Abstract
Background
Acute cholangitis (AC) is a serious bile duct infection that arises from bile obstruction and can lead to significant morbidity and mortality. The neutrophil‒lymphocyte ratio (NLR) is a widely used biomarker of inflammation. This study aims to assess the ability of NLR to predict disease severity and clinical outcomes.
Methods
We performed a retrospective single-center observational analysis of 197 AC patients who received treatment in the Department of Hepatobiliary Surgery at the First Affiliated Hospital of Chongqing Medical University between November 2021 and December 2023.
Results
This study revealed that the five biomarkers (white blood cell (WBC) count, C-reactive protein (CRP), procalcitonin (PCT) levels and neutrophil percentage (N%)) increased significantly with increasing severity of AC. The analysis of biomarkers aimed at distinguishing patients with moderate to severe AC from those with mild AC, as well as severe AC from mild to moderate AC, revealed that the area under the curve (AUC) values for the NLR were 0.847 and 0.800, respectively. These AUC values were significantly higher than those of traditional inflammatory markers, including WBC count (0.657, 0.635), CRP (0.711, 0.720) and N% (0.710, 0.674). Furthermore, the NLR was strongly positively correlated with other inflammatory markers according to the results of Spearman’s test (p<0.05). NLR was consistently a significant predictor of severe AC in both models (OR: 1.036, 1.039). AC patients with a high NLR (>15.93) level at admission had a lower survival rate during hospitalization.
Conclusion
NLR may serve as a convenient and simple biomarker for risk stratification and prognosis prediction in patients with AC.
Keywords: acute cholangitis, neutrophil‒lymphocyte ratio, inflammation, biomarker, sepsis
Graphical Abstract
Introduction
Acute cholangitis (AC) is a serious and potentially life-threatening infection of the biliary tract, commonly precipitated by biliary obstruction and most frequently results from various benign conditions—particularly choledocholithiasis, or malignant tumors. Clinically, AC is characterized by the classic triad of fever, jaundice, and abdominal pain, which is collectively referred to as Charcot’s triad, and this biliary stenosis or blockage increases biliary pressure, leading to bacterial accumulation and subsequent cholangiovenous reflux within the biliary tree, which induces a systemic inflammatory response.1–3 If not promptly treated, this condition can trigger a cascade of complications, including sepsis, liver abscesses, and ultimately multiorgan failure.4 This disease not only poses a significant risk to patient health but also imposes a considerable economic burden on healthcare systems, underscoring the need for timely and effective management strategies.5
Current management approaches for AC primarily include antibiotic therapy and biliary drainage.3 However, these treatments can be hindered by delayed diagnosis and the presence of comorbidities, which complicate the clinical presentation and adversely affect patient outcomes.3,6 The Tokyo Guidelines 2018 (TG18) provide a framework for the diagnosis and management of AC, nevertheless, there remains a gap in understanding how inflammatory markers can be used to predict disease severity and inform treatment decisions.2
Neutrophils play a crucial regulatory role in adaptive immunity and serve as the primary effector cells during the systemic inflammatory response syndrome (SIRS). The neutrophil-to-lymphocyte ratio (NLR), calculated as the simple ratio of neutrophil count to lymphocyte count in peripheral blood, is a biomarker that reflects two key components of the immune system: the innate immune response, primarily mediated by neutrophils, and adaptive immunity, supported by lymphocytes. SIRS is associated with the suppression of neutrophil apoptosis, which augments neutrophil-mediated killing as part of the innate response.7,8 An elevated NLR typically results from an increase in neutrophils accompanied by a decrease in lymphocytes. An early rise in NLR (within 6 hours) following acute physiological stress suggests that NLR may serve as an earlier marker of acute stress compared to other laboratory parameters such as white blood cell (WBC) count, bacteremia, and C-reactive protein (CRP).9 The NLR has emerged as a valuable marker in various inflammatory conditions, with clinical studies confirming its sensitivity in diagnosing systemic infection, sepsis, and bacteremia, as well as its strong predictive and prognostic utility.7,10–13 Recent studies have showed that elevated NLRs are correlated with increased infection severity and poor clinical outcomes in patients with bile duct infections.14–17 However, research on the role of the NLR in AC remains substantially limited. Specifically, evidence is scarce regarding: the association between NLR and distinct severity grades of AC; the comparative diagnostic performance of NLR versus other commonly used inflammatory markers for risk stratification; and the prognostic value of NLR in predicting clinical outcomes.
In this study, we employed a retrospective design to analyze clinical data from patients diagnosed with AC, as per the TG18. This method allows for the collection of comprehensive data, providing an opportunity to evaluate real-world clinical outcomes and identify trends in disease presentation and management. By focusing on inflammatory markers, particularly the NLR, this study aims to improve our understanding of the relationship between these biomarkers and the clinical course of AC. Ultimately, it could contribute to the development of risk stratification protocols that improve patient outcomes and guide clinical decision-making in managing this critical condition.
Materials and Methods
Study Design
This single-center investigation employed a retrospective analysis of hospital medical records. T This study was conducted and reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. The objective of the study was to assess the diagnostic performance of the NLR at the time of admission in predicting the severity of AC. The primary endpoint was to compare the predictive capability of the NLR for distinguishing between moderate/severe and mild AC, as well as severe versus mild/moderate AC, relative to other biomarkers including WBC count, neutrophil percentage (N%), CRP, and procalcitonin (PCT) levels. The secondary endpoint involved identifying risk factors associated with moderate-to-severe and severe AC.
Patients
All adult patients aged 18 years or older with a confirmed diagnosis of AC who received treatment in the Department of Hepatobiliary Surgery at the First Affiliated Hospital of Chongqing Medical University between November 2021 and December 2023 were included in this study.
AC was diagnosed in accordance with the TG18 for AC and acute cholecystitis (Table S1). Specifically, the diagnostic criteria encompassed the presence of systemic inflammation, indicated by symptoms such as fever or chills, abnormal white blood cell counts (either elevated or decreased), or increased CRP levels; evidence of cholestasis, demonstrated by jaundice or elevated liver enzyme levels; and abdominal imaging findings, including biliary ductal dilation or signs suggestive of biliary obstruction.4 The severity of AC was assessed based on the TG18 criteria (Table S2) for diagnosis and severity grading, and cases were classified into mild (grade I), moderate (grade II), or severe (grade III) categories.4
The exclusion criteria were defined as follows: 1) individuals under 18 years of age; 2) patients diagnosed with conditions known to impact immune function, including hematological disorders, malignant neoplasms, or autoimmune diseases; 3) patients who had administered immunomodulatory medications, such as glucocorticoids or chemotherapeutic agents, within three months prior to hospital admission; 4) patients who were complicated with acute myocardial infarction, stroke, uremia, and other acute or chronic diseases; 5) patients who had received oral or intravenous antibiotic therapy within one week preceding admission; and 6) patients with incomplete clinical data.
Data Collection
In this study, a comprehensive set of variables was collected and analyzed, encompassing patients’ demographic characteristics (including age, sex, body mass index, primary diagnosis, comorbidities, prior surgical history, and previous antibiotic usage), clinical parameters (such as heart rate, mean arterial pressure, state of consciousness, PaO2/FiO2 ratio, length of hospital stay, modality of biliary drainage, and in-hospital mortality), as well as laboratory findings. The laboratory data comprised measurements of coagulation indices—international normalized ratio of prothrombin time (Pt-INR) and prothrombin time (PT)—complete blood count components including WBC count, N%, absolute neutrophil and lymphocyte counts, platelet count, liver function tests (alkaline phosphatase (ALP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), γ-glutamyltransferase (GGT), albumin (ALB), and total bilirubin), inflammatory markers (PCT and CRP), tumor marker carbohydrate antigen 19-9 (CA19-9), and blood culture results. The NLR was computed by dividing the neutrophil count (×109/L) by the lymphocyte count (×109/L).
Statistical Analysis
Continuous variables are presented as the median (interquartile range, IQR) and were compared using ANOVA (BMI and PaO2/FiO2) or the Kruskal–Wallis H-test, depending on the variable distribution and the number of variables. The Jonckheere‒Terpstra test was used to assess the trend of each inflammatory biomarker according to the severity of AC. Categorical variables are presented as frequencies (proportions) and were compared using the chi‒square test. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic efficacy of all inflammatory markers for severity assessment, and the areas under the curve (AUCs) were calculated with 95% confidence intervals (CIs). The cutoff value was determined by calculating the maximum value of the Youden index (sensitivity + specificity – 1). Correlation analysis was performed using Spearman correlation. Multivariate logistic regression models were applied to identify the risk factors for moderate-to-severe and severe AC. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were reported for all variables retained in the final model. The Kaplan–Meier method was used for survival analysis, with the Log rank test applied to assess differences in survival curves between groups. Differences were considered statistically significant at a two‒sided P value of <0.05. All statistical analyses were performed by using SPSS software (version 24.0; SPSS Inc., Chicago, IL, USA) and GraphPad Prism (version 8.0; La Jolla, CA, USA). The DeLong test was used to compare AUCs between groups using MedCalc software (version 19.0; Mariakerke, Belgium).
Results
Patient Clinical Characteristics
During this study period, 331 patients with AC were screened, and 197 patients were enrolled in this retrospective study. Among the 134 excluded patients, 34 had received antibiotic treatment prior to admission, and other reasons for exclusion are detailed in Figure 1. The most common indication for biliary drainage was AC caused by choledocholithiasis, followed by hepatolithiasis. There were 81 (41.1%) grade I, 53 (26.9%) grade II, and 63 (32.0%) grade III cases of AC. The median age of all the patients was 69 years, with 104 (52.8%) being female. Patients in the grade II and grade III groups were older than those in the grade I group. A total of 182 (92.4%) patients underwent endoscopic retrograde cholangiopancreatography (ERCP), and nine (4.6%) patients underwent percutaneous transhepatic biliary drainage (PTBD). Three patients with choledocholithiasis combined with cholecystolithiasis underwent surgical treatment, and one patient underwent surgery after the initial ERCP failure. Two (1.0%) patients opted for conservative treatment. Finally, 12 (6.1%) patients died during hospitalization. The baseline characteristics and main clinical features of the 197 enrolled patients are summarized in Table 1.
Figure 1.
Flowchart of included patients.
Table 1.
Baseline Characteristics and Clinical Features of the AC Severity Grading Groups
| Characteristics | Total (n=197) | Grade I (n=81) | Grade II (n=53) | Grade III (n=63) | P‒value |
|---|---|---|---|---|---|
| Age (years) | 69 (50–80) | 50 (36–69) | 78 (68–86) | 73 (64–80) | <0.001 |
| Sex (male/female) | 93/104 | 36/45 | 24/29 | 32/31 | 0.750 |
| BMI (Kg/m2) | 22.2 (20.0–25.0) | 23.4 (21.5–25.1) | 21.3 (19.4–25.3) | 21.3 (19.3–24.6) | 0.011 |
| Heart rate (beats/min) | 86 (77–101) | 79 (75–90) | 88 (77–99) | 97 (80–110) | <0.001 |
| MAP (mmHg) | 90 (80–98) | 92 (86–98) | 92 (86–101) | 73 (64–90) | <0.001 |
| WBC (109/L) | 9.0 (5.9–13.8) | 7.5 (5.1–9.7) | 11.0 (7.0–14.3) | 11.2 (6.1–18.9) | <0.001 |
| N% | 84.1 (75.4–90.3) | 79.7 (69.9–86.1) | 84.9 (76.5–91.3) | 87.5 (81.4–91.4) | <0.001 |
| PLT (109/L) | 169 (106–242) | 208 (155–274) | 183 (150–267) | 78 (47–124) | <0.001 |
| ALT (U/L) | 150 (77–254) | 198 (71–373) | 138 (79–212) | 144 (78–192) | 0.118 |
| AST (U/L) | 122 (65–234) | 126 (63–309) | 146 (72–259) | 113 (61–138) | 0.124 |
| ALP (U/L) | 293 (189–429) | 303 (175–451) | 336 (204–424) | 257 (192–392) | 0.470 |
| GGT (U/L) | 446 (280–764) | 487 (361–776) | 446 (285–762) | 368 (257–690) | 0.298 |
| TB (μmol/L) | 92.8 (49.5–145.2) | 79.8 (45.9–131.5) | 111 (72.9–165.5) | 89.5 (47.5–162) | 0.139 |
| ALB (g/L) | 35.0 (29.0–40.0) | 40 (35–44) | 34 (27–38) | 29 (25–31) | <0.001 |
| CA19-9 (U/mL) | 23.1 (18.2–107.4) | 21.8 (17.3–72.4) | 26.1 (17.5–277.9) | 23.8 (20.3–85.5) | 0.187 |
| PCT (ng/mL) | 1.23 (0.19–7.95) | 0.20 (0.08–1.04) | 2.06 (0.31–10.6) | 6.56 (1.65–29.96) | <0.001 |
| CRP (mg/L) | 85.6 (23.4–210.7) | 26.9 (12.5–152) | 107 (64.4–166.6) | 198 (61–258) | <0.001 |
| NLR | 13.9 (5.9–23.7) | 6.1 (4.0–10.6) | 15.0 (7.7–26.9) | 19.7 (11.1–41.9) | <0.001 |
| INR | 1.07 (0.98–1.21) | 1.01 (0.96–1.09) | 1.06 (0.95–1.19) | 1.31 (1.14–1.45) | <0.001 |
| PT (s) | 13.7 (12.9–15.3) | 13.2 (12.7–13.7) | 13.6 (12.6–14.8) | 15.7 (14.6–17.6) | <0.001 |
| PaO2/FiO2 | 362 (299–438) | 413 (362–459) | 352 (312–400) | 288 (235–385) | <0.001 |
| Blood culture (n, %) | 191 (97.0%) | 77 (95.1%) | 51 (96.2%) | 63 (100%) | 0.090 |
| Positive blood culture (n, %) | 72 (37.7%) | 22 (28.6%) | 19 (37.3%) | 30 (47.6%) | 0.068 |
| Disturbance of consciousness (n, %) | 7 (3.6%) | 0 (0.0) | 0 (0.0) | 7 (11.1%) | <0.001 |
| Length of stay (days) | 8 (6–10) | 7 (5–9) | 8 (6–14) | 9 (7–14) | 0.010 |
| Biliary drainage | 0.149 | ||||
| ERCP (n, %) | 182 (92.4%) | 79 (97.6%) | 48 (90.5%) | 55 (87.3%) | |
| PTBD (n, %) | 9 (4.6%) | 1 (1.2%) | 3 (5.7%) | 5 (7.9%) | |
| Surgery (n, %) | 4 (2.0%) | 1 (1.2%) | 2 (3.8%) | 1 (1.6%) | |
| Conservative therapy (n, %) | 2 (1.0%) | 0 | 0 | 2 (3.2%) | |
| In-hospital mortality (n, %) | 12 (6.1%) | 0 (0.0) | 3 (5.7%) | 9 (14.3%) | <0.001 |
Note: p<0.05 was considered significant.
Abbreviations: BMI, body mass index; MAP, mean artery pressure; WBC, white blood cell count; N%, neutrophil percent, PLT, platelet count, ALT, alanine aminotransferase; AST, aspartate aminotransferase; ALP, alkaline phosphatase; GGT, γ-glutamyltransferase; ALB, Albumin; TB, total bilirubin; CA19-9, carbohydrate antigen 19-9; PCT, procalcitonin; CRP, C-reactive protein; NLR, neutrophil‒lymphocyte ratio; PT, prothrombin time; INR, International normalized ratio; PaO2, arterial partial pressure of oxygen; FiO2, fraction of inspired oxygen; ERCP, endoscopic retrograde cholangiopancreatography; PTCD, percutaneous transhepatic cholangial drainage; AC, Acute cholangitis.
Changes in Inflammatory Markers (NLR, PCT, CRP, N%, and WBC Count) According to the Severity of AC
The trends in NLR, PCT level, CRP level, N%, and WBC count according to the severity of AC are shown in Figure 2. The median values for NLR, CRP concentration, and PCT concentration across the different groups were as follows: NLR‒grade I: 6.1 (4.0–10.6), grade II: 15.0 (7.7–26.9), grade III: 19.7 (11.1–41.9); CRP concentration‒grade I: 26.9 mg/L (12.5–152), grade II: 107 mg/L (64.4–166.6), grade III: 198 mg/L (61–258); PCT concentration‒grade I: 0.20 ng/mL (0.08–1.04), grade II: 2.06 ng/mL (0.31–10.6), grade III: 6.56 ng/mL (1.65–29.96). Significant differences were observed between the severity grading groups for NLR, CRP level, and PCT level (P <0.001). Statistically significant differences were found in all inflammatory biomarker levels among the groups with varying severity with all biomarkers showing an increasing trend corresponding to greater AC severity (P <0.001).
Figure 2.
The results of the comparison of five biomarkers among the AC severity grading groups are presented. A statistically significant increasing trend was observed in NLR (A), PCT (B) and CRP (C) along with increasing grade. D (N%) and E (WBC), there was a statistically significant difference between grade I and grade II/grade III, but no significant difference between grade II and grade III. ns P > 0.05, * P<0.05, ** P<0.01, *** P<0.001.
Abbreviations: CRP, C-reactive protein; NLR, neutrophil‒lymphocyte ratio; PCT, procalcitonin; WBC, white blood cell count; N%, neutrophil percent; ROC, Receiver operating characteristic; AC, Acute cholangitis.
Ability of the NLR Level to Predict the Severity of AC
The ROC curves illustrating the ability of the NLR, PCT level, CRP level, N% and WBC count to predict moderate/severe (versus mild) or severe (versus mild/moderate) AC are shown in Figure 3, respectively. The AUC for the NLR in predicting moderate/severe AC was significantly greater than that for N%, CRP levels, and WBC count (Table 2 and Table 3). Similarly, the AUC of the NLR for predicting severe AC was also significantly greater than that for N%, CRP levels, and WBC count (Table 4 and Table 5). No statistically significant differences were observed between the AUCs of the NLR and PCT levels for predicting either moderate/severe or severe AC (Table 3 and Table 5). Based on the Youden index, the optimal cutoff values for the NLR were 13.42 for predicting moderate/severe AC (sensitivity 78.5%; specificity 85.2%) and 15.93 for predicting severe AC (sensitivity 74.6%; specificity 76.9%) (Table 2 and Table 4).
Figure 3.
(A) ROC analysis of five biomarkers for predicting grade II/grade III AC. (B) ROC analysis of five biomarkers for predicting grade III AC.
Abbreviations: CRP, C-reactive protein; NLR, neutrophil‒lymphocyte ratio; PCT, procalcitonin; WBC, white blood cell count; N%, neutrophil percent; ROC, Receiver operating characteristic; AC, Acute cholangitis.
Table 2.
Performance of Inflammatory Markers in Discriminating Grade II/Grade III AC Patients from Grade I AC Patients
| Variables | AUC (95% CI) | Cut-off | Sensitivity (%) | Specificity (%) | Youden Index |
|---|---|---|---|---|---|
| NLR | 0.847 (0.789–0.895) | 13.42 | 78.5 | 85.2 | 0.636 |
| PCT | 0.831 (0.772–0.881) | 0.58 ng/mL | 83.6 | 74.1 | 0.577 |
| CRP | 0.711 (0.643–0.774) | 36.7 mg/L | 80.2 | 63.0 | 0.431 |
| N% | 0.710 (0.641–0.772) | 87.4% | 47.4 | 84.0 | 0.314 |
| WBC | 0.657 (0.586–0.723) | 9.73×109/L | 62.1 | 79.0 | 0.411 |
| NLR+PCT | 0.873 (0.818–0.916) | ||||
| NLR+CRP | 0.847 (0.789–0.894) | ||||
| NLR+N% | 0.852 (0.784–0.898) | ||||
| NLR+WBC | 0.856 (0.800–0.902) |
Abbreviations: CRP, C-reactive protein; NLR, neutrophil‒lymphocyte ratio; PCT, procalcitonin; WBC, white blood cell count; N%, neutrophil percent; AUC, areas under the curve; CI, confidence interval; AC, Acute cholangitis.
Table 3.
The P value for the Comparison of the AUC in Discriminating Between Grade I Patients and Grade II/Grade III AC Patients
| Variables | PCT | CRP | N% | WBC |
|---|---|---|---|---|
| NLR | 0.5875 | 0.0002 | <0.001 | <0.001 |
| PCT | 0.0015 | 0.0014 | <0.001 | |
| CRP | 0.9685 | 0.1364 | ||
| N% | 0.1777 |
Note: p<0.05 was considered significant.
Abbreviations: CRP, C-reactive protein; NLR, neutrophil‒lymphocyte ratio; PCT, procalcitonin; WBC, white blood cell count; N%, neutrophil percent; AUC, areas under the curve; AC, Acute cholangitis.
Table 4.
Performance of Inflammatory Markers in Discriminating Grade III AC Patients from Grade I/Grade II AC Patients
| Variables | AUC (95% CI) | Cut-off | Sensitivity (%) | Specificity (%) | Youden Index |
|---|---|---|---|---|---|
| NLR | 0.800 (0.737–0.854) | 15.93 | 74.6 | 76.9 | 0.515 |
| PCT | 0.807 (0.745–0.860) | 1.35 ng/mL | 82.5 | 69.4 | 0.519 |
| CRP | 0.720 (0.652–0.781) | 134 mg/L | 61.9 | 72.4 | 0.343 |
| N% | 0.674 (0.604–0.739) | 86.3% | 60.3 | 67.9 | 0.282 |
| WBC | 0.635 (0.564–0.703) | 11.02×109/L | 54.0 | 73.1 | 0.271 |
| NLR+PCT | 0.835 (0.775–0.884) | ||||
| NLR+CRP | 0.784 (0.720–0.839) | ||||
| NLR+N% | 0.794 (0.731–0.848) | ||||
| NLR+WBC | 0.794 (0.730–8.848) |
Abbreviations: CRP, C-reactive protein; NLR, neutrophil‒lymphocyte ratio; PCT, procalcitonin; WBC, white blood cell count; N%, neutrophil percent; AUC, areas under the curve; CI, confidence interval; AC, Acute cholangitis.
Table 5.
The P value for the Comparison of the AUC in Discriminating Between the Grade III AC Patients and Grade I/Grade II AC Patients
| Variables | PCT | CRP | N% | WBC |
|---|---|---|---|---|
| NLR | 0.8217 | 0.0263 | <0.001 | <0.001 |
| PCT | 0.0150 | 0.0013 | <0.001 | |
| CRP | 0.2698 | 0.0355 | ||
| N% | 0.4068 |
Note: p<0.05 was considered significant.
Abbreviations: CRP, C-reactive protein; NLR, neutrophil‒lymphocyte ratio; PCT, procalcitonin; WBC, white blood cell count; N%, neutrophil percent; AUC, areas under the curve; AC, Acute cholangitis.
Relationships Between the NLR and Other Inflammatory Markers
The relationships between the NLR and the other inflammatory markers in AC patients are illustrated in Figure 4. A positive association was observed between the NLR and CRP levels, N%, PCT levels, and WBC count. Notably, the NLR showed a strong correlation with both N% and PCT levels (r=0.7632, r=0.6538).
Figure 4.
The relationship between NLR and WBC count (A) r=0.6430, P<0.001), N% (B) r=0.7632, P<0.001), CRP (C) r=0.6104, P<0.001), and PCT (D) r=0.6538, P<0.001) in AC patients was analyzed using Spearman’s test.
Abbreviations: CRP, C-reactive protein; NLR, neutrophil‒lymphocyte ratio; PCT, procalcitonin; WBC, white blood cell count; N%, neutrophil percent; AC, Acute cholangitis.
Multivariate Analyses for Predicting Moderate-to-Severe and Severe AC
Two logistic regression models were constructed (Table 6). All variables with P < 0.001 in univariable analysis, along with clinically important covariates, were included in a multivariable logistic regression model. In these models, moderate-to-severe AC and severe AC were used as the dependent variables, while the indices that showed significant differences among the three groups were used as independent variables to determine whether the NLR is a reliable predictor of severe AC. We found that the NLR was the only significant predictor of both moderate-to-severe and severe AC (OR: 1.176 and 1.050, respectively).
Table 6.
Results of Multivariate Logistic Regression Analysis for Factors Predicting Moderate-to-Severe and Severe AC
| Variables | Multivariate Analysis 1 | Multivariate Analysis 2 | ||||
|---|---|---|---|---|---|---|
| Adjusted OR | 95% CI | P‒value | Adjusted OR | 95% CI | P‒value | |
| Age | 1.085 | 1.049–1.122 | <0.001 | 1.005 | 0.979–1.031 | 0.735 |
| PLT | 0.997 | 0.992–1.003 | 0.295 | 0.989 | 0.984–0.994 | <0.001 |
| NLR | 1.176 | 1.098–1.260 | <0.001 | 1.050 | 1.021–1.079 | <0.001 |
| CRP | 0.995 | 0.989–1.001 | 0.077 | 1.002 | 0.997–1.006 | 0.508 |
| PCT | 1.182 | 1.025–1.363 | 0.022 | 1.030 | 0.995–1.067 | 0.095 |
Notes: Model 1 for moderate-to-severe AC; Model 2 for severe AC. p<0.05 was considered significant.
Abbreviations: CRP, C‒reactive protein; NLR, neutrophil‒lymphocyte ratio; PCT, procalcitonin; PLT, platelet count; OR, odds ratio; CI, confidence interval; AC, Acute cholangitis.
Associations Between the NLR or PCT Level and in-Hospital Mortality Risk
To investigate the relationships between survival time and independent risk factors in patients with severe AC, we stratified the patient cohort based on optimal cutoff values: 15.93 for the NLR (defining high- and low-NLR groups) and 1.35 ng/mL for PCT levels (defining high- and low-PCT groups). Kaplan‒Meier survival curve analysis demonstrated that patients with high NLR or high PCT levels at admission had significantly lower survival rates (P < 0.05) (Figure 5). These findings underscore the prognostic significance of the NLR and PCT levels in evaluating patient outcomes during hospitalization.
Figure 5.
Kaplan‒Meier survival curve analysis of the associations between the NLR (A) or PCT (B) level and in-hospital mortality risk.
Abbreviations: NLR, neutrophil‒lymphocyte ratio; PCT, procalcitonin.
Discussion
We conducted a retrospective cohort study to investigate the associations of five inflammatory biomarkers with disease severity and prognosis in patients with AC. The main findings of this research are as follows: 1) The five inflammatory biomarkers differed across the various severity levels of AC. The NLR, CRP levels, and PCT levels exhibited a clear increasing trend in correlation with the severity of AC; 2) In terms of predicting moderate/severe and severe AC, the diagnostic efficacy of the NLR and PCT levels was comparable and significantly superior to that of the WBC count, CRP levels, and N%; 3) The NLR was positively correlated with all the other inflammatory biomarkers studied; 4) Multivariate analysis for predicting severe AC identified the NLR as an independent risk factor; and 5) Lower NLR and PCT levels in AC patients at admission correlated with significantly longer median survival times.
AC is a potentially life-threatening form of systemic infectious inflammation resulting from biliary obstruction. This condition can lead to severe complications, including sepsis and multiorgan failure, making prompt diagnosis and intervention critical for patient survival.18 Characterized by the classic triad of fever, jaundice, and abdominal pain, AC presents with varied clinical manifestations, ranging from mild symptoms to severe septic shock.1,18 The complexity of its management necessitates a thorough understanding of the underlying pathophysiology, specifically inflammation, and associated risk factors to optimize treatment strategies and improve patient outcomes. However, early and rapid identification of different disease severities and prognoses for patients with AC is highly challenging. The TG18 is known to be the standard for the severity assessment of AC, this guideline includes the evaluation of six organ systems, requiring complex items such as vital signs and laboratory results, and it may not easily applicable to the emergency setting or clinics with limited equipment. In this condition, biomarkers seem to be more helpful for early diagnosis than other methods, as they are easily obtained and measured. Of note, the TG18 currently employs WBC count and CRP level as diagnostic criteria for inflammation, but their effectiveness is compromised by various confounding factors, and their diagnostic utility significantly decreases in the presence of severe systemic infections.19–23
Neutrophils, whose functions include adhesion and phagocytosis, are the first responders in innate immunity. They rapidly react to and clear pathogens upon invasion. Lymphocytes, the main players in adaptive immunity, offer precise pathogen recognition, in contrast to the broader immune response of neutrophils. Bacterial infections lead to a marked increase in the numbers of neutrophils and their inflammatory mediators. However, after early severe inflammation, the immune system frequently undergoes immunosuppression that resulting in a decline in absolute or proportional lymphocyte counts, and might be responsible for a series of subsequent adverse outcomes. The NLR leverages this interrelationship to effectively indicate the balance between innate and adaptive immunity.24,25 In this study, we retrospectively analyzed the clinical data of 197 AC patients at admission and comprehensively investigated the role of inflammatory markers, particularly the NLR, in predicting disease severity and clinical outcomes in patients with AC, which is poorly reported by previous research. We found that the levels of all the traditional inflammatory markers in the patients increased as the severity of cholangitis increased and there were significant differences in the PCT level and CRP level among the different groups (P<0.05). Specifically, the median NLR in patients with severe AC was significantly greater than that in patients with moderate AC (P <0.05), and this difference also exist in patients with moderate AC and mild AC (P <0.05), inferring NLR can be one indicator reflect AC severity for the risk stratification of patients with AC. Indeed, our present results were similar to those of previous studies in which the accuracy of the NLR was superior to that of certain conventional laboratory diagnostic markers, such as WBC count and CRP levels, in systemic bacterial infection and sepsis.7,12,26,27 Further ROC curve analysis revealed that compared with CRP levels, WBC count, and N%, both the NLR and PCT levels exhibited significantly higher AUCs for predicting moderate-to-severe and severe AC. As to NLR, the AUC for discriminating patients with moderate/severe AC was 0.847, which was the highest among the five biomarkers. The optimal cutoff value was 13.42, and the sensitivity and specificity were 78.5% and 85.2%, respectively. The AUC of the NLR for predicting severe AC was 0.800, which was greater than those of WBC count, CRP levels, and N%. The optimal cutoff value was 15.93, and the sensitivity and specificity were 74.6% and 76.9%, respectively. All of these results indicated that the NLR had high sensitivity and specificity in the risk stratification of patients with AC. Additionally, despite there was no significant difference in AUCs between the NLR and PCT level, indicating that the predictive ability of both markers was comparable. We found that the combination of the NLR and PCT level exhibited the greatest diagnostic efficacy in predicting moderate-to-severe and severe AC. Thus, compared with single biomarker, joint indicators containing NLR and PCT may be superior in discriminating AC severity. We propose that the NLR be considered the first-line screening tool for early risk stratification in resource-limited or primary care settings where PCT is not readily available. Our data demonstrate that NLR alone provides predictive performance that is non-inferior to PCT for both moderate-to-severe and severe AC. In contrast, when maximum diagnostic accuracy is required—such as in tertiary referral centers where decisions regarding ICU admission or emergency biliary decompression are made—the combination of NLR and PCT (NLR + PCT) may be preferred, as this approach yielded the highest diagnostic performance in our study.
Additionally, as a classical parameter mirroring the presumed impaired immunity, the NLR has been reported as a significant prognostic value for predicting the outcomes of bacterial infectious diseases and sepsis.11,28,29 In this study, multivariable analysis identified the NLR and PLT as independent risk factors for severe AC, while age, PCT, and NLR were independent predictors of moderate-to-severe AC. Notably, NLR was the only factor that remained significant in both severity models. In another aspect, Kaplan‒Meier curve analysis revealed that patients with high NLRs and high PCT levels at admission had a significantly increased risk of in-hospital mortality (Log rank test, P < 0.05). These findings suggest that both NLR and PCT levels may be associated with clinical outcomes in hospitalized patients with AC. Elevated NLR levels at admission may serve as valuable warning signs, prompting closer monitoring and more aggressive management of high-risk patients. However, given the exploratory nature of our analysis and the modest sample size, these results should be interpreted with caution. Further prospective studies are warranted to confirm the prognostic utility of these biomarkers.
Previous studies have established PCT as a valuable biomarker for diagnosis and assessment of various bacterial infectious diseases and sepsis.30–33 A growing body of research indicates that PCT is a more accurate indicator of AC severity than conventional biomarkers.1,34,35 On the basis of this strong evidence, the TG18 guidelines formally endorsed PCT as a vital biomarker for grading AC severity.4 In this study, as aforementioned, we found no statistically significant difference in the stratification of AC severity between the NLR and PCT level and indeed, our analysis revealed that the NLR was the only inflammatory marker independently linked to severe AC after accounting for confounders, indicating NLR may have greater real-world predictive stability than PCT levels. Compared with PCT, the NLR, which is calculated from a routine complete blood count, is more feasible for widespread adoption, primarily because of its faster turnaround time and lower cost. This makes it a particularly practical alternative in resource-limited settings and for general outpatient or emergency room patient screening purposes.
Some experts have suggested that monitoring PCT levels can help clinicians adjust the regimen of antimicrobial therapy and perform urgent biliary decompression in AC patients.1,34,36 In this study, we observed a moderate-to-strong positive correlation between NLR and both PCT (r=0.6538) and CRP (r=0.6104) levels in patients with AC. While these findings suggest that NLR may reflect a systemic inflammatory state similar to that indicated by PCT and CRP, we acknowledge that correlation does not imply equivalence in clinical utility. Whether NLR can independently guide urgent biliary decompression decisions requires further prospective validation.
This study has several limitations. The single-center retrospective design inherently carries risks of selection bias, and the relatively small sample size limits the generalizability of the results. Another limitation is the absence of non-acute cholangitis (non-AC) patients as a control group. Since previous studies have already established the diagnostic utility of the NLR for AC, and our primary objective was to assess the role of NLR in risk stratification among AC patients, including non-AC controls was deemed unnecessary for this investigation. Our proposed NLR cut-off values were derived from a single cohort and may not be directly generalizable to other populations, healthcare settings, or ethnic groups. External validation in independent, preferably multicenter, prospective cohorts is essential before these thresholds can be recommended for routine clinical use. Future studies should also evaluate optimal cut-off values across different clinical subgroups to enhance their applicability. Additionally, we excluded 34 patients who had received antibiotics prior to hospitalization. Although this exclusion may have somewhat overestimated the predictive value of NLR, antibiotic therapy reduces the systemic inflammatory response by decreasing bacterial load and the release of pro-inflammatory cytokines. This reduction lowers NLR, WBC, and CRP levels, potentially increasing false-negative results. Furthermore, because this was a retrospective study, we were unable to obtain detailed information on the type, duration, and dosage of antibiotic use, which could have introduced additional confounding factors. To avoid bias from these variables, these patients were excluded. Finally, the small number of death events may have limited the statistical power of the survival analysis. Therefore, the results should be considered exploratory and require validation in studies with larger sample sizes and longer follow-up periods.
Conclusion
In conclusion, our findings suggest that NLR may serve as a valuable and cost-effective biomarker for the early identification of high-risk AC patients. If validated in future prospective studies, this approach could facilitate timely risk stratification and potentially improve clinical outcomes, while also providing a more accessible alternative to costly inflammatory markers such as PCT. However, given the limitations of this study, these findings require further external validation before they can be routinely implemented in clinical practice.
Funding Statement
The authors declare that no funding was received for this study.
Data Sharing Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Ethics Statement
This study was approved by the Institutional Review Board of the First Affiliated Hospital of Chongqing Medical University (protocol number K2023-099). The Institutional Review Board waived the requirement for informed consent because this was a low-risk retrospective medical record review study using existing clinical data, with no direct patient contact and no impact on patient care. All data were anonymized or de-identified before analysis and were kept strictly confidential. The study was conducted in accordance with the Declaration of Helsinki.
Author Contributions
Xin Deng: Methodology, Investigation, Formal analysis, Data curation, Conceptualization and Writing – original draft. Tong Mou: Data curation, Methodology and Writing – original draft. Yu Zhu: Formal analysis, Supervision and Writing – review & editing. Jing-Wen Wang: Conceptualization, Data Curation, Supervision, Formal analysis and Writing – review & editing. All authors gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.
Disclosure
The author(s) report no conflicts of interest in this work.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.