Bruce H. Davis, M.D.
Trillium Diagnostics, LLC
Brewer, Maine U.S.A.
www.trilliumdx.com

Incidence of Severe Sepsis Mortality of Severe Sepsis
300
250
200
150
100
250,000
Estimated annual 12 million cases with suspected
Sepsis in North America, UK, and Europe with 1,400 deaths per day
150,000
50,000
50
0
AIDS* Colon Breast
Cancer §
CHF † Severe
Sepsis
‡
AIDS* Breast
Cancer
§
AMI
† Severe
Sepsis
†
National Center for Health Statistics, 2001.
Association. 2000.
§
American Cancer Society, 2001. *American Heart
‡
Angus DC et al. Crit Care Med. 29:1303, 2001.
‡

Standard of Care Diagnostic Assays of Infection/Sepsis
Leukocyte Counts (neutrophilia) - CBC
– absolute counts
– band counts or left shift (immaturity index)
Cultures for suspected infection
Sedimentation Rate
C-Reactive Protein (CRP)
New Generation Assays of Infection/Sepsis
Granulocyte or PMN CD64 (Leuko64, Trillium Diagnostics)
Cytokine and receptor levels (intracellular or plasma, TNF-a, IL-6
(Septest), IL-12, CD14, CD16, etc.)
Procalcitonin plasma levels (Brahms)
Endotoxin Activity Assay (Spectral Diagnostics)
TREM-1 (Triggering Receptor Expressed on Myeloid cells)
LightCycler SeptiFast Test (Roche)
Triage Sepsis Panel (CRP, MIP-3, NGal Biosite)

From Wood and Borowitz (2006), Henry’s Laboratory Medicine

PMN CD64 expression is negligible in the healthy state (<2,000 molecules per cell) - low false positive rate
PMN CD64 expression becomes elevated under the influence of the inflammatory related cytokines, such as interferong
(3-4 hrs),
G-CSF (4-6 hrs), IL-12
Increased PMN CD64 expression results in enhanced antibodymediated functional responses (phagocytosis, oxidative burst, bactericidal activity) in PMNs – pathophysiologically significant change during inflammation
PMN CD64 becomes elevated in the presence of infection/sepsis
– Final cytokine pathway effect at cellular level – barometer of “sickness”
– Better performance than cell counts, left shift, and CRP
High specificity - PMN CD64 expression is not elevated in:
– Malignancy of myeloid cells (CML, MPD, MDS)
–
Any drug therapy (other than cytokines)
–
Clinical conditions with localized tissue damage (myocardial ischemia, uncomplicated surgery, and exercise injury)
– Pregnancy
– Auto-immune disorders (Rheumatoid Arthritis, Systemic Lupus Erythematosis)

PMN CD64: Publications indicating utility as an inflammatory marker in sepsis and infection detection
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Guyre et al: J Clin Invest 86:1892-96, 1990
Davis BH et al: Laboratory Hematology, 1:3-12, 1995
Herrara et al: J. Med. Micro. 12:34 , 1996
Quayle JA et al: J Immunol 91: 266-73, 1997
Leino et al. Clin Exp Immunol 107:37-43, 1997
Fjaertoft et al, Pediatr Res 45:871-76, 1999
Moallem HJ et al: Scand J Immunol 52:184-89, 2000
Bakke AC et al: Clin Appl Immunol Rev 1:267-75, 2001
Barth E et al: Cytokine 14: 299-302, 2001
Qureshi et al , Clin Exp Immunol 125:258, 2001
Fisher et al, Intensive Care Med. 27: 1848-52, 2001
Hirsch et al, Shock 16: 103-8, 2001
Layseca-Espinosa et al,, Pediatr Allergy Immunol 13: 319-27, 2002
Ng et al, Pediatr Res 51: 296-303, 2002
Allen E et al: Ann Rheum Dis 61:522-5, 2002
Wagner et al, Shock 19:5-12, 2003
Briggs et al, Lab Hematol 9:117-124, 2003
Ng PC et al, Pediatr Res 56: 796-803, 2004
Davis BH, Expert Rev Mol Diag, 5:193-207, 2005
Davis BH and Bigelow NC, Laboratory Hematology, 11:137-147, 2005
Fjaertoft G et al, Acta Paediatr 94:295-302, 2005
Davis BH et al, Arch Path Lab Med, 130(5):654-61, 2006
Matsui et al, J Rheumatol 33(12): 2416-24, 2006
Livaditi et al, Cytokine 36: 283-290, 2006
Cho et al, Thrombosis Res, in press, 2007
Bhandari et al, Pediatrics, in press
,
2007

30000
20000
10000
Davis BH et al. Laboratory Hematology, 1:3-12, 1995
        Controls N=50
40000
0
0 10000 20000
Absolute Neutrophil Count (mill/L)
30000

Comparison of Neutrophil CD64, Manual Myeloid Immaturity
Counts, and Automated Hematology Analyzer Flags as
Indicators of Infection or Sepsis
Davis BH and Bigelow NC, Laboratory Hematology, 11:137-147, 2005
Methods
» 160 patient blood samples selected from hospital laboratory based upon blood counter flagging
» Assays performed: CBC, manual leukocyte differential counts
(H20-A), PMN CD64 by flow cytometry
» Retrospective blinded chart review with scoring:
–
0 = No Infection or inflammation
– 1 = Localized infection or tissue injury
– 2 = moderate suspicion for systemic infection and/or tissue injury
– 3 = Documented sepsis and/or severe tissue injury

Davis BH and Bigelow NC, Laboratory Hematology, 11:137-147, 2005
70,000 70,000
60,000 r = 0.539
60,000
50,000 r = 0.169
50,000
40,000 40,000
30,000
30,000
20,000
20,000
10,000
10,000
0
0 20 40
Percent Band Forms
60 80
0
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
Immature Myeloid Fraction
Result: Moderate correlation between PMN CD64 Expression and band% and weaker correlation with immature myeloid fraction
Conclusion: Indicates CD64, a measure of cell activation and cytokine functional upregulation, to be a related, but likely independent of left shift

Davis BH and Bigelow NC, Laboratory Hematology, 11:137-147, 2005
70,000 40,000
A B
60,000
P < 0.0001
35,000
P = 0.0001
30,000
50,000 P = 0.9497
P < 0.0001
25,000
P < 0.0001
40,000 P < 0.0001
20,000
P = 0.0001
P = 0.0194
30,000
15,000
P = 0.2592
20,000 P < 0.0001
10,000 P < 0.0001
10,000 5,000
P = 0.0018
0
0 1 2
Clinical Sepsis Score
3
0
0 1 2
Clinical Sepsis Score
3
80
P < 0.0001
70
60
50
P = 0.0002
P < 0.0001
40
30
20
P
P < 0.0001
10
0
0
P = 0.0027
1 2
Clinical Sepsis Score
P = 0.2417
3
C
0.40
0.30
0.20
0.00
0
P = 0.0623
0.10
P
P = 0.7230
P = 0.0430
P = 0.1284
P = 0.0094
P = 0.6631
1 2
Clinical Sepsis Score
3
D

Davis BH and Bigelow NC, Laboratory Hematology, 11:137-147, 2005
Sensitivity
Specificity
PPV
NPV
Efficiency
LR+
LR-
Neutrophil
CD64 (MESF
> 5,000)
94.12%
100.00%
100.00%
94.87%
97.18%
>100
0.06
Neutrophil
Count
(> 7,500 x
10
6
.L)
79.41%
94.59%
93.10%
83.33%
87.32%
14.69
0.22
CBC Analyzer
Flag (IG/Band 1 or 2)
94.12%
97.30%
96.97%
94.74%
95.77%
34.82
0.06
Band
Percent
(>10%)
87.50%
89.19%
87.50%
89.19%
88.41%
8.09
0.14
Immature
Myeloid
Fraction
(>0.00)
46.88%
82.86%
71.43%
63.04%
65.67%
2.73
0.64
Positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+), and the negative likelihood ratio (LR-) for clinical evidence of infection/sepsis indicate neutrophil CD64 to have the better diagnostic performance relative to left shift determinants (morphology or flags) and cell counts

Infection/Sepsis Markers in Emergency Room Patients
Davis BH et al, Arch Path Lab Med, 130(5):654-61, 2006
Methods
» Patients randomly selected from emergency department encounters (N=100)
» Assays performed: CBC, band counts, Westergren
Sedimentation Rate, C-reactive protein, PMN CD64
» Retrospective blinded chart review with scoring:
–
0 = No Infection or inflammation
– 1 = Localized infection or tissue injury
– 2 = moderate suspicion for systemic infection and/or tissue injury
– 3 = Documented sepsis and/or severe tissue injury

Infection/Sepsis Markers in Emergency Room Patients
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
30
25
20
15
10
5
0
0
0
0
Davis BH et al, Arch Pathol Lab Med. 130(5):654-61, 2006
50
P < 0.0001
P < 0.0001
45
P = 0.0031
40 P = 0.0005
P = 0.1011
P = 0.0314
35 P = 0.0054
30
P = 0.0565
P = 0.3193
25
P < 0.0001
20
P = 0.0070
15
P = 0.0072
10
5
0
0
1 2
Clinical Inflammatory Score
3
1 2
Clinical Inflammatory Score
3
P = 0.2144
P = 0.3363
P = 0.9961
P = 0.0043
P = 0.0777
P = 0.1804
1 2
Clinical Inflammatory Score
3
12
10
8
6
4
2
0
0
20
18
16
14
P = 0.1013
P = 0.0010
P = 0.2782
P = 0.0001
P = 0.1643
P = 0.8482
1 2
Clinical Inflammatory Score
3

Infection/Sepsis Markers in Emergency Room Patients
Davis BH et al, Arch Pathol Lab Med. 130(5):654-61, 2006
Sensitivity
Neutrophil
CD64
(MESF >
2,000)
87.88%
Specificity 71.21%
PPV
NPV
Efficiency
LR+
LR-
60.42%
92.16%
76.77%
3.05
0.17
Neutrophil
Count
(> 9,000 x
10
6
.L)
60.00%
50.79%
36.73%
72.73%
53.76%
1.22
0.79
Band
Percent
(>10%)
68.18%
76.32%
62.50%
80.56%
73.33%
2.88
0.42
Erythrocyte
Sedimentation
Rate (>40 mm/Hr)
50.00%
65.52%
37.50%
76.00%
60.98%
1.45
0.76
C-reactive
Protein (>2.0 mg/dL)
88.24%
59.38%
53.57%
90.48%
69.39%
2.17
0.20
Positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+), and the negative likelihood ratio
(LR-) show neutrophil CD64 to have the best diagnostic performance

CD64 on neutrophils is a sensitive and specific marker for detection of infection in patients with rheumatoid arthritis.
Matsui T , Ohsumi K , Ozawa N , Shimada K , Sumitomo S , Shimane K , Kawakami M , Nakayama H ,
Sugii S , Ozawa Y , Tohma S .
J Rheumatol 33 (12): 2416-24, 2006
Department of Rheumatology, Sagamihara National Hospital, National Hospital Organization,
Kanagawa, Japan. t-matsui@sagamihara-hosp.gr.jp
OBJECTIVE: In inflammatory diseases, differentiation between infection and disease flares is often clinically difficult because of similar signs and symptoms, such as fever and elevation of inflammatory markers. In rheumatoid arthritis (RA), infection is not only one of the major complications but also one of the frequent causes of death. Use of biologic agents such as tumor necrosis factor-a blockers has been reported to increase the incidence of tuberculosis or opportunistic infections. We examined the utility of CD64 (FcgRI) expressed on neutrophils as a marker for detection of infection complicated with RA.
METHODS: We measured the expression level of CD64 per neutrophil quantitatively by flow cytometry in 279 samples from 237 patients with RA with various levels of disease activity or types of infection, and in 52 samples from 36 controls including subjects with infection.
RESULTS: CD64 expression was significantly higher among RA patients with infection (median 4156 molecules per neutrophil, interquartile range 2583-8587) than in those without infection (884, IQR
670-1262) (p < or = 0.001). The sensitivity of CD64 on neutrophils for the diagnosis of infection (using a cutoff value of 2000 molecules per cell) was 92.7% and specificity was
96.5%.
CD64 expression was not affected by the disease activity of RA or the use of corticosteroids, disease modifying antirheumatic drugs, and biologic agents. CD64 was upregulated in infection by bacteria, viruses, fungi, and mycobacteria.
CONCLUSION: Our results suggest that quantitative measurement of CD64 expression on neutrophils can be used as a sensitive and specific marker to detect infection complicating
RA .

Neutrophil CD64 expression and serum IL-8: Sensitive early markers of severity and outcome in sepsis
Olga Livaditi, Anastasia Kotanidou, Aikaterini Psarra, Ioanna Dimopoulou, Christina Sotiropoulou,
Kallirroi Augustatou, Chryssa Papasteriades, Apostolos Armaganidis, Charis Roussos, Stylianos
E. Orfanos, and Emmanuel E. Douzinas
Department of Critical Care, University of Athens Medical School, Athens, Greece
Cytokine, received 20 September 2006; revised 29 December 2006; accepted 7 February
2007. Available online 27 March 2007.
Abstract
The aim of the present study was to investigate which biomarker/s reliably assess severity and mortality early in the sepsis process. In 47 critically-ill patients within the 24 h of septic onset,
Interleukins (IL)-8, 1β, -6, -10, and -12p70, tumor necrosis factor-α (TNF-α), procalcitonin (PCT) and C-reactive protein (CRP) were measured in serum. Additionally, CD64 expression was measured in neutrophils. In early sepsis, neutrophil CD64 expression and IL-8 levels are the only biomarkers that increased with sepsis severity, differentiating disease stages: sepsis, severe sepsis and septic shock (p < 0.001). The biomarkers that best evaluate the severity of sepsis (via
APACHE II) were CD64, IL-8 and IL-6 (p < 0.01), and the severity of organ failure (via SOFA) were
CD64 and IL-8 (p < 0.01). CD64 expression and IL-8 levels were associated with mortality within
28-days (OR = 1.3, p = 0.01 for CD64 and OR = 1.26, p = 0.024 for IL-8 by logistic regression analysis) and ROC curve analysis showed high sensitivity and specificity for predicting sepsis stages and the 28 day mortality. We conclude that there is an early increase of neutrophil CD64 expression and IL-8 levels during sepsis . Based on this single measurement it is possible to reliably assess the stage, detect the severity and predict the 28-day mortality of sepsis.

www.Trilliumdx.com
Components:
 Reagent A: Cocktail of Anti-CD64
FITC and Anti-CD163 PE monoclonal antibodies
 Reagent B: 10X Red Cell Lysis Buffer
(flow cytometry version only)
 Reagent C: Fluorescent microsphere suspension for instrument set-up and quantitation (traceable to NIST SRM
8640)
 Software DVD: automated data analysis and reporting; allows for bead value assignment; package insert; MSDS information; instrument acquisition protocols

Two Versions
 Flow Cytometry (75 and 250 test sizes)
 Hematology Analyzer (Abbott Sapphire and Cell Dyn 4000, 100 test size)
*Patent pending, CE marked
Distribution by IQ Products in EU

1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
0
Trillium Diagnostics Leuko64 Assay:
Sample Stability – Preanalytical Blood Storage (< 48 hours)
Sample Stability - RT vs 4C Sample Stability RT vs 4C
N1 (RT)
N2 (RT)
N3 (RT)
N4 (RT)
N5 (RT)
N1 (4C)
N2 (4C)
N3 (4C)
N4 (4C)
N5 (4C)
2.00
1.80
1.60
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00
8 24 30
Time (hours)
30 48 72 0 8 24
Time (hours)
30 48 72
Normal Sample Stability - RT vs 4C
6.00
5.00
4.00
3.00
2.00
1.00
0.00
9.00
8.00
7.00
0
N1 (RT)
N2 (RT)
N3 (RT)
N4 (RT)
N5 (RT)
8
N1 (4C)
N2 (4C)
N3 (4C)
N4 (4C)
N5 (4C)
24
Time (hours)
30 48 72
Abnormal Sample Stability - RT vs 4C
8
6
4
2
0
12
10
0
A3 RT
A4 RT
A5 RT
A6 RT
A7 RT
8
A3 4C
A4 4C
A5 4C
A6 4C
A7 4C
24
Time (hours)
30 48 72
A3 RT
A4 RT
A5 RT
A6 RT
A7 RT
A3 4C
A4 4C
A5 4C
A6 4C
A7 4C

2.00
1.80
1.60
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00
20,000
18,000
16,000
14,000
12,000
10,000
8,000
6,000
4,000
2,000
0
0 2 4
Time (hours)
6
Normal Sample Stability, post Staining RT vs 4C
0
Trillium Diagnostics Leuko64 Assay:
Sample Stability – Post-Staining Blood Storage (< 4 hours)
Normal Sample Stability, post Staining RT vs 4C
N1 (RT)
N2 (RT)
N3 (RT)
N4 (RT)
N5 (RT)
N1 (4C)
N2 (4C)
N3 (4C)
N4 (4C)
N5 (4C)
2
N1 (RT)
N2 (RT)
N3 (RT)
N4 (RT)
N5 (RT)
4
Time (hours)
N1 (4C)
N2 (4C)
N3 (4C)
N4 (4C)
N5 (4C)
6
24
24
Abnormal Sample Stability, post Staining RT vs 4C
2.00
1.50
1.00
0.50
0.00
4.00
3.50
3.00
2.50
A1 RT
A2 RT
A3 RT
A4 RT
A5 RT
A1 4C
A2 4C
A3 4C
A4 4C
A5 4C
0 2 4
Time (hours)
6 24
45,000
Abnormal Sample Stability, post Staining RT vs 4C
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
A1 (RT)
A2 (RT)
A3 (RT)
A4 (RT)
A5 (RT)
A1 (4C)
A2 (4C)
A3 (4C)
A4 (4C)
A5 (4C)
0 2 4
Time (hours)
6 24

Trillium Diagnostics Leuko64 Assay:
Instrument Set-up and Assay Standardization with Beads (reagent C)
10
0
10
1
10
2
Side Scatter
10
3
10
4
10
0
10
1
10
2
CD64 FITC
10
3
10
4
10
0
10
1
10
2
CD163 PE
10
3
10
4
10
0
10
1
10
2
CD64 FITC
10
3
10
4
10
0
10
1
10
2
CD163 PE
10
3
10
4
10
0
10
1
10
2
FL3-Height
10
3
10
4

Leuko64 Software: Automated cluster finding gating of calibration beads – co-developed with Verity Software House
Purpose of calibration beads:
• Instrument set-up
• CD64 Index
• CD163 Index
• Lot to lot correlations
Trillium Diagnostics, LLC *** Leuko64 Assay
Bead Calibration
BHD.FACS.01 2-6-03.01.001
Gated Events
CD64 FITC Index
CD163 PE Index
1443
2.00
100.00
Calibration Values for Lot Specific CD64 and
CD163 Index Units with Data Collected on a
Becton Dickinson FACScan or FACSCalibur
Instrument.
Leuko64 Calibration Beads Lot # 03-001
Expiration: 31 January 2004
Auto
0.1
1 10
CD64 FITC (CD64 Index)
Gate1: Beads only
100
Gate2: Bead Singlets
Calibration
Bead
Gating
10 100 1000 10000
CD163 PE (CD163 Index)
1 10 100
FL3-Height
1000 10000
Quanti CALC(Wi n32) 1.2

Software uses cluster finding algorithms to locate lymphocytes, monocytes, and granulocytes.
Lymphocytes serve as an internal negative control (CD64 negative) and software will alert user if lymph gate has a CD64 index greater than 1.00

Monocytes serve as an internal positive control
(monocytes normally have moderate levels of CD64)
Software will alert user if monocyte gate has a CD64 index less than
3.00, which may indicate need for gate adjustment or failure to add proper antibody volume (reagent
A).

PMN CD64 Index reported with values of < 1.00 typical of healthy individuals
Software has database function that can imported into Microsoft
Excel

PMN CD64 Index reported with values of >1.50 indicative of infection

Fjaertoft et al Pediatr Res 45:871-76, 1999
Similar reports by: Layseca-Espinosa et al. Pediatr Allergy Immunol, 2002 13(5): 319-27,
Ng et al. Pediatr Res, 2002. 51(3): 296-303, and Ng et al. Pediatr Res, 2004; 56(5): 796-803

Neonatal Study: PMN CD64 Index correlates best with C-
Reactive Protein and presence of sepsis
Neonatal Samples: Correlation of CRP and PMN CD64
Y=1.0404X – 1.068
r = 0.6732
r = 0.6732
6.00
5.00
4.00
3.00
2.00
PMN CD64 in Neonate Samples
11.00
10.00
9.00
8.00
7.00
6.00
5.00
4.00
3.00
2.00
1.00
1.00
0.00
0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00 5.50 6.00
PMN CD64 Index
0.00
No Infection Treated for Infection
Infection Detection
Sensitivity
Specificity
Pos. Predictive Value
Neg. Predictive Value
Likelihood Ratio
Standard Lab Tests
47.6%
92.6%
83.3%
69.4%
6.43
Leuko64 Assay
90.5%
96.3%
95.0%
92.9%
24.46

Neonatal Infection
60
55
50
45
40
35
Procalcitonin r = 0.415
30
25
20
15
10
5
0
0.0
CRP r = 0.628
1.0
2.0
3.0
4.0
5.0
PMN CD64 Index
Neonatal Infection
60
55
50
45
40
35
30
25 r = 0.211
20
15
10
5
0
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
18.0
20.0
C Reactive Protein
6.0
7.0
8.0
Procalcitonin
CRP (mg/dL)

Characteristics
IL-6 (pg/ml)
IL-10 (pg/ml)
Neutrophil CD64
Elastase (μg/mL)
Monocyte CD64
Monocyte CD163 hsCRP
Healthy Controls
(n=55)
4.7

12.6
7.8

10.5
1117

221
57.9

34.4
7.0

2.2
16777

8855
0.20

0.31
suspected DIC
(n=97)
115.6

134.7
29.0

55.4
4071

3707
358.4

509.8
13.8

7.1
23268

25130
8.8

8.0
P value
0.002
0.002
<0.001
0.026
<0.001
0.025
<0.001
Data from Dr. Han-Ik Cho, Department of Laboratory Medicine,
Seoul National University College of Medicine, Seoul, Korea

Characteristics
IL-6 (pg/ml)
IL-10 (pg/ml)
Survivors
(n=69)
79.3

110.9
23.6

52.0
Neutrophil CD64
Elastase (μg/mL)
3077

2627
395.8

572.9
Monocyte CD64 12.4

5.0
Monocyte CD163 24341

27134 hsCRP 8.02

8.45
Non-survivors
(n=28)
226.3

143.1
45.6

63.3
6816

4796
242.0

187.8
17.5

10.2
20309

18672
11.16

6.31
P value
<0.001
0.123
<0.001
0.086
0.002
0.495
0.152
Data from Dr. Han-Ik Cho, Department of Laboratory Medicine,
Seoul National University College of Medicine, Seoul, Korea

Comparison of neutrophil CD64 and IL-6 according to concomitant infection between non-overt DIC and overt DIC.
Data from Dr. Han-Ik Cho, Department of Laboratory Medicine,
Seoul National University College of Medicine, Seoul, Korea

Table 1.
Characteristics of the neonatal population.
Variables
Gestational age (weeks)*
Birth weight (gms)*
Male gender (%)
Vaginal Delivery (%)
1-min. Apgar score**
5-min. Apgar score**
Ventilation days*
NCPAP days*
Days on Oxygen*
Length of Stay (days)*
No
(n=123)
Sepsis
32.55

0.47
1969

94
68 (55)
Sepsis
(n=40) present
34.72

0.95
2325

200
24/39 (62) p value
0.031
0.078
0.492
33/120 (28)
7 (1 - 9)
8 (1 - 9)
14.0

2.3
3.6

0.5
19.1

2.8
38.7

3.6
13/38 (34)
6 (1 – 9)
9 (3 – 9)
12.0

4.8
2.5

1.0
18.0

6.3
26.8

7.1
0.428
0.876
0.419
0.674
0.292
0.863
0.116
*Mean

SEM; ** Median (range); NCPAP: nasal continuous positive airways pressure
From Bhandari V, Wang C, Rinder C, and Rinder H, submitted for publication, Pediatrics (April, 2007)

Neonatal Sepsis – Yale Study
Table 2.
Characteristics of the sepsis episodes .
Variables
Age at sepsis work up (days) *
Hematocrit (%)*
White Blood Cell Count/ mm 3 *
Segmented neutrophils (%) *
Bands (%) *
Platelet count (k/ mm 3 ) *
Absolute Neutrophil Count (/ mm 3 )*
Absolute Band Count (/ mm 3 )*
Immature/Total neutrophil ratio *
PMN CD64 index *
*Mean

SEM
No Sepsis
(n=165)
12.3

1.5
42.7

0.8
14.0

0.5
41.9

1.3
4.5

0.3
285.3

8.5
6,324

326
698

60
0.05

0.00
2.63

0.20
Sepsis present
(n=128)
22.1

3.1
41.7

0.9
19.2

1.2
40.9

1.5
14.0

0.9
176.0

8.5
8,929

704
2,716

242
0.14

0.01
5.61

0.85
p value
0.002
0.371
<0.0001
0.596
<0.0001
<0.0001
0.0004
<0.0001
<0.0001
0.0002
“For all sepsis episodes, using ROC analysis, CD64 had an AUC of 0.74; using a cutoff value of
2.30, CD64 in combination with ANC had the highest negative predictive value (93%) for ruling out sepsis and 95% sensitivity for diagnosing sepsis . For confirmed culture-positive sepsis episodes, CD64 had the highest AUC (0.852) of all hematologic variables , with a sensitivity of 80%, and a specificity of 79%, using a cutoff value of 4.02.”
From Bhandari V, Wang C, Rinder C, and Rinder H, submitted for publication, Pediatrics (April, 2007)

100
80
60
40
20
ABC
ANC cd64
I_T_ratio
Plt
0
0 20 40
100-Specificity
60 80 100
ROC curve analysis of hematologic parameters in confirmed sepsis episodes.
CD64 had the highest area under the curve (AUC: 0.852).
From Bhandari V, Wang C,
Rinder C, and Rinder H, submitted for publication, Pediatrics (April, 2007)

Sample #1
Flow Cytometer
Sample #3
Flow Cytometer
Sample #47
Flow Cytometer
Sample #4
Flow Cytometer
10 0 10 1 10 2
CD163 PE
Sample #1
CD-4000
10 3 10 4 10 0 10 1 10 2
CD163 PE
Sample #3
CD-4000
10 3 10 4 10 0 10 1 10 2
CD163 PE
Sample #47
CD-4000
10 3 10 4 10 0 10 1 10 2
CD163 PE
Sample #4
CD-4000
10 3 10 4
10
0
10
1
10
3
10
2
FL3
CD64 Expression
10
4
10
0
10
1
10
3
10
2
FL3
CD64 Expression
10
4
10
0
10
1
10
3
10
2
FL3
CD64 Expression
10
4
10
0
10
1
10
3
10
2
FL3
CD64 Expression
10
4

Trillium Diagnostics, LLC *** Leuko64 Assay
Neutrophils
ACH 29.20050901.110003.3672
G a t e d Ev e nt s
PMN CD6 4 I nd e x
PMN CD1 6 3 I nd e x
3 7 4 7
9 . 4 4
5 2 4 . 7 9
Flow Cytometry - FACScan
Trillium Diagnostics, LLC *** Leuko64 Assay
Neutrophils
0.1
ACH-29.01.001
FL1 ()
Gated Events
PMN CD64 Index
100
23893
9.12
Abbott Cell Dyn Sapphire
Gate3: Refined PMNs
0.1
1 10
CD64 FITC ()
Gate1: Exclude Beads
100
Gate2: Crude PMNs
100 1000 10000 100000
FL2 ()
Gate3: Refined PMNs
100 1000 10000 100000
FL2 ()
100 1000 10000 100000
FL2 ()
100 1000 10000 100000
CD163 PE ()
100 1000 10000 100000
CD163 PE ()
100 1000 10000 100000
CD163 PE ()
Quanti CALC(Wi n32) 1.2
Quanti CALC(Wi n32) 1.2

Sapphire
Inter-Instrument Correlation
10.00
9.00
8.00
7.00
6.00
5.00
4.00
y = 0.986x + 0.203
r
2
= 0.9177
N = 44
3.00
2.00
1.00
0.00
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
PMN CD64 Index (FACScan)
16.00
14.00
12.00
10.00
8.00
6.00
4.00
CD-4000
Inter-Instrument Correlation y = 0.9661x + 0.0541
r
2
= 0.9718
N = 82
2.00
0.00
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
16.00
CD64 Index (FACScan)

Screening for infection/sepsis or illness severity in outpatients and hospitalized patients - triage role
Therapeutic monitor of antibiotic response in infection
– potential indicator for conversion of I.V. to oral therapy
– benefit of reduction in antibiotic use and subsequent development of resistant organisms
Therapeutic monitor of G-CSF therapy
Infection screening of post-operative and post-chemotherapy patients, HIV+ patients, and others at risk for infection/sepsis
Distinction between inflammatory leukemoid reaction and myeloproliferative disorder in patients with unexplained neutrophilia
Adjunct test with blood cultures
– Earlier indicator of patients with sepsis prior to culture result availability
– Interpretation of false positive blood cultures with contaminate bacteria

Acknowledgements:
Kathleen T Davis - Trillium
Nancy C Bigelow – Trillium
Karen Becker - Trillium
Victoria Kinney and
Hematology Lab
– MMC
Dan Sobel
– MMC
Neonatology
Sam Machin - UCL, U.K.
Carol Briggs – UCL, U.K.
Harvey Rinder
– Yale Univ
Paul Guyre - Dartmouth
Bob Kisabeth
– Mayo
Abe Schwartz - CQC
Bruce Bagwell – Verity
Ben Hunsburger
– Verity
Don Wright - Abbott
Steve Scott
– Abbott
Richard Kendall - Abbott
R&D Systems, Inc.
IQ Products, BV