|Year : 2020 | Volume
| Issue : 4 | Page : 615-619
Diagnostic accuracy of various biomarkers of sepsis (serum pro-calcitonin, high-sensitivity C-reactive protein, and C-reactive protein) and band cell percentage in critically lll patients: A prospective, observational, cohort study
Bikram Kumar Gupta1, Badri Prasad Das2, Vanita Ramesh Mhaske3, Shubham Tomar4, Kapil Rastogi5
1 Department of Anaesthesiology, Division of Critical Care Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India
2 Department of Anaesthesiology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India
3 Department of Obstetrics and Gynaecology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India
4 Department of Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India
5 Department of Anaesthesiology, Integral Institute of Medical Sciences and Research, Lucknow, Uttar Pradesh, India
|Date of Submission||05-Jan-2021|
|Date of Decision||11-Jan-2021|
|Date of Acceptance||13-Feb-2021|
|Date of Web Publication||27-May-2021|
Dr. Kapil Rastogi
Department of Anaesthesiology, Integral Institute of Medical Sciences and Research, Lucknow, Uttar Pradesh
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Despite the advances in medical sciences, the morbidity and mortality due to sepsis in critically ill medical or surgical patients remains high, hence the need for an early and accurate diagnosis. In the current armamentarium, we have various biomarkers such as procalcitonin (PCT), high-sensitivity C-reactive protein (hs-CRP), CRP, and band cell percentage for an early clue. Aims: This study explores the accuracy of these markers in distinguishing sepsis from systemic inflammatory response syndrome (SIRS) and their correlation with sequential organ failure assessment (SOFA) scoring in critically ill patients. Materials and Methods: After ethical committee approval and written informed consent from guardians, 180 consecutive patients, with clinically suspected infection from any source fulfilling at least two criteria of SIRS, were enrolled and 150 eligible patients were investigated and analyzed prospectively in one cohort, which was later subdivided into two different groups (Group A and Group B) based on microbiology reports, as having SIRS or sepsis, respectively. Samples for cultures (blood, tracheal, or urine as required), biomarkers such as PCT, hs-CRP, and CRP, and band cell percentage were sent from each patient on days 1, 2, 3, and 5 and whenever there were fever spikes. Clinical follow-up was done for 28 days, and demographics, ventilator days, duration of intensive care unit (ICU) stay, and the survival rates were noted. Statistical Analysis: Receiver operating characteristics, area under curve (AUC-ROC) was used for each of the biomarker variables to decide the cutoff values and performance. Correlation coefficient was also seen for each of the biomarkers with SOFA scoring. Results: Attributes of performance for all the biomarkers were satisfactory but was best for PCT (AUC-ROC of 0.987) followed by band cell percentage (0.881). SOFA scoring could also be used with good diagnostic accuracy (AUC-ROC of 0.920). SOFA score correlated best with PCT among the four biomarkers in diagnosing sepsis (Spearman's coefficient of + 0.734). Band cell percentage was significantly higher in the expired group of sepsis patients than survived patients (P = 0.02) and correlated well with ICU stay and 28-day mortality than rest (Spearman's coefficient of − 0.54). Conclusions: The addition of PCT to the standard workup of critically ill patients with suspected sepsis increases diagnostic certainty and generates improved patient management. Band cell percentage also provides a cost-effective alternative to PCT with an analogous diagnostic performance.
Keywords: Band cell percentage, C-reactive protein, high-sensitivity C-reactive protein, procalcitonin, sepsis, sequential organ failure assessment score
|How to cite this article:|
Gupta BK, Das BP, Mhaske VR, Tomar S, Rastogi K. Diagnostic accuracy of various biomarkers of sepsis (serum pro-calcitonin, high-sensitivity C-reactive protein, and C-reactive protein) and band cell percentage in critically lll patients: A prospective, observational, cohort study. Anesth Essays Res 2020;14:615-9
|How to cite this URL:|
Gupta BK, Das BP, Mhaske VR, Tomar S, Rastogi K. Diagnostic accuracy of various biomarkers of sepsis (serum pro-calcitonin, high-sensitivity C-reactive protein, and C-reactive protein) and band cell percentage in critically lll patients: A prospective, observational, cohort study. Anesth Essays Res [serial online] 2020 [cited 2022 Aug 16];14:615-9. Available from: https://www.aeronline.org/text.asp?2020/14/4/615/316979
| Introduction|| |
Sepsis is defined as life-threatening organ dysfunction caused by a deregulated host response to infection where organ dysfunction is identified as an acute change in total quick sequential organ failure assessment (qSOFA) score ≥2 consequent to infection. Sepsis can be difficult to distinguish from other noninfectious conditions in critically ill patients admitted with the clinical signs of acute inflammation, what we call as systemic inflammatory response syndrome (SIRS). This issue is of supreme importance, given that therapies and outcomes greatly differ between patients with and those without sepsis. Given the paramount importance of the timely diagnosis of sepsis at the time of admission to intensive care unit (ICU), microbiological culture analysis, considered to be the gold standard, cannot be always relied upon. Thus, there is an unmet need for the laboratory tools distinguishing between SIRS and various forms of sepsis, though, to date, no single clinical or biological indicator of sepsis has gained unanimous acceptance.
With the above background, this study was conducted with an aim to evaluate the various biomarkers such as procalcitonin (PCT), high-sensitivity C-reactive protein (hs-CRP), CRP, and band cell percentage at the time of admission and to compare their clinically informative values for distinguishing sepsis from severe systemic noninfectious inflammation in newly admitted, critically ill patients with suspected infection.
Settings and study design
After ethics and hospital research committee approval (Dean/2014-15/EC/1385 dated 02.09.2015), written informed consent was taken from the guardians of each patient, for participation in the study and use of the patient data for research and educational purposes. All the procedures adapted follows the guidelines laid down in the declaration of Helsinki (1964). A single-centric, prospective, observational, cohort study was conducted for a period of 2 years, from September 2015 to September 2017, in the ICU of the division of critical care medicine, in our tertiary care hospital. The study included newly admitted adult patients, aged 20–80 years, either with medical or surgical ailments, who were clinically suspected with infection from any source fulfilling at least two criteria of SIRS and requiring blood, urine or endo-tracheal culture. While those who were already diagnosed with culture reports at primary care setups, or with pregnancy, morbid obesity, trauma, burn, cardiomyopathy with ejection fraction <40%, neutropenia, or immunosuppression were excluded from the study. Dropouts included patients with no indication of antimicrobials or culture or had early discharge or left against medical advice or those who died before investigated, were excluded.
| Materials and Methods|| |
Enrollment of eligible patients was done consecutively whenever there was a clinical suspicion of having sepsis or SIRS during their hospital stay. They were shifted to the ICU and managed according to the SSC guidelines and within 3 h of suspected diagnosis, blood, urine, and endotracheal cultures were sent from consecutive patients according to the need, followed by the biomarkers (serum PCT, hs-CRP, CRP) and band cell percentage. On the 7th day, on obtaining the microbiological culture and sensitivity reports, the cohort was subgrouped into those having SIRS (Group A) or Sepsis (Group B). An independent blinded resident on duty collected biomarker and culture reports from each of those patients, without knowing, to which group the patient belonged to. Then, the principal investigator retrospectively analyzed the diagnostic efficacy of the biomarkers within the cohort taking microbiological culture as the gold standard. This is a planned prospective study, with retrospective analysis within the two cohorts. The study procedure followed is depicted in [Figure 1].
|Figure 1: Study procedure. PCT = Serum pro-calcitonin, hs-CRP = High-sensitivity C-reactive protein, CRP = C-reactive protein), c/s = Culture sensitivity, BC = Band cell percentage, SIRS = Systemic Inflammatory Response Syndrome|
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Clinical and laboratory follow-up
All the patients were clinically followed up in the ICU till 28 days, discharge or death, whichever was earlier. Blood samples were sent for the investigation (PCT, hsCRP, CRP, and band cell percentage), and SOFA score was analyzed on the 1st day (on admission), 2nd, 3rd, and 5th day. The cultures were sent on the 1st day, and all these were repeated whenever there was a fever spike. Demographics, ventilator days, duration of ICU stay, and survival rate were also noted and analyzed.
Positive cultures was defined by the isolation of organism with significant colony count >105, among patients with clinical suspicion of infection. The cutoff for the significant values of PCT, hsCRP, CRP, and band cell percentage was decided based on the standard literature.,,,
Sealed envelope sample size calculator was used for the sample size calculation. For qualitative data, Chi-square test and for quantitative data (frequency with %, mean ± standard deviation, median with 25th and 75th percentiles), Student-t test or Mann–Whitney U-test (for skewed data) was used. If group differences were there for the continuous variables, one-way analysis of variance (ANOVA) test was used. Keeping α-error <5%, β-value = 20%, power of the study came to be 80%. Statistical significance was declared when P ≤ 0.05. SPSS for Windows, Version 16.0. SPSS Inc., Chicago.
The accuracy of each modality was expressed using the sensitivity and specificity. The predictive abilities regarding sepsis of different biomarkers were expressed as the area under the receiver operating characteristics curve (AUC-ROC) (mean, 95% confidence interval [CI]), derived from logistic regression analysis using the SPSS for Windows, Version 16.0. (Chicago, SPSS Inc.). The correlation was calculated using the Spearman's coefficient. Statistical significance was declared when P value was less than or equal to 0.05.
| Results|| |
One hundred and eighty enrolled patients were assessed for eligibility and after excluding 20 out of them, 160 eligible patients were allocated into two groups (69 in Group A and 91 in Group B) according to the culture reports. After excluding dropouts (4 and 6 in Group A and B, respectively), 150 patients in the cohort (65 in Group A and 85 in Group B) were analyzed. The CONSORT for our study is depicted in [Figure 2].
The two groups were comparable with respect to age, sex, but the APACHE-II score was more severe in Group B as expected (17.45 ± 4.44 vs. 25.26 ± 7.37, P = 0.01), as shown in [Table 1]. About 58% (38/65) in Group A and 40% (34/85) in Group B survived (P = 0.045), as shown in [Figure 3]. The average ICU stay was 6 days in Group A and 9 days in Group B (P = 0.05), and the average ventilator duration was 6 days and 8 days, respectively (P = 0.05), as shown in [Figure 4].
|Figure 3: Bar diagram showing the survival rate. Group A: Systemic inflammatory response syndrome, Group B: Sepsis|
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|Figure 4: Bar diagram showing intensive care unit stay. SIRS = Systemic inflammatory response syndrome|
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In Group B, the most common organism we found was Acinetobacter (59%), followed by Escherichia More Details coli (31%) and Klebsiella (5%), with lower respiratory tract infection (25/85) as the most common primary source of infection followed by urinary tract infection (17/85) and skin and musculoskeletal system (13/85), as shown in [Figure 5] and [Figure 6].
|Figure 5: Pie diagram showing microbiology. Commonest organism isolated was Acinetobacter followed by Escherichia coli in blood|
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|Figure 6: Bar diagram showing case distribution. CRBSI = Catheter related blood stream infections), GIT = Gastrointestinal tract), UTI = Urinary Tract infection), RTI = Lower respiratory tract infection)|
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In our study, PCT had the highest diagnostic performance followed by SOFA score and band cell %, (AUC-ROC of 0.987, 0.920, and 0.881, respectively), as shown in [Table 2], [Figure 7] and [Figure 8]. SOFA scoring could also be used with good diagnostic accuracy (AUC-ROC of 0.920) which correlated best with PCT among the four biomarkers in diagnosing sepsis (Spearman's coefficient of +0.734). Band cell percentage was significantly higher in the expired group of sepsis patients than survived patients (P = 0.02) and correlated well with ICU stay and 28 days mortality than rest (Spearman's coefficient of − 0.54).
|Table 2: Area under receiver operator characteristic curves of biomarkers, band cell percentage, and sequential organ failure assessment score|
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|Figure 7: Area under receiver operating characteristics curves of biomarkers, band cell %, and sequential organ failure assessment score. PCT = Serum pro-calcitonin, BC = Band cell percentage), hs-CRP = High-sensitivity C-reactive protein, CRP = C-reactive protein, SOFA = Sequential Organ Failure Assessment score|
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|Figure 8: Bar diagram showing the sensitivity and specificity of biomarkers, band cell %, and sequential organ failure assessment. PCT = Serum pro-calcitonin, BC = Band cell percentage, hs-CRP = High-sensitivity C-reactive protein, CRP = C-reactive protein, SOFA = Sequential Organ Failure Assessment score|
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| Discussion|| |
Lactate, being not so accurate in diagnosing sepsis timely, it has been combined with other inflammatory cytokines and chemokines, including CRP, pro-calcitonin, and other biomarkers of neutrophil and monocyte activation, to increase the efficacy as a biomarker. Pro- and anti-inflammatory biomarkers have been included into a multi-marker panel and have helped to identify the patients who are developing severe sepsis before organ dysfunction has advanced too far.
Müller, et al. investigated 101 patients admitted to a medical ICU and suggested that PCT is a more reliable marker of sepsis than is CRP, interleukin 6 (IL-6), and lactate levels. He found that, 99% of the patients at admission had SIRS, 53% had sepsis, and 5% developed sepsis during their stay in the ICU. Calcitonin precursors, CRP, and lactate levels increased with the severity of infection (P < 0.01, one-way ANOVA). In a receiver operating characteristic curve analysis, calcitonin precursors were found to be the most reliable laboratory variable for the diagnosis of sepsis as compared with CRP, IL-6, and lactate (P < 0.01, for each comparison). Calcitonin precursor concentrations of >1 ng.mL−1 had sensitivity of 89% and specificity of 94% for the diagnosis of sepsis. High serum concentrations of calcitonin precursors were associated with the poor prognosis (P = 0.01).
Brunkhorst et al. compared PCT with CRP, white blood cell and thrombocyte count, and APACHE-II score (AP-II). He found that PCT (0.4 ± 3.4 ng.mL−1 for SIRS, 0.5 ± 2.9 ng.mL−1 for sepsis, 6.9 ± 3.9 ng.mL−1 for severe sepsis, and 12.9 ± 4.4 ng.mL−1 for septic shock) was useful to discriminate between sepsis and severe sepsis, in contrast to CRP, blood cell counts, or body temperature. Neither CRP, cell counts, nor the degree of fever showed significant differences between sepsis and severe sepsis, whereas white blood cell count and platelet count differed significantly between severe sepsis and septic shock.
Mare et al. found that increased levels of band cells were more prevalent in sepsis than with SIRS. Band cells were present in most patients with SIRS (mean = 66%) when compared with no SIRS (mean = 29%; P < 0.01) and with healthy controls (0%). The prevalence of band cells was higher in definite sepsis (mean = 82%) than in patients with possible sepsis (mean = 63%; P < 0.05) or with N-I SIRS (mean = 39%; P < 0.001), and they had a sensitivity of 84% and a specificity of 71% for the detection of definite sepsis. Raised blood levels of band cells have diagnostic significance for sepsis, provided that measurements are not confined to patients with normal world blood cell counts, whereas an increased prevalence of myelocytes and metamyelocytes may have prognostic application.
Performance of the biomarkers (PCT, CRP, and hs CRP), band cell percentage, and SOFA score for distinguishing sepsis from SIRS has never been compared together and correlated earlier. The primary outcome of our study was the satisfactory performance of all the biomarkers, but the attributes were best for PCT (AUC-ROC of 0.987) followed by band cells (0.881). SOFA scoring could also be used with good diagnostic accuracy (AUC-ROC of 0.920) which correlated best with PCT among the four biomarkers in diagnosing sepsis (Spearman's coefficient of + 0.734), which was the secondary outcome of the study. Band cell percentage was significantly higher in the expired group of sepsis patients than survived patients (P = 0.02) and correlated well with ICU stay and 28-day mortality than rest (Spearman's coefficient of −0.54).
But our study had some limitations. This was only an observational study and whether the diagnosis ascertained by any modality, influences the decision-making process, also needs to be evaluated.
| Conclusions|| |
Based on the results of the present study, it can be concluded that the addition of pro-calcitonin to the standard clinical workup of critically ill patients with suspected sepsis increases diagnostic certainty and generates improved patient management. Band cell percentage also provides a cost-effective alternative to PCT with an analogous diagnostic performance, especially, in a low-resource country like India.
The authors are thankful to the patients' guardians for their consent and the Department of Anesthesia, Medicine, Surgery, and Nursing Officers for their support in the study. The guardians reviewed the study findings and gave written permission to the authors to publish the article. All of the authors participated to take care of the patients described in the study.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Singer M, Deutschman CS, Seymour CW, Hari MS, Annane D, Bauer M, et al
. The third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA 2016;315:801-10.
Carlet J. Rapid diagnostic methods in the detection of sepsis. Infect Dis Clin North Am 1999;13:483-94.
Barati M, Alinejad F, Bahar MA, Tabrisi MS, Shamshiri AR, Bodouhi NO, et al
. Comparison of WBC, ESR, CRP and PCT serum levels in septic and non-septic burn cases. Burns 2008;34:770-4.
Laupland KB. Fever in the critically ill medical patient. Crit Care Med 2009;37:S273-8.
Levin PD, Idrees S, Sprung CL, Weissman C, Weiss Y, Moses AE, et al
. Antimicrobial use in the ICU: Indications and accuracy – An observational trial. J Hosp Med 2012;7:672-8.
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.
Faix JD. Biomarkers of sepsis. Crit Rev Clin Lab Sci 2013;50:23-36.
Müller B, Becker KL, Schächinger H, Rickenbacher PR, Huber PR, Zimmerli W, et al
. Calcitonin precursors are reliable markers of sepsis in a medical intensive care unit. Crit Care Med 2000;28:977-83.
Brunkhorst FM, Wegscheider K, Forycki ZF, Brunkhorst R. Procalcitonin for early diagnosis and differentiation of SIRS, sepsis, severe sepsis, and septic shock. Intensive Care Med 2000;26 Suppl 2:S148-52.
Mare TA, Treacher DF, Shankar-Hari M, Beale R, Lewis SM, Chambers DJ, et al
. The diagnostic and prognostic significance of monitoring blood levels of immature neutrophils in patients with systemic inflammation. Crit Care 2015;19:57.
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7], [Figure 8]
[Table 1], [Table 2]