25 January 2023: Clinical Research
Changes in Heparin-Binding Protein, Procalcitonin, and C-Reactive Protein Within the First 72 Hours Predict 28-Day Mortality in Patients Admitted to the Intensive Care Unit with Septic ShockHui Xue1ABCDEFG, Feng Yu1AFG*
Med Sci Monit 2023; 29:e938538
BACKGROUND: This study aimed to evaluate the possible associations of heparin-binding protein (HBP), procalcitonin (PCT), and C-reactive protein (CRP) levels with 28-day mortality in septic shock patients admitted to Intensive Care Units (ICUs).
MATERIAL AND METHODS: Blood samples were taken at ICU admission and measured again 72 h later to calculate changes in HBP (ΔHBP), changes in PCT (ΔPCT), changes in CRP (ΔCRP), and changes in Sequential Organ Failure Assessment (DSOFA) relative to baseline.
RESULTS: Variables included in the univariable logistic regression model for survival were age, Acute Physiology and Chronic Health Evaluation (APACHE) II scores, decreasing ΔSOFA, decreasing DHBP, decreasing ΔPCT, and decreasing ΔCRP. Survival was directly related to decreasing ΔHBP with odds ratio (OR)=9.95 (95% confidence interval [CI] 4.63 to 21.35; P<0.001), decreasing ΔPCT with OR=7.85 (3.74 to 16.49; P<0.001), decreasing ΔCRP with OR=5.83 (2.84 to 11.97; P<0.001), decreasing ΔSOFA with OR=1.93 (1.00 to 3.75; P=0.051) and APACHE II score with OR=1.93 (1.14 to 1.68; P=0.001). In a multivariable logistic regression model for survival, only decreasing DHBP with OR=7.18 (2.91 to 17.69; P<0.001), decreasing ΔPCT with OR=5.17 (2.12 to 12.56; P<0.001), and decreasing ΔCRP with OR=4.33 (1.77 to 10.61; P=0.001) remained significant.
CONCLUSIONS: Measuring changes in HBP, PCT, and CRP within 72 h of admission may aid in predicting 28-day mortality for patients with septic shock in ICUs.
Keywords: Antimicrobial Cationic Peptides, biomarkers, procalcitonin, Sepsis, Shock, Septic
Septicemia is defined as an aberrant immune reaction to an infection that results in life-threatening organ dysfunction, based on SEPSIS-3 consensus criteria . Septic shock refers to cases of sepsis characterized by abnormalities in the circulatory, molecular, and metabolic systems. Approximately 5.3 million people have sepsis each year, making it a severe public health problem . Guidelines for evidence-based management have emphasized serum biological markers as indicators of the context of sepsis, as well as scoring systems based on risk factors associated with patient mortality [3,4]. Among patients with sepsis, reliable predictive biomarkers and scoring systems can aid clinicians in making rapid yet appropriate treatment decisions. Indeed, several studies have emphasized the value of conventional biological markers for detecting sepsis and its outcomes, like procalcitonin (PCT) or C-reactive protein (CRP) [5–7]. Although elevated serum PCT levels are associated with bacterial infection and sepsis, a meta-analysis of 18 studies found that PCT did not distinguish between sepsis and non-septic systemic inflammation [8,9]. CRP, an acute-phase reactive protein, is the most commonly used clinical biomarker, and its level in the plasma of healthy individuals is less than 1 mg/L . Not only do bacterial infections and sepsis lead to increased levels of CRP, but so does injury . Several studies have shown that changes in biochemical markers, and not only absolute values, can predict therapeutic response and survival following the diagnosis of sepsis [12,13].
CAP37, also known as heparin-binding protein (HBP), is produced within the vesicles and azurophil granules in human polymorphonuclear leukocytes, and neutrophils rapidly secrete it under bacterial stimulation . The release of HBP causes vessel leakage or swelling, which is commonly dysregulated in cases of septic shock due to its potent chemoattractant capacity for the monocytes and macrophages [15,16]. As a result of its versatility, HBP may be able to serve as an inducible biological marker in the case of septic shock [17,18]. Although effective control of sepsis may lead to rapid decreases in HBP levels, whether kinetics in HBP can provide greater insight into treatment responses and outcomes remains unclear.
Scores such as SOFA and APACHE II are commonly used in ICUs to assess patient disease severity and predict outcomes . The APACHE II score is calculated based on the worst values within the first 24 h of ICU admission . According to some studies, organ failure is associated with a high mortality rate, and dynamic assessment of organ dysfunction in critically ill patients after ICU admission can be used to predict the outcome . Therefore, this prospective, single-center study of 146 patients admitted to the intensive care unit with septic shock conducted between July 2020 and June 2022, aimed to evaluate the prognostic value of kinetics of heparin-binding protein, procalcitonin, C-reactive protein levels, SOFA scores, and APACHE II scores as factors associated with in-hospital mortality.
Material and Methods
Anhui Medical University First Affiliated Hospital’s Emergency Intensive Care Unit (EICU) was the site of this prospective study, which took place between July 2020 and June 2022. Anhui Medical University’s First Affiliated Hospital’s ethics review committee approved this study (No. PJ2022-12-13), and all authorized delegates of the included patients signed consent forms.
We included patients who met the third version of the diagnostic criteria for septic shock as defined by the International Guidelines . We excluded patients with these criteria: (1) age <18 years, (2) incomplete clinical records, and (3) ICU stay <72 h. We excluded some patients with malignancies as well as hematological diseases, autoimmune diseases, immune deficiency diseases, and patients who received a transplant. Our institution’s standard management protocol is derived from the Surviving Sepsis Campaign (SSC) guidelines, and this was followed for all enrolled patients .
As part of our ICU admission process, patients received a preliminary evaluation that included the gathering of data on age, sex, underlying disease, type of infection, and comorbidities. APACHE II scores were calculated within the first 24 h of ICU admission, and SOFA scores were calculated after admission and again at 72 h. Blood samples were taken after admission to the ICU and measured again 72 h later. Blood samples was used to measure levels of serum HBP, serum PCT, serum CRP, white blood cells (WBC), platelets, and biochemistry, and for arterial blood gas analysis. Before antibiotic use, blood cultures and drug sensitivity tests (bilateral and double sets) were done. The primary endpoint was 28 days of ICU admission. Non-survivors were identified as those who died before 28 days, while survivors were identified as those who had been discharged from the ICU before 28 days. ICU stays were measured as the time spent in the ICU prior to transfer or death.
The lower reference limit for serum HBP concentration was 5.9 ng/ml, as measured via an immunofluorescence assay (Joinstar Biomedical Technology Co., LTD, Hangzhou, China). PCT levels were detected using a semi-quantitative solid-phase immunoassay (Brahms Diagnostica GmbH, Berlin, Germany) (limit of detection, 0.5 ng/ml). CRP concentration was measured using latex immunoturbidimetry (Lifotronic Technology Co., LTD, Shenzhen, China), and the normal reference range was 0–10 mg/L. Kinetics in HBP, PCT, and CRP (ΔHBP, ΔPCT, and ΔCRP, respectively) were calculated by subtracting baseline levels from 72-h levels . Therefore, ΔHBP=HBP72H–HBP0H, ΔPCT=PCT72H–PCT0H, ΔCRP=CRP72H–CRP0H, and ΔSOFA=SOFA72H–SOFA0H. Δ >0 indicates an increasing trend, while Δ ≤0 indicates a decreasing trend or no change .
All experimental data were analyzed using SPSS 26.0 v. (IBM, Armonk, N.Y., USA). For normally distributed continuous variables, including SOFA scores and APACHE II scores, the results are presented as mean±standard deviation (mean±S.D). We used t tests to compare the 2 groups. Non-normally distributed variables, including age, ICU stay, WBC, serum HBP, serum PCT, serum CRP, and changes in each marker, are expressed using medians and interquartile ranges (IQRs). The Mann-Whitney U test, was used for comparisons between the 2 groups. Percentages are reported for qualitative variables such as sex, comorbidities, and type of infection. These data were compared between groups using chi-square testing. Statistical significance was defined as a P value <0.05 (95% confidence interval [CI]). The effect of clinical characteristics and important variables on prognosis was assessed using logistic regression. For the univariable model, we included biologically significant variables. For the multivariable model, variables with P<0.10 in univariable logistic regression were entered. Multivariable models were considered significant if they had P<0.05 .
We prospectively screened 247 patients with septic shock admitted to our ICU between July 2020 and June 2022. After eligibility evaluation, 146 patients finally participated in the study, of whom 82 (56%) and 64 (44%) were survivors and non-survivors, respectively. The reasons for the exclusion are shown in Figure 1. Thirty patients presented with immunodeficiency. Twenty-three patients with missing WBC values, leukopenia (WBC <3×109/L), or hyperleukocytosis (WBC >50×109/L) were excluded from the study. Other exclusions included 5 patients whose samples hemolyzed, 16 patients who had received heparin or albumin treatment before HBP measurements, 5 patients with incomplete PCT or CRP data, 5 patients aged <18 years, and 17 who died less than 72 h after enrollment. Therefore, 146 patients participated in the final study.
Table 1 summarizes the main baseline characteristics of the patients included in the study. A comparison was made between those who survived and those who did not survive regarding demographics, comorbidities, type of infection, blood tests, clinical scores, and ICU stay. Of the patients who were in septic shock, 43.8% died, and 65.7% of infections originated in the lungs. Bloodstream infection was diagnosed in approximately half of the included patients with septic shock (43.8%), and the rate of bloodstream infection was significantly higher in non-survivors than in survivors (53.1% vs 36.6%; P=0.046). APACHE II scores were markedly higher for non-survivors than for survivors (P<0.001), with other indicators not showing statistically significant differences.
THE EVOLUTION OF HBP LEVELS, PCT, AND CRP LEVELS AMONG SURVIVORS AND NON-SURVIVORS FOLLOWING SEPTIC SHOCK:
The kinetic data of HBP, PCT, and CRP between admission and the first 72 h of admission are shown in Figure 2. Non-survivors showed an increasing trend in HBP levels, which were significantly higher than the survivor group at 72 h of admission (Table 2, P<0.001). PCT levels increased in non-survivors but not in survivors. PCT levels can discriminate survivors from non-survivors on admission (Table 2, P<0.001) or at the first 72 h of admission (Table 2, P<0.001). CRP levels showed no difference between survivors and non-survivors on admission (Table 2, P=0.557) and at 72 h (Table 2, P=0.245).
COMPARISON ACCURACY OF BIOMARKERS AND CLINICAL SCORE:
In the univariable logistic regression model for survival, age, APACHE II score, decreasing ΔSOFA, decreasing ΔHBP, decreasing ΔPCT, and decreasing ΔCRP were the main variables. The results are shown in Table 3. Survival was directly related to decreasing ΔHBP, with an odds ratio (OR)=9.95 (95% confidence interval 4.63 to 21.35), P<0.001; decreasing ΔPCT with OR=7.85 (3.74 to 16.49), P<0.001; decreasing ΔCRP with OR=5.83 (2.84 to 11.97), P<0.001; decreasing ΔSOFA with OR=1.93 (1.00 to 3.75), P=0.051; APACHE II score with OR=1.39 (1.14 to 1.68), P=0.001. Age was not significant and was excluded from the multivariate analysis because P=0.1 was an inclusion condition.
A multivariable logistic regression model for survival was developed by screening the variables from the univariate analysis. Only decreasing ΔHBP with OR=7.18 (2.91 to 17.69), P<0.001, decreasing ΔPCT with OR=5.17 (2.12 to 12.56) P<0.001, and decreasing ΔCRP with OR=4.33 (1.77 to 10.61) P=0.001 remained significant (Table 3).
Our study demonstrated that patient prognosis, including treatment response and survival, were not always related to HBP, PCT, or CRP absolute values, but were closely linked to their kinetics. PCT levels clearly differentiated between survivors and non-survivors on admission to the ICU and the first 72 h after admission, while HBP just showed this difference in the first 72 h after admission. Decreasing values of HBP, decreasing values of PCT, and decreasing values of CRP were able to predict, respectively, a 7-fold, 5-fold, and 4-fold greater chance for patients with septic shock to survive.
CRP is often used clinically as a marker to support the diagnosis of sepsis . In our results, absolute CRP levels could not differentiate survivors from non-survivors on admission and the first 72 h of admission (Table 2, P=0.557 and 0.245, respectively). Previous studies have demonstrated that changes in CRP levels, but not absolute levels, can forecast death rates in patients with sepsis . CRP levels in ventilator-associated pneumonia patients varied significantly between day 1 and day 4. According to Seligman et al , these decreases in CRP levels were also associated with higher survival rates. A decrease in CRP by 25% or more from the previous day was shown by Yentis et al to be a good indicator of regression of sepsis, with a sensitivity of 97% and specificity of 88% . A decline in CRP prior to the clinical resolution of sepsis and was related to the severity of the disease. Hoeboer et al reported that rapid decreases in CRP were most predictive of the antibiotic response in seriously ill patients with fever . Our results agree with the results of Yentis et al in patients with sepsis; in our septic shock patients, the decrease of CRP levels was significantly predictive of survival, with OR=5.83 (Table 3, P<0.001) in the univariable, with OR=4.33 (Table 3, P<0.001) in the multivariable logistic regression.
In our results, PCT levels were significantly higher in non-survivors on admission (Table 2, P<0.001) and the first 72 h of admission (Table 2, P<0.001). PCT concentrations dramatically decreased among survivors within the first 72 h after ICU admission but only decreased very slightly or remained elevated in non-survivors. According to Guan et al , PCT levels above 10 ng/ml can predict survival if they decrease by more than 25% compared with the baseline value after 5 days. In a study involving 180 patients with sepsis, Charles et al determined that a more than 30% reduction in PCT from day 2 to day 3 can independently predict survival, reporting an odds ratio (OR) of 2.94 (1.22, 7.09) (P<0.05) . According to a prospective study of 144 sepsis patients admitted to ICUs, a PCT reduction of less than 15% in the first 72 h reliably predicted death, with an OR of 3.9 (1.6, 7.09; P<0.001) . Nevertheless, similar to the results of our analysis, the decrease in PCT levels was significantly predictive of survival, with OR=7.85 (Table 3, P<0.001) in the univariable analysis, with OR=5.17 (Table 3, P<0.001) in multivariable logistic regression analysis.
Our data suggest HBP clearance may also be a promising prognosis marker for 28-day mortality in patients with septic shock. HBP concentrations of 15 ng/ml were found by Linder et al to be a better indicator of a septic shock than PCT, CRP, or WBC (sensitivity 87.1%; specificity 95.1%). Additionally, 12 h prior to the onset of circulatory collapse, HBP levels were significantly higher . Another international, multicenter, prospective study highlighted HBP as the best indicator to predict organ failure (AUC=0.8) . HBP concentrations may have been predictive of the development of sepsis into septic shock in previous studies, but the importance of HBP clearance remains unclear. In the current study, HBP levels were significantly higher in non-survivors in the first 72 h of admission (Table 2, P<0.001). HBP concentrations dramatically decreased among survivors within the first 72 h after ICU admission but only slightly decreased or remained elevated in non-survivors. Furthermore, the decrease in HBP levels was significantly predictive of survival, with OR=9.95 (Table 3, P<0.001) in the univariable analysis, with OR=7.18 (Table 3, P<0.001) in the multivariable logistic regression analysis. Together, these results indicate that the kinetics of HBP concentrations within the first 72 h were strongly correlated with better survival following the diagnosis of sepsis. Thus, clinicians may wish to adjust the therapeutic regimen for patients exhibiting inadequate clearance of HBP.
In clinical practice, the SOFA score is a commonly used measure of multi-organ dysfunction syndrome, where high scores often indicate critical illness and poor outcomes . Vincent et al demonstrated that multiple-organ dysfunction and high SOFA scores for any organ were associated with increased mortality . They found that 44% of non-survivors, and only 20% of survivors (P<0.001), had significantly elevated SOFA scores in patients admitted to the ICU for at least 1 week. Our results with SOFA scores were similar to those of Vincent et al – decreasing SOFA scores were predictive of survival, with OR=1.93 (Table 3, P=0.051) in the univariable analysis, but not in the multivariable logistic regression analysis (Table 3, P=0.146).
This study had several limitations, including its small sample size. Thus, a prospective, multicenter, clinical study is required to confirm our findings. Moreover, data on HBP, PCT, CRP, and other parameters were collected at few time points and need to be tested and analyzed at more time points to reduce data bias. Further studies are needed to determine whether heparin or albumin treatment alters HBP measurements, as patients receiving such treatments were excluded from this study. Future studies may also need to investigate how antimicrobial therapy influences biomarker clearance and outcomes.
The present results demonstrate that changes in HBP, PCT, and CRP levels in the first 72 h after ICU admission were associated with the 28-day mortality rate of ICU patients with septic shock. In any of these marker values, a decrease is associated with survival.
FiguresFigure 1. Flow chart of inclusion and exclusion process. PCT – procalcitonin; CRP – C-reactive protein; HBP – heparin-binding protein; WBC – white blood cell counts; (GraphPad Software, San Diego, CA, USA). Figure 2. Kinetics of serum HBP, PCT, and CRP in survivors and non-survivors. The upper and lower edges of the box plot represent the 25th and 75th percentiles, respectively. The inner horizontal line represents the median and the whiskers represent the 10th and 90th percentiles. (A) Box plot represents kinetics of serum HBP (HBP0: HBP measurement at the time of admission; HBP1: HBP measurement at the first 72 h of admission). Comparing between groups, P=0.301 at the time of admission and P<0.001 at the first 72 h of admission for heparin-binding protein (HBP). (B) Box plot represents kinetics of serum PCT (PCT0: PCT measurement at the time of admission; PCT1: PCT measurement at the first 72 h of admission). P<0.001 at the time of admission and P<0.001 at the first 72 h of admission for procalcitonin (PCT). (C) Box plot represents kinetics of serum CRP (CRP0: CRP measurement at the time of admission; CRP1: CRP measurement at the first 72 h of admission). P=0.557 at the time of admission and P=0.245 in the first 72 h of admission for CRP. HBP – heparin-binding protein; PCT – procalcitonin; CRP – C-reactive protein. (GraphPad Software, San Diego, CA, USA).
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