Procalcitonin and MR-Proadrenomedullin Combination with SOFA and qSOFA Scores for Sepsis Diagnosis and Prognosis: A Diagnostic Algorithm

Spoto, Silvia; Cella, Eleonora; Cesaris, Marina De; Locorriere, Luciana; Mazzaroppi, Silvia; Nobile, Edoardo; Lanotte, Arcangela M.; Pedicino, Lucia; Fogolari, Marta; Costantino, Sebastiano; Dicuonzo, Giordano; Ciccozzi, Massimo; Angeletti, Silvia

doi:10.1097/shk.0000000000001023

Cited by 52 publications

(58 citation statements)

References 35 publications

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“…For instance, a patient can have a qSOFA ≥2 in acute conditions other than sepsis (e.g., hypovolemia, severe heart failure, or large pulmonary embolism) [ 24 ]. A recent study showed that to improve sepsis identification, the qSOFA score should be used in combination with laboratory tests such as procalcitonin [ 25 ]. However, measurements of procalcitonin were not routine clinical practice in our institution, especially in the preintervention period.…”

Section: Discussionmentioning

confidence: 99%

Clinical Utility of Rapid Pathogen Identification for Detecting the Causative Organisms in Sepsis: A Single-Center Study in Korea

Kim

Jeong

Kim

et al. 2018

Canadian Journal of Infectious Diseases and Medical Microbiolog

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Purpose The aim of this pre- and postintervention cohort study was evaluating how effectively rapid pathogen identification with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) detected the causative organisms in sepsis. Methods All consecutive adult patients who had bacteremia within 72 h of intensive care unit admission and met ≥2 quick Sequential Organ Failure Assessment criteria at intensive care unit admission were analyzed. The patients whose microorganisms were identified via MALDI-TOF MS between March 2014 and February 2016 formed the postintervention group. The patients whose microorganisms were identified by using conventional methods between March 2011 and February 2013 formed the preintervention group. Results The postintervention group (n=58) had a shorter mean time from blood draw to receiving the antimicrobial susceptibility results than the preintervention group (n=40) (90.2 ± 32.1 vs. 108.7 ± 43.1 h; p=0.02). The postintervention group was also more likely to have received active antimicrobial therapy by the time the susceptibility report became available (77% vs. 47%; p=0.005). Its 28-day mortality was also lower (40% vs. 70%; p=0.003). Univariate analysis showed that identification via MALDI-TOF MS (odds ratio, 0.28; 95% confidence interval, 0.12–0.66; p=0.004) and active therapy (odds ratio, 0.38; 95% confidence interval, 0.16–0.95; p=0.04) were associated with lower 28-day mortality. Conclusion Rapid microorganism identification via MALDI-TOF MS followed by appropriate antimicrobial therapy may improve the clinical outcomes of patients with sepsis.

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Section: Discussionmentioning

confidence: 99%

Clinical Utility of Rapid Pathogen Identification for Detecting the Causative Organisms in Sepsis: A Single-Center Study in Korea

Kim

Jeong

Kim

et al. 2018

Canadian Journal of Infectious Diseases and Medical Microbiolog

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“…NLCR was calculated as absolute neutrophil count divided by absolute lymphocyte count [15,17]. We explicitly did not study the value of inflammatory markers that were not routinely measured in our hospital, such as procalcitonin and other newly developed markers such as mid-regional pro-adrenomedullin [28].…”

Section: Candidate Predictorsmentioning

confidence: 99%

“…Besides using vital signs, there have been several attempts to predict the prognosis of patients with infectious conditions using biomarkers like lactate and other inflammatory markers [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28]. When evaluating the prognostic value of biomarkers, the interest is in the value that can be added to already available clinical information (e.g., history and physical examination) [29].…”

Section: Introductionmentioning

confidence: 99%

Added value of inflammatory markers to vital signs to predict mortality in patients suspected of severe infection

Takada

Hoogland

Yano

et al. 2020

The American Journal of Emergency Medicine

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To evaluate the added value of inflammatory markers to vital signs to predict mortality in patients suspected of severe infection. Methods: This study was conducted at an acute care hospital (471-bed capacity). Consecutive adult patients suspected of severe infection who presented to either ambulatory care or the emergency department from April 2015 to March 2017 were retrospectively evaluated. A prognostic model for predicting 30-day inhospital mortality based on previously established vital signs (systolic blood pressure, respiratory rate, and mental status) was compared with an extended model that also included four inflammatory markers (C-reactive protein, neutrophil-lymphocyte ratio, mean platelet volume, and red cell distribution width). Measures of interest were model fit, discrimination, and the net percentage of correctly reclassified individuals at the pre-specified threshold of 10% risk. Results: Of the 1015 patients included, 66 (6.5%) died. The extended model including inflammatory markers performed significantly better than the vital sign model (likelihood ratio test: p b 0.001), and the c-index increased from 0.69 (range 0.67-0.70) to 0.76 (range 0.75-0.77) (p = 0.01). All included markers except C-reactive protein showed significant contribution to the model improvement. Among those who died, 9.1% (95% CI −2.8-21.8) were correctly reclassified by the extended model at the 10% threshold. Conclusions: The inflammatory markers except C-reactive protein showed added predictive value to vital signs. Future studies should focus on developing and validating prediction models for use in individualized predictions including both vital signs and the significant markers.

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“…Auch die Entwicklung von Algorithmen zur Diagnose von Sepsis oder septischem Schock kann z. B. bei Einbeziehung von MR-proADM, SOFA und qSOFA signifikant Überlebende und später Verstorbene unterscheiden [34]. Welche Biomarker dabei erhöht sind, hängt aber auch von den auslösenden Pathogenen ab.…”

Section: Biomarker In Kombinationunclassified

Diagnostik der Sepsis

Schürholz¹

2018

Intensivmed.up2date

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Procalcitonin and MR-Proadrenomedullin Combination with SOFA and qSOFA Scores for Sepsis Diagnosis and Prognosis: A Diagnostic Algorithm

Cited by 52 publications

References 35 publications

Clinical Utility of Rapid Pathogen Identification for Detecting the Causative Organisms in Sepsis: A Single-Center Study in Korea

Clinical Utility of Rapid Pathogen Identification for Detecting the Causative Organisms in Sepsis: A Single-Center Study in Korea

Added value of inflammatory markers to vital signs to predict mortality in patients suspected of severe infection

Diagnostik der Sepsis

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