Association of Serum CX3CL1 and TSLP Expression with Postoperative Pain Severity in Patients Undergoing Laparoscopic Cholecystectomy: A Prospective Study

Abstract

Objective

To investigate the association between preoperative serum CX3CL1 and TSLP levels and postoperative pain severity in patients with acute calculous cholecystitis undergoing laparoscopic cholecystectomy (LC).

Methods

We prospectively enrolled 379 patients with acute calculous cholecystitis undergoing LC. According to the 24-hour postoperative visual analog scale (VAS) score, patients were classified into mild pain (MP, n=261) and moderate-to-severe pain (MSP, n=118) groups. Preoperative serum CX3CL1 and TSLP were measured by enzyme-linked immunosorbent assay (ELISA). Receiver operating characteristic (ROC) curves were constructed to evaluate their predictive value, alone and in combination. Multivariable logistic regression identified independent risk factors. A nomogram was developed and internally validated using a 7:3 split.

Results

Preoperative serum CX3CL1 and TSLP levels were significantly higher in the MSP group (both P<0.001). Both showed moderate positive correlations with C-reactive protein (CRP) and postoperative VAS scores (r=0.410–0.456). The combined biomarker model (CX3CL1 + TSLP) achieved an area under the curve (AUC) of 0.860 (95% confidence interval [CI], 0.819–0.900). Multivariable logistic regression identified gallbladder wall thickness, onset-to-surgery time, intraoperative drainage tube placement, Tokyo Guidelines 2018 (TG18) grade, Generalized Anxiety Disorder-7 (GAD-7) score, Patient Health Questionnaire-9 (PHQ-9) score, Athens Insomnia Scale (AIS) score, CRP, CX3CL1, and TSLP as independent risk factors. The nomogram demonstrated AUCs of 0.859 and 0.892 in the training and validation sets, with good calibration and clinical net benefit.

Conclusion

Elevated preoperative serum CX3CL1 and TSLP levels are independently associated with moderate-to-severe pain following LC, and their combined detection may help identify high-risk patients. The nomogram integrating these biomarkers with clinical risk factors shows favorable predictive performance; however, external multicenter validation is required before clinical application.

Introduction

Acute cholecystitis is an acute inflammatory disease caused by cystic duct obstruction, characterized by high incidence and significant risk of complications, and has become one of the common acute abdominal conditions in general surgery. It affects approximately 200,000 cases annually in the United States and constitutes an important component of gallbladder diseases.^1,2 With the advancement of minimally invasive surgical techniques, laparoscopic cholecystectomy (LC) has become the standard treatment for acute cholecystitis due to its advantages of minimal trauma, rapid recovery, and short hospital stay, and is widely recommended as a first-line therapeutic strategy.^3,4 Although LC has significantly improved perioperative outcomes, postoperative pain remains an important factor affecting recovery quality. Studies have shown that approximately one-third of patients experience suboptimal early postoperative analgesia, and the severity of acute pain is closely associated with persistent pain in the long term. Postoperative pain not only delays short-term recovery but may also increase the risk of chronic pain development.^5,6 Furthermore, factors such as the inflammatory severity of acute cholecystitis itself, timing of surgery, and individual variability may exert complex effects on postoperative pain. Currently, reliable means for predicting the severity of postoperative pain remain lacking in clinical practice.⁷ Existing prediction models for postoperative pain following LC primarily rely on clinical characteristics and intraoperative factors.⁸ However, these models are constrained by subjective assessments and uncontrollable intraoperative variables. Objective biological indicators accessible preoperatively remain lacking. Therefore, exploring the factors associated with the occurrence and severity of postoperative pain in patients with acute cholecystitis undergoing LC is of important clinical significance for optimizing perioperative management and improving patient prognosis.

C-X3-C motif chemokine ligand 1 (CX3CL1) mediates immune-neural interactions through its receptor C-X3-C motif chemokine receptor 1 (CX3CR1) and plays a key role in inflammatory responses and neuroimmune regulation. Its altered expression is closely associated with neuroinflammation levels in various diseases.^9,10 CX3CL1 is also involved in the regulation of biliary system inflammation; previous studies have demonstrated its significant upregulation and secretion in biliary epithelial cells, contributing to inflammation-related pathological processes in biliary tract diseases.¹¹ In the field of pain, the CX3CL1/CX3CR1 signaling axis drives glial cell activation through activation of the p38 mitogen-activated protein kinase (p38 MAPK) pathway to promote hyperalgesia in inflammatory and neuropathic pain models. Clinical studies have found significantly elevated cerebrospinal fluid and serum CX3CL1 levels in patients with chronic pain, suggesting its potential value as a neuroinflammation-related biomarker for pain.^12–14 However, its clinical predictive value for acute pain following LC remains to be systematically investigated.

Thymic stromal lymphopoietin (TSLP) is a pleiotropic cytokine predominantly derived from epithelial cells. It not only participates in the initiation and maintenance of type 2 immune responses and plays a critical regulatory role in allergic diseases, but is also widely involved in various pathological processes including infection, chronic inflammation, and malignancy.¹⁵ Studies have shown that TSLP drives glial cell reactivity, neuronal injury, and peripheral sensory nerve sensitization through activation of the thymic stromal lymphopoietin receptor/signal transducer and activator of transcription 5 (TSLPR/STAT5) pathway, thereby promoting mechanical hyperalgesia. Targeted inhibition of this pathway can attenuate pain behavior, suggesting that TSLP is a key proinflammatory factor involved in pain initiation and maintenance.^16–18 However, the expression characteristics and clinical predictive significance of TSLP in postoperative pain following LC have not been clearly reported.

Serum CX3CL1 and TSLP can be measured via a single preoperative blood draw using enzyme-linked immunosorbent assay (ELISA), objectively reflecting neuroimmune sensitization, and may serve as novel biomarkers for preoperative risk stratification. Both are detectable by standardized ELISA with mature technology and controllable costs. They enable objective preoperative assessment without additional invasive procedures. This offers a clear advantage over models dependent on intraoperative or subjective factors. Based on the above, this study aimed to detect preoperative serum CX3CL1 and TSLP levels in patients with acute cholecystitis undergoing LC, explore their correlation with pain severity at 24 hours postoperatively, and assess the clinical value of a combined predictive model for moderate-to-severe postoperative pain, with the goal of enabling early recognition and tailored analgesic strategies.

Materials and Methods

General Data

Sample Size Calculation: This study aimed to construct a prediction model for moderate-to-severe postoperative pain (MSP) based on multivariable logistic regression and develop a nomogram. Sample size calculation employed two complementary approaches. First, following the events per variable (EPV) principle proposed by Peduzzi et al: according to a large-scale survey of ambulatory surgical patients by McGrath et al (n=5703), the overall incidence of moderate-to-severe pain at 24 hours postoperatively was approximately 30%, with the laparoscopic cholecystectomy subgroup (n=205) showing an incidence as high as 57.1%.¹⁹ Considering that this study involved Canadian ambulatory surgical populations from 20 years ago, whereas the present study enrolled hospitalized LC patients with significantly more intensive perioperative analgesic management than day surgery, and given that modern multimodal analgesia concepts have advanced considerably over the past two decades, this study adopted a conservative estimate of 30% for sample size calculation. With 10 planned predictive variables and applying the conservative EPV≥10 criterion, the required number of MSP events was at least 100 cases, corresponding to a total sample size of approximately 333 cases. Second, supplementary assessment was performed using the prediction model sample size framework proposed by Riley et al (pmsampsize R package, version 1.1.3): setting the anticipated C-statistic at 0.85 and the anticipated shrinkage factor at ≥0.90, the calculated minimum sample size was 354 cases. This study ultimately enrolled 379 LC patients, including 118 MSP cases, yielding an EPV of 11.8, which satisfied the requirements of both frameworks.

Inclusion Criteria: (1) Age 18–75 years; (2) Clinically diagnosed gallstone disease with acute cholecystitis;^20,21 (3) Preoperative abdominal ultrasonography confirming gallstones with imaging characteristics consistent with acute cholecystitis; (4) American Society of Anesthesiologists (ASA) physical status classification I–III, scheduled for laparoscopic cholecystectomy; (5) Normal cognitive function, capable of cooperating with postoperative pain assessment; (6) Signed informed consent.

Exclusion Criteria: (1) Acalculous cholecystitis, gallbladder polyps, gallbladder adenomyomatosis, gallbladder carcinoma, or other gallbladder space-occupying lesions. Given that the pathophysiological mechanisms of acalculous cholecystitis fundamentally differ from those of calculous cholecystitis, whereas gallbladder polyps, adenomyomatosis, and space-occupying lesions mostly undergo elective prophylactic resection with postoperative pain mechanisms distinct from the acute inflammatory pain of interest in this study, these conditions were excluded to ensure homogeneity of the study population; (2) Biliary pancreatitis or concomitant common bile duct stones requiring simultaneous management; (3) Mirizzi syndrome; (4) Prior upper abdominal surgical history; (5) Long-term preoperative use of analgesics or opioids (>3 months), or use of corticosteroids or immunosuppressants within 1 week preoperatively; (6) History of chronic pain (eg, fibromyalgia, neuropathic pain, chronic low back pain); (7) Severe psychiatric history (eg, severe anxiety disorder, depression, schizophrenia) or cognitive dysfunction; (8) Severe cardiac, pulmonary, hepatic, or renal insufficiency, or severe coagulation dysfunction; (9) Pregnant or lactating women; (10) Participation in other clinical trials within the past 3 months.

This study prospectively enrolled patients with acute calculous cholecystitis scheduled for LC at the Department of Hepatobiliary Surgery, the Second Hospital of Hebei Medical University, from July 2023 to December 2025. An initial assessment of 480 cases was performed; 101 cases were excluded (18 refused informed consent, 78 did not meet inclusion criteria, 5 had missing preoperative visual analog scale [VAS] score data), with 379 cases ultimately enrolled. The subject screening flowchart is shown in Figure 1. This study was approved by the Ethics Committee of the Second Hospital of Hebei Medical University (approval number: 2023-R452).

Figure 1.

Flowchart of subject screening.

LC Surgical Method

All LC procedures were performed by the same team of hepatobiliary surgeons with associate chief physician rank or above and an annual surgical volume exceeding 100 cases, following a standardized protocol. Conventional LC was performed using the four-port technique: a 10 mm longitudinal incision at the umbilicus was made to establish pneumoperitoneum (CO₂ pressure 12–14 mmHg); a 10 mm main operating port was placed 2 cm below the xiphoid process; and 5 mm auxiliary ports were placed at the right anterior axillary line at the level of the umbilicus and 3 cm below the right costal margin at the midclavicular line, respectively. The Calot triangle was dissected in an antegrade fashion, followed by clipping and dividing the cystic duct and cystic artery. The gallbladder bed was dissected using an electrocautery hook, and the gallbladder was extracted intact through the umbilical port. After achieving hemostasis, the operative field was irrigated with warm saline. Single-incision LC was performed through a single 2–3 cm incision at the umbilicus with insertion of a multichannel trocar; operating instruments were introduced through the same incision, with the remaining procedural steps identical to conventional LC. No incision extension was performed intraoperatively, and no conversion to laparotomy occurred.

Perioperative and Postoperative Pain Management

Intraoperative anesthesia was administered by the same team of attending anesthesiologists or above, each with more than 5 years of clinical experience and an annual anesthesia case volume exceeding 500, according to departmental standardized protocols. Anesthesia induction was performed with midazolam, propofol, sufentanil (0.3–0.5 μg/kg), and rocuronium, and maintained with continuous inhalation of sevoflurane during surgery, with additional sufentanil (5–10 μg per dose) administered as needed at the anesthesiologist’s discretion. A uniform multimodal analgesic regimen was adopted postoperatively: upon return to the ward, patients routinely received intravenous parecoxib sodium 40 mg (every 12 h for a total of 2 doses), and were connected to a patient-controlled intravenous analgesia (PCIA) pump (formulation: sufentanil 2 μg/kg plus tropisetron 5 mg, diluted to 100 mL; background infusion 2 mL/h, bolus dose 0.5 mL, lockout time 15 min). If the postoperative VAS score was ≥4, rescue analgesia was provided: intravenous tramadol 50–100 mg or intravenous dezocine 5 mg.

Clinical Data Collection and Observation Indicators

Clinical data collected and recorded included sex, age, body mass index (BMI), comorbid underlying diseases including hypertension and diabetes, smoking history (≥1 pack-year; those who quit <1 year were still counted), alcohol consumption history (≥14 units/week), preoperative fever, preoperative nausea/vomiting, gallbladder wall thickness (GWT), pericholecystic fluid collection, stone impaction, time from onset to surgery, anesthesia method, anesthesia duration, surgical approach, operative time, intraoperative blood loss, intraoperative gallbladder rupture, intraoperative stone spillage, intraoperative drain tube placement (IDTP), Tokyo Guidelines 2018 grade (TG18),²¹ Generalized Anxiety Disorder-7 (GAD-7) score,²² Patient Health Questionnaire-9 (PHQ-9) score,²³ Athens Insomnia Scale (AIS) score;²⁴ laboratory indicators included white blood cell count (WBC), neutrophil percentage (NEUT%), hemoglobin (Hb), albumin (ALB), C-reactive protein (CRP), procalcitonin (PCT), total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total bilirubin (TBIL), direct bilirubin (DBIL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), prothrombin time (PT), and international normalized ratio (INR).

Pain Assessment and Grouping

Postoperative pain was assessed using the VAS according to Huskisson.²⁵ Patients marked their pain intensity on a 100 mm horizontal line (0 = no pain, 100 = worst imaginable pain) preoperatively, and at 24 and 48 hours postoperatively, in a quiet environment. The distance from the zero point to the mark was measured to the nearest 1 mm and recorded as a score from 0 to 10. Patients were classified into the mild pain (MP) group (VAS <4) or MSP group (VAS ≥4) based on the 24-hour postoperative score.²⁶

Serum CX3CL1 and TSLP Detection

Fasting venous blood samples were collected in the early morning preoperatively and at 24 and 48 hours postoperatively. After standing at room temperature for 1 hour, samples were centrifuged at 1000 × g for 20 minutes to obtain serum. Serum CX3CL1 and TSLP levels were measured by ELISA using commercial kits (CX3CL1: E-EL-H0044; TSLP: E-EL-H1598; Elabscience Biotechnology Co., Ltd., Wuhan, China) according to the manufacturer’s instructions. Optical density (OD) was measured at 450 nm using a microplate reader (iMark, Bio-Rad, Hercules, CA, USA). All samples were assayed in duplicate with a coefficient of variation (CV) <10%, and mean values were used for analysis. Measurements were performed by a technician blinded to clinical data.

Statistical Methods

Statistical analysis was performed using SPSS 26.0 and R software (version 4.3.1). Continuous variables with normal distribution were expressed as mean ± standard deviation and compared using the t-test; non-normally distributed variables were expressed as median (interquartile range) and compared using the Mann–Whitney U-test. Categorical variables were expressed as count (percentage) and compared using the χ²-test. P < 0.05 was considered statistically significant. The final cohort of 379 patients had complete data with no missing values for any analyzed variables; accordingly, a complete-case analysis was performed, and sensitivity analyses such as multiple imputation were not conducted. Spearman correlation analysis was used to assess correlations between preoperative serum CX3CL1 and TSLP levels and inflammatory markers as well as postoperative pain. Receiver operating characteristic (ROC) curves were constructed to evaluate the predictive performance of CX3CL1 and TSLP for moderate-to-severe pain. Multivariate logistic regression was performed to identify independent risk factors. A nomogram was constructed using the rms package in R. The cohort was randomly divided into a training set (n=265) and a validation set (n=114) at a 7:3 ratio. Model discrimination was assessed using ROC curves, calibration by the Hosmer-Lemeshow test and calibration curves, and clinical utility by decision curve analysis (DCA).

Results

Comparison of Preoperative Baseline Characteristics and Clinical Indicators Between the MP and MSP Groups

A total of 379 LC patients were enrolled, of whom 118 developed MSP at 24 hours postoperatively. Compared with the MP group, the MSP group had significantly higher GWT, longer time from onset to surgery, and elevated preoperative VAS, GAD-7, PHQ-9, AIS, and CRP levels (all P < 0.001). The proportions of IDTP and TG18 grade II–III were also significantly greater in the MSP group (all P<0.001). Additionally, the MSP group showed significantly greater postoperative PCIA bolus demands, higher total PCIA consumption, and a higher rate of rescue analgesia than the MP group (all P < 0.001) (Table 1).

Table 1.

Comparison of Preoperative Baseline Characteristics and Clinical Indicators Between the MP and MSP Groups

Variables	MP Group (n=261)	MSP Group (n=118)	t/Z/χ2	P
Gender [n (%)]			0.795*	0.373
Male	110 (42.15)	44 (37.29)
Female	151 (57.85)	74 (62.71)
Age [M (P25, P75), years]	53 (49, 57)	54 (49, 59)	−1.025ˆ	0.305
BMI (kg/m2, ±s)	23.25 ± 1.94	23.52 ± 2.04	−1.238#	0.216
Hypertension [n (%)]	71 (27.20)	39 (33.05)	1.349*	0.245
Diabetes [n (%)]	50 (19.16)	26 (22.03)	0.419*	0.517
Smoking history [n (%)]	65 (24.90)	34 (28.81)	0.644*	0.422
Alcohol consumption history [n (%)]	55 (21.07)	28 (23.73)	0.335*	0.563
Preoperative fever [n (%)]	123 (47.13)	63 (53.39)	1.276*	0.259
Preoperative nausea/vomiting [n (%)]	177 (67.82)	85 (72.03)	0.677*	0.410
GWT [M (P25, P75), mm]	4 (3, 4.5)	4 (3, 5)	−4.326ˆ	<0.001
Pericholecystic fluid collection [n (%)]	88 (33.72)	46 (38.98)	0.986*	0.321
Stone impaction [n (%)]	53 (20.31)	29 (24.58)	0.874*	0.350
Time from onset to surgery [M (P25, P75), h]	33 (27, 40)	38 (26, 46)	−2.444ˆ	<0.001
Anesthesia method [n (%)]			1.666*	0.197
General anesthesia	214 (81.99)	103 (87.29)
General anesthesia + epidural anesthesia	47 (18.01)	15 (12.71)
Anesthesia duration (min, ±s)	91.24 ± 17.78	93.58 ± 18.10	−1.181#	0.238
Surgical approach [n (%)]			2.594*	0.107
Conventional LC	243 (93.10)	104 (88.14)
Single-incision LC	18 (6.90)	14 (11.86)
Operative time (min, ±s)	72.30 ± 13.57	73.77 ± 14.20	−0.962#	0.337
Intraoperative blood loss (mL, ±s)	42.60 ± 11.08	44.31 ± 10.35	−1.418#	0.157
Intraoperative gallbladder rupture [n (%)]	36 (13.79)	24 (20.33)	2.613*	0.106
Intraoperative stone spillage [n (%)]	18 (6.90)	15 (12.71)	3.457*	0.063
IDTP [n (%)]	91 (34.87)	61 (51.69)	9.581*	0.002
TG18 grade [n (%)]			16.394*	<0.001
Grade I	158 (60.54)	45 (38.14)
Grade II–III	103 (39.46)	73 (61.86)
PreoperativeVAS [M (P25, P75), points]	3 (2, 3)	4 (3, 5)	−6.878ˆ	<0.001
GAD-7 [M (P25, P75), points]	9 (7, 10)	10 (8, 11)	−3.604ˆ	<0.001
PHQ-9 [M (P25, P75), points]	7 (6, 8)	8 (6, 9)	−2.316ˆ	<0.001
AIS [M (P25, P75), points]	6 (6, 7)	7 (6, 8)	−3.615ˆ	<0.001
WBC [M (P25, P75), ×109/L]	9.3 (8.2, 10.1)	9.4 (8.3, 10.5)	−1.490ˆ	0.136
NEUT% (%, ±s)	77.85 ± 7.36	78.73 ± 7.17	−1.084#	0.279
Hb (g/L, ±s)	132.40 ± 17.77	129.56 ± 19.25	1.403#	0.161
ALB [M (P25, P75), g/L]	41 (38, 44)	41 (38, 43)	−0.714ˆ	0.475
CRP [M (P25, P75), mg/L]	49 (45, 54)	56 (52, 61)	−7.820ˆ	<0.001
PCT [M (P25, P75), ng/mL]	0.30 (0.25, 0.36)	0.33 (0.24, 0.39)	−1.768ˆ	0.077
TC (mmol/L, ±s)	4.38 ± 0.91	4.43 ± 0.96	−0.537#	0.592
TG [M (P25, P75), mmol/L]	1.75 (1.71, 1.80)	1.76 (1.72, 1.80)	−0.925ˆ	0.355
LDL-C [M (P25, P75), mmol/L]	2.8 (2.4, 3.0)	2.6 (2.3, 3.0)	−1.217ˆ	0.224
HDL-C [M (P25, P75), mmol/L]	1.19 (1.13, 1.25)	1.18 (1.13, 1.24)	−1.028ˆ	0.304
TBIL [M (P25, P75), μmol/L]	23 (18, 26)	23 (19, 27)	−0.636ˆ	0.525
DBIL [M (P25, P75), μmol/L]	7 (6, 8)	7 (6, 9)	−1.333ˆ	0.182
ALT (U/L, ±s)	47.90 ± 9.37	49.73 ± 10.24	−1.708#	0.088
AST [M (P25, P75), U/L]	39 (33, 46)	41 (34, 49)	−1.753ˆ	0.080
GGT [M (P25, P75), U/L]	47 (40, 54)	48 (40, 58)	−1.055ˆ	0.292
PT [M (P25, P75), s]	13 (12, 14)	13 (12, 14)	−0.940ˆ	0.347
INR (±s)	1.07 ± 0.14	1.10 ± 0.18	−1.775#	0.077
Postoperative PCIA bolus demands [M (P25, P75), times]	2 (1, 3)	4 (2, 6)	−7.768ˆ	<0.001
Postoperative PCIA total consumption [M (P25, P75), mL]	52 (48, 56)	60 (54, 68.25)	−9.073ˆ	<0.001
Rescue analgesia [n (%)]			47.29*	<0.001
No	246 (94.25)	80 (67.80)
Yes	15 (5.75)	38 (32.20)

Notes: * denotes χ² value; ˆ denotes Z value; # denotes t value. Postoperative PCIA bolus demands, total consumption, and rescue analgesia rate are derivative indicators of postoperative pain severity and were used for descriptive intergroup comparison only; they were not included in subsequent multivariate regression analyses.

Abbreviations: BMI, body mass index; GWT, gallbladder wall thickness; LC, laparoscopic cholecystectomy; IDTP, intraoperative drain tube placement; TG18, Tokyo Guidelines 2018 grade; VAS, visual analog scale; GAD-7, Generalized Anxiety Disorder-7; PHQ-9, Patient Health Questionnaire-9; AIS, Athens Insomnia Scale; WBC, white blood cell count; NEUT%, neutrophil percentage; Hb, hemoglobin; ALB, Albumin; CRP, C-reactive protein; PCT, procalcitonin; TC, total cholesterol; TG, triglycerides; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TBIL, total bilirubin; DBIL, direct bilirubin; ALT, alanine aminotransferase; AST, aspartate aminotransferase; GGT, gamma-glutamyl transferase; PT, prothrombin time; INR, international normalized ratio; MP, mild pain; MSP, moderate-to-severe postoperative pain; PCIA, patient-controlled intravenous analgesia.

Dynamic Changes in Preoperative and Postoperative Serum CX3CL1, TSLP Levels, and VAS Scores in the Overall Cohort

In the overall cohort, serum CX3CL1 and TSLP levels showed consistent trends: both increased significantly at 24 hours postoperatively compared with preoperative levels, and subsequently decreased significantly at 48 hours postoperatively (all P<0.001, Figure 2A and B). The VAS score increased significantly at 24 hours postoperatively compared with the preoperative level, and was significantly higher at 24 hours than at 48 hours postoperatively (all P<0.05, Figure 2C).

Figure 2.

Dynamic changes in perioperative serum CX3CL1, TSLP levels, and VAS scores in the overall cohort. (A) Dynamic changes in serum CX3CL1 levels in the overall cohort preoperatively, at 24 hours postoperatively, and at 48 hours postoperatively; (B) Dynamic changes in serum TSLP levels in the overall cohort preoperatively, at 24 hours postoperatively, and at 48 hours postoperatively; (C) Dynamic changes in VAS scores in the overall cohort preoperatively, at 24 hours postoperatively, and at 48 hours postoperatively. *P < 0.05, ***P < 0.001.

Comparison of Preoperative Serum CX3CL1 and TSLP Levels Between the MP and MSP Groups

Preoperative serum CX3CL1 and TSLP levels were significantly higher in the MSP group than in the MP group (CX3CL1: Z=−8.314, P<0.001; TSLP: Z=−8.848, P<0.001) (Figure 3).

Figure 3.

Comparison of preoperative serum CX3CL1 and TSLP levels between the MP and MSP groups. (A) Comparison of preoperative serum CX3CL1 between the MP and MSP groups (Z=−8.314, P < 0.001); (B) Comparison of preoperative serum TSLP between the MP and MSP groups (Z=−8.848, P < 0.001). ***P < 0.001.

Correlation Analysis of Preoperative Serum CX3CL1 and TSLP Levels with Inflammatory Indicators and Postoperative Pain

Spearman correlation analysis showed a positive correlation between preoperative serum CX3CL1 and TSLP levels (r=0.477, P<0.001). Both CX3CL1 and TSLP showed moderate positive correlations with preoperative CRP (CX3CL1: r=0.456, P<0.001; TSLP: r=0.431, P<0.001) and with the 24-hour postoperative VAS score (CX3CL1: r=0.434, P<0.001; TSLP: r=0.410, P<0.001) (Figure 4).

Figure 4.

Scatter plots of preoperative serum CX3CL1 and TSLP levels with CRP and the 24-hour postoperative VAS score. (A) Correlation between CX3CL1 and TSLP (r=0.477, P < 0.001); (B) Correlations of CX3CL1 and TSLP with CRP (r=0.456, 0.431, both P < 0.001); (C) Correlations of CX3CL1 and TSLP with the 24-hour postoperative VAS score (r=0.434, 0.410, P < 0.001).

ROC Analysis of Preoperative Serum CX3CL1 and TSLP Levels for Predicting Postoperative MSP

ROC curve analysis showed that the area under the curve (AUC) for serum CX3CL1 and TSLP alone in predicting postoperative MSP was 0.761 (0.707–0.814) and 0.784 (0.733–0.835), respectively. When the two biomarkers were combined, the AUC increased to 0.860 (0.819–0.900), with specificity higher than that of each individual indicator (Table 2 and Figure 5).

Table 2.

Predictive Efficacy of CX3CL1 and TSLP Levels Alone and in Combination for Postoperative MSP

Variable	Cut-Off value	AUC	Sensitivity	Specificity	P value	95% CI
CX3CL1	4.360 ng/mL	0.761	72.03	69.35	<0.001	0.707–0.814
TSLP	0.985 ng/mL	0.784	67.80	77.39	<0.001	0.733–0.835
CX3CL1 + TSLP	-	0.860	66.10	90.42	<0.001	0.819–0.900

Abbreviations: CX3CL1, C-X3-C motif chemokine ligand 1; TSLP, Thymic stromal lymphopoietin.

Figure 5.

ROC curves of CX3CL1, TSLP alone and in combination for predicting postoperative MSP.

Multivariable Logistic Regression Analysis of Factors Influencing Postoperative MSP

Postoperative MSP at 24 hours was used as the dependent variable (MP=0; MSP=1). Statistically significant variables from univariate analysis—GWT, time from onset to surgery, IDTP, TG18 grade, GAD-7, PHQ-9, AIS, CRP, CX3CL1 level, and TSLP level—were included as independent variables (the preoperative VAS score was a diagnostic symptom indicator of acute cholecystitis, exhibiting collinearity with disease severity parameters and thus not an independent preoperative predictor; therefore, it was excluded). Multivariate logistic regression analysis showed that the variance inflation factor (VIF) for all predictors was <2, indicating no multicollinearity in the model. Increased GWT (OR=1.430, 95% CI: 1.122–1.822), increased time from onset to surgery (OR=1.032, 95% CI: 1.005–1.059), IDTP (OR=2.221, 95% CI: 1.239–3.981), TG18 grade II–III (OR=2.217, 95% CI: 1.248–3.939), increased GAD-7 (OR=1.212, 95% CI: 1.071–1.371), increased PHQ-9 (OR=1.180, 95% CI: 1.010–1.378), increased AIS (OR=1.205, 95% CI: 1.017–1.428), increased CRP (OR=1.081, 95% CI: 1.031–1.134), increased CX3CL1 level (OR=1.471, 95% CI: 1.070–2.020), and increased TSLP level (OR=1.259, 95% CI: 1.098–1.444) were all independent risk factors for postoperative MSP (P<0.05) (Table 3). Additionally, sensitivity analysis showed that with additional adjustment for postoperative PCIA bolus demands, total consumption, and rescue analgesia based on the main model, both CX3CL1 (OR=1.701, 95% CI: 1.094–2.644, P=0.018) and TSLP (OR=1.266, 95% CI: 1.013–1.583, P=0.038) remained independent predictors of moderate-to-severe postoperative pain, supporting the robustness of the main findings.

Table 3.

Multivariable Logistic Regression Analysis of Factors Influencing MSP at 24 Hours After LC

Variable	β	S.E	Walds	P	OR	95% CI	VIF
GWT	0.358	0.124	8.370	0.004	1.430	1.122–1.822	1.048
Time to Operation	0.031	0.013	5.356	0.021	1.032	1.005–1.059	1.033
IDTP	0.798	0.298	7.180	0.007	2.221	1.239–3.981	1.018
TG18 Grade	0.796	0.293	7.368	0.007	2.217	1.248–3.939	1.032
GAD-7	0.192	0.063	9.260	0.002	1.212	1.071–1.371	1.030
PHQ-9	0.166	0.079	4.375	0.036	1.180	1.010–1.378	1.026
AIS	0.186	0.086	4.649	0.031	1.205	1.017–1.428	1.019
CRP	0.078	0.024	10.309	0.001	1.081	1.031–1.134	1.591
CX3CL1	0.386	0.162	5.663	0.017	1.471	1.070–2.020	1.791
TSLP	0.230	0.070	10.830	<0.001	1.259	1.098–1.444	1.767

Abbreviations: GWT, gallbladder wall thickness; IDTP, intraoperative drain tube placement; TG18, Tokyo Guidelines 2018 grade; GAD-7, Generalized Anxiety Disorder-7; PHQ-9, Patient Health Questionnaire-9; AIS, Athens Insomnia Scale; CRP, C-reactive protein; CX3CL1, C-X3-C motif chemokine ligand 1; TSLP, Thymic stromal lymphopoietin.

Construction of the Nomogram Model

Based on the independent risk factors identified through multivariate logistic regression, a nomogram was developed to predict the risk of postoperative MSP (Figure 6). In the nomogram, the score for each influencing factor and the total score can be calculated according to the patient’s clinical data, thereby yielding the predicted probability of MSP. The discriminative ability of the nomogram model was evaluated using ROC curves. The results showed an AUC of 0.859 (0.813–0.905) in the training set and 0.892 (0.819–0.966) in the validation set (Figure 7). The AUCs in both the training and validation sets exceeded 0.7, indicating good predictive performance of the model. Calibration was assessed using calibration curves and the Hosmer-Lemeshow test. The results showed that P values in both the training and validation sets were >0.05 (training set: χ²=10.635, P=0.223; validation set: χ²=5.716, P=0.421), suggesting good model fit. However, the calibration curve of the validation set showed some fluctuation in the low-risk interval (predicted probability <0.2), with overall calibration slightly inferior to that of the training set (Figure 8A and B). Clinical utility was evaluated using DCA. The results showed that when threshold probabilities ranged from 0.09–0.91 in the training set and 0.05–0.88 in the validation set, the net benefit of this model was significantly higher than that of other strategies, indicating favorable potential for clinical application (Figure 9A and B).

Figure 6.

Nomogram model for predicting postoperative MSP.

Figure 7.

ROC curves of the nomogram model.

Figure 8.

Calibration curves of the nomogram model. (A) training set; (B) validation set.

Figure 9.

Decision curves of the nomogram model. (A) training set; (B) validation set.

Discussion

The results showed that preoperative serum CX3CL1 and TSLP levels were significantly elevated in the moderate-to-severe pain group; both were positively correlated with CRP and postoperative VAS scores, and their combined predictive performance was favorable. Multivariable analysis confirmed that both were independent risk factors for MSP. The nomogram model constructed accordingly exhibited good discrimination, calibration, and clinical effectiveness in internal validation, suggesting its potential predictive application value; however, external validation and prospective interventional studies are still required to confirm its clinical utility.

This study showed that GWT, time from onset to surgery, IDTP, TG18 grade, GAD-7, PHQ-9, AIS, and CRP were all independent risk factors for postoperative MSP. The reasons are analyzed as follows: GWT reflects aggravated local inflammation and fibrosis, which is closely associated with increased surgical difficulty and tissue injury, thereby promoting postoperative pain;²⁷ prolonged time from onset to surgery and elevated CRP reflect local inflammatory progression and systemic inflammatory burden, respectively, which synergistically promote inflammatory mediator release and peripheral and central sensitization, exacerbating postoperative pain.²⁸ IDTP, as an additional invasive stimulus, can aggravate local pain and inflammatory responses, whereas sleep disorders impair the body’s pain regulatory capacity.⁸ Furthermore, higher TG18 grades indicate more severe disease and greater surgical trauma, with a concomitant increase in the risk of adverse postoperative outcomes;²⁹ anxiety and depression lower the pain threshold and amplify pain perception through central modulation, jointly aggravating postoperative pain.³⁰ The above multifactorial interplay constitutes a complex pathological network of postoperative pain, suggesting that clinical management should integrate inflammation control, optimization of surgical timing, and psychological and sleep interventions.

CX3CL1 is a membrane-associated protein with both chemokine and adhesion molecule properties, whereas TSLP is a key inflammatory cytokine derived from epithelial cells; both play important roles in immune-inflammatory responses and neuroimmune interactions.^31,32 Studies have shown that the CX3CL1/CX3CR1 signaling axis is significantly upregulated in postoperative pain, spinal cord injury, and trigeminal neuropathic pain models, driving pain and central sensitization through astrocyte activation, promotion of proinflammatory cytokine release, and induction of GABAergic system dysfunction; blockade of this axis effectively ameliorates pathological changes.^33–36 On the other hand, the role of TSLP in inflammatory diseases and pain regulation has also received increasing attention. Studies have shown that TSLP can drive glial cell reactivity, neuronal apoptosis, and inflammatory cascades in the spinal cord and dorsal root ganglia through activation of the TSLPR/STAT5 signaling pathway, and synergize with transient receptor potential vanilloid 1 (TRPV1) channels to promote the development of mechanical hyperalgesia.^37–40 Although the above evidence suggests that both CX3CL1 and TSLP are closely associated with inflammatory pain, clinical studies in LC postoperative pain remain relatively scarce.

This study found that preoperative CX3CL1 and TSLP levels were significantly higher in the MSP group than in the MP group; the two biomarkers were positively correlated with each other and both were positively correlated with CRP levels, suggesting that they may jointly participate in perioperative inflammatory responses and influence the severity of postoperative pain. Multivariable logistic regression further showed that, after full adjustment for traditional clinical risk factors, including gallbladder wall thickness, onset-to-surgery time, IDTP, TG18 grade, GAD-7, PHQ-9, AIS, and CRP, CX3CL1 and TSLP remained independent predictors of MSP, suggesting that they provide additional risk information beyond conventional clinical indicators and may contribute to improved precision in preoperative risk stratification. It is hypothesized that under the condition of acute cholecystitis, local inflammatory responses may induce increased release of CX3CL1 and TSLP into the peripheral blood. CX3CL1 may promote monocyte/macrophage chemotaxis and proinflammatory mediator release through its receptor CX3CR1, whereas TSLP may activate type 2 immune responses and enhance sensory neuron sensitivity; the two may synergistically amplify peripheral inflammation-neural interactions. Previous studies also support the above mechanisms: the CX3CL1/CX3CR1 axis participates in the development of postoperative pain, whereas TSLP can promote inflammatory responses and nociceptive sensitization, and inhibition of either can alleviate pain, providing mechanistic references for this study.^16,41–43 However, this evidence is primarily derived from animal experiments; whether the serum level changes observed in this study correspond to the above effects at local tissue or central levels remains to be further validated.

From a clinical translation perspective, first, both CX3CL1 and TSLP are serum indicators detectable by standardized ELISA, with relatively controllable costs and mature technology, making them feasible for implementation in primary hospitals. A single preoperative blood collection can provide predictive information without additional invasive procedures, with ELISA results typically available within 24 hours, meeting the requirements of perioperative point-of-care testing. Second, the nomogram model constructed based on the above indicators integrates inflammatory burden (CRP), local lesion severity (GWT, TG18 grade), surgical invasiveness indicators (IDTP), and psychological and sleep status (GAD-7, PHQ-9, AIS), enabling multidimensional risk stratification. This facilitates anesthesiologists and surgeons in formulating individualized analgesic protocols preoperatively—for example, pre-emptive multimodal analgesic strategies for high-risk patients, optimization of epidural block timing, or enhanced follow-up by the acute pain service (APS). Furthermore, as key mediators of inflammation-neural interactions, preoperative levels of CX3CL1 and TSLP may reflect patients’ pre-existing neuroimmune sensitization status, and may in the future guide the selection of targeted anti-inflammatory analgesic drugs, providing biomarker support for the transition from “empirical analgesia” to “mechanism-oriented precision analgesia”. However, it should be objectively recognized that incorporating these biomarkers into routine assessment still faces practical challenges: the standardization of ELISA assays, quality control systems, and reference intervals remains to be harmonized, and the cost-effectiveness of large-scale application remains unevaluated. Moreover, the availability and operational standardization of current testing procedures across medical institutions at different levels still vary, and their clinical translation requires further confirmation through external validation.

This study has the following limitations. First, the nomogram model underwent only single-center internal validation without multicenter external validation; the relatively high homogeneity and limited sample size of the single-center cohort carry a risk of model overfitting, and generalizability remains to be further confirmed. Second, pain assessment relied solely on the subjective VAS score, which carries a risk of reporting bias; future studies may benefit from integrating objective pain-related physiological indicators (eg, heart rate variability, dynamic inflammatory biomarker monitoring) for comprehensive validation. Postoperative analgesic consumption was not included as a covariate in the main model, given that all patients received a uniform analgesic protocol and postoperative opioid use is largely a downstream consequence of pain severity rather than an independent confounder. A sensitivity analysis additionally adjusting for postoperative PCIA bolus demands, total consumption, and rescue analgesia showed that CX3CL1 and TSLP remained significant independent predictors, supporting the robustness of the main findings. Third, the detection time points for CX3CL1 and TSLP were limited to preoperative, 24-hour postoperative, and 48-hour postoperative time points, lacking dynamic monitoring data at longer postoperative time windows (eg, 72 hours or 7 days), precluding assessment of their association with chronic postsurgical pain (CPSP). Fourth, the association between serum level changes and molecular mechanisms at local tissue (eg, gallbladder wall, dorsal root ganglia) or central spinal cord levels is speculative, lacking validation through animal experiments or transcriptomics. Fifth, this study did not strictly quantify the incremental predictive value of these two biomarkers through nested model comparisons or metrics such as the net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Sixth, this study evaluated only acute pain at 24 hours postoperatively and did not record complication rates at 30 and 90 days postoperatively (the Clavien–Dindo classification was not adopted), precluding a comprehensive reflection of the postoperative course. Future prospective multicenter studies with expanded sample sizes are needed, integrating genomic/metabolomic data, and animal models are required to elucidate the specific regulatory mechanisms of the CX3CL1/CX3CR1 and TSLPR/STAT5 pathways in LC postoperative pain, to facilitate the transformation of this predictive model into a clinical decision-making tool.

In conclusion, elevated preoperative serum CX3CL1 and TSLP levels may be associated with an increased risk of MSP following LC in patients with acute cholecystitis, and combined detection of these biomarkers may help identify high-risk populations for postoperative pain.

Funding Statement

This work was supported by the Medical Science Research Project of Hebei (Grant No. 20241253).

Data Sharing Statement

The datasets used and/or analyzed in the current study are available from the corresponding author upon reasonable request.

Ethical Statement

This study was approved by the Ethics Committee of the Second Hospital of Hebei Medical University (Approval No. 2023R452) and adheres to the principles outlined in the Declaration of Helsinki. Written informed consent was obtained from all participants, ensuring their confidentiality and anonymity throughout the research process.

Disclosure

The authors report no conflicts of interest in this work.