Risk Prediction With Procalcitonin and Clinical Rules in Community-Acquired Pneumonia

Clinical Research, Investigation, and Systems Modeling of Acute Illness Laboratory, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Annals of emergency medicine (Impact Factor: 4.68). 08/2008; 52(1):48-58.e2. DOI: 10.1016/j.annemergmed.2008.01.003
Source: PubMed


The Pneumonia Severity Index and CURB-65 predict outcomes in community-acquired pneumonia but have limitations. Procalcitonin, a biomarker of bacterial infection, may provide prognostic information in community-acquired pneumonia. Our objective is to describe the pattern of procalcitonin in community-acquired pneumonia and determine whether procalcitonin provides prognostic information beyond the Pneumonia Severity Index and CURB-65.
We conducted a multicenter prospective cohort study in 28 community and teaching emergency departments. Patients presenting with a clinical and radiographic diagnosis of community-acquired pneumonia were enrolled. We stratified procalcitonin levels a priori into 4 tiers: I: less than 0.1; II: greater than 0.1 to less than 0.25; III: greater than 0.25 to less than 0.5; and IV: greater than 0.5 ng/mL. Primary outcome was 30-day mortality.
One thousand six hundred fifty-one patients formed the study cohort. Procalcitonin levels were broadly spread across tiers: 32.8% (I), 21.6% (II), 10.2% (III), and 35.4% (IV). Used alone, procalcitonin had modest test characteristics: specificity (35%), sensitivity (92%), positive likelihood ratio (1.41), and negative likelihood ratio (0.22). Adding procalcitonin to the Pneumonia Severity Index in all subjects minimally improved performance. Adding procalcitonin to low-risk Pneumonia Severity Index subjects (classes I to III) provided no additional information. However, subjects in procalcitonin tier I had low 30-day mortality, regardless of clinical risk, including those in higher risk classes (1.5% versus 1.6% for those in Pneumonia Severity Index classes I to III versus classes IV/V). Among high-risk Pneumonia Severity Index subjects (classes IV/V), one quarter (126/546) were in procalcitonin tier I, and the negative likelihood ratio of procalcitonin tier I was 0.09. Procalcitonin tier I was also associated with lower burden of other adverse outcomes. Similar results were observed with CURB-65 stratification.
Selective use of procalcitonin as an adjunct to existing rules may offer additional prognostic information in high-risk patients.

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Available from: Derek C Angus, Nov 13, 2014
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    • "Both scales do not evaluate information about the inflammatory response of the host to infection, well known as one of the major prognostic aspects in pneumonia. Poor performance of risk scores in prediction of high risk patients is mainly caused by low positive likelihood ratios at the recommended cut-offs for 30-day mortality.[17181920212223] "
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    ABSTRACT: INTRODUCTION: Community acquired pneumonia (CAP) may present as life-threatening infection with uncertain progression and outcome of treatment. Primary aim of the trial was determination of the cut-off value of serum interleukin-6 (IL-6) and procalcitonin (PCT) above which, 30-day mortality in hospitalized patients with CAP, could be predicted with high sensitivity and specificity. We investigated correlation between serum levels of IL-6 and PCT at admission and available scoring systems of CAP (pneumonia severity index-PSI, modified early warning score-MEWS and (Confusion, Urea nitrogen, respiratory rate, Blood pressure, ≥65 years of age-CURB65). METHODS: This was prospective, non-randomized trial which included 101 patients with diagnosed CAP. PSI, MEWS and CURB65 were assessed on first day of hospitalization. IL-6 and PCT were also sampled on the first day of hospitalization. RESULTS: Based on ROC curve analysis (AUC ± SE = 0.934 ± 0.035; 95%CI(0.864-1.0); P = 0.000) hospitalized CAP patients with elevated IL-6 level have 93.4% higher risk level for lethal outcome. Cut-off value of 20.2 pg/ml IL-6 shows sensitivity of 84% and specificity of 87% in mortality prediction. ROC curve analysis confirmed significant role of procalcitonin as a mortality predictor in CAP patients (AUC ± SE = 0.667 ± 0.062; 95%CI(0.546-0.789); P = 0.012). Patients with elevated PCT level have 66.7% higher risk level for lethal outcome. As a predictor of mortality at the cut-off value of 2.56 ng/ml PCT shows sensitivity of 76% and specificity of 61.8%. CONCLUSIONS: Both IL-6 and PCI are significant for prediction of 30-day mortality in hospitalized patients with CAP. Serum levels of IL6 correlate with major CAP scoring systems.
    Annals of Thoracic Medicine 07/2014; 9(3):162-7. DOI:10.4103/1817-1737.134072 · 1.80 Impact Factor
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    • "Community-acquired pneumonia (CAP) is common and associated with significant mortality [1–3]. Severity assessment is an important step in the management of CAP [4–6] because the early identification of individuals at high risk of death may help in deciding the site of care and the intensity of management [7]. Furthermore, subjective clinical judgment can underestimate pneumonia severity [8], and this may result in under-treatment and poor outcomes [9, 10]. "
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    ABSTRACT: Background: Several models have been developed to predict the risk of mortality in community-acquired pneumonia (CAP). This study aims to systematically identify and evaluate the performance of published risk prediction models for CAP. Methods: We searched MEDLINE, EMBASE, and Cochrane library in November 2011 for initial derivation and validation studies for models which predict pneumonia mortality. We aimed to present the comparative usefulness of their mortality prediction. Results: We identified 20 different published risk prediction models for mortality in CAP. Four models relied on clinical variables that could be assessed in community settings, with the two validated models BTS1 and CRB-65 showing fairly similar balanced accuracy levels (0.77 and 0.72, resp.), while CRB-65 had AUROC of 0.78. Nine models required laboratory tests in addition to clinical variables, and the best performance levels amongst the validated models were those of CURB and CURB-65 (balanced accuracy 0.73 and 0.71, resp.), with CURB-65 having an AUROC of 0.79. The PSI (AUROC 0.82) was the only validated model with good discriminative ability among the four that relied on clinical, laboratorial, and radiological variables. Conclusions: There is no convincing evidence that other risk prediction models improve upon the well-established CURB-65 and PSI models.
    10/2013; 2013(10):504136. DOI:10.1155/2013/504136
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    • "Pro-ADM is a biomarker of prognostic value (Table 5). Added to a clinical pneumonia severity score [36], pro-ADM could be used to identify the more severe patients for close monitoring and/or needing ICU care [37-40]. "
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    ABSTRACT: In the context of worldwide increasing antimicrobial resistance, good antimicrobial prescribing in more needed than ever; unfortunately, information available to clinicians often are insufficient to rely on. Biomarkers might provide help for decision-making and improve antibiotic management. The purpose of this expert panel review was to examine currently available literature on the potential role of biomarkers to improve antimicrobial prescribing, by answering three questions: 1) Which are the biomarkers available for this purpose?; 2) What is their potential role in the initiation of antibiotic therapy?; and 3) What is their role in the decision to stop antibiotic therapy? To answer these questions, studies reviewed were limited to recent clinical studies (<15 years), involving a substantial number of patients (>50) and restricted to controlled trials and meta-analyses for answering questions 2 and 3. With regard to the first question concerning routinely available biomarkers, which might be useful for antibiotic management of acute infections, these are currently limited to C-reactive protein (CRP) and procalcitonin (PCT). Other promising biomarkers that may prove useful in the near future but need to undergo more extensive clinical testing include sTREM-1, SuPAr, ProADM, and presepsine. New approaches to biomarkers of infections include point-of-care testing and genomics.
    Annals of Intensive Care 07/2013; 3(1):22. DOI:10.1186/2110-5820-3-22 · 3.31 Impact Factor
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