Literature DB >> 31036824

The usefulness of C-reactive protein and procalcitonin to predict prognosis in septic shock patients: A multicenter prospective registry-based observational study.

Seung Mok Ryoo1, Kap Su Han2, Shin Ahn1, Tae Gun Shin3, Sung Yeon Hwang3, Sung Phil Chung4, Yoon Jung Hwang4, Yoo Seok Park4, You Hwan Jo5, Hyung Lan Chang5, Gil Joon Suh6, Kyoung Min You7, Gu Hyun Kang8, Sung-Hyuk Choi9, Tae Ho Lim10, Won Young Kim11.   

Abstract

The objective of this study was to evaluate the prognostic value of C-reactive protein (CRP), procalcitonin (PCT), and their combination for mortality in patients with septic shock. This multicenter, prospective, observational study was conducted between November 2015 and December 2017. A total of 1,772 septic shock patients were included, and the overall 28-day mortality was 20.7%. Although both CRP and PCT were elevated in the non-survivor group, only CRP had statistical significance (11.9 mg/dL vs. 14.7 mg/dL, p = 0.003, 6.4 ng/mL vs. 8.2 ng/mL, p = 0.508). Multivariate analysis showed that CRP and PCT were not independent prognostic markers. In the subgroup analysis of the CRP and PCT combination matrix using their optimal cut-off values (CRP 14.0 mg/dL, PCT 17.0 ng/dL), both CRP and PCT elevated showed significantly higher mortality (Odds ratio 1.552 [95% Confidence intervals 1.184-2.035]) than both CRP and PCT not elevated (p = 0.001) and only PCT elevated (p = 0.007). However, both CRP and PCT elevated was also not an independent predictor in multivariate analysis. Initial levels of CRP and PCT alone and their combinations in septic shock patients had a limitation to predict 28-day mortality. Future research is needed to determine new biomarkers for early prognostication in patients with septic shock.

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Year:  2019        PMID: 31036824      PMCID: PMC6488613          DOI: 10.1038/s41598-019-42972-7

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


Introduction

Sepsis is a life threatening organ dysfunction evoked by abnormal host response to infection, and the Sequential Organ Failure Assessment (SOFA) score is used to calculate the degree of organ dysfunction in sepsis[1,2]. Septic shock is defined as a subset of sepsis in which underlying circulatory and cellular metabolism abnormalities are profound enough to substantially increase mortality[2]. We can evaluate the degree of shock by measuring mean arterial blood pressure as a circulatory abnormality and serum lactate level as a cellular metabolic abnormality[3]. However, proven biomarkers that reflect the severity of infection in patients with sepsis have not yet been identified, and current guidelines by the Surviving Sepsis Campaign do not provide any biomarkers that can evaluate or identify an infection, except procalcitonin (PCT) for indicating the timing of de-escalating antibiotics[3]. C-reactive protein (CRP) is a traditional biomarker which is elevated in inflammatory states including rheumatoid arthritis and infection[4]. Aside from its roles as a biomarker, CRP also functions as a part of the defense mechanism against inflammation and pathogen invasion[5]. However, CRP has low specificity for diagnosing sepsis, and the plasma level of CRP is not a reliable indicator for the degree of systemic inflammation[6]. PCT is used as an indicator for antibiotics treatment because the level of PCT is higher in fungal, parasitic, and bacterial infections than in viral infections. Accordingly, high early levels of PCT in sepsis have been suggested to be associated with unfavorable prognosis[7]. Nevertheless, early PCT levels are subject to alteration by the type and severity of the initial cause of the sepsis and not necessarily the severity of the sepsis itself; therefore, it is not recommended to utilize early PCT level as a definite indicator of prognosis[8]. Research about the diagnostic ability of CRP and PCT has been conducted in sepsis, but data on the early prognostic value of CRP and PCT are lacking. This study evaluated the prognostic values of CRP and PCT for mortality prediction in septic shock cases.

Results

Of the 2,264 eligible patients in the Korean Shock Society (KoSS) septic shock registry, we excluded 124 patients due to missing 28-day mortality data and 367 patients due to missing CRP or PCT data. Finally, 1,772 patients were included and divided into 1,406 (79.3%) survivors and 366 (20.7%) non-survivors. (Fig. 1)
Figure 1

Diagram of included patients. Abbreviations: CRP, C-reactive protein; PCT, Procalcitonin.

Diagram of included patients. Abbreviations: CRP, C-reactive protein; PCT, Procalcitonin. The non-survivor group was male predominant (63.7% vs. 57.8% p = 0.041). Subjects were older (70.1 ± 13.0 years vs. 66.8 ± 13.7 years, p < 0.001) and had more co-morbidities, including diabetes and chronic pulmonary disease (35.5% vs. 28.5%, p = 0.009; 12.3% vs. 7.0%, p = 0.001; respectively), than the survivors. Their initial heart rate was faster (112.2 ± 25.0 vs. 104.2 ± 23.0, p < 0.001). Pneumonia was more frequent in the non-survivors (48.1% vs. 27.3%, p < 0.001); however, urinary tract infection and hepatobiliary and pancreas infection were more common in the survivors (19.1% vs. 26.7%, p = 0.001; 16.4% vs. 21.1%, p = 0.048; respectively). The severity scores, including maximum SOFA and Acute Physiology and Chronic Health evaluation (APACHE) II scores were higher in the non-survivor group (10.0 [8.0–13.0] vs. 7.0 [5.0–10.0], p < 0.001; 24.0 [18.0–34.0] vs. 18.0 [13.0–24.0], p < 0.001; respectively) (Table 1).
Table 1

Baseline and clinical characteristics of the study population grouped into survivors and non-survivors.

CharacteristicsTotal (n = 1,772)Survivors (n = 1,406)Non-survivors (n = 366)p-value
Age, years67.5 ± 13.666.8 ± 13.770.1 ± 13.0<0.001
Male1,045 (59.0)812 (57.8)233 (63.7)0.041
Past medical history
Hypertension723 (40.8)560 (39.8)163 (44.5)0.103
Diabetes531 (30.0)401 (28.5)130 (35.5)0.009
Coronary artery disease226 (12.8)177 (12.6)49 (13.4)0.683
Stroke211 (11.9)160 (11.4)51 (13.9)0.179
Chronic pulmonary disease144 (8.1)99 (7.0)45 (12.3)0.001
Metastatic cancer434 (24.5)331 (23.5)103 (28.1)0.068
Vital signs at shock recognition
Systolic blood pressure, mmHg89.4 ± 23.189.1 ± 22.390.4 ± 26.10.384
Diastolic blood pressure, mmHg54.3 ± 16.053.7 ± 14.956.4 ± 19.60.016
Pulse rate, beats/min105.8 ± 23.6104.2 ± 23.0112.2 ± 25.0<0.001
Infection focus
Pneumonia560 (31.6)384 (27.3)176 (48.1)<0.001
Urinary tract infection446 (25.2)376 (26.7)70 (19.1)0.001
Hepatobiliary and pancreas infection356 (20.1)296 (21.1)60 (16.4)0.048
Gastrointestinal infection303 (17.1)230 (16.4)73 (19.9)0.104
Laboratory findings
White blood cell count (×103/μL)10.2 [5.1–16.6]10.2 [5.3–16.5]9.8 [4.2–17.0]0.342
Hemoglobin, g/dL11.0 ± 2.511.1 ± 2.410.7 ± 2.80.003
Creatinine, mg/dL1.3 [0.9–2.2]1.3 [0.9–2.0]1.6 [1.0–2.6]<0.001
Blood urea nitrogen, mg/dL26.6 [18.0–40.4]25.5 [17.0–37.0]33.0 [21.7–49.0]<0.001
Aspartate transaminase, IU/L39.0 [24.0–82.0]38.0 [24.0–76.0]44.5 [27.0–105.0]0.001
Alanine transaminase, IU/L25.0 [14.0–54.0]26.0 [15.0–52.0]25.0 [14.0–58.3]0.825
Initial lactate level, mmol/L3.3 [1.9–5.4]3.0 [1.8–4.9]4.9 [2.7–8.3]<0.001
C-reactive protein, mg/dL12.3 [4.6–21.8]11.9 [4.3–21.0]14.7 [5.8–25.1]0.003
Procalcitonin, ng/mL6.8 [1.1–27.6]6.4 [1.0–26.8]8.2 [1.1–30.7]0.508
Severity score
Maximum SOFA8.0 [5.0–11.0]7.0 [5.0–10.0]10.0 [8.0–13.0]<0.001
APACHE-II score19.0 [14.0–26.0]18.0 [13.0–24.0]24.0 [18.0–34.0]<0.001

Values were expressed as means ± standard deviation, medians [interquartile range], or numbers (%) Abbreviations: SOFA, Sequential Organ Failure Assessment; APACHE, Acute Physiology and Chronic Health Evaluation.

Baseline and clinical characteristics of the study population grouped into survivors and non-survivors. Values were expressed as means ± standard deviation, medians [interquartile range], or numbers (%) Abbreviations: SOFA, Sequential Organ Failure Assessment; APACHE, Acute Physiology and Chronic Health Evaluation. Serum creatinine, blood urea nitrogen, aspartate transaminase, and initial lactate levels were significantly higher in the non-survivors (1.3 [0.9–2.0] vs. 1.6 [1.0–2.6], p < 0.001; 25.5 [17.0–37.0] vs. 33.0 [21.7–49.0], p < 0.001; 38.0 [24.0–76.0] vs. 44.5 [27.0–105.0], p = 0.001; 3.0 [1.8–4.9] vs. 4.9 [2.7–8.3], p < 0.001; respectively). However white blood cell count was not different (10.2 [5.3–16.5] vs. 9.8 [4.2–17.0], p = 0.342; Table 1). The initial PCT level also did not differ significantly (odds ratios (OR) 0.999 [95% confidence intervals (CI) 0.997–1.001]); however, initial CRP level was significantly higher in the non-survivors (OR 1.013 [95% CI 1.004–1.022]). Although in univariate logistic regression, CRP increased the 28-day mortality rate it was not an independent predictor of 28-day mortality in multivariate logistic regression analysis (Table 2). The optimal cut-off values of CRP and PCT in receiver operating characteristic (ROC) curve were 14 mg/dL and 17 ng/dL, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of CRP were 52.5%, 56.4%, 23.9%, and 82.0%, respectively, and those of PCT were 39.1%, 65.7%, 22.8%, and 80.5, respectively.
Table 2

Univariate and multivariate analysis for 28-day mortality.

CharacteristicsUnivariate OR [95% CI]Multivariate OR [95% CI]p-value
Age, years1.019 [1.010–1.028]1.014 [1.003–1.025]0.009
Chronic lung disease1.851 [1.275–2.687]
Pulse rate, beats/min1.014 1.009–1.019]
Pneumonia2.465 [1.947–3.122]2.113 [1.609–2.775]<0.001
Urinary tract infection0.648 [0.487–0.862]
Maximum SOFA1.242 [1.201–1.284]1.163 [1.109–1.220]<0.001
APACHE-II1.089 [1.074–1.103]1.025 [1.006–1.044]0.008
Creatinine, mg/dL1.150 [1.072–1.234]0.876 [0.777–0.988]0.031
Blood urea nitrogen, mg/dL1.016 [1.011–1.021]
Aspartate transaminase, IU/L1.000 [1.000–1.001]
Initial lactate level, mmol/L1.211 [1.169–1.254]1.163 [1.119–1.208]<0.001
C-reactive protein, mg/dL1.013 [1.004–1.022]
Procalcitonin, ng/mL0.999 [0.997–1.001]

Logistic regression analysis with backward elimination method.

Abbreviations: OR, odds ratio; CI, confidence interval; SOFA, Sequential Organ Failure Assessment; APACHE, Acute Physiology and Chronic Health Evaluation.

Univariate and multivariate analysis for 28-day mortality. Logistic regression analysis with backward elimination method. Abbreviations: OR, odds ratio; CI, confidence interval; SOFA, Sequential Organ Failure Assessment; APACHE, Acute Physiology and Chronic Health Evaluation. The combination matrix of CRP and PCT was compared to determine the 28-day mortality of each group (Fig. 2). The OR of both CRP and PCT elevated was 1.552 (95% CI 1.184–2.035), and the mortality rate was 26.9%. The 28-day mortality of both CRP and PCT elevated was significantly higher than that of only PCT elevated (17.8%) and both CRP and PCT not elevated (18.1%). However, the 28-day mortality of patients with only CRP elevated was 21.5% which was not significantly different from those with both CRP and PCT elevated (p = 0.079) (Fig. 2, Table 3). Nevertheless, in the multivariate logistic regression analysis, both CRP and PCT elevated was not an independent predictor of 28-day mortality.
Figure 2

Mortality of procalcitonin (PCT), C-reactive protein (CRP), and their combinations. Optimal cut off of CRP elevation was defined as ≥14 mg/dL and PCT elevation was defined as ≥17 ng/mL. Overall 28-day mortality was 20.7%. The mortality rates of both CRP and PCT not elevated, only CRP elevated, only PCT elevated, and both CRP and PCT elevated were 18.1%, 21.5%, 17.8%, and 26.9%, respectively. The mortality of both CRP and PCT elevated was significantly higher than for both not elevated and only PCT elevated.

Table 3

Baseline and clinical characteristics of the study population using optimal cut-off values for C-reactive protein and procalcitonin.

CharacteristicsBoth CRP and PCT not elevated (n = 691)Only CRP elevateda (n = 455)Only PCT elevatedb (n = 276)Both CRP and PCT elevated (n = 350)p-value
Age, years66.9 ± 13.968.9 ± 13.067.8 ± 13.966.7 ± 13.70.054
Male415 (60.1)265 (58.2)180 (65.2)185 (52.9)0.016
Past medical history
Hypertension247 (35.7)194 (42.6)116 (42.0)166 (47.4)0.002
Diabetes202 (29.2)119 (26.2)89 (32.2)121 (34.6)0.056
Coronary artery disease105 (15.2)53 (11.6)33 (12.0)35 (10.0)0.081
Stroke87 (12.6)56 (12.3)26 (9.4)42 (12.0)0.571
Chronic pulmonary disease57 (8.2)45 (9.9)16 (5.8)26 (7.4)0.246
Metastatic cancer162 (23.4)119 (26.2)68 (24.6)85 (24.3)0.777
Vital signs at shock recognition
Systolic blood pressure, mmHg91.8 ± 24.092.3 ± 24.183.0 ± 17.585.7 ± 22.6<0.001
Diastolic blood pressure, mmHg54.7 ± 15.955.5 ± 16.951.7 ± 12.053.9 ± 17.60.016
Pulse rate, beats/min103.6 ± 23.7106.9 ± 23.0105.0 ± 22.3109.5 ± 24.10.001
Infection focus
Pneumonia223 (32.3)183 (40.2)54 (19.6)100 (28.6)<0.001
Urinary tract infection142 (20.5)103 (22.6)85 (30.8)116 (33.1)<0.001
Hepatobiliary and pancreas infection133 (19.2)74 (16.3)76 (27.5)73 (20.9)0.003
Gastrointestinal infection136 (19.7)69 (15.2)46 (16.7)52 (14.9)0.126
Laboratory findings
White blood cell count (×103/μL)9.6 [5.1–15.3]11.6 [5.7–17.9]9.5 [4.5–17.0]10.5 [4.4–17.8]0.058
Hemoglobin, g/dL11.1 ± 2.510.7 ± 2.411.4 ± 2.711.2 ± 2.60.001
Creatinine, mg/dL1.1 [0.8–1.6]1.2 [0.9–2.0]1.7 [1.2–2.5]2.1 [1.4–2.9]<0.001
Blood urea nitrogen, mg/dL21.2 [15.0–31.0]26.0 [18.7–39.0]29.0 [20.8–40.3]38.0 [28.0–51.9]<0.001
Aspartate transaminase, IU/L35.0 [23.0–69.3]35.0 [23.0–60.0]58.0 [28.0–148.0]45.0 [29.0–93.3]<0.001
Alanine transaminase, IU/L23.0 [14.0–49.0]23.0 [13.0–43.0]35.5 [16.0–89.8]29.0 [16.0–59.0]<0.001
Initial lactate level, mmol/L2.9 [1.7–5.0]2.8 [1.7–4.7]4.0 [2.4–6.5]4.3 [2.7–6.4]<0.001
CRP, mg/dL5.1 [1.2–9.4]22.0 [17.5–29.3]5.5 [0.7–9.9]25.0 [18.8–30.3]<0.001
PCT, ng/mL1.2 [0.4–5.4]3.3 [1.0–8.1]41.8 [24.5–66.7]46.0 [25.6–94.9]<0.001
Severity score
Maximum SOFA7.0 [5.0–10.0]7.0 [5.0–10.0]9.0 [6.0–12.0]10.0 [7.0–12.0]<0.001
APACHE-II score18.0 [12.0–24.0]19.0 [14.0–26.0]19.0 [13.3–26.0]22.0 [15.0–28.0]<0.001
28-day mortality125 (18.1)98 (21.5)49 (17.8)94 (26.9)0.006

Values were expressed as means ± standard deviation, medians [interquartile range], or numbers (%).

aCRP elevation ≥14.0 mg/dL.

bPCT elevation ≥17.0 ng/mL Abbreviations: CRP, C-reactive protein; PCT, procalcitonin; SOFA, Sequential Organ Failure Assessment; APACHE, Acute Physiology and Chronic Health Evaluation.

Mortality of procalcitonin (PCT), C-reactive protein (CRP), and their combinations. Optimal cut off of CRP elevation was defined as ≥14 mg/dL and PCT elevation was defined as ≥17 ng/mL. Overall 28-day mortality was 20.7%. The mortality rates of both CRP and PCT not elevated, only CRP elevated, only PCT elevated, and both CRP and PCT elevated were 18.1%, 21.5%, 17.8%, and 26.9%, respectively. The mortality of both CRP and PCT elevated was significantly higher than for both not elevated and only PCT elevated. Baseline and clinical characteristics of the study population using optimal cut-off values for C-reactive protein and procalcitonin. Values were expressed as means ± standard deviation, medians [interquartile range], or numbers (%). aCRP elevation ≥14.0 mg/dL. bPCT elevation ≥17.0 ng/mL Abbreviations: CRP, C-reactive protein; PCT, procalcitonin; SOFA, Sequential Organ Failure Assessment; APACHE, Acute Physiology and Chronic Health Evaluation.

Discussion

In our study, the initial levels of CRP and PCT did not show significant association with 28-day mortality. When we compared the combination matrix of CRP and PCT using the optimal cut-off values, the mortality rate of patients with elevated CRP and PCT was significantly higher than that of patients with non-elevated CRP and PCT or only elevated PCT. However, both CRP and PCT elevated was not an independent predictor of 28-day mortality. Sepsis is an infectious condition associated with organ dysfunction; therefore, a diagnosis of infection is crucial. Most sepsis-related infection symptoms and variables such as fever and tachycardia are not necessarily sepsis-specific. Therefore, in order to increase the accuracy of sepsis diagnosis, physicians should survey for other indicators such as biomarkers (e.g., CRP, PCT), imaging data (e.g., X-ray), and organ dysfunction[9]. A previous study showed that patients with mixed bacterial pneumonia had significantly higher serum levels of CRP and PCT than in those with viral infection alone[10]. Another study in neonatal sepsis patients also reported that both CRP and PCT showed relatively good performance in discriminating proven sepsis from controls, and their combination increased the accuracy of neonatal sepsis diagnoses[11]. However, the primary outcome of both previous studies was diagnosis of infection and sepsis. The early prognostic value of CRP and PCT in septic shock cases that received protocol-driven resuscitation bundle therapy at emergency departments (EDs) remains unclear. Our current data show that CRP, PCT, and their combination have limited ability in predicting mortality in septic shock cases. CRP was associated with 28-day mortality in univariate models only and not in the multivariate model. We speculate that initial CRP and PCT might be measured too early to reflect disease severity. However, that initial levels of CRP and PCT were obtained before resuscitation, specifically before antibiotics administration which can influence CRP and PCT levels, could be considered strength of this study. PCT induction occurs at approximately 2–4 hours after the onset of sepsis, and peaks at 24–48 hours[6]. Thus, because CRP elevation is also expected to occur 24–48 hours after the initial inflammatory response[4], initial CRP and PCT may not be considered to be useful markers in patients with acute and critical conditions. A systemic review and meta-analysis study showed that PCT levels were significantly different between surviving and non-surviving sepsis patients[12]. Among 25 analyzed studies, only four were conducted at EDs. Because most studies were conducted at intensive care units (ICUs), the measured time of PCT is doubtful. Additionally, the heterogeneity among the studies was very high. The mortality reported in the studies ranged from 13% to 69%, and the severity of infection ranged from sepsis to septic shock. Another recent study also reported that the levels of PCT and CRP at admission showed association with mortality. However, their obtained sample time was the morning after admission, and mortality was excessively high, sepsis was 43.33%, and septic shock was 75%[13]. In contrast, a recent study performed in pediatrics reported that median CRP and PCT were not associated with mortality; overall mortality was 33.3%, and samples were obtained on the first day of ICU admission[14]. Because of these varying results, other studies using biomarkers have been conducted to predict prognosis. Huang et al. studied PCT clearance. In their study, although PCT levels on days 1, 3, and 5 were not associated with prognosis, PCT clearance rates at days 3 and 5 were significantly higher in the survivor group[15]. Another study also evaluated the PCT trend and reported that a decrease in the initial PCT level of more than 80% on day 4, rather than initial PCT level, was predictive for survival[16]. Hahn et al. demonstrated a PCT to CRP ratio to detect late onset neonatal sepsis. In their study, the area under the curve of PCT/CRP was 0.73 for distinguishing between proven and suspected sepsis[11]. However, this study did not report the prognostic value of the PCT/CRP ratio. In our study, we evaluated the combination of CRP and PCT for their prognostic power in predicting mortality. We found that patients who had elevation of both CRP and PCT had significantly higher mortality rate than did the other groups, except those who had elevation of CRP only. Because CRP is associated with immunity[4] and reflects an inflammatory condition[5] which is associated with the host defense mechanism, it might more directly influence mortality, whereas PCT is a very sensitive biomarker of bacterial infection[6], Moreover, antibiotics administration time could confound the spread of bacterial infection therefore, it might confound the initial PCT value. If so, the PCT variation trend, rather than initial value, may be more associated with prognosis as shown previously[16]. In this study, because of the nature of a prospective multi-center observational study, we were unable to determine a trend for PCT. In contrast, previous studies reported that several days were needed for the CRP levels to peak, whereas PCT levels peaked at 24–48 hours after sepsis, despite induction after approximately 2–4 hours[6]. Therefore, initial CRP and PCT levels in this study might be underestimated. As is well known, PCT and CRP are suitable markers for the diagnosis of sepsis, and they have been used for the early detection of infection and guiding of antibiotics therapy. However, in this study we were unable to confirm a limited ability to predict mortality in septic shock patients, specifically considering initial CRP and PCT levels. Although infection is a cause of sepsis, the degree of shock or organ failure as a result of septic shock may be more suitable for predicting mortality. Future research will most likely focus on the development of new biomarkers or combinations of markers with clinical signs for predicting prognosis of early septic shock and guiding therapy. This study had some limitations. Due to its prospective observational design, we were unable to obtain additional laboratory data such as repeated CRP and PCT levels. Analyzing the biomarkers several days after sepsis development may show an association with mortality. However, in the clinical setting, because factors are required which can predict mortality early-on, biomarkers obtained several days after diagnosis are not helpful. Moreover, during septic shock management various factors influence mortality; therefore, more valuable results may be obtained if possible risk factors can be controlled. CRP was more predictive than PCT, and elevation of both CRP and PCT was associated with the highest mortality rate among all combinations. However, CRP and PCT alone as well as their combination were not independent predictors of 28-day mortality in septic shock cases. Further studies are needed to identify the biomarkers for early prognostication in patients with septic shock.

Methods

Setting and study population

This was a multicenter prospective, observational, registry-based study using KoSS septic shock registry data. The KoSS, a multicenter clinical research consortium for septic shock, was organized in 2013, and KoSS investigators have been prospectively collecting data from septic shock patients at the EDs of 10 teaching hospitals throughout South Korea from October 2015. The institutional review board of Asan Medical Center [2015-1253] and each institution (Korea University Anam Hospital [HRPC2016-184], Samsung Medical Center [SMC2015-09-057], Yonsei University College of Medicine Severance Hospital [4-2015-0929], Gangnam Severance Hospital [3-2015-0227], Seoul National University Bundang Hospital [B-1409/266-401], Seoul National University College of Medicine [J-1408-003-599], Seoul National University Boramae Medical Center [16-2014-36], Hallym University College of Medicine Gangnam Secred Heart Hospital [2015-11-142], Korea University Guro Hospital [KUGH15358-001], Hanyang University Hospital [HYUH2015-11-013-007]) approved the study protocol, and informed consent was obtained before data collection. All experiments were performed in accordance with relevant guidelines and regulations[17]. Adult (≥18 years) septic shock patients, defined by suspected or confirmed infection and evidence of refractory hypotension or hypoperfusion, were enrolled in the registry[18-20]. Refractory hypotension was defined as persistent hypotension which was systolic blood pressure (SBP) <90 mm Hg, a mean arterial pressure <70 mm Hg, or an SBP decrease of >40 mm Hg after adequate intravenous fluid challenge (20–30 mL/kg or at least 1 L or more of crystalloid solution administered over 30 minutes), or as the need for vasopressors after fluid resuscitation[21]. Hypoperfusion was defined as a serum lactate concentration of ≥4 mmol/L[22]. Patients who signed a “Do Not Attempt Resuscitation” order, met the inclusion criteria six hours after ED arrival, were transferred from other hospitals without meeting the inclusion criteria upon ED arrival, or were directly transferred from an ED to other hospitals were not enrolled in in the KoSS septic shock registry. The case report form, standard definitions of 200 variables including clinical characteristics, therapeutic interventions, and outcomes of patients with septic shock, and an investigator manual were developed based on a literature review and consensus by the study investigators. Data were collected via a standardized registry form and entered into a web-based electronic database registry. Outliers or incorrect values are primarily filtered by this data entry system. Additionally, the principal investigator of each site has a designated local research coordinator who is responsible for ensuring the accuracy of data and verifying records. The quality management committee (QMC), which consists of emergency physicians, local research coordinators, and investigators in each ED, monitors and reviews data quality regularly. The QMC gives feedback to each research coordinator and investigator of the results of the quality management process through the query function in the system or directly by phone to clarify data[17].

Data collection

All KoSS septic shock registry data were collected from November 2015 to December 2017. Demographic and clinical data, including age, gender, previous medical history, initial vital signs, severity, and laboratory values on admission, and interventions were retrieved from the septic shock registry. Maximum SOFA and APACHE-II scores were evaluated using the worst parameters within 24 hours after ED arrival[17,23]. All laboratory parameters, including CRP and PCT levels, were measured at the ED upon initial septic shock recognition. We determined the cut-off values of CRP and PCT to predict 28-day mortality using the Youden Index and divided patients into subgroups as follows: both CRP and PCT not elevated, only CRP or PCT elevated, and both CRP and PCT elevated. The primary clinical outcome of this study was the 28-day mortality rate. We evaluated the predictive ability of CRP, PCT, and their combination for 28-day mortality rates.

Statistical analyses

Continuous variables were expressed as means ± standard deviation or medians with the interquartile range if the assumption of a normal distribution was violated. Categorical variables were expressed as numbers and percentages. To analyze the baseline characteristics and laboratory examinations in survivor and non-survivor groups, Student’s t-test was used to compare the means of normally distributed continuous variables; the Mann-Whitney U test was used to compare non-continuous variables. The Chi-squared or Fisher’s exact test was used to compare categorical variables[17]. The optimal cut-off value of CRP was predicted by the Youden Index using ROC curve analysis in a univariate model. Multivariate analyses were performed using a logistic regression with a backward elimination method to evaluate the association between the clinical factors, including laboratory data and 28-day mortality. The results of the multivariate logistic regression were reported as OR and 95% CI. We conducted an Analysis of Variance and Kruskal-Wallis analysis to evaluate differences between subgroup analyses. All tests in this study were two-sided, and a p-value < 0.01 was considered to be statistically significant. All statistical analyses were performed using SPSS for Windows version 20.0 (SPSS Inc., Chicago, IL, USA).
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Journal:  Intensive Care Med       Date:  1996-07       Impact factor: 17.440

Review 3.  2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference.

Authors:  Mitchell M Levy; Mitchell P Fink; John C Marshall; Edward Abraham; Derek Angus; Deborah Cook; Jonathan Cohen; Steven M Opal; Jean-Louis Vincent; Graham Ramsay
Journal:  Crit Care Med       Date:  2003-04       Impact factor: 7.598

4.  Prediction of microbial infection and mortality in medical patients with fever: plasma procalcitonin, neutrophilic elastase-alpha1-antitrypsin, and lactoferrin compared with clinical variables.

Authors:  A W Bossink; A B Groeneveld; L G Thijs
Journal:  Clin Infect Dis       Date:  1999-08       Impact factor: 9.079

5.  Trial of early, goal-directed resuscitation for septic shock.

Authors:  Paul R Mouncey; Tiffany M Osborn; G Sarah Power; David A Harrison; M Zia Sadique; Richard D Grieve; Rahi Jahan; Sheila E Harvey; Derek Bell; Julian F Bion; Timothy J Coats; Mervyn Singer; J Duncan Young; Kathryn M Rowan
Journal:  N Engl J Med       Date:  2015-03-17       Impact factor: 91.245

6.  Serum Procalcitonin and Procalcitonin Clearance as a Prognostic Biomarker in Patients with Severe Sepsis and Septic Shock.

Authors:  Min-Yi Huang; Chun-Yu Chen; Ju-Huei Chien; Kun-Hsi Wu; Yu-Jun Chang; Kang-Hsi Wu; Han-Ping Wu
Journal:  Biomed Res Int       Date:  2016-03-20       Impact factor: 3.411

7.  Role of procalcitonin and C-reactive protein in differentiation of mixed bacterial infection from 2009 H1N1 viral pneumonia.

Authors:  Shin Ahn; Won Young Kim; Sung-Han Kim; SangBum Hong; Chae-Man Lim; YounSuck Koh; Kyung Soo Lim; Won Kim
Journal:  Influenza Other Respir Viruses       Date:  2011-03-30       Impact factor: 4.380

8.  Relationship of Serum Procalcitonin, C-reactive Protein, and Lactic Acid to Organ Failure and Outcome in Critically Ill Pediatric Population.

Authors:  Imran Siddiqui; Lena Jafri; Qalab Abbas; Ahmed Raheem; Anwar Ul Haque
Journal:  Indian J Crit Care Med       Date:  2018-02

9.  Serial Procalcitonin Predicts Mortality in Severe Sepsis Patients: Results From the Multicenter Procalcitonin MOnitoring SEpsis (MOSES) Study.

Authors:  Philipp Schuetz; Robert Birkhahn; Robert Sherwin; Alan E Jones; Adam Singer; Jeffrey A Kline; Michael S Runyon; Wesley H Self; D Mark Courtney; Richard M Nowak; David F Gaieski; Stefan Ebmeyer; Sascha Johannes; Jan C Wiemer; Andrej Schwabe; Nathan I Shapiro
Journal:  Crit Care Med       Date:  2017-05       Impact factor: 7.598

10.  Clinical significance of the detection of procalcitonin and C-reactive protein in the intensive care unit.

Authors:  Qinhao Li; Xiaona Gong
Journal:  Exp Ther Med       Date:  2018-03-15       Impact factor: 2.447

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  18 in total

1.  Clinical utility of procalcitonin in bacterial infections in patients undergoing hematopoietic stem cell transplantation.

Authors:  Amit Bansal; Preethi Jeyaraman; S K Gupta; Nitin Dayal; Rahul Naithani
Journal:  Am J Blood Res       Date:  2020-12-15

2.  Prognostic factors for late death in septic shock survivors: a multi-center, prospective, registry-based observational study.

Authors:  Sang-Min Kim; Seung Mok Ryoo; Tae Gun Shin; Yoo Seok Park; You Hwan Jo; Tae Ho Lim; Sung Phil Chung; Sung-Hyuk Choi; Gil Joon Suh; Won Young Kim
Journal:  Intern Emerg Med       Date:  2021-10-03       Impact factor: 3.397

3.  Thromboprophylaxis and clinical outcomes in moderate COVID-19 patients: A comparative study.

Authors:  Asmaa S Mohamed; Hosam M Ahmad; Alyaa S A Abdul-Raheem; Fatma M M Kamel; Ali Khames; Ahmed F Mady
Journal:  Res Social Adm Pharm       Date:  2022-07-16

4.  Cytokines as Potential Biomarkers for Differential Diagnosis of Sepsis and Other Non-Septic Disease Conditions.

Authors:  Augustina Frimpong; Ewurama D A Owusu; Jones Amo Amponsah; Elizabeth Obeng-Aboagye; William van der Puije; Abena Fremaah Frempong; Kwadwo Asamoah Kusi; Michael Fokuo Ofori
Journal:  Front Cell Infect Microbiol       Date:  2022-06-23       Impact factor: 6.073

Review 5.  Role of Procalcitonin in the Prognosis of Mortality in Patients Admitted to the Intensive Care Unit: A Review Study.

Authors:  Mahdiye Jafari; Farzaneh Fazeli; Majid Sezavar; Sara Khashkhashi; Benyamin Fazli; Nooshin Abdollahpour; Alireza Sedaghat
Journal:  Tanaffos       Date:  2021-04

Review 6.  Tryptophanyl-tRNA Synthetase as a Potential Therapeutic Target.

Authors:  Young Ha Ahn; Se-Chan Oh; Shengtao Zhou; Tae-Don Kim
Journal:  Int J Mol Sci       Date:  2021-04-26       Impact factor: 5.923

7.  C-reactive protein, procalcitonin, D-dimer, and ferritin in severe coronavirus disease-2019: a meta-analysis.

Authors:  Ian Huang; Raymond Pranata; Michael Anthonius Lim; Amaylia Oehadian; Bachti Alisjahbana
Journal:  Ther Adv Respir Dis       Date:  2020 Jan-Dec       Impact factor: 4.031

8.  Glycoproteoform Profiles of Individual Patients' Plasma Alpha-1-Antichymotrypsin are Unique and Extensively Remodeled Following a Septic Episode.

Authors:  Tomislav Čaval; Yu-Hsien Lin; Meri Varkila; Karli R Reiding; Marc J M Bonten; Olaf L Cremer; Vojtech Franc; Albert J R Heck
Journal:  Front Immunol       Date:  2021-01-14       Impact factor: 7.561

9.  The predictive and diagnostic accuracy of long pentraxin-3 in COVID-19 pneumonia

Authors:  Ahmed Bilal Genç; Selçuk Yaylacı; Hamad Dheir; Ahmed Cihad Genç; Kubilay İşsever; Deniz Çekiç; Havva Kocayiğit; Erdem Çokluk; Alper Karacan; Mehmet Ramazan Şekeroğlu; Hande Toptan Çakar; Ertuğrul Güçlü
Journal:  Turk J Med Sci       Date:  2021-04-30       Impact factor: 0.973

10.  Machine Learning Identifies Complicated Sepsis Course and Subsequent Mortality Based on 20 Genes in Peripheral Blood Immune Cells at 24 H Post-ICU Admission.

Authors:  Shayantan Banerjee; Akram Mohammed; Hector R Wong; Nades Palaniyar; Rishikesan Kamaleswaran
Journal:  Front Immunol       Date:  2021-02-22       Impact factor: 7.561

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