Clinical utility of procalcitonin and its association with pathogenic microorganisms

Figures & data

Figure 1. The word cloud model of procalcitonin. We conducted literature research in PubMed with the keywords “procalcitonin” (title search), and drew the word cloud with WordArt (http://wordart.com) based on 1000 articles containing procalcitonin in titles from 2017 to 2021. The word cloud displays the size of a word proportionally to the number of times the word appears in a section of text.

Table 1. Overview of common pathogens and their associations with procalcitonin.

Pathogenic microorganisms	Diseases	Patient groups	Cutoff levels for PCT	Diagnostic efficacy	Study types	Publication Date	References
Bacteria
G+
Staphylococcus aureus	Bacteremia	Patients with clustered G^+ and G^– bacteremia	>0.5 ng/mL	AUC 0.65 (95%CI 52–78)	Observational study	2013	[25]
	IE	Patients admitted for IE	≥1.7 ng/mL	AUC 0.727 (95%CI 64.5–81.0)	Cohort study	2020	[26]
CoNS	Bacteremia	Patients with febrile neutropenia	<0.5 ng/mL	n.m.	Multicentre prospective clinical study	2004	[27]
	BSI	Patients with at least one blood culture grew CoNS	0.001 ng/mL	SEN 86% and 100% (on day −1 and 0); SPE 60% and 80% (on day −1 and 0)	Exploratory study	2007	[28]
Streptococci	Erysipelas (predominantly caused by Streptococci)	Consecutive patients presenting with a final diagnosis of either erysipelas or DVT	>0.25 ng/mL	SEN 37.1% (95%CI 21.5–55.1); SPE 90.0% (95%CI 68.3–98.8)	Prospective observational study	2015	[29]
G^+/G^–*	Bacteremia	Patients in ICUs	16.0 ng/mL	AUC 0.79 (95%CI 71–88)	Retrospective cohort study	2008	[30]
G^+/fungi	BSI	Patients older than 18 years of age	1.3 ng/mL	AUC 0.763 (95%CI 69.3–83.2)	Prospective observational study	2015	[31]
G^+/candidemia	Sepsis	Patients in ICUs	2.12 ng/mL	AUC 0.800 (p = 0.001)	Prospective study	2012	[32]
G^–
Escherichia coli	Sepsis	Patients with sepsis	2.32 ng/mL	AUC 0.778 (95%CI 71.1–84.5)	Retrospective analysis	2016	[33]
Klebsiella pneumoniae	Sepsis	Patients with sepsis	2.81 ng/mL	AUC 0.859 (95%CI 80.0–91.7)	Retrospective analysis	2016	[33]
Enterobacteriaceae /  nonfermentative G^–	BSI	Patients older than 18 years of age	3.1 ng/mL	AUC 0.691 (95%CI 59.3–78.9)	Prospective observational study	2015	[31]
G^–/all	BSI	Hematological patients with febrile neutropenia	0.56 ng/mL	SPE 76.8%	Unknown	2019	[34]
		Patients with burns	1.73 ng/mL	AUC 0.761 (95%CI 66.7–85.4)	Retrospective analysis	2020	[16]
G^–/G^+	BSI	Patients with BC-positive sepsis	0.495 ng/mL	AUC 0.628 (95%CI 57.6–67.9)	Retrospective study	2017	[35]
		Patients with BSI	7.54 ng/mL	AUC 0.581 (95%CI 51–65)	Retrospective analysis	2019	[36]
		Patients older than 18 years of age	10.8 ng/mL	AUC 0.765 (95%CI 72.5–80.5)	Prospective observational study	2015	[31]
	Sepsis	Patients with burns	0.57 ng/mL	AUC 0.687 (95%CI 60.9–76.5)	Observational study	2018	[37]
		Patients with sepsis	2.44 ng/mL	AUC 0.793 (95%CI 74.3–84.3)	Retrospective analysis	2016	[33]
G^–/candidemia	Sepsis	Patients in ICUs	8.06 ng/mL	AUC 0.897 (p < 0.001)	Prospective study	2012	[32]
G^–/fungi	Sepsis	Patients with sepsis	3.11 ng/mL	AUC 0.820 (95%CI 75.3–88.7)	Retrospective analysis	2016	[33]
	BSI	Patients older than 18 years of age	1.6 ng/mL	AUC 0.944 (95%CI 91.9–96.9)	Prospective observational study	2015	[31]
G^–/suspected	Sepsis	Patients with sepsis	2.41 ng/mL	AUC 0.870 (95%CI 80.4–93.6)	Retrospective analysis	2016	[33]
Multidrug-resistant G^–	BSI	Patients with burns	1.42 ng/mL	AUC 0.865 (95%CI 76.4–96.5)	Retrospective analysis	2020	[16]
Fungi
Candida	Candida infection	Patients with sepsis	2.5 ng/mL	AUC 0.76 (95%CI 68–84)	Retrospective case–control study	2017	[38]
	Candidemia	Patients admitted to the surgical ICU	2 ng/mL	AUC 0.97	Prospective observational study	2010	[39]
	Sepsis	Patients in ICUs	5.5 ng/mL	AUC 0.96	Retrospective study	2006	[40]
		Patients with a diagnosis of severe sepsis or septic shock	≤6.08 ng/mL	AUC 0.93	Single-centre retrospective study	2014	[41]
Virus (bacterial coinfection)
2009 pandemic H1N1 influenza virus	Influenza	Patients in ICUs	<0.29 ng/mL	AUC 0.716 (95%CI 67–75)	A CHAID decision-tree analysis from a prospective, multicentre, observational study	2016	[42]
	Pneumonia	Patients in ICUs	0.5 ng/mL	AUC 0.72 (95%CI 64–80)	Review (a prospective cohort study, systematic review and individual patient data meta-analysis)	2014	[43]
		Patients visiting emergency department and diagnosed as CAP caused by 2009 H1N1 infection	1.5 ng/mL	AUC 0.698 (95%CI 52.3–87.3)	Retrospective study	2011	[44]
		Patients with severe influenza pneumonia	0.8 ng/mL	AUC 0.90 (95%CI 78–100)	Retrospective observational study	2011	[45]
RSV	Pneumonia	Vietnamese children under 5 years old	2.25 ng/mL	AUC 0.749 (95%CI 57.1–92.7)	Cross-sectional study	2020	[46]
H7N9 virus	H7N9 influenza	Patients with H7N9 infection	0.81 ng/mL	AUC 0.96 (95%CI 91–100)	Retrospective study	2016	[47]
Respiratory virus	Acute bronchiolitis	Infants with acute bronchiolitis	1.5 ng/mL	AUC 0.88 (p < 0.0001)	Retrospective cohort chart review	2014	[48]
Mycoplasma
Mycoplasma pneumoniae	CAP	Adults hospitalized with CAP	CRP/PCT ratio >350 μg/ng	AUC 0.90 (95%CI 83–95)	Retrospective study	2021	[49]
		Children with 3–18 years of age	<0.25 ng/mL	AUC 0.81 (95%CI 70–0.92)	Prospective cohort study	2020	[50]
		Patients hospitalized with CAP	CRP/PCT ratio >400 mg/μg	AUC 0.73 (p < 0.001)	Retrospective single-center study	2019	[51]
Rickettsia
Orientia tsutsugamushi	Scrub typhus	Patients with acute scrub typhus	1.3 ng/mL	AUC 0.84	Retrospective study	2017	[52]
Parasite
Plasmodium	Malaria	Patients with Plasmodium falciparum malaria	25 ng/mL	n.m.	Retrospective study	2001	[53]

AUC: area under the curve; BC: blood culture; BSI: bloodstream infection; CAP: community-acquired pneumonia; CHAID: chi-squared automatic interaction detection; CI: confidence interval; CoNS: Coagulase-negative staphylococci; DVT: deep vein thrombosis; G⁺: Gram-positive; G^–: Gram-negative; ICU: intensive care unit; IE: infective endocarditis; n.m.: not mentioned; RSV: respiratory syncytial virus; SEN: sensitivity; SPE: specificity.

*PCT levels to distinguish Gram-positive from Gram-negative bacteremia.

Figure 2. The specific mechanism of PCT variation caused by different pathogenic microorganisms. (a) Staphylococcus aureus activates TLR2 and TLR4 on monocytes and granulocytes through LTA to stimulate the production of cytokines, including TNF-alpha, and these cytokines ultimately promote the release of PCT. (b) The surface molecule LPS of Escherichia coli acts on macrophages and neutrophils, and promotes the production of IL-1, IL-6, TNF-alpha and other cytokines through the TLR4/NF-κB pathway. These inflammatory mediators such as bacterial endotoxin and interleukin can stimulate the secretion of PCT. (c) Group A Streptococcus activates the TLR2 and TLR4 receptors of macrophages, which activates the NF-κB pathway and stimulates the production of IL-1, IL-6, IL-8, TNF-alpha and other cytokines. (d) Streptococcus pneumoniae induces macrophage NF-κB translocation by activating TLR4, supplemented by cell wall components to activate TLR2, thereby stimulating the secretion of TNF-alpha inflammatory cytokines to promote the release of PCT. (e) Pathogens have different virulence mechanisms, leading to different host inflammatory responses, and differences in these pathogens’ specific signaling lead to different serum PCT concentrations, according to the data from Table 1. (f) When a bacterial infection occurs, the release of LPS from bacteria and the cytokines stimulated by it can induce the expression of CALC-I in the extra-thyroid organs and cells such as liver, pancreas, kidney, lung, intestine and within leukocytes, leading to a sharp increase of PCT levels.

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