Procalcitonin and New Biomarkers

Mir, Nabiel; Ho, Dong-Ru; Toews, Jason R.; Walsham, James

doi:10.1007/978-3-319-64774-6_5

Cited by 2 publications

(4 citation statements)

References 61 publications

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“…These, together with their positive clinical results, also contribute signi cantly to health care costs. However, improper test requests and interpretations can also lead to unnecessary administration and procedures to patients [6].…”

Section: Introductionmentioning

confidence: 99%

The impact of procalcitonin to C-reactive protein ratio (PCR) kinetics as a predictor of mortality in nosocomial bloodstream infections

Hakyemez

Aslan

Durdu

2020

Preprint

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Background: This study was performed to investigate the combination of serum C-reactive protein (CRP) and procalcitonin (PCT) kinetics as a best marker in predicting mortality in patients with nosocomial blood stream infection (BSI).Methods: We retrospectively reviewed the medical records of patients ≥ 18 years of age with nosocomial BSIs hospitalized in intensive care units during the period from January 2016 to June 2018. Eighty-four patients who met the inclusion criteria were included in the study. Clinical, microbiological and biochemical data were compared in patients who survivors and deaths. Binary logistic regression analyses (backward LR) were used to identify independent risk factors. A receiver operating characteristic (ROC) curve analysis was performed to compare the predictive accuracy. The kinetic changes were expressed as Δ (delta) and defined the as difference between level on day 5 and level at day 1 of BSI.Results: Of the 84 included patients, 46 (58.4%) had survivors and 35 (41.6%) had deaths. In univariate analysis, renal disease (p = 0.007), cardiac disease (p = 0.042), septic shock (p = <0.001), maximum SOFA (p = <0.001) and APACHE-II (p <0.001), ΔCRP (p = 0.004), ΔPCT (p = <0.001), and ΔPCR (p = 0.025) were significantly higher in non-survivors than in survivors. In the logistic regression analysis, APACHE-II score (odds ratio (OR) = 1.46, 95% confidence interval (CI) = 1.20-1.78, p <0.001), ΔCRP (OR = 1.18, %95 CI =1.04-1.34, p = 0.009), ΔPCT (OR = 0.87, 95% CI = 0.79-0.95, p = 0.001), and ∆PCR (OR = 36.78, 95% CI = 4.52-299.01, p = 0.001) were independent predictors of 28-day mortality. After a ROC analysis, the AUC of ∆PCR was higher than that of ∆PCT for mortality in ICU patients (0.745 vs. 0.712, p <0.001).Conclusions: The PCR kinetic was a strong independent predictor of mortality in patients with nosocomial BSIs in intensive care units. Especially in patients with CRP and PCT tested together, it is expected to be a fast and rational tool for clinical practice.

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Section: Introductionmentioning

confidence: 99%

The impact of procalcitonin to C-reactive protein ratio (PCR) kinetics as a predictor of mortality in nosocomial bloodstream infections

Hakyemez

Aslan

Durdu

2020

Preprint

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

“…Existing biomarkers cannot fully re ect these features [7]. They do not replace a comprehensive clinical evaluation, but they increase the support data, the clinician must make rational decisions [6].…”

Section: Introductionmentioning

confidence: 99%

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The impact of procalcitonin to C-reactive protein ratio (PCR) kinetics as a predictor of mortality in nosocomial bloodstream infections

Hakyemez

Aslan

Durdu

2020

Preprint

View full text Add to dashboard Cite

Purpose: To investigate the combination of serum C-reactive protein (CRP) and procalcitonin (PCT) kinetics in predicting mortality in nosocomial blood stream infections (BSIs).Materials and Methods: We retrospectively reviewed the medical records of patients ≥ 18 years of age with nosocomial BSIs hospitalized in intensive care units (ICU). Clinical, microbiological and biochemical data were compared in patients who survivors and deaths. Binary logistic regression analyses were used to identify independent risk factors. The kinetic changes were defined the as difference between level on 5th day and level at 1st day of BSI.Results: Of the 84 included patients, 49 (58.4%) had survivors and 35 (41.6%) had deaths. In univariate analysis, renal disease (p=0.007), cardiac disease (p=0.042), septic shock (p=<0.001), SOFA (p=<0.001) and APACHE-II (p <0.001), ΔCRP (p=0.004), ΔPCT (p=<0.001), and ΔPCR (p=0.025) were significantly higher in non-survivors. In the logistic regression analysis, APACHE-II score (OR=1.46, 95% CI=1.20-1.78, p <0.001), ΔCRP (OR=1.18, %95 CI =1.04-1.34, p=0.009), ΔPCT (OR=0.87, 95% CI=0.79-0.95, p=0.001), and ∆PCR (OR=36.78, 95%C = 4.52-299.01, p=0.001) were independent predictors of 28-day mortality.Conclusions: The ∆PCR kinetic was a strong independent predictor of mortality in nosocomial BSIs in ICUs.

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Procalcitonin and New Biomarkers

Cited by 2 publications

References 61 publications

The impact of procalcitonin to C-reactive protein ratio (PCR) kinetics as a predictor of mortality in nosocomial bloodstream infections

The impact of procalcitonin to C-reactive protein ratio (PCR) kinetics as a predictor of mortality in nosocomial bloodstream infections

The impact of procalcitonin to C-reactive protein ratio (PCR) kinetics as a predictor of mortality in nosocomial bloodstream infections

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