PCT: Procalcitonin as diagnostic marker for sepsis
In CAMAN: Finite Mixture Models and Meta-Analysis Tools - Based on C.A.MAN

PCT	R Documentation

Procalcitonin as diagnostic marker for sepsis

Description

Procalcitonin is a promising marker for identification of bacterial infections. The accuracy and clinical value of procalcitonin for diagnosis of sepsis in critically ill patients was assessed in this meta-analysis.

Medline, Embase, ISI Web of Knowledge, the Cochrane Library, Scopus, BioMed Central, and Science Direct were searched, from inception to Feb 21, 2012, and reference lists of identified primary studies. We included articles written in English, German, or French that investigated procalcitonin for differentiation of septic patients–those with sepsis, severe sepsis, or septic shock–from those with a systemic inflammatory response syndrome of non-infectious origin. Studies of healthy people, patients without probable infection, and children younger than 28 days were excluded. Two independent investigators extracted patient and study characteristics; discrepancies were resolved by consensus.

This search returned 3487 reports, of which 30 fulfilled the inclusion criteria, accounting for 3244 patients.

Usage

data("PCT")

Format

A data frame consisting of 35 data sets (rows) and 10 attributes (columns)

Variable Names in order from left to right:

Study: Study

Year: Year

TP: True positive

FP: False positive

FN: False negative

TN: True negative

logitTPR: logit-true positive rate

logitTNR: logit-true negative rate

varlogitTPR: Variance of logit TPR

varlogitTNR: Variance of logit TPR

References

Wacker C, Prkno A, Brunkhorst FM, Schlattmann P. Procalcitonin as a diagnostic marker for sepsis: a systematic review and meta-analysis. Lancet Infect Dis. 2013 May;13(5):426-35. doi: 10.1016/S1473-3099(12)70323-7

Examples

#Use the VEM-algorithm for a diagnostic meta-analysis based on a mixture 
#of bivariate  normal densities.
#Study specific fixed variances are based on logit transformed 
#sensitivity and specificity. 

data(PCT)
names(PCT)
   
m0 <- bivariate.VEM(obs1 = logitTPR, obs2 = logitTNR,
                    var1 = varlogitTPR, var2 = varlogitTNR,
                    type = "meta", data=PCT, startk=20)

CAMAN documentation built on Sept. 22, 2023, 5:12 p.m.