discriminatory ability and ability of DNI
to predict 28-day mortality in patients with acute PE (23). To determine the additional predictive power
of the DNI, we compared it with the C index to assess whether the DNI provided the better prognostic
value. In addition, the PESI is a useful scoring system to predict mortality in patients with acute PE. To
identify improvement of the predictive power of the DNI for 28-day mortality, we compared the
change in AUC, the integrated discrimination improvement (IDI), and continuous net reclassification
improvement (NRI) values between the PESI and PESI+DNI.Although previous studies estimated cutoff values based only on events, we also estimated optimal cut-off values for the dichotomization of the
clinical outcome variable based on time-to-event data using the technique devised by Contal and
O’Quigley(16, 20). We selected the optimal cut-off point by maximizing the HR. To identify the exact
cut-off point, we determined the cut-off point in the discovery cohort by using the Contal and
O’Quigley method, after which we performed internal validation using bootstrapping (a mean HR of
1,000 repetitions). We performed internal validation with >3.0% of the optimal cut-off points and
calculated HR, accuracy, sensitivity, specificity, negative predictive value (NPV), and positive
predictive value (PPV) to predict 28-day mortality. Statistical analyses were performed using SAS
software, version 9.2 (SAS Institute Inc., Cary, NC); R software, version 3.2.5 for Windows (the R
foundation for statistical computing, Vienna, Austria; http://www.R-project.org/); and MedCalc,
version 12.7.0 (MedCalc Software, Ostend, Belgium). A p-value < 0.05 was considered significant.
RESULTS
A total of 447patients were included in this study. The enrolment, exclusions, and clinical outcome data
for patients with acute PE are shown in Figure 1. Of 447 study patients, 46 died within 28 days. Of 46
deaths, 7 patients had chest pain and 5 had haemoptysis. There was no significant difference in the
development of chest pain between the survival (20.7%) and non-survival group (15.2%, p=0.38).
However, the development of haemoptysis was significantly higher in the mortality group (10.87%)
than in the survival group (2.99%, p=0.022). There were significant differences in DNI values on ED
Copyright © 2017 by the Shock Society. Unauthorized reproduction of this article is prohibited.
admission between the survival (1.16%) and non-survival (4.41%) groups according to 28-day
mortality (p< 0.001) (Table 1 and appendix 2, http://links.lww.com/SHK/A654). The mean PESI score
was significantly higher in the non-survival (125.9± 38.4) than in the survival (102± 37) group (p<
0.001). Of 415 study patients, 44 (10.6%) developed the hypotension or shock. Figures showed effects
obtained for time, by group, and by interaction according to 28-day mortality and the development of
hypotension or shock (Fig. 2A, B and appendix 3, http://links.lww.com/SHK/A654).The AUC for the
DNI on ED admission for predicting 28-day mortality was 0.767 (p< 0.001) (Fig. 2C). When the PESI
was combined with DNI on ED admission in the ROC analysis, the AUC increased significantly from
0.695 to 0.809 (p< 0.001) (Fig. 3A and appendix 4, http://links.lww.com/SHK/A654). In the prediction
of 28-day mortality, when the DNI at time-0 was added to the PESI, the change in the AUC was 0.114
(range, 0.051–0.177, p=0.001), NRI was 0.104 (range, 0.044–0.163, p=0.001), and IDI was 0.337
(range, 0.16–0.514, p=0.04). Thus, the predictive power of DNI for 28-day mortality improved. When
the DNI at time-0 was added to the PESI, the change in the AUC, IDI, and NRI values were higher
than that with the addition of the WBC count at time-0 to the PESI (Appendix 5,
http://links.lww.com/SHK/A654).
We demonstrated that the DNI on ED admission in the univariable Cox regression analyses differed
significantly between the survival and non-survival groups, stratified by 28-day mortality (Appendix 6
and 7, http://links.lww.com/SHK/A654). The multivariable Cox regression model demonstrated that
the DNI on ED admission (HR, 1.107; 95% CI, 1.042–1.177; p = 0.001) was a significant independent
predictor of 28-day mortality in patients with acute PE (Table 2). To improve the statistical reliability,
all variables that were significant (p<0.05) in the univariable analysis were included in the
multivariable Cox proportional hazard model of this study. The multivariable Cox proportional hazard
model, including all these variables, further confirmed the significant association between increased
DNI values at time-0 and time-24 and an increased risk of 28-day mortality and development of shock
or hypotension among patients with PE (Appendices8, 9, and 10, http://links.lww.com/SHK/A654).We
confirmed that this probability is consistent with the occurrence rate of actual events using the
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calibration plot (Appendix 11, http://links.lww.com/SHK/A654).The Kaplan–Meier curves (Fig. 3B)
demonstrated that the DNI value on ED admission independently predicted 28-day mortality in patients
with acute PE (p < 0.001). The optimal cut-off of DNI for predicting 28-day mortality was 3.0% at ED
admission (p < 0.001(sensitivity: 54.35% [39–69.1]; specificity: 88.78% [85.3–91.7])); a DNI >3.0% at
ED admission was strongly associated with an increased riskof short-term mortality among patients
with acute PE (HR, 7.447; 95% CI, 4.183–13.366; p< 0.001) (Appendix 12,
http://links.lww.com/SHK/A654). We performed internal validation using bootstrapping (a mean HR
of 1,000 repetitions). The results obtained by internal validation were similar to those of the deviation
cohort (Table 3).The Harrell’s C-index of DNI on ED admission for predicting 28-day mortality was
0.752 (95% CI 0.673–0.82, p< 0.001). The white blood cell (WBC) count, platelet count, and
haemoglobin level can also be determined automatically along with the CBC. The C-statistic of the
DNI on ED admission was statistically superior to that of the WBC count, platelet count, and
haemoglobin level on ED admission for predicting 28-day mortality. Compared with the Harrell Cindex of the present study, the C-statistic of the DNI on ED admission was not statistically inferior to
that of the PESI score and hs-CRP level for predicting 28-day mortality. In addition, the C-statistic of
the DNI on ED admission was statistically superior to that of the troponin I and D-dimer level for
predicting 28-day mortality (Fig. 4 and appendix 13,http://links.lww.com/SHK/A654).
DISCUSSION
To the best of our knowledge, this is the first study to determine the usefulness of the DNI, reflecting
the number of circulating immature granulocytes, to predict short-term mortality in patients with acute
PE in an emergency setting. Acute PE is generally a critical condition that leads to death soon after ED
admission (1). Risk stratification should be promptly conducted in the ED (1). In the present study, we
demonstrated that DNI was a significant independent predictor of 28-day mortality in patients with
acute PE. We determined that DNI values >3.0% on ED admission could significantly predict 28-day
mortality in this group of patients. Hence, these DNI values—obtained rapidly, easily, and
inexpensively as part of the CBC measurement—can be used to assess severity regardless of
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haemodynamic instability in patients with acute PE (15, 22, 24). Predicting the prognosis of patients
with acute PE has been based on clinical features and markers reflecting myocardial injury or
dysfunction (1). In haemodynamically stable patients, RV hypokinesis and dilatation measured by
echocardiography or RV dysfunction assessed by multi-detector CT are well-known independent
predictors of short-term mortality (1, 25, 26). In the present study, age, systolic blood pressure, white
blood cell count, haemoglobin level, NT-pro BNP, D-dimer, hs-CRP, t-CO2, RV dilatation, and the
PESI (including age; sex; a history of cancer, heart failure, and chronic lung disease; heart rate
≥110/min; systolic blood pressure <110 mm Hg; respiratory rate ≥30/min; temperature <36 °C; alerted
mental status; and oxygen saturation <90%) were risk factors for 28-day mortality among patients with
acute PE. Although many studies have attempted to stratify risk in patients with acute PE, simple and
readily available markers to assess prognosis are still needed in the emergency setting (8). Despite the
relative complexity of using 11 predictors to calculate the PESI in the emergency setting, the PESI is
based only on variables related to the medical history and physical examination; it does not require
laboratory evaluation (9). Although this is a benefit, it does mean that the score simply reflects the
general and current condition of a patient, it might not reflect the severity of a specific disease (27).
Moreover, variability in even one or two parameters (such as age or sex) may lead to the classification
of patients as being high- or low-risk (27). Using ROC analysis, we demonstrated that the PESI
combined with DNI on ED admission improved its discriminative power to predict 28-day mortality.
In acute PE, a higher value of troponin is strongly correlated with RV dysfunction as marker of
cardiomyocyte damage (6). NT-proBNP, a stress-related marker released by myocytes, is elevated in
patients with adverse outcomes after acute PE (28, 29). A systemic review by Sanchez et al.
demonstrated that the unadjusted relative risk to predict in-hospital or 30-day mortality was 8.3 (95%
CI 3.6–19.3) for troponin-T, 9.5 (95% CI 3.1–28.6) for brain natriuretic peptide, and 5.7 (95% CI 2.2–
15.1) for NT-proBNP(26). Higher values of cardiac markers were significantly associated with an
increased risk of short-term mortality in haemodynamically stable patients with acute PE (1, 26). In the
present study, we also compared the Harrell’s C-index of PESI score, D-dimer, and troponin-I for
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predicting 28-day mortality. The C-statistic of DNI at ED admission was not statistically inferior to that
of PESI score and hs-CRPfor predicting 28-day mortality. The C-statistic of the DNI on ED admission
was statistically superior to that of the troponin I and D-dimer level for predicting 28-day mortality.
Considering the easy availability and cost-effectiveness of the DNI compared with the measurement of
natriuretic peptides, troponins, and C-reactive protein, DNI may represent a valuable alternative marker
for risk stratification in patients with PE.In addition, PE may be completely asymptomatic and be
discovered incidentally during diagnostic work-up for another disease or at autopsy(30).The DNI at
time 0 may not reflect the exactduration between the onset of symptoms and measurement of the DNI
on ED admission.As a result, this suggests the possibility that lower DNI values in some patients were
assessed because the patients presented too early for an increase in the DNI to be apparent. The present
study demonstrated a significant association between increased DNI values at time 0 and time 24 and
an increased risk of 28-day mortality and the development of shock or hypotension among patients
with PE. Serial DNI measurements should be considered because the DNI value can be easily
determined without additional burdens of cost or time.
Although the pathophysiological mechanisms by which PE induces severe morbidity and mortality are
not completely understood, Virchow’s triad (blood flow alteration, damage to the vessel wall, and
hypercoagulability) is considered the main mechanism (31). However, inflammation (including that
occurring as a result of ischaemia, pulmonary arterial hypertension, and thrombus-endothelial
interaction) also plays an important role (8). Abul et al. demonstrated that in patients with PE, the CRP
(a well-known marker of inflammation and tissue damage) is strongly associated with RV dysfunction
and mortality at 36 months (8). Intravascular healing processes are activated by damage-associated
molecular patterns of non-infectious cellular debris that cause the release of several immune
components, such as cytokines, chemokines, and several types of leukocytes. These contribute to the
inflammatory responses of PE as a double-edged sword: The impaired thrombosis resolves, but the risk
of PE-related complications increases (31-33). Inflammation following PE contributes to damage and
dysfunction of the RV and to cardiac inflammation (8, 14, 34). In addition, vascular inflammatory
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reactions and pulmonary parenchymal inflammation can be induced by PE (12). Despite the benefit of
thrombus resolution by late activation of the neutrophil population, neutrophils are significantly
associated with acute severe damage to the lung parenchyma and the RV of the heart in the early stage
of the acute inflammatory response following acute PE (14, 31). There is a significant increase in PMN
infiltration into the alveolar cavity; this damages the tissues (12). Watts et al. demonstrated that the
influx of neutrophils in the inflammatory phase starts 8–18 h after PE (34). Changes occur in the RV
within 24 h of PE; the colour changes to white and there is increased myeloperoxidase activity,
indicating the presence and activation of PMNs in the RV (14, 31, 34).
Given the importance of neutrophils in the pathogenesis of acute PE, several studies have suggested
mechanisms to explain this early and rapid release of immature granulocytes. In patients with upper
gastrointestinal haemorrhage (UGIH),Kong et al. proposed that massive bleeding at the injured site
preferentially induces rapid expansion of circulating neutrophils to compensate for the loss of active
neutrophils secondary to the massive loss, consumption, and destruction of mature cells(22, 35).
Massive haemorrhage or shock is associated with the production of proinflammatory cytokines and
chemokines(22, 36). In the pathogenesis of acute PE,First, the haematopoietic system is rapidly able to
switch from steady-state to emergency granulopoiesis to compensate for the loss of active neutrophils
secondary to massive consumption resulting from neutrophil infiltration and from the destruction of
mature cells under stress conditions such as severe infection and hypoperfusion(34, 36, 37). The
increased production of pro-inflammatory cytokines and chemokines (such as interleukin (IL)-6, IL-8,
and tumour necrosis factor-alpha) induces rapid expansion of neutrophils soon after PE. This
exacerbates the local and systemic inflammatory response. However, severe systemic and sterile
inflammation can result in microvascular dysfunction, tissue damage, and dysregulation of metabolism
(36). Second, widespread inflammation requires a profound ‘compensatory’ downregulation of immune
responses (37). Neutrophil paralysis—known as dysregulated neutrophil function—attenuates tissue
damage in severe sterile inflammation as a result of impaired migration of neutrophils to the injured
site and neutrophil sequestration in remote organs (37, 38). Consequently, the number of circulating
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immature granulocytes may increase to compensate for the rapid decrease in the number of active
neutrophils. Under these conditions, the host is highly susceptible to infections. Moreover,
dysregulation of immune mechanisms may increase mortality (37). Third, sustained hypotension and
shock as a result of overt RV failure are significantly associated with higher mortality in patients with
acute PE; hence, immediate reperfusion therapy is needed (1, 2). Sauneuf et al. proposed bone marrow
exhaustion as a further mechanism by which severe ischaemia-induced inflammation can lead to
transient failure in the regulation of neutrophil release during ischaemia and following resuscitation
(39, 40). In particular, haemodynamic instability or persistent severe inflammation due to an increase in
the severity of acute PE may affect critical regulatory mechanisms for neutrophil release from the bone
marrow. Our results suggest that patients with acute PE should be carefully monitored if the DNI value
exceeds 3.0%, considering the association between this value and 28-day mortality (HR, 7.477; 95%
CI, 4.183–13.366; p < 0.001).
A previous study by Kong et al. reported that the optimal cut-off values for DNI on ED admission and
on day 1 were 1% (HR, 4.09) and 2.6% (HR, 7.85) and that these levels were associated with an
increased hazard of 30-day mortality following upper gastrointestinal bleeding (22). Regarding the
severity of disease, Yune et al. demonstrated that DNI values >8.4% on admission (HR, 3.227) and
DNI >10.5% on day 1 (HR, 3.292) were associated with increased 30-day mortality in patients
surviving out-of-hospital cardiac arrest (20). These findings imply that a higher DNI reflects greater
severity of systemic and sterile inflammation and of the disease process (20).Considering mechanisms
for this early and rapid release of immature granulocytes,an increased DNI may not be solely specific
to pulmonary embolism-related mortality. Therefore, the DNI predicts the mortality for severe diseases
associated with severe inflammation, reflecting increased pro-inflammatory cytokines and other
mediators.
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Study limitations
This study has some limitations. First, it was a single-centre retrospective study, increasing the
possibility of selection bias. Large, multi-centre, prospective studies and randomized clinical trials are
required to validate the clinical usefulness of the DNI as a prognostic marker in patients with acute PE.
Second, we assessed only short-term mortality in patients with PE; the long-term clinical outcomes also
need to be assessed. Third, although the troponin, D-dimer, and hs-CRP levels in most patients were
obtained at time-0, these values at time-24 were not mandatorily determined in patients with acute PE
to ensure cost-effectiveness. In this study, we could not directly compare the predictability of clinical
outcomes with values at time-0 and time-24 for the troponin, D-dimer, and hs-CRP levels.However, the
DNI, as a promising predictor of acute PE, has the additional benefit of being automatically analyzed
with the CBC, which is routinely and immediately performed in critically ill patients, without
additional time or costs required. Considering the disease severity of PE, the CBC test is
usuallyperformed serially in the intensive care unit. In this situation, an increased DNI is able to predict
severity in patients with acute PE, and the DNI as a marker of severity canhelp clinicians consider more
specific markers with a higher cost. Fourth, although we excluded patients with infectious conditions
within 24 h of ED admission a priori(41), the production of immature granulocytes by the bone
marrow may be influenced by infection, in addition to stress and systemic inflammation. Further
studies are needed to identify the clinical effects of the DNI in patients with infection and systemic
sterile inflammation. Finally, although studies have investigated the effects of systemic inflammation,
we were unable to evaluate measures of the inflammatory response (such as pro-inflammatory
cytokines and chemokines) and to compare the DNI with such inflammatory markers. Further studies
are required to compare directly DNI values and indicators of the severity of systemic inflammation as
prognostic markers in patients with acute PE. In addition, the pathophysiological mechanisms by which
acute PE induces severe morbidity and mortality are not completely understood; therefore, further
molecular studies are needed to validate the direct effects of immature granulocytes on the progression
of acute PE.
Copyright © 2017 by the Shock Society. Unauthorized reproduction of this article is prohibited.
CONCLUSION
The DNI values obtained as part of the CBC can be easily determined with no additional cost or time
burden. An increased DNI value is useful as a marker to predict 28-day mortality in patients with acute
PE.
Declaration of Interests
The authors declare no conflict of interests
Disclosure of funding
J. S. You received support from the Basic Science Research Program of the National Research
Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF2015R1C1A1A01054641), and the Yonsei University Future-leading Research Initiative for 2015
(2015-22-0096). S.P. Chung and T.Y. Kong were supported by basic Science Research Program
through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and
future Planning (2017R1A2B4012378). J.S.You received research fund from Siemens Health Care.
However, the fund did not exceed $10,000/year. The funding bodies had no role in the design,
collection, analysis, or interpretation of this study. The other authors have no financial conflicts of
interest.
Copyright © 2017 by the Shock Society. Unauthorized reproduction of this article is prohibited.
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Figure legends
Figure 1.Flow diagram of patient enrolment, exclusions, and clinical outcomes.
PE, pulmonary embolism; ED, emergency medicine; CT, computed tomography; DNAR, do not
attempt resuscitation
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Figure 2. Linear mixed model of the DNI to estimate significant differences between groups over time
according to 28-day mortality (A) and the occurrence of in-hospital hypotension or shock (B); receiver
operating characteristic curves for the predictability of the DNI on ED admission for 28-day mortality
(C) and the occurrence of in-hospital hypotension or shock(D).
DNI, delta neutrophil index; AUC, area under the curve; ED, emergency department
Copyright © 2017 by the Shock Society. Unauthorized reproduction of this article is prohibited.
Figure 3. (A) A combination of the DNI and the PESI significantly improves the area under the curve
compared to the PESI alone; (B) based on the Kaplan-Meier curves for 28-day mortality, results of the
log-rank tests demonstrate that a higher DNI is an independent risk factor for patients with acute
pulmonary embolism.
DNI, delta neutrophil index; PESI, Pulmonary Embolism Severity Index
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Figure 4. Comparison of Harrell C-indices for assessing the discriminatory ability of biomarkers
measured on admission to stratify the risk of 28-day mortality.
PESI, Pulmonary Embolism Severity Index; WBC, white blood cell count
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Table 1.Clinical characteristics of patients with acute pulmonary embolism, stratified by 28-day
mortality.
N= 447
(100 %)
65.0±16.2
193 (43.18)
104.5±37.8
28-day Mortality
Survival
Death
N=401 (89.7 N=46 (10.3 p-value
%)
%)
64.4±16.4
70.4±13.1
0.016*
171 (42.64)
22 (47.83)
0.502
102.0±37.0 125.9±38.4 <0.001*
123.9±28.6
96.2±21.8
18.4±3.9
94.2±6.5
36.8±0.7
124.9±28.2
95.9±21.3
18.3±3.8
94.3±6.6
36.8±0.7
115.1±30.5
98.6±25.8
19.0±5.1
92.8±6.4
36.9±0.8
0.028*
0.424
0.404
0.132
0.089
55 (12.30)
90 (20.13)
17 (3.80)
47 (11.72)
83 (20.70)
12 (2.99)
8 (17.39)
7 (15.22)
5 (10.87)
0.268
0.380
0.022*
49 (10.96)
63 (14.09)
44 (10.97)
58 (14.46)
5 (10.87)
5 (10.87)
0.983
0.507
32 (7.16)
26 (6.48)
6 (13.04)
0.124
169 (37.81)
42 (9.40)
153 (34.23)
140 (34.91)
38 (9.48)
136 (33.92)
29 (63.04)
4 (8.70)
17 (36.96)
<0.001*
>0.999
0.681
40 (8.95)
40 (8.95)
8 (1.79)
90 (20.13)
34 (8.48)
39 (9.73)
8 (2.00)
78 (19.45)
6 (13.04)
1 (2.17)
0 (0.00)
12 (26.09)
0.281
0.104
>0.999
0.289
74 (16.55)
65 (16.21)
9 (19.57)
0.562
142 (31.77)
253 (56.60)
372 (83.22)
128 (28.64)
128 (31.92)
233 (58.10)
336 (83.79)
116 (28.93)
14 (30.43)
20 (43.48)
36 (78.26)
12 (26.09)
0.838
0.058
0.342
0.687
63.4±9.9
63.3±10.1
63.7±7.6
0.790
40.7±16.7
168 (37.58)
40.2±16.5
143 (35.66)
45.6±17.4
25 (54.35)
0.069
0.013*
9.9±4.7
7.5±4.4
9.8±4.6
7.3±4.2
12.1±5.5
9.8±5.2
0.001*
0.002*
Total
Variables
Age (years)
Male gender [n (%)]
PESI score (point)
Initial vital sign
Systolic blood pressure (mmHg)
Heart rate (bpm)
Respiratory rate (bpm)
O2 saturation (%)
Body temperature (°C)
Initial symptom [n (%)]
Altered mental status
Chest pain
Hemoptysis
Comorbidity [n (%)]
Congestive heart failure
Coronary artery occlusive disease
Chronic obstructive pulmonary
disease
Malignancy
Previous DVT or PE
Chronic kidney disease
Treatment modality [n (%)]
Tissue plasminogen activator
Inferior vena cava filter
Thrombectomy
Usage of LMWH
Usage of unfractionated
heparin/LMWH
Localization of thrombosis [n
(%)]
Main pulmonary artery
Lobar pulmonary artery
Segmental pulmonary artery
Sub-segmental pulmonary artery
Echocardiographic findings
Left ventricular ejection fraction
(%)
RVSP (mmHg)
Right ventricular dilatation [n (%)]
Laboratory data
White blood cell count (10^3/μL)
Neutrophil count (10^3/μL)
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Platelet count (10^3/μL)
Hemoglobin (g/dL)
Creatinine (mg/dL)
Creatinine Kinase-MB (mcg/L)
Troponin I (mcg/L)
D-dimer (mcg/L)
hs C-reactive protein (mg/L)
Arterial blood PH
tCO2 (mmol/L)
Delta neutrophil index Time-0 (%)
Delta neutrophil index Time-24
(%)
234±124
12.6±2.3
0.9±0.6
3.4±4.1
0.06±0.09
4109±5534
54±69
7.44±0.08
21.2±3.9
1.49±2.94
235±124
12.6±2.3
0.9±0.7
3.4±4.2
0.06±0.09
3745±4292
49±65
7.44±0.07
21.4±3.6
1.16±2.36
2.74±4.78
2.37±4.25
226±126
0.629
11.8±2.2
0.013*
0.9±0.5
0.620
2.7±2.0
0.067
0.05±0.05
0.277
7458±11558 0.045*
102±88
<0.001*
7.43±0.11
0.420
19.7±5.1
0.036*
4.41±5.17 <0.001*
6.20±7.40
0.002*
PESI, Pulmonary Embolism Severity Index; DVT, deep vein thrombosis; PE, pulmonary embolism;
LMWH, low molecular weight heparin; RVSP, right ventricle systolic pressure; hs C-reactive protein,
high sensitivity C-reactive protein. Data are expressed as the mean ± standard deviation or number
(percentage). *P<0.05.
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Table 2.Multivariable Cox proportional hazard regression analysis for predictors of 28-day
mortality in patients with acute pulmonary embolism.
Multivariable cox proportional hazard regression analysis (28-day
mortality)
Variable
PESI score (per 1
point)
Right ventricular
dilatation
Hemoptysis on
admission
White blood cell
count (per 10^3/μL)
Neutrophil count
(per 10^3/μL)
Hemoglobin (per 1
g/dL)
D-dimer ((per 1
mcg/L))
hs C-reactive protein
(per 1 mg/L)
tCO2 (per 1
mmol/L)
Delta neutrophil
index Time-0 (per 1
%)
Delta neutrophil
index Time-24 (per
1 %)
HR (95% CI)
p-value
HR (95% CI)
p-value
1.009 (1.000-1.018)
0.047*
1.007 (0.998-1.016)
0.125
2.618 (1.243-5.513)
0.011*
3.171 (1.450-6.933)
0.004*
4.174 (1.318-13.222)
0.015*
3.124 (0.914-10.683)
0.069
0.869 (0.669-1.130)
0.295
0.783 (0.585-1.048)
0.100
1.158 (0.886-1.515)
0.283
1.315 (0.970-1.783)
0.078
0.956 (0.814-1.124)
0.590
0.923 (0.780-1.091)
0.348
1.006 (1.002-1.011)
0.002*
1.002 (0.996-1.008)
0.570
1.005 (1.001-1.009)
0.015*
1.005 (1.001-1.009)
0.010*
0.961 (0.891-1.036)
0.302
0.945 (0.869-1.028)
0.186
1.107 (1.042-1.177)
0.001*
1.040 (1.001-1.081)
0.047*
HR, hazard ratio; CI, confidence interval; PESI, Pulmonary Embolism Severity Index; hs C-reactive
protein, high sensitivity C-reactive protein. *P<0.05.
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Table 3. Sensitivity and specificity analysis of the delta neutrophil index (DNI) to predict 28-day
mortality.
28-day mortality (DNI Time-0 >3.0%)
Hazard ratio (95% CI)
Discovery cohort
p-value
Internal validation
cohort
p-value
7.477 (4.183-13.366)
<0.001*
7.477 (4.183-13.366)
<0.001*
28-day mortality (DNI Time-0 >3.0%)
Internal validation
Discovery cohort
cohort
Sensitivity % (95% CI)
54.4 (39.0-69.1)
54.4 (40.0-68.2)
Specificity % (95% CI)
88.8 (85.3-91.7)
88.8 (85.4-91.9)
Positive predictive value % (95% CI)
35.7 (24.5-46.9)
35.8 (24.7-47.0)
Negative predictive value % (95% CI)
94.4 (92.1-96.7)
94.4 (92.0-96.8)
Accuracy % (95% CI)
85.2 (81.9-88.5)
85.3 (81.9-88.6)
DNI, delta neutrophil index; CI, confidence interval. *P<0.05.
The optimal cut-off point was determined in the discovery cohort by using Contal and O’Quigley’s
method. A cut-off of 3% was applied to the population, and the sensitivity and specificity was
estimated in DNI. When the same cut-offs were applied to the validation cohort using bootstrapping
(mean HR of 1,000 repetitions), the Sensitivity and specificity analysis obtained by internal validation
were similar to deviation cohort.
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