- Research note
- Open access
- Published:
Presepsin values and prognostic nutritional index predict mortality in intensive care unit patients with sepsis: a pilot study
BMC Research Notes volume 14, Article number: 245 (2021)
Abstract
Objective
Sepsis is a major cause of mortality for critically ill patients. This study aimed to determine whether presepsin values can predict mortality in patients with sepsis.
Results
Receiver operating characteristic (ROC) curve analysis, Log-rank test, and multivariate analysis identified presepsin values and Prognostic Nutritional Index as predictors of mortality in sepsis patients. Presepsin value on Day 1 was a predictor of early mortality, i.e., death within 7 days of ICU admission; ROC curve analysis revealed an AUC of 0.84, sensitivity of 89%, and specificity of 77%; and multivariate analysis showed an OR of 1.0007, with a 95%CI of 1.0001–1.0013 (p = 0.0320).
Introduction
Despite adequate treatment with appropriate antibiotics, sepsis is the main cause of mortality in intensive care unit (ICU) patients. Sepsis criteria were updated in 2016 [1, 2], and sepsis is now defined as a syndrome that can lead to lethal multiorgan failure, for which an increase of ≥ 2 in the Sequential Organ Failure Assessment (SOFA) score is associated with a high in-hospital mortality rate [1]. Early goal-directed management (i.e., early recognition of severe sepsis) and early initiation of aggressive and supportive therapy are important for reducing in-hospital mortality [3, 4]. Procalcitonin (PCT) is a biomarker used for sepsis with the highest specificity and is widely adopted in clinical settings. However, PCT values can be elevated by non-septic conditions, which can in turn lead to false-positive results [5,6,7]. Presepsin is a subtype of soluble CD14 (CD14-ST) [8] which is released into the circulation during monocyte activation upon the recognition of lipopolysaccharide from infectious agents [9]. Presepsin values are correlated with severity of sepsis [10] and are thus potentially useful for predicting the prognosis of sepsis and monitoring the course of the disease [9, 11]. Moreover, presepsin values can be measured in less than 17 min by a chemiluminescent enzyme immunoassay (CLEIA) with a compact fully automated immunoanalyzer (PATHFAST®; Mitsubishi Chemical Medience Corporation, Tokyo, Japan) [12], which is another advantage.
Inflammation-based prognostic scores, including the Glasgow Prognostic Score (GPS; based on serum C-reactive protein (CRP) and albumin levels), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), prognostic nutritional index (PNI; based on albumin and lymphocyte counts), and the prognostic index (PI; based on serum CRP and white blood cell counts), have been adopted as significant prognostic biomarkers for several types of cancer [13]. However, no study has assessed the association of mortality with presepsin values alone or in combination with the above-mentioned inflammation-based prognostic scores in septic ICU patients. The present study aimed to test the following hypotheses: (1) presepsin can predict early and long-term mortality in sepsis patients; and (2) presepsin is superior to inflammation-based prognostic scores in predicting early/long-term mortality, and its predictive ability can be improved by combining it with inflammation-based prognostic scores.
Materials and methods
Patients and study design
The study design, inclusion and exclusion criteria, and definition of “inflammation presepsin scores [iPS]” used in the present study have been published previously [14]. Mortality was categorized as 28-, 60-, 90-, and 180-day mortality. Presepsin values, inflammation-based prognostic scores, iPS, and changes (Δ) in presepsin values relative to baseline values at each sampling point were compared between survivors and non-survivors.
Laboratory assessments
Presepsin concentration was measured by CLEIA (PATHFAST®; Mitsubishi Chemical Medience Corporation, Tokyo, Japan) [12]. Assay results were obtained within 17 min. This assay can detect systemic infection (sepsis) within the range of 300 to 500 pg/ml.
Statistical analysis
Categorical data are reported as percentages and compared using Fisher’s exact test. Continuous data are reported as medians with inter-quartile ranges and compared using the Mann–Whitney U test. ROC curves were generated for presepsin values, inflammation-based prognostic scores, iPS, and Δpresepsin, and areas under the curve (AUCs), cut-off values, sensitivities, and specificities were calculated. Presepsin values, inflammation-based prognostic scores, iPS, Δpresepsin, SOFA, and quick SOFA (qSOFA) (with P < 0.05 in univariate analysis) were examined further by multivariate logistic regression analysis for identifying potential predictors of mortality associated with sepsis. P < 0.05 was considered statistically significant. JMP software version 11.0.0 (SAS Institute Inc., NC, USA) was used for all statistical analyses.
Results
Baseline characteristics of patients are shown in Table 1. No significant differences in age or sex were observed among sepsis patients. Presepsin values of survivors were higher than those of non-survivors (Figs. 1, 2).
ROC curve analysis, Log-rank test, and multivariate analysis revealed that presepsin values and Prognostic Nutritional Index are predictors of mortality in sepsis patients (Additional file 1: Table S1, Additional file 2: Table S2, Additional file 3: Table S3, Additional file 4: Table S4). Presepsin value on Day 1 was found to be a predictor of early mortality, i.e., death within 7 days of ICU admission, with an AUC of 0.84, sensitivity of 89%, and specificity of 77% in ROC curve analysis, and an OR of 1.0007 with a 95%CI of 1.0001–1.0013 (p = 0.0320) in multivariate analysis (Additional file 5: Table S5, Additional file 6: Table S6, Additional file 7: Table S7).
Discussion
Severe sepsis is a syndrome accompanied by lethal organ dysfunction due to dysregulated host responses to infection, and is associated with a mortality rate higher than 50% [15]. Sepsis initiates the activation of both pro- and anti-inflammatory responses [16], both of which are amplified by non-immunologic pathways including cardiovascular, neuronal, autonomic, hormonal, bioenergetic, metabolic, and coagulation pathways [17,18,19]. Presepsin, a subtype of CD14-ST, is secreted from granulocytes by infectious stimuli in an animal sepsis model [20] and can thus be used as a highly specific biomarker for diagnosing bacterial sepsis. Presepsin values are useful for diagnosing early stage sepsis in emergent patients and are independently associated with the degree of organ dysfunction, coagulation disorders, and ICU mortality [21, 22].
The present study demonstrated that presepsin is a predictor of mortality in septic patients. AUC values of presepsin for predicting 28-day mortality were all higher than each of the presepsin AUC values for 60-, 90-, and 180-day mortality. Moreover, multivariate analysis revealed that only the presepsin value on Day 1 predicted mortality rates. Collectively, these findings suggest that the AUC of presepsin on Day 1 might be effective in predicting early mortality (Additional file 1: Table S1, Additional file 4: Table S4).
We also investigated the ability of presepsin values on Day 1 to predict early mortality (i.e., death within 7 days of ICU admission). The AUC of presepsin on Day 1 to predict death within 7 days of ICU admission was 0.84 (Additional file 5: Table S5). Multivariate logistic regression analysis for mortality found the presepsin value on Day 1 to be a significant independent predictor of death within 7 days of ICU admission (OR, 1.0007; 95%CI, 1.0001–1.0013; p = 0.032; Additional file 6: Table S6). Ulla et al. reported that a higher level of presepsin at presentation in the emergency department was correlated to 60-day mortality [23]. Masson et al. found that presepsin levels measured at the time of presentation among patients with severe sepsis or septic shock were higher in non-survivors than in survivors [24], and our findings were consistent with these results.
In the present study, presepsin cut-off values for predicting each designation of mortality were higher than previously reported cut-offs for diagnosing either sepsis (300 to 500 pg/ml) or severe sepsis (500 to 1000 pg/ml) [25, 26]. Klouche reported that a cut-off presepsin value for mortality in sepsis patients was 1926 pg/ml [27]. These results suggest the need to adopt a higher presepsin cut-off value for predicting mortality associated with sepsis.
The presepsin values for ΔDay 3-Day 1 in 28- or 180-day mortality showed higher specificity for predicting 28- or 180-day mortality compared with presepsin values on Days 1, 2, 3, and 5 alone for all mortality (Additional file 1: Table S1). These findings suggest that Δpresepsin Day 3-Day 1 may be useful as a “rule in” test for predicting mortality. Log-rank test also revealed Δpresepsin Day 3-Day 1 and Δpresepsin Day 2-Day 1 to be independent predictors of mortality in septic patients (Additional file 2: Table S2). Presepsin values on Days 3 and 5 had higher AUCs for predicting 28-day mortality than the presepsin values on Days 1 and 2 (Additional file 1: Table S1). These results suggest the importance not only of measuring presepsin values at the time of ICU admission but also monitoring its changes on Day 2 and thereafter following ICU admission, in order to predict mortality in sepsis patients.
The AUC, sensitivity, and specificity of PNI for predicting 28-day mortality were 0.73, 70%, and 80%, respectively (Additional file 1: Table S1). Log-rank test revealed PNI as an independent predictor of all mortality in sepsis patients (Additional file 2: Table S2). Previously, we found that NLR is superior to other inflammation-based prognostic scores in predicting mortality among patients with gastrointestinal perforation and pneumonia [28, 29]. With regard to 28-day mortality, however, the present study found PNI to be a predictor of mortality in sepsis patients. Pinato et al. [30] reported that PNI is a predictor of poor overall survival in patients with hepatocellular carcinoma. In the Albumin Italian Outcome Sepsis trial, albumin replacement did not improve survival at 28 and 90 days among patients with severe sepsis or septic shock [31]. However, our findings suggest that, of the many variables that can be investigated for assessing inflammation, hypoalbuminemia and lymphocytopenia (albumin and lymphocyte counts used to calculate PNI) are important variables for predicting mortality in sepsis patients. In the context of predicting 28-day mortality, PNI shows a lower AUC than that of presepsin, but in clinical environments where presepsin values cannot be measured, PNI at presentation may be useful for determining 28-day mortality.
No previous study has assessed the association between presepsin values, PNI, and mortality in patients with sepsis according to the Sepsis-3 definition. Our findings are novel in this respect. Further studies will be needed to clarify how presepsin values and PNI can predict mortality in sepsis patients.
Conclusions
Presepsin was found to be a predictor of mortality in patients with sepsis. In particular, the presepsin value on Day 1 is useful for predicting early mortality (i.e., death within 7 days of ICU admission). In addition to measuring presepsin values at the time of ICU admission, any changes in these values on Day 2 and thereafter following ICU admission should be monitored in order to predict mortality in sepsis patients. In the context of 28-day mortality, PNI was found to be a predictor for mortality in sepsis patients. Further studies aimed at understanding the exact role of presepsin values and PNI in predicting mortality in sepsis patients are warranted.
Limitations
This study has several limitations. First, the present study was conducted in a single center with a small cohort. Second, we used a single biomarker, and comparisons were not made between presepsin and other biomarkers. Third, presepsin is elevated when renal function is reduced [32], which suggests that the diagnostic accuracy of presepsin may be influenced by declined renal function.
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Abbreviations
- GPS:
-
Glasgow prognostic score
- CRP:
-
C-reactive protein (CRP)
- NLR:
-
Neutrophil to lymphocyte ratio
- PLR:
-
Platelet to lymphocyte ratio
- PNI:
-
Prognostic nutritional index
- PI:
-
Prognostic index
- ROC:
-
Receiver operating characteristic
- AUC:
-
Area under the curve
References
Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA. 2016;315:801–10.
Vincent JL, Sakr Y, Sprung CL, Ranieri VM, Reinhart K, Gerlach H, et al. Sepsis occurrence in acutely ill patients investigators, sepsis in european intensive care units: results of the SOAP study. Crit Care Med. 2006;34:344–53.
Angus DC, van der Poll T. Severe sepsis and septic shock. N Engl J Med. 2013;369:840–51.
Dellinger RP, Levy MM, Rhodes A, Annane D, Gerlach H, Opal SM, et al. Surviving sepsis campaign guidelines committee including the pediatric subgroup: surviving sepsis campaign: international guidelines for management of severe sepsis and septic shock 2012. Crit Care Med. 2013;41:580–637.
Pierrakos C, Vincent J-L. Sepsis biomarkers: a review. Crit Care. 2010;14:R15.
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;13:426–35.
Kibe S, Adams K, Barlow G. Diagnostic and prognostic biomarkers of sepsis in critical care. J Antimicrob Chemother. 2011;66(Suppl 2):ii33-40.
Shirakawa K, Naitou K, Hirose J, Takahashi T, Furusako S. Presepsin (sCD14-ST): development and evaluation of one-step ELISA with a new standard that is similar to the form of presepsin in septic patients. Clin Chem Lab Med. 2011;49:937–9.
Shozushima T, Takahashi G, Matsumoto N, Kojika M, Okamura Y, Endo S. Usefulness of presepsin (sCD14-ST) measurements as a marker for the diagnosis and severity of sepsis that satisfied diagnostic criteria of systemic inflammatory response syndrome. J Infect Chemother. 2011;17:764–9.
Behnes M, Bertsch T, Lepiorz D, Lang S, Trinkmann F, Brueckmann M, et al. Diagnostic and prognostic utility of soluble CD14 subtype (presepsin) for severe sepsis and septic shock during the first week of intensive care treatment. Crit Care. 2014;18(5):507.
Endo S, Suzuki Y, Takahashi G, Shozushima T, Ishikura H, Murai A, et al. Usefulness of presepsin in the diagnosis of sepsis in a multicenter prospective study. J Infect Chemother. 2012;18:891–7.
Okamura Y, Yokoi H. Development of a point-of-care assay system for measurement of presepsin (sCD14-ST). Clin Chim Acta. 2011;412:2157–61.
Kinoshita A, Onoda H, Imai N, Iwaku A, Oishi M, Fushiya N, et al. Comparison of the prognostic value of inflammation-based prognostic scores in patients with hepatocellular carcinoma. Br J Cancer. 2012;107:988–93.
Shimoyama Y, Umegaki O, Kadono N, Minami T. Presepsin values predict septic acute kidney injury, acute respiratory distress syndrome, disseminated intravascular coagulation, and shock. Shock. 2021;55:501–6.
Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome and associated costs of care. Crit Care Med. 2001;29:1303–10.
Hotchkiss RS, Monneret G, Payen D. Sepsis-induced immunosuppression: from cellular dysfunctions to immunotherapy. Nat Rev Immunol. 2013;13(12):862–74.
Levy MM, Fink MP, Marshall JC, Abraham E, Angus D, Cook D, Cohen J, Opal SM, Vincent JL, Ramsay G, International Sepsis Definitions Conference. SCCM/ESICM/ACCP/ATS/SIS international sepsis definitions conference. Intensive Care Med. 2001;2003(29):530–8.
Calandra T, Cohen J. The international sepsis forum consensus conference on definitions of infection in the intensive care unit. Crit Care Med. 2005;33:1538–48.
Tunkel AR, Hartman BJ, Kaplan SL, Kaufman BA, Roos KL, Scheld WM, Whitley RJ. Practice guidelines for the management of bacterial meningitis. Clin Infect Dis. 2004;39:1267–84.
Naitoh K, Shirakawa K, Hirose J, Nakamura M, Takeuchi T, Hosaka Y, Furusako S. The new sepsis marker, sCD14-ST (PRESEPSIN): induction mechanism in the rabbit sepsis models. Crit Care. 2010;14:P19.
Liu B, Chen Y-X, Yin Q, Zhao Y-Z, Li C-S. Diagnostic value and prognostic evaluation of Presepsin for sepsis in an emergency department. Crit Care. 2013;17(5):R244.
Masson S, Caironi P, Fanizza C, Thomae R, Bernasconi R, Noto A, et al. Circulating presepsin (soluble CD14 subtype) as a marker of host response in patients with severe sepsis or septic shock: data from the multicenter, randomized ALBIOS trial. Intensive Care Med. 2015;41:12–20.
Ulla M, Pizzolato E, Lucchiari M, et al. Diagnostic and prognostic value of presepsin in the management of sepsis in the emergency department: a multicenter prospective study. Crit Care. 2013;17(4):R168.
Masson S, Caironi P, Spanuth E, et al. Presepsin (soluble CD14 subtype) and procalcitonin levels for mortality prediction in sepsis: data from the Albumin Italian Outcome Sepsis trial. Crit Care. 2014;18(1):R6.
Chenevier-Gobeaux C, Borderie D, Weiss N, Mallet-Coste T, Claessens Y-E. Presepsin (sCD14-ST), an innate immune response marker in sepsis. Clin Chim Acta. 2015;450:97–103.
Carpio R, Zapata J, Spanuth E, Hess G. Utility of presepsin (sCD14-ST) as a diagnostic and prognostic marker of sepsis in the emergency department. Clin Chim Acta. 2015;450:169–75.
Klouche K, Cristol JP, Devin J, Gilles V, Kuster N, Larcher R, et al. Diagnostic and prognostic value of soluble CD14 subtype (Presepsin) for sepsis and community-acquired pneumonia in ICU patients. Ann Intensive Care. 2016. https://doi.org/10.1186/s13613-016-0160-6.
Shimoyama Y, Umegaki O, Agui T, Kadono N, Minami T. Neutrophil to lymphocyte ratio and platelet to lymphocyte ratio are superior to other inflammation-based prognostic scores in predicting the mortality of patients with gastrointestinal perforation. JA Clin Rep. 2017;3:49.
Shimoyama Y, Umegaki O, Inoue S, Agui T, Kadono N, Minamiet T. The neutrophil to lymphocyte ratio is superior to other inflammation-based prognostic scores in predicting the mortality of patients with pneumonia. Acta Med. 2018;72:591–3.
Pinato DJ, North BV, Sharma R. A novel, externally validated inflammation-based prognostic algorithm in hepatocellular carcinoma: the prognostic nutritional index (PNI). Br J Cancer. 2012;106:1439–45.
Caironi P, Tognoni G, Masson S, Fumagalli R, Pesenti A, et al. Albumin replacement in patients with severe sepsis or septic shock. N Engl J Med. 2014;370:1412–21.
Nagata T, Yasuda Y, Ando M, Abe T, Katsumo T, Kato S, Tsuboi N, et al. Clinical impact of kidney function on Presepsin levels. PLoS ONE. 2015;10(6): e0129159. https://doi.org/10.1371/journal.pone.0129159.
Acknowledgements
Not applicable.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Support was provided solely from institutional and/or departmental sources.
Author information
Authors and Affiliations
Contributions
YS designed the study, performed the data collection and statistical analysis, and wrote the first draft of the manuscript; OU, NK, and TM designed the study and performed the manuscript revision. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Ethics approval and consent to participate
Written informed consent was obtained from all patients enrolled in this study or their families. The study protocol was approved by the Ethics Committee of Osaka Medical College (Osaka, Japan).
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Additional file 1: Table S1.
Receiver operating characteristic curve analysis.
Additional file 2: Table S2.
Log-rank test (all presepsin and variables for which P<0.05 are shown).
Additional file 3: Table S3.
Predictors of mortality in sepsis patients (univariate analysis).
Additional file 4: Table S4.
Predictors of mortality in sepsis patients (multivariate analysis).
Additional file 5: Table S5.
Receiver operating characteristic curve analysis (Presepsin on Day 1 for predicting early or late mortality).
Additional file 6: Table S6.
Receiver operating characteristic curve analysis (Inflammation-based prognostic scores, iPS, and SOFA for predicting early mortality).
Additional file 7: Table S7.
Univariate and multivariate analyses for predicting mortality in sepsis patients.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
About this article
Cite this article
Shimoyama, Y., Umegaki, O., Kadono, N. et al. Presepsin values and prognostic nutritional index predict mortality in intensive care unit patients with sepsis: a pilot study. BMC Res Notes 14, 245 (2021). https://doi.org/10.1186/s13104-021-05659-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1186/s13104-021-05659-9