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EP.019
Predicting secondary infections using cell-surface markers of immune cell dysfunction: the INFECT study.

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Predicting secondary infections using cell-surface markers of immune cell dysfunction: the INFECT study

 

Summary

•Immune dysfunction is increasingly recognised amongst critically ill patients
 
•Detecting immune dysfunction is challenging
 
•We have validated 3 measures of immune dysfunction in a multi-centre study, and used them to predict secondary infection and prolonged organ support
 
•These measures work best in combination, and when measured serially during admission
 

Background

Critically ill patients are at high risk of secondary infection

This has been associated with failure of key immune cell functions

We have previously identified 3 markers of immune cell function which could additively predict secondary infection1

 

These measures are :

Neutrophil CD88 -  a measure of C5a-mediated neutrophil dysfunction2

Monocyte HLA-DR a marker of diminished monocyte responsiveness

Percentage of Tregsan immuno-suppressive subset of T-cells 


Results

148 patients recruited from

4 geographically and clinically diverse ICUs

 

Data available from 138 patients

 

Infection developed in 51 (37%) of patients.  VAP accounted for 55% of infections


Flow cytometers were standardised successfully

High (ICC >0.9) inter and intra-rater reliability of all measures used

Patients developing infection have persistently low CD88

Patients developing infection have persistently low HLA-DR

Patients developing infection have higher proportions of Tregs prior to infection 


At optimal cut-off, each marker significantly predicted the subsequent risk of secondary infection with a modest predictive ability 

However in combination, predictive ability is significantly enhanced

Modelled clinical use

Identifies a patient as ‘high risk’ of secondary infection

On Day 1 ‘high risk’ patients odds of developing infection were 1.22 (95% CI 0.61-2.46)

 

However

 

By day 2-4 ‘high risk’ patients odds of developing infection were 3.22 (1.42-7.32)

 

Test remains effective at days 6-8 OR4.76 (1.68-13.48)

 

‘High risk’ patients identified at day 2-4 also experienced longer length of stay  (16 days vs 11 p=0.008) and fewer days alive and free of organ support (5 days vs 9 days p=0.02)

 

Using this testing approach would lead to a significant reduction in study size or numbers needed to treat for a novel immunomodulatory therapy.

References

1. Conway Morris A, Anderson N, Brittan M, et al. Combined dysfunctions of immune cells predict nosocomial infection in critically ill patients. British journal of anaesthesia. 2013;111(5):778-787.

2. Morris AC, Brittan M, Wilkinson TS, et al. C5a-mediated neutrophil dysfunction is RhoA-dependent and predicts infection in critically ill patients. Blood. 2011;117(19):5178-5188.

3.Conway Morris A, Datta D, Shankar-Hari M, et al. Predictive value of cell-surface markers in infections in critically ill patients: protocol for an observational study (ImmuNe FailurE in Critical Therapy (INFECT) Study). BMJ Open. 2016;6(7):e011326-e011326. 

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