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  • Letter
  • Open Access

Circulating neutrophil counts and mortality in septic shock

  • 1Email author,
  • 2,
  • 3,
  • 4,
  • 5,
  • 5,
  • 1,
  • 2,
  • 4,
  • 2,
  • 5, 6 and
Contributed equally
Critical Care201418:407

https://doi.org/10.1186/cc13728

  • Published:

Keywords

  • Septic Shock
  • Validation Cohort
  • Endothelial Damage
  • Blood Vessel Wall
  • Neutrophil Adhesion

Polynuclear neutrophils can play dual roles in sepsis: on the one hand they mediate major antimicrobial activities and on the other hand they can contribute to the development of multiple organ failure [1]. Nonetheless, in spite of the importance of these cells in sepsis, the influence of the circulating neutrophil count (CNC) on the prognosis of septic patients with this pathology has not been properly evaluated.

We analyzed the association between CNC and outcome in two cohorts of patients with diagnostic criteria of septic shock (SS) [2]: the first was recruited in the context of a single center study (EXPRESS study, discovery cohort, n = 195; Table 1), and the second in the context of a multi-centric study (GRECIA study, validation cohort, n = 194; Table 2). Written informed consent was obtained from each patient or their legal representative. The two studies were approved by the Research Ethics Committee of the Hospital Clínico Universitario, Valladolid, Spain (for the EXPRESS study) and Hospital Universitario Río Hortega, Valladolid, Spain (coordinating center for the GRECIA study).
Table 1

Clinical characteristics of the patients in the discovery study in survivors and non-survivors at 28 days

 

Total (n = 195)

Survivors (n = 125)

Non-survivors (n = 70)

P

Patient details

    

     Gender (male)

125 (64.1%)

79 (63.2%)

46 (65.7%)

NS

     Age (years)

71.6 ± 11.1

70.2 ± 11.1

74.2 ± 10.7

0.014

     Hypertension

109 (55.9%)

71 (56.8%)

38 (54.3%)

NS

     Cardiovascular disease

87 (44.6%)

54 (43.2%)

33 (47.1%)

NS

     Cancer

44 (22.5%)

21 (16.8%)

23 (32.8%)

0.010

     COPD

33 (16.9%)

24 (19.2%)

9 (12.8%)

NS

     Diabetes

31 (15.9%)

24 (19.2%)

7 (10%)

NS

     Obesity

32 (16.4%)

21 (16.8%)

11 (15.7%)

NS

     Smoker

27 (13.8%)

17 (13.6%)

10 (14.2%)

NS

     Chronic renal failure

26 (13.3%)

15 (12.0%)

11 (15.7%)

NS

     Alcohol abuse

12 (6.1%)

8 (6.4%)

4 (5.7%)

NS

     Inmunosuppression

9 (4.6%)

5 (4.0%)

4 (5.7%)

NS

     Hepatic disease

6 (3.1%)

4 (3.2%)

2 (2.8%)

NS

Clinical status at admission

    

     APACHE II

14.7 ± 5.9

13.9 ± 5.8

16.2 ± 5.9

0.013

     Mechanical ventilation

134 (68.7%)

83 (66.4%)

51 (72.9%)

NS

     OARF

41 (21.0%)

19 (15.2%)

22 (31.4%)

0.008

Presumed source of infection

    

     Digestive system

115 (58.9%)

76 (60.8%)

39 (55.7%)

NS

     Respiratory system

19 (9.7%)

14 (11.2%)

5 (7.1%)

NS

     Central nervous system

20 (10.2%)

14 (11.2%)

6 (8.5%)

NS

     Urinary system

10 (5.1%)

5 (4.0%)

5 (7.1%)

NS

     Endocardium

7 (3.5%)

5 (4.0%)

2 (2.8%)

NS

     Catheter

34 (17.4%)

26 (20.8%)

8 (11.4%)

NS

     Wound/skin, soft tissue

28 (14.3%)

20 (16.0%)

8 (11.4%)

NS

     Other/unknown

55 (28.2%)

35 (28.0%)

20 (28.5%)

NS

Type of surgery

    

     Abdominal

99 (50.7%)

56 (44.8%)

43 (61.4%)

0.030

     Cardiac

71 (36.4%)

54 (43.2%)

17 (24.3%)

     Other

25 (12.8%)

15 (12.0%)

10 (14.3%)

Urgent surgery

    

     Yes

130 (66.6%)

77 (61.6)%

53 (75.7%)

0.045

Documented microbial agent

    

     Gram-negative

67 (41.6%)

48 (44.4%)

19 (35.8%)

NS

     Gram-positive

68 (42.2%)

47 (43.5%)

21 (39.6%)

NS

     Fungi

24 (14.9%)

16 (14.8%)

8 (15.1%)

NS

Laboratory data

    

     Bilirubin (mg/dL)

1.4 ± 1.3

1.5 ± 1.4

1.2 ± 1.0

NS

     Glycemia (mg/dL)

166.4 ± 65.1

165.4 ± 58.3

168.2 ± 76.0

NS

     Procalcitonin (ng/mL)

19.3 ± 32.5

16.5 ± 28.6

24.3 ± 38.1

NS

     CRP (mg/mL)

231.8 ± 119.2

221.9 ± 106.6

249.4 ± 138.1

NS

     INR

1.7 ± 0.9

1.6 ± 0.9

1.7 ± 0.8

NS

     Platelets (×103/μl)

190.2 ± 140.0

196.9 ± 143.5

178.2 ± 133.5

NS

     Leukocytes (×103/μl)

16.3 ± 10.1

16.4 ± 9.0

16.2 ± 11.7

NS

     Monocytes (×103/μl)

0.7 ± 0.4

0.7 ± 0.4

0.6 ± 0.5

NS

     Lymphocyte (×103/μl)

1.1 ± 0.7

1.1 ± 0.8

1.0 ± 0.6

NS

     Neutrophils (×103/μl)

14.4 ± 9.4

14.4 ± 8.4

14.3 ± 11.1

NS

     Basophils (×103/μl)

0.1 ± 0.0

0.1 ± 0.1

0.1 ± 0.0

NS

     Eosinophils (×103/μl)

0.1 ± 0.0

0.1 ± 0.0

0.1 ± 0.0

NS

For the demographic characteristics of the patients, differences between groups were assessed using the χ2 test for categorical variables and the Student's t-test for continuous variables when appropriate. Continuous variables are expressed as mean ± standard deviation. APACHE, Acute Physiology and Chronic Health Evaluation; COPD, chronic obstructive pulmonary disease; CRP, C reactive protein; INR, international normalized ratio; NS, not significant; OARF, oliguric acute renal failure.

Table 2

Clinical characteristics of the patients in the validation study in survivors and non-survivors at 28 days

 

Total (n = 194)

Survivors (n = 132)

Non-survivors (n = 62)

P

Patient details

    

     Gender (male)

126 (64.9%)

85 (64.3%)

41 (66.1%)

NS

     Age (years)

67.1 ± 13.3

65.3 ± 14.3

71.1 ± 9.5

<0.001

     Inmunosuppression

35 (18.0%)

15 (11.3%)

20 (32.2%)

<0.001

     Diabetes

32 (16.4%)

21 (15.9%)

11 (17.7%)

NS

     Cardiovascular disease

24 (12.3%)

14 (10.6%)

10 (16.1%)

NS

     Cancer

18 (9.2%)

10 (7.5%)

8 (12.9%)

NS

     COPD

23 (11.8%)

12 (9.0%)

11 (17.7%)

NS

     Chronic renal failure

15 (7.7%)

10 (7.5%)

5 (8.0%)

NS

     Alcohol abuse

12 (6.1%)

7 (5.3%)

5 (8.0%)

NS

     Hepatic disease

4 (2.0%)

1 (0.7%)

3 (4.8%)

NS

Clinical status at admission

    

     APACHE II score

22.6 ± 7.0

21.0 ± 6.5

25.9 ± 7.1

<0.001

     Mechanical ventilation

150 (77.7%)

93 (70.9%)

57 (91.9%)

<0.001

     OARF

39 (20.1%)

17 (12.8%)

22 (35.4%)

<0.001

Presumed source of infection

    

     Respiratory system

67 (34.5%)

45 (34.1%)

22 (35.5%)

NS

     Digestive system

52 (26.8%)

32 (24.2%)

20 (32.3%)

NS

     Urinary system

26 (13.4%)

21 (15.9%)

5 (8.1%)

NS

     Catheter

16 (8.2%)

11 (8.3%)

5 (8.1%)

NS

     Wound/skin, soft tissue

15 (7.7%)

11 (8.3%)

4 (6.5%)

NS

     Other/unknown

18 (9.3%)

12 (9.1%)

6 (9.7%)

NS

Documented microbial agent

    

     Gram-negative

52 (26.8%)

36 (27.2%)

16 (25.8%)

NS

     Gram-positive

33 (17.0%)

25 (18.9%)

8 (12.9%)

NS

     Fungi

12 (6.1%)

4 (3.0%)

8 (12.9%)

0.020

Laboratory data

    

     Bilirubin (mg/dL)

1.4 ± 2.2

1.4 ± 2.1

1.6 ± 2.4

NS

     Glycemia (mg/dL)

168 ± 64.0

167 ± 62.4

172.0 ± 67.6

NS

     INR

1.8 ± 3.1

1.9 ± 3.8

1.6 ± 0.6

NS

     Platelets (×103/μl)

177.4 ± 118.5

173.6 ± 105.2

186.4 ± 146.1

NS

     Leukocytes (×103/μl)

18.0 ± 16.4

18.4 ± 17.0

17.3 ± 15.3

NS

     Monocytes (×103/μl)

0.7 ± 1.7

0.8 ± 20.2

0.6 ± 0.9

NS

     Lymphocyte (×103/μl)

1.8 ± 70.5

1.6 ± 73.5

2.3 ± 64.1

NS

     Neutrophils (×103/μl)

14.9 ± 12.5

15.6 ± 12.9

13.6 ± 11.5

NS

     Basophils (×103/μl)

0.1 ± 0.0

0.1 ± 0.0

0.1 ± 0.0

NS

     Eosinophils (×103/μl)

0.1 ± 0.0

0.1 ± 0.0

0.1 ± 0.0

NS

For the demographic characteristics of the patients, differences between groups were assessed using the χ2 test for categorical variables and the Student's t-test for continuous variables when appropriate. Continuous variables are expressed as mean ± standard deviation. APACHE, Acute Physiology and Chronic Health Evaluation; COPD, chronic obstructive pulmonary disease; INR, international normalized ratio; NS, not significant; OARF, oliguric acute renal failure.

When patients of the discovery cohort were split based on deciles for CNC at SS diagnosis, those with CNC <7,226 cells/mm3 (decile 2) died earlier than the other non-survivors (Figure 1). Multivariate Cox regression analysis showed that patients with CNC below this cutoff value had an almost two-fold risk of death (Figure 1). The cutoff value was evaluated again in the validation cohort, with similar results (Figure 1). Counts of other leukocyte subtypes had no significant association with outcome.
Figure 1
Figure 1

Impact of circulating neutrophil count on mortality: Kaplan-Meier survival curves. Groups were compared by the log-rank test (Mantel- Haenzel). Bottom: multivariate Cox regression analysis for mortality risk. Circulating neutrophil count (CNC) was adjusted by age, sex and Acute Physiology and Chronic Health Evaluation II score. Time was censored at 28 days following diagnosis. CI, confidence interval; Cum, cumulative; HR, hazard ratio.

Although normal reference values in blood vary depending on sex, race and age, available literature supports that 7,226 cells/mm3 is at the upper limit of normal CNC values [3]. Patients with insufficient numbers of circulating neutrophils during the early stages of SS could have difficulties mounting effective innate responses against the invading microbe(s). Increased neutrophil adhesion to the vascular endothelium in sepsis could contribute to lower CNC. Neutrophils adhered to the blood vessel wall seem to induce endothelial damage [4], forming leukocyte aggregates that could lead to microvascular thrombosis [1, 5]. Host immunity compromise and/or increased endothelial damage could both impair outcome in these patients.

CNC at diagnosis is a major prognostic factor in SS. Our work provides a CNC cutoff that is potentially useful as a prognostic indicator.

Notes

Abbreviations

CNC: 

Circulating neutrophil count

SS: 

Septic shock.

Declarations

Acknowledgements

Discovery study (EXPRESS) was supported by ISCIII, 'Proyectos de Investigación Sanitaria, PI 10/01362. Validation study (GRECIA) was supported by Proyectos de investigación en Biomedicina, Health Council, Castilla y León Goverment, Spain (BOCYL-D-26072010). Investigators of the EXPRESS group: Esther Gómez-Sánchez, Sandra Gutiérrez, Felipe Bobillo, Francisco Gandía,Verónica Iglesias , Lucia Rico, Raquel Almansa, Raúl Ortiz de Lejarazu (Hospital Clínico Universitario, Valladolid, Spain). Investigators of the GRECIA group: Pedro Merino, Marta María García-García (Hospital Universitario Río Hortega, Valladolid, Spain); M Jesús López Pueyo, Jose Antonio Fernandez Ratero, Miguel Martinez Barrios, Fernando Callejo Torre, Sergio Ossa Echeverri (Hospital General Yagüe, Burgos, Spain); Demetrio Carriedo Ule, Ana M Domínguez Berrot, Fco Javier Díaz Domínguez (Complejo Hospitalario de León, Spain); Susana Moradillo (Hospital Río Carrión, Palencia, Spain); Braulio Alvarez Martínez (Hospital del Bierzo, Ponferrada, Spain); Noelia Albalá, Juan Carlos Ballesteros, Marta Paz Perez, Elena Perez Losada (Hospital Clínico Universitario de Salamanca, Spain); Santiago Macías, Rafael Pajares García, Noelia Recio García Cervigón (Hospital General de Segovia Spain); M Mar Gobernado Serrano, M José Fernández Calavia, Daniel Moreno Torres (Complejo Hospitalario de Soria, Spain); Concha Tarancón, Teresa Loreto, Priscila Carcelen (Hospital Virgen de la Concha, Spain).

Authors’ Affiliations

(1)
Unidad de Investigación Biomédica, Hospital Clínico Universitario de Valladolid, SACYL/IECSYL, Avda Ramón y Cajal 3, Valladolid, 47005, Spain
(2)
Servicio de Anestesiología, Hospital Clínico Universitario de Valladolid, SACYL, Avda Ramón y Cajal 3, Valladolid, 47005, Spain
(3)
Servicio de Medicina Preventiva, Hospital Clínico Universitario de Valladolid, SACYL, Avda Ramón y Cajal 3, Valladolid, Spain
(4)
Servicio de Medicina Intensiva, Hospital Clínico Universitario de Valladolid, SACYL, Avda Ramón y Cajal 3, Valladolid, 47005, Spain
(5)
Servicio de Medicina Intensiva, Hospital Universitario Río Hortega, SACYL, Calle Dulzania, 2, Valladolid, 47012, Spain
(6)
Centro de investigación en red de enfermedades respiratorias (CIBERES), Hospital Universitario Río Hortege, Calle Dulzania, 2, Valladoid, 47012, Spain

References

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Copyright

© BioMed Central Ltd. 2014

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