White blood cell count and mortality in patients with acute pulmonary embolism

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1 Research Article White blood cell count and mortality in patients with acute pulmonary embolism Carmen Venetz, 1 Jose Labarère, 2 David Jimenez, 3 and Drahomir Aujesky 1 * Although associated with adverse outcomes in other cardiovascular diseases, the prognostic value of an elevated white blood cell (WBC) count, a marker of inflammation and hypercoagulability, is uncertain in patients with pulmonary embolism (PE). We therefore sought to assess the prognostic impact of the WBC in a large, state-wide retrospective cohort of patients with PE. We evaluated 14,228 patient discharges with a primary diagnosis of PE from 186 hospitals in Pennsylvania. We used random-intercept logistic regression to assess the independent association between WBC count levels at the time of presentation and mortality and hospital readmission within 30 days, adjusting for patient and hospital characteristics. Patients with an admission WBC count <5.0, , , , and > /L had a cumulative 30-day mortality of 10.9%, 6.2%, 5.4%, 8.3%, and 16.3% (P < 0.001), and a readmission rate of 17.6%, 11.9%, 10.9%, 11.5%, and 15.0%, respectively (P < 0.001). Compared with patients with a WBC count /L, adjusted odds of 30-day mortality were significantly greater for patients with a WBC count < /L (odds ratio [OR] 1.52, 95% confidence interval [CI] ), /L (OR 1.55, 95% CI ), or > /L (OR 2.22, 95% CI ), respectively. The adjusted odds of readmission were also significantly increased for patients with a WBC count < /L (OR 1.34, 95% CI ) or > /L (OR 1.29, 95% CI ). In patients presenting with PE, WBC count is an independent predictor of short-term mortality and hospital readmission. Am. J. Hematol. 88: , VC 2013 Wiley Periodicals, Inc. Introduction Evidence suggests that the white blood cell (WBC) count is associated with adverse outcomes in patients with cardiovascular diseases, such as acute coronary syndrome, heart failure, and ischemic stroke [1 7]. In acute coronary syndrome, WBCs cause myocardial injury via vascular plugging, direct injury to myocytes and the coronary endothelium, and pro-inflammatory cytokines [3]. Neutrophilic infiltration and the production of reactive oxygen species has been postulated as a mechanism for left ventricular failure [8]. Acute pulmonary embolism (PE) is a major health problem; in 2010, 190,000 patients were discharged with a primary diagnosis of PE from US hospitals [9], with an estimated average 30-day mortality of 9% [10]. Early death after PE is strongly associated with right ventricular dysfunction [11]. Animal and autopsy studies demonstrated that neutrophils are not only involved in the development of venous thrombosis but that an influx of neutrophils and other WBCs may contribute to right ventricular dysfunction following PE [12 17]. Moreover, the WBC count also correlates with levels of fibrinogen, factor VII, and factor VIII and thus, may be a marker for hypercoagulability [18]. Based on a previously observed association between an elevated WBC count and short-term mortality in patients with PE [19], we hypothesized that an elevated WBC at baseline, a marker of inflammation and hypercoagulability, may indicate a worse prognosis in patients with this illness. We therefore examined the association between the admission WBC count and 30-day mortality and hospital readmission in a large, statewide sample of patients with acute PE. If found, such association may be useful to riskstratifying patients with acute PE, given that WBC count is a low-cost, routinely available laboratory parameter. Methods Patient identification and eligibility We identified patients with PE discharged from 186 nongovernmental (i.e., non-veterans Administration) acute care hospitals in Pennsylvania, USA (01/01/2000 to 11/30/2002) using the VC 2013 Wiley Periodicals, Inc. American Journal of Hematology Pennsylvania Health Care Cost Containment Council (PHC4) database [10]. This database contains information on demographic characteristics, insurance status, International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis and procedure codes, hospital region and number of beds for all patients. We included inpatients aged 18 years who were discharged with a primary diagnosis of PE based on the following ICD-9-CM codes: 415.1, , , and [10]. To ensure that we identified the most severely ill patients with PE as the primary reason for hospitalization, we also included inpatients with a secondary diagnosis code for PE,and one of the following primary codes that may represent complications or treatments of this condition: respiratory failure (518.81), cardiogenic shock (785.51), cardiac arrest (427.5), secondary pulmonary hypertension (416.8), syncope (780.2), thrombolysis (99.10), and intubation or mechanical ventilation (96.04, 96.05, ). We excluded all other patients who had a secondary ICD-9-CM code for PE or those who were transferred from another health care facility, because such patients are more likely to have PE as a complication of hospitalization and we did not know whether PE was diagnosed and treated before the patient was transferred. We excluded follow-up records for patients who were subsequently transferred to Additional Supporting Information may be found in the online version of this article. 1 Division of General Internal Medicine, Bern University Hospital, Bern, Switzerland; 2 Techniques de l Ingenierie Medicale et de la Complexite, UMR 5525 Centre National de la Recherche Scientifique, Universite Joseph Fourier-Grenoble 1, Grenoble, France; 3 Respiratory Department, Ramon y Cajal Hospital, IRYCIS, Madrid, Spain Conflict of interest: Nothing to report 677 *Correspondence to: Drahomir Aujesky, Division of General Internal Medicine, Bern University Hospital, Inselspital, 3010 Bern, Switzerland. drahomir.aujesky@insel.ch Contract grant sponsor: National Heart, Lung, and Blood Institute; Contract grant number: 1-R21-HL A1; Contract grant sponsor: Swiss National Science Foundation; Contract grant number: 33CSCO / Received for publication 24 March 2013; Revised 3 May 2013; Accepted 7 May 2013 Am. J. Hematol. 88: , Published online 14 May 2013 in Wiley Online Library (wileyonlinelibrary.com). DOI: /ajh

2 other hospitals. We also excluded patients without the identifiers required for linkage to the necessary clinical data and those for whom mortality information was not available. For this analysis, we also excluded patients without a documented WBC count on admission. Patient and hospital characteristics Patient demographic characteristics (age, gender, race, and insurance status) were abstracted from the PHC4 Database [10]. Baseline clinical variables and laboratory parameters (including WBC counts) were obtained by linking eligible patients to the Atlas Database (MediQual, Marlborough, MA). This Database includes clinical findings at presentation for all inpatients treated at non-governmental acute care hospitals in Pennsylvania [10]. The PHC4 and Atlas databases were matched by PHC4 staff using unique patient identifiers (patient date of birth, gender, and social security number); we had no access to personal patient identifiers [10]. We quantified severity of illness using the Pulmonary Embolism Severity Index (PESI), a prognostic model for patients with PE that was developed and validated using these clinical data from the PHC4 and Atlas databases [10]. On the basis of the PESI, each patient is classified into one of five severity classes (I V), with 30-day mortality ranging from 1.1% to 24.5% [10]. To ascertain whether patients received thrombolytic therapy, we used ICD-9-CM procedure codes (99.10) from the PHC4 and Atlas databases. We abstracted the hospital region within Pennsylvania, number of beds per hospital site, and annual number of PE admissions for each site from the PHC4 database. We defined hospital teaching status based on data from the Council of Teaching Hospitals of the Association of American Medical Colleges. Because 76% of teaching hospitals, only 12% of nonteaching hospitals, had at least 350 hospital beds, we created a composite hospital-level variable for our statistical modeling based on teaching status and size (i.e., small nonteaching hospitals with fewer than 350 beds, large nonteaching hospitals with at least 350 beds, and teaching hospitals). Admission white blood cell count and outcomes Because the distribution of mortality by WBC count was J-shaped (figure in the Supporting Information), we categorized WBC counts into five categories by subdividing patients with WBC counts /L into quartiles ( , , , and > /L), whereas we assigned patients with WBC counts < /L to a separate category labeled subquartile [2]. This categorization ensured that the second quartile, which had the lowest mortality and readmission rate, would serve as the appropriate reference group for comparing the odds of death and readmission. Our primary study outcome was all-cause mortality within 30 days after admission by linking patients to the National Death Index using unique patient identifiers, including social security number, name, date of birth, and sex. The National Death Index has a sensitivity and specificity of 97% for identifying mortality [20 22]. To ascertain our secondary outcome, hospital readmission for any reason to any acute care hospital in Pennsylvania within 30 days of presentation, we used the PHC4 database. Statistical analyses We compared baseline patient characteristics across the five categories of WBC counts using chi-square tests for categorical variables and Kruskal Wallis rank tests for continuous variables. We used survival analyses and the log-rank test to compare the cumulative 30-day mortality and hospital readmission rates by WBC level. Surviving patients were censored at 30 days. To adjust for severity of illness, we also stratified our comparisons of mortality by WBC count categories and the five PESI severity risk classes. Missing values were assumed to be normal, a strategy that was successfully used to derive the PESI [10]. We used multivariable logistic regression to examine the independent association between admission WBC count and mortality, after adjusting for patient demographics (age, gender, race, and insurance type), comorbid diseases (history of cancer, chronic lung disease, and heart failure), and physical examining findings (pulse 110/minute, systolic blood pressure <100 mmhg, respiratory rate 30/minute, altered mental status, temperature <36 C, and arterial oxygen saturation <90%) comprising the PESI, laboratory values (hemoglobin, sodium, creatinine, glucose, and troponin), thrombolysis, and hospital characteristics (region within Pennsylvania, annual volume of PE, and size and teaching status). To account for patient clustering within hospital, we used random-intercept logistic regression with the two levels defined by patient and hospital site. We examined whether the addition of WBC count to PESI improved 30-day mortality risk prediction using the increase in the area under the receiver operating characteristic (ROC) curve and the net reclassification improvement (NRI) index. The NRI index quantifies the magnitude of improvement in risk prediction offered by the addition of the WBC count to the PESI based on upward and downward movements in the predicted probabilities of 30-day mortality [23]. We expected that the addition of WBC count to the PESI would increase the modelbased predicted probabilities for patients who died within 30 days of admission and decrease the model-based predicted probabilities for patients who were alive. We used the same logistic regression model to examine the association between WBC count and readmission within 30 days in patients discharged alive. Patients who were still hospitalized 30 days after admission and those without a documented readmission status were excluded from this analysis. To account for heterogeneity in length of hospital stay, we also calculated the number of hospital-free days from discharge to 30 days of follow-up or readmission, which ever occurred first, and compared the readmission incidence rates across categories of WBC count. All analyses were performed using Stata Results Of the 17,733 patient discharges who met our inclusion criteria, we excluded 323 patients with only a secondary code indicative of PE (1.8%), 767 patient transfers from another hospital (4.3%), 265 subsequent transfers to another hospital (1.5%), 777 without a match to key clinical findings (4.4%), and 70 patients without a linkage to the National Death Index (0.4%), leaving a sample of 15,531 patient discharges with PE (Fig. 1). Of these, we excluded 1303 (8.4%) discharges with an undocumented WBC count on admission. Our final study sample comprised 14,228 patient discharges with a diagnosis of PE from 186 Pennsylvania hospitals (Fig. 1). Overall, 822 (5.8%) had a WBC count below /L and 3278 (23.0%) had a WBC count above /L. Compared with the 14,228 enrolled patients, the 1303 patients excluded because of an undocumented WBC count were significantly younger (median age, 66 vs. 67 years; P ) and less likely to be men (37.1 vs. 40.4%; P ) and to have heart failure (13.0 vs.16.1%; P ) but were more likely to have a history of cancer (22.6 vs. 19.3%; P ). They were also less likely to have a pulse 110/minute (12.8 vs. 18.1%; P < 0.001), a systolic blood pressure <100 mmhg (7.8 vs. 10.7%; P ), a respiratory rate 30 breaths/minute (8.7 vs. 15.1%; P < 0.001), and an arterial oxygen saturation <90% (3.6 vs. 8.3%; P < 0.001) on admission. Comparison of baseline patient characteristics by white blood cell count level Patients with a WBC count > /L were older, more likely to have chronic lung disease and heart failure, and more likely to have clinical and biological signs of disease severity (tachycardia, hypotension, tachypnea, altered mental status, hypothermia, hypoxemia, hyponatremia, and elevated creatinine, glucose, and troponin levels) than patients with a WBC count /L (table in the Supporting Information). There was a higher proportion of patients in PESI risk class V among patients with a WBC count > /L. Patients with a WBC count < / L were more likely to have a history of cancer and anemia and to be in PESI risk class IV than patients with a WBC /L. Association of white blood cell count and 30-day mortality Overall 1300 of the 14,228 patients (9.1%) died within 30 days of admission. Patients with an admission WBC count <5.0, , , , and > /L had a cumulative probability of 30-day mortality of 10.9%, 6.2%, 5.4%, 8.3%, and 16.3%, respectively (P < 0.001) (Fig. 2). When stratified by each of the five PESI risk classes at presentation, mortality was highest among patients with a 678 American Journal of Hematology

3 Figure 1. Patient flow chart. WBC count > /L, followed by patients with a WBC count < /L (Table I). After adjustment, the odds of 30-day mortality remained significantly increased for patients with a WBC count < /L (odds ratio [OR] 1.52, 95% confidence interval [CI] ), /L (OR 1.55, 95% CI ), and > /L (OR 2.22, 95% CI ) (Table II). No evidence of first-order interaction was found between PESI risk classes and WBC count categories with regard to 30-day mortality (P ). The addition of WBC count to the PESI was associated with improved risk prediction for 659 (50.7%) of 1300 patients who died within 30 days of admission and with worse risk prediction for 641 (49.3%) patients. Conversely, risk prediction improved for 8068 patients (62.4%) and deteriorated for 4860 patients (37.6%) who were alive by 30 days of follow-up. The corresponding NRI index was 0.26 (95% CI ), indicating improvement in risk prediction. This finding was consistent with a modest but statistically significant increase in the area under the ROC curve (0.78 [95% CI ] vs [95% CI ] for the PESI with and without WBC count, P < 0.001). Association of white blood cell count and 30-day readmission The 30-day readmission rate was estimated in 13,261 patients, after the exclusion of 840 patients who died in the hospital, 93 who were still hospitalized 30 days after admission, and 34 with unknown readmission status. Overall, 1647 (12.4%) patients were readmitted within 30 days. Patients with an admission WBC count <5.0, , , , and > /L had a cumulative probability of 30-day readmission of 17.6%, 11.9%, 10.9%, 11.5%, and 15.0%, respectively (P < 0.001). After adjustment, patients with a WBC count < /L (OR 1.34, Figure 2. Kaplan Meier estimates of 30-day mortality were 10.9%, 6.2%, 5.4%, 8.3%, and 16.3% for patients with an admission white blood cell count of <5.0, , , , and >12.6x10 9 /L, respectively (P < 0.001). 95% CI ) and > /L (OR 1.29, 95% CI ) had significantly increased odds of 30-day readmission (Table II). The median (25 75th percentiles) length of hospital stay for patients who were discharged alive by 30 days of follow-up were 5 days (4 8), 6 days (4 8), 6 days (4 8), 6 days (4 8), and 6 days (5 9) for admission WBC counts <5.0, , , , and > /L, respectively (P < 0.001). The corresponding readmission incidence rates were 8.2, 5.3, 4.9, 5.2, and 7.2 per 1000 hospital-free days (P < 0.001), indicating that differences in readmission rates by WBC count were not related to differing length of hospital stay across categories of WBC count. American Journal of Hematology 679

4 TABLE I. Association of Mortality and Quartile of White Blood Cell Count Stratified by Severity of Illness Admission white blood cell count (310 9 /L) Pulmonary Embolism Severity Subquartile Quartile 1 Quartile 2 Quartile 3 Quartile 4 Index risk class < >12.6 P-value 30-Day mortality, n/n (%) I 2/124 (1.6) 5/745 (0.7) 5/700 (0.7) 9/715 (1.2) 10/447 (2.2) 0.10 II 4/153 (2.6) 22/816 (2.7) 15/793 (1.9) 24/704 (3.4) 27/529 (5.1) 0.02 III 13/188 (6.9) 36/764 (4.7) 28/742 (3.8) 51/762 (6.7) 77/664 (11.6) <0.001 IV 24/177 (13.5) 41/522 (7.8) 35/547 (6.4) 49/484 (10.1) 93/590 (15.7) <0.001 V 47/180 (26.1) 110/587 (18.7) 99/584 (16.9) 145/663 (21.9) 329/1048 (31.4) <0.001 Discussion Our results demonstrate that after adjustment for patientand hospital-related confounders, and thrombolytic therapy, patients with an elevated WBC count (> /L) had a significantly higher 30-day mortality. This was also true, albeit to a lesser extent, for patients with a low WBC count (< /L). Importantly, the higher mortality among patients with elevated/low WBC count was observed across all PESI risk classes. Our findings are consistent with a retrospective study reporting an independent association between an elevated WBC count (> /L) and 30- day mortality in 150 patients with PE [19]. Similarly, data from the RIETE registry showed that an elevated WBC is significantly associated with adverse outcomes in patients with acute venous thromboembolism who have cancer [24]. There are several biologically plausible explanations for the association between an elevated WBC count and increased mortality in PE. The relationship between elevated WBC count and left ventricular dysfunction in patients with acute coronary syndrome and the various potential mechanisms of myocardial injury mediated by leukocytes have been described in detail [3]. There is growing evidence from animal and autopsy studies that acute PE with at least moderately severe pulmonary hypertension results in right ventricular myocyte lysis and infiltration by neutrophils, macrophages, and lymphocytes in humans and rats [12 15,17] and that this inflammation independently amplifies injury [25]. Therefore, an elevated WBC count may indicate PE-related right heart dysfunction, a known factor for adverse prognosis in patients with PE [11]. Evidence also suggests that the WBC count correlates with levels of fibrinogen, factor VII, and factor VIII [18]. Thus, an elevated WBC may be a marker for hypercoagulability, which may carry a worse prognosis [26]. Future prospective studies should examine whether an elevated WBC count reflects right ventricular dysfunction and hypercoagulability in patients with acute PE. Another explanation for the observed association between elevated WBC count and adverse outcomes may be the presence of unmeasured prognostic factors that are unrelated to right ventricular dysfunction. Besides infection or inflammation, elevated WBC count occurs in a variety of non-cardiovascular clinical situations, such as trauma, intensive physical exercise, therapy with drugs such as steroids or lithium, malignancy, poisoning, psychosis, diabetic acidosis, and general in-hospital admissions and has been shown to be a predictor of mortality in respiratory disease, malignancy, and head trauma [27]. Large, prospective studies conducted in healthy populations have also shown an association between a raised WBC count and mortality [28,29]. The relationship between elevated WBC count and adverse outcomes remains incompletely understood because of its association with a multitude of underlying disease states, suggesting that elevated WBC may be an unspecific reaction to a variety of conditions, perhaps as part of a generalized stress response [30]. Thus, it is possible that WBCs have no causal role in death following PE TABLE II. Association Between Level of White Blood Cell Count and Outcome Outcomes Adjusted odds ratio a 95% Confidence interval P-value 30-day all-cause mortality <0.001 Admission WBC count (310 9 /L) < > day readmission rate b Admission WBC count (310 9 /L) < > WBC, white blood cell. a The odds ratios were adjusted for patient demographics (age, gender, race, and insurance type), comorbid diseases (history of cancer, chronic lung disease, and heart failure) and physical examining findings (systolic arterial blood pressure <100 mmhg, pulse 110 beats/minute, respiratory rate 30 breaths/ minute, altered mental status, body temperature <36 C, and arterial oxygen saturation <90%) comprising the Pulmonary Embolism Severity Index, laboratory values (hemoglobin, sodium, creatinine, glucose, and troponin), thrombolytic therapy, and hospital characteristics (region within Pennsylvania, annual volume of pulmonary embolism, and size and teaching status). b Adjusted odds ratios of 30-day readmission were estimated after the exclusion of 840 patients who died in the hospital, 93 who were still hospitalized 30 days after admission, and 34 with unknown readmission status, leaving a sample of 13,261 patients. but rather reflect an inflammatory response either to thrombosis or to its risk factors. Consistent with a study examining the relationship between WBC count and mortality in patients with acute myocardial infarction, we found a J-shaped distribution of mortality by WBC count [2], with patients with WBC levels < /L having an increased mortality rate. Given that more than 36% of these patients had cancer and 65% were anemic, the low WBC count and the higher mortality likely reflect greater severity of illness and higher prevalence of comorbid conditions, in particular cancer and/or its treatments. Our study also shows that, after adjustment for patient and hospital characteristics and thrombolytic therapy, an elevated/low WBC count in the acute phase of PE is an independent predictor for future hospital admissions, reinforcing the prognostic importance of this laboratory parameter. Our findings may have both clinical and research implications. Clinically, patients with PE who have a high/low WBC count at the time of presentation carry a higher risk of short-term mortality and hospital readmission, and may, therefore, potentially benefit from more intensive surveillance in the hospital and after discharge. However, the usefulness of the WBC count for risk stratification in PE must be further validated before its clinical use can be 680 American Journal of Hematology

5 recommended. To date, the PESI remains the most validated clinical prognostic tool for PE. The prognostic benefit of adding the WBC count to the PESI appears to be rather modest. Further research is warranted to determine whether WBC count correlates with other inflammatory markers, such as C-reactive protein and interleukins, right ventricular dysfunction, and hypercoagulability, and whether antiinflammatory treatment is associated with improved outcomes for patients with PE. Evidence from animal studies suggests that treatment with anti-pmn antibodies, anti- CINC antibodies, and the nonsteroidal anti-inflammatory drug Ketorolac reduced the inflammation in right ventricular tissue and significantly improved right ventricular contractile function [25]. Our study has potential limitations. First, patients in our sample were identified by use of ICD-9-CM codes for PE rather than standardized radiographic criteria, and patient eligibility may therefore be subject to selection biases owing to hospital coding procedures. Although we could not validate the accuracy of ICD-9-CM codes for PE in our dataset, 96% of patients with specific codes for PE had objectively documented disease on the basis of chart review criteria in a prior study [31]. Second, our sample excluded 8.4% of younger, healthier, and less severely ill patients in whom the WBC count was not measured at the time of admission. However, the exclusion of these lower risk patients, of whom probably a small proportion had an elevated/low WBC count, is unlikely to change our study results. Third, because measures of right ventricular function, other inflammatory markers (e.g., C-reactive protein, interleukins), and markers of hypercoagulability were not available in our database, we could not examine whether these measures are correlated with admission WBC levels. Similarly, we could not examine whether WBC counts are associated with PErelated cause of death. Fourth, we were not able to adjust our results for other potential confounders that may influence WBC levels and prognosis, such as concomitant inflammatory or infectious diseases, the extent of cancer, and treatments (chemotherapy, steroids). Fifth, we had no information on WBC count after hospital admission and discharge; thus, the prognostic implication of transient versus persistent elevation of WBC levels could not be analyzed. Sixth, we could not study the impact of leukocyte subtypes on patient prognosis. Finally, our study was observational in nature and we could detect only statistical associations, not causality, from our data. Thus, we cannot determine whether WBC count has a direct effect on patient prognosis or is a mere marker of severity of illness and stress. In conclusion, in this large sample of patients hospitalized with acute PE, an elevated/low admission WBC count was associated with a higher risk of 30-day mortality and readmission. The WBC count may serve as an easy-to-use marker to identify patients with PE who are at higher risk for adverse outcomes. Future studies should examine whether WBC levels are correlated with other inflammatory markers, hypercoagulability, and right ventricular dysfunction in patients with acute PE, and whether anti-inflammatory treatment is associated with improved outcomes. References 1. Barron HV, Harr SD, Radford MJ, et al. 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