Diagnostic Accuracy of Biomarkers for Early Multiple Organ Dysfunction in Critically Ill Patients: A Multicenter Prospective Observational Study

Shock and organ damage occur in critically ill patients in the emergency department because of biological responses to invasion, and cytokines play an important role in their development. It is important to predict early multiple organ dysfunction (MOD) because it is useful in predicting patient outcomes and selecting treatment strategies. This study examined the accuracy of biomarkers, including interleukin (IL)-6, in predicting early MOD in critically ill patients compared with that of quick sequential organ failure assessment (qSOFA). This observational study was conducted at ve universities from 2016 to 2018. Data of adult patients with systemic inammatory response syndrome who presented to the emergency department or were admitted to the intensive care unit were prospectively evaluated. qSOFA score and each biomarker (IL-6, IL-8, IL-10, tumor necrosis factor-α, C-reactive protein, and procalcitonin [PCT]) level were assessed on Days 0, 1, and 2. The primary outcome was set as MOD on Day 2, and the area under the receiver operating characteristic curve (AUROC) was analyzed to evaluate qSOFA scores and biomarker levels. scores improved the accuracy of early MOD prediction. Prognostic value of a combined approach of IL-6 and baseline qSOFA A, AUROC for baseline qSOFA (Day with IL-6 (Day B, AUROC for baseline qSOFA (Day 0) with IL-6 (Day 1) C, AUROC for baseline qSOFA (Day 1) with IL-6 (Day 1) Comparison of AUROC revealed that the combination model using additional serum IL-6 concentration on Days 0 and 1 had a signicantly higher AUROC than the baseline model that uses only the qSOFA score. AUROC = area under the receiver operating characteristic curve, qSOFA = quick sequential organ failure assessment, IL = interleukin.


Introduction
Excessive immune response with the overproduction of in ammatory mediators leads to systemic in ammatory response syndrome (SIRS), which is crucial for the development of multiple organ dysfunction (MOD) [1]. MOD is an independent prognostic factor for intensive care unit (ICU) mortality [2]. Patients with MOD have longer ICU stays and higher mortality rates [3,4]. The early detection of MODS may help identify patients at a risk of prolonged illness and death. Therefore, predicting early MOD can improve patient outcomes and quality of care. Sequential organ failure assessment (SOFA) is a scale used to score organ failure and predict mortality by determining disease severity [5]. However, blood tests, including those of arterial blood gases, are essential to assess SOFA. In contrast, quick SOFA (qSOFA) was designed as a simple tool that can be used in the emergency department (ED) and can be used without performing blood tests [6]. qSOFA is considered a useful index for identifying patients with high mortality and those requiring systemic management in the ICU and is highly convenient in primary care [7]. In addition, the in-hospital mortality predictive effectiveness of qSOFA was statistically higher than that of SOFA in cases of suspected infection outside the ICU [8]. However, qSOFA is affected by the severity of infection and quality of the health care system, and factors such as biomarkers that correlate with systemic in ammation are not included in the score. Therefore, the addition of simple blood tests, including those of cytokines, as in the present study, may improve the diagnostic accuracy of qSOFA for sepsis [9,10,11].
Interleukin (IL)-6 is a proin ammatory cytokine released by immune cells and re ects the degree of hypercytokinemia involved in systemic in ammatory changes [12]. IL-6 peaks at 6 h after invasion and is induced earlier than C-reactive protein (CRP) and procalcitonin (PCT). Furthermore, IL-6 enables earlier diagnoses of SIRS, and IL-6 levels re ect the severity and outcome of sepsis [13,14,15]. In this study, we investigated whether adding biomarkers such as IL-6 to qSOFA would provide a more accurate prediction of early MOD in critically ill patients.

Settings
This prospective observational study was conducted using data from EDs and ICUs from 5 university hospitals in Japan as a secondary analysis of a study. This study was approved by the Institutional Review Board of the University of Occupational and Environmental Health (approval number H28-120).

Study population
This study included patients with SIRS between September 2016 and September 2018. The inclusion criteria were patient emergency admission (ICU or ED), age ≥ 20 years at the time of obtaining consent, patients predicted to undergo hospitalization > 48 h, and patients with a diagnosis of SIRS according to the American College of Chest Physicians/Society of Critical Care Medicine criteria on admission. Patients with trauma were included if they had multiple injuries (≥ 2 injured area) and had a predicted Injury Severity Score ≥ 10, and patients with burns were included if they had a Burn Index ≥ 15. Patients who received steroids, immunosuppressive drugs, or preparations that affected serum IL-6 concentration within 1 week before emergency transport or ICU admission, those with HIV infection, those who were pregnant, or those considered ineligible for enrollment were excluded.

Data collection
The patient information included demographic characteristics, etiology of admission, comorbidities, presence of hemodynamic instability, and history of treatment in the ED/ICU. Blood samples were collected 6 h after admission (Day 0) and the following morning (Day 1). Blood samples on Day 2 were collected during the morning period. The in ammatory biological markers included CRP, IL-6, IL-8, IL-10, tumor necrosis factor (TNF)-α, and PCT; serum CRP levels were measured immediately using commercially available assays at each hospital; IL, TNF-α, and PCT levels were measured at an outside facility after serum samples were frozen and stored at − 20 °C (IL-6, PCT, Roche Diagnostics, Mannheim, Germany; IL-8, IL-10, BioSource Europe, Nivelles, Belgium; TNF-α, R&D Systems, Minneapolis, MN, USA). MOD was de ned as more than two organs with a SOFA score ≥ 2. qSOFA and SOFA scores were recorded on Days 0, 1, and 2. The Acute Physiology and Chronic Health Evaluation (APACHE) II scores were recorded on admission.

Statistical analysis
The outcome as an early MOD was assessed on Day 2 because reversible derangements induced by the inciting event or incomplete resuscitation may be re ected 24 h after admission. To evaluate the accuracy of predicting MOD by adding biomarkers to qSOFA, we developed a baseline model to predict MOD (Day 2) using a logistic regression analysis. We calculated the area under the receiver operating characteristic curve (AUROC) by drawing an ROC curve for the blood concentration of each biomarker on Days 0 and 1 to determine which biomarker and time points were most predictive of MOD on Day 2. The biomarkers and days with the highest AUROC were used in the model added to qSOFA to evaluate whether the model improves the accuracy of predicting MOD. ROC curves were drawn, and AUROC values were compared between the baseline model and the model with the biomarker added to qSOFA. We calculated the net reclassi cation improvement (NRI) to compare each model and presented the values with 95% con dence intervals (CIs). The results were compared using Mann-Whitney U tests and chisquare tests. P-values < 0.05 were considered statistically signi cant. All statistical analyses were performed using R version 3.5.3 and JMP 13.2.1.

Results
Of 199 patients included in this study, the following patients were excluded: 5 who withdrew their consent, 4 who were on steroids before admission, 7 who died within 48 h of admission, 1 who was discharged within 48 h of admission, and 21 who had deviated from the protocol for biomarker testing and SOFA score calculation. Of 161 eligible patients, 96 patients had MOD on Day 2 ( Figure 1). Patients with MOD had signi cantly higher qSOFA, SOFA, APACHE II scores, mortality rates, fewer ICU-free days, ventilator-free days, renal replacement therapy (RRT)-free days ( Table 1).
The ROC analysis of each biomarker on Days 0 and 1 was performed to assess MOD on Day 2. The results showed that IL-6 on Day 1 had the highest AUC (AUC: 0.790; 95% CI: 0.711-0.852) ( Table 2)

Discussion
In this study, IL-6 on Day 1 was the most accurate biomarker for predicting early MOD. Furthermore, the addition of IL-6 blood levels to qSOFA was a more accurate predictor of early MOD. Although previous studies implicated that patients with MOD had poor prognosis, including increased mortality and hospitalization days [2,3], this study also con rmed that patients with MOD on Day 2 had poor prognosis ( Table 1).
Cytokine storms play an important role in the pathogenesis of MOD, and various cytokines have been assessed for their accuracy in predicting MOD. IL-6 is a cytokine involved in in ammatory responses and is released in response to tissue injuries and in ammatory stimuli, resulting in a physiological response.
IL-6 acts locally and systemically and is a proin ammatory mediator and an anti-in ammatory regulator that stimulates anti-in ammatory cytokines, including IL-10 [16]. The mediators of acute in ammation and infection, such as CRP, IL-6, and PCT, have long been involved in the pathophysiology of critically ill patients and are routinely used for diagnostic, prognostic, and treatment monitoring in the ICU [16,17,18]. Compared with other biomarkers such as CRP and PCT, IL-6 responds more quickly to in ammatory stimuli, peaking at 3-6 h. This suggests that it has an advantage in predicting risk at admission. In this regard, several reports have shown that IL-6 is a useful biomarker for detecting early sepsis; however, CRP and PCT are still often within the reference range owing to their much slower rates [19,20,21]. However, the AUROC in Table 2 revealed that IL-6 peaked on Day 1, and PCT had a higher AUROC than IL-6 on Day 0. This may indicate that IL-6 levels have an early increase in the blood but remain more re ective of MOD than other biomarkers after Day 1. In a study examining various cytokine concentrations in patients with severe sepsis, IL-6 and IL-8 in the rst 24 h predicted organ dysfunction on Day 3 [22]. In light of these ndings, the present study shows that IL-6 may predict early MOD with greater accuracy than other biomarkers.
However, it is cumbersome to accurately predict organ failure and mortality using a single biomarker alone; therefore, a combination of biomarkers and severity scores has been proposed to provide better results. Oberholzer et al. suggested that IL-6 and APACHE II scores were correlated and showed that these combined models increased the accuracy of predicting mortality in patients with severe sepsis [23]. In addition, a study examining factors that predicted mortality 90 days after ICU admission found that combining SAPS II with IL-6 and soluble suppression of tumorigenesis-2 improved prediction accuracy [24].
The accuracy of predicting post-hospital organ failure and in-hospital mortality using qSOFA has been previously reported [25,26]. In contrast, a previous study reported that positive qSOFA scores had high speci city but poor sensitivity for predicting in-hospital mortality, acute organ dysfunction, and ICU admission in patients with infection outside the ICU, and the limits of qSOFA accuracy of the predictions have been reported [27]. The combination of IL-6 and qSOFA improved the accuracy of predicting early MOD in this study. Since qSOFA does not require testing, the improvement in predictive accuracy obtained without increasing healthcare costs is a major advantage. The combination in this study was qSOFA on admission and IL-6 on Day 1, which is also in line with that used in clinical practice. Typically, qSOFA is screened for sepsis on admission, and Il-6, which does not peak upon admission, is measured on Day 1.
In the future, a new scoring system that combines severity scores and biomarkers to predict MODs needs to be investigated.

Limitations
This study had some limitations. First, the sample size was small. This study included patients with a variety of diseases. Second, one of the problems with qSOFA is that it is di cult to assess consciousness in patients with cognitive impairment before the onset of infection [28].

Conclusion
We compared each biomarker as a predictor of MOD on Day 2. IL-6 on Day 1 had the highest predictive value. Furthermore, the addition of IL-6 (Day 1) to qSOFA score (Day 0) predicted MOD on Day 2 with greater accuracy. The present study showed that adding IL-6 to qSOFA could predict early MOD.   H28-120), and all subjects provided informed consent, and written informed consent was obtained from all subjects prior to participation.

Consent for publication
This manuscript, including tables and gures, has not been published elsewhere and is not under consideration by another journal. All authors have approved the manuscript and agree with submission.

Availability of data and materials
The data of this study are available from the authors, but restrictions apply to the availability of these data, which are not publicly available. However, data are available from the authors upon reasonable request.    If the NRI is positive and the 95%CI does not straddle zero, the predictive ability of the new model is considered to be signi cantly improved from the baseline model.    Prognostic value of a combined approach of IL-6 and baseline qSOFA A, AUROC for baseline qSOFA (Day 0) with IL-6 (Day 0) B, AUROC for baseline qSOFA (Day 0) with IL-6 (Day 1) C, AUROC for baseline qSOFA (Day 1) with IL-6 (Day 1) Comparison of AUROC revealed that the combination model using additional serum IL-6 concentration on Days 0 and 1 had a signi cantly higher AUROC than the baseline model that uses only the qSOFA score. AUROC = area under the receiver operating characteristic curve, qSOFA = quick sequential organ failure assessment, IL = interleukin.

Figure 2
Prognostic value of a combined approach of IL-6 and baseline qSOFA A, AUROC for baseline qSOFA (Day 0) with IL-6 (Day 0) B, AUROC for baseline qSOFA (Day 0) with IL-6 (Day 1) C, AUROC for baseline qSOFA (Day 1) with IL-6 (Day 1) Comparison of AUROC revealed that the combination model using additional serum IL-6 concentration on Days 0 and 1 had a signi cantly higher AUROC than the baseline model that uses only the qSOFA score. AUROC = area under the receiver operating characteristic curve, qSOFA = quick sequential organ failure assessment, IL = interleukin. Figure 2