Nomogram integrating systemic immune-inflammation index and blood lipid ratio to predict postoperative gastrointestinal dysfunction in elderly gallstone patients

Abstract

BACKGROUND

Gastrointestinal dysfunction is a common complication in elderly patients with cholelithiasis after undergoing laparoscopic cholecystectomy, and it can markedly hinder postoperative recovery. The systemic immune-inflammation index (SII) and the total cholesterol (TC)/high-density lipoprotein cholesterol ratio (HDL-C) may reflect the underlying inflammatory and metabolic states associated with postoperative outcomes. However, the combined predictive value of these two indicators remains unclear.

AIM

To develop a nomogram based on SII and TC/HDL-C for predicting poor postoperative gastrointestinal function in elderly patients with gallstones.

METHODS

In this retrospective cohort study, 123 elderly patients with cholelithiasis from Hefei BOE Hospital were included and randomly assigned to the modeling cohort (n = 86) and the validation cohort (n = 37) in a 7:3 ratio. Gastrointestinal function was evaluated 30 days after surgery. Risk factors were identified using binary logistic regression. A nomogram was then constructed, and its performance was evaluated using the area under the curve, calibration curve, and decision curve analysis.

RESULTS

In the modeling cohort, TC/HDL-C, SII, operation time, TC, neutrophil count, lymphocyte count, gallbladder wall thickness > 5 mm, and postoperative ambulation time ≥ 1 day were significantly higher in the poor gastrointestinal function group than in the good function group (P < 0.05). Logistic regression analysis identified TC/HDL-C [odds ratio (OR) = 1.628, 95% confidence interval (CI): 1.378-1.869], SII (OR = 3.411, 95%CI: 1.763-5.509), gallbladder wall thickness (OR = 1.524, 95%CI: 1.167-1.881), operation time (OR = 2.406, 95%CI: 1.858-2.954), and postoperative ambulation time (OR = 3.457, 95%CI: 1.109-5.805) as independent risk factors for postoperative gastrointestinal dysfunction. The area under the curves of the nomogram in the modeling and validation cohorts were 0.889 and 0.828, respectively. The calibration and decision curves indicated that the model demonstrated good consistency and clinical utility.

CONCLUSION

The nomogram model developed based on the SII and TC/HDL-C provides a reliable tool for preoperative risk stratification and may assist in guiding individualized perioperative management.

Key Words: Systemic immune-inflammation index; Total cholesterol to high-density lipoprotein cholesterol ratio; Gallstones; Gastrointestinal function; Nomogram

Core Tip: A nomogram was built in the current research to forecast unsatisfactory gastrointestinal performance after surgery in aged patients with gallstones. The constructed nomogram includes the systemic immune-inflammation index, the ratio of total cholesterol to high-density lipoprotein cholesterol, gallbladder wall thickness, operative duration, and the timing of ambulation after surgery. This tool showed strong predictive accuracy, with an area under the curve of 0.889 in the training cohort and 0.828 in the validation cohort. It also provided well-calibrated estimates and offered practical clinical benefit, thereby supporting the early recognition of individuals at elevated risk for the purpose of delivering focused interventions.

INTRODUCTION

According to epidemiological findings, gallstones affect around 5% to 25% of the adult population across European and American nations. The likelihood of developing gallstones rises markedly as age advances, with older individuals facing a risk roughly 4 times to 10 times greater than that observed in the general adult population[1]. Elderly individuals frequently exhibit clinical signs that are either atypical or nonspecific, making them prone to being missed. As a consequence, delays in both diagnosis and intervention can occur, potentially leading to complications like biliary pancreatitis and cholangitis, which in turn seriously diminish their quality of life[2]. Laparoscopic cholecystectomy now represents the mainstay of clinical care for gallstones. Still, postsurgical gastrointestinal issues arise frequently in this patient group. According to reports, around 62.86% of individuals suffer from postsurgical discomforts like nausea and vomiting, which delays their recovery[3]. Thus, spotting high-risk cases early and delivering tailored interventions are key to enhancing gastrointestinal recovery and improving long-term outcomes in older adults. The systemic immune-inflammation index (SII) is a broad marker for evaluating systemic inflammation and has shown meaningful clinical relevance in hepatobiliary surgery[4]. Likewise, the total cholesterol (TC)-to-high-density lipoprotein cholesterol ratio (HDL-C) ratio serves as an integrated lipid measure that captures both cardiovascular risk and a fuller picture of lipid metabolism[5]. Based on this, the present work hypothesizes that the systemic inflammatory load indicated by SII and the lipid disturbance captured by the TC/HDL-C ratio might jointly drive the pathophysiological processes leading to poor postsurgical gastrointestinal outcomes in older gallstone patients. Nevertheless, few studies have explored how SII and TC/HDL-C jointly affect gastrointestinal recovery after surgery in this specific group. Therefore, this study aims to systematically evaluate the predictive value of preoperative SII and TC/HDL-C for postoperative gastrointestinal function recovery in elderly patients with gallstones by constructing a nomogram prediction model, thereby providing a reference for the early identification of high-risk patients and the implementation of individualized clinical interventions.

MATERIALS AND METHODS

Study objects

A total of 123 elderly patients with gallstones who underwent laparoscopic cholecystectomy at Hefei BOE Hospital from January 2021 to June 2023 were enrolled. They were divided into a modeling cohort (n = 86) and a model validation cohort (n = 37) in a 7:3 ratio.

Inclusion criteria: (1) Meeting the diagnostic criteria for gallstones with confirmation by imaging[6]; (2) Age ≥ 60 years; (3) All were undergoing laparoscopic cholecystectomy for the first time at our hospital; (4) Ability to complete at least one month of follow-up through regular hospital visits or telephone contact, with complete clinical data; (5) No history of mental illness, with good compliance; and (6) No contraindications to laparoscopic cholecystectomy.

Exclusion criteria: (1) Presence of coagulation disorders; (2) Recent history of diuretic use or other relevant medications; (3) Participation in other clinical interventional studies prior to enrollment; (4) Severe hepatic or renal dysfunction; and (5) Complicated by severe biliary diseases, gastrointestinal diseases, or other conditions that may interfere with this study.

Sample size calculation: This study employed the sample size formula for multivariate correlation research: N = U_αS/β[7]. Based on preliminary tests, Uα = 1.96 and S/β = 5.66, resulting in a sample size of n = 123.

Methods

Data collection: Preoperative data were collected for all patients through the electronic medical record system. The collected information included: Patient demographic characteristics (age, gender, body mass index), lifestyle habits (alcohol consumption history, breakfast and exercise habits), disease characteristics (stone diameter, number of stones, and gallbladder wall thickness), preoperative laboratory parameters (TC, triglycerides, HDL-C, low-density lipoprotein cholesterol, neutrophil count, lymphocyte count, and platelet count), as well as perioperative indicators (operation time and time to ambulation after surgery). The SII and TC/HDL-C ratio were calculated, with SII = (neutrophil count × platelet count)/Lymphocyte count.

Postoperative follow-up and grouping: All patients were followed up for one month postoperatively. Using a combination of outpatient review and telephone follow-up, trained researchers assessed the gastrointestinal function of elderly gallstone patients at 30 days post-surgery using the Intake, Feeling nauseated, Emesis, Physical Exam, and Duration of symptoms[8] comprehensive scoring system. The Intake, Feeling nauseated, Emesis, Physical Exam, and Duration of symptoms score comprises five components: Dietary intake, nausea, vomiting, abdominal physical examination, and symptom duration, each quantified as follows: (1) Dietary intake: Normal eating scores 0 points; restricted intake scores 1 point; inability to eat orally scores 3 points; (2) Nausea: Absent scores 0 points; mild and severe score 1 and 3 points, respectively; (3) Vomiting: Asymptomatic scores 0 points; vomiting volume < 100 mL scores 1 point; vomiting volume ≥ 100 mL scores 3 points; (4) Abdominal physical exam: No abdominal distention scores 0 points; significant distention without tympany scores 1 point; severe distention with definite tympany scores 3 points; and (5) Symptom duration: Resolution within 24 hours scores 0 points; persistence for 24-72 hours scores 1 point; persistence ≥ 72 hours scores 3 points. Patients with a total score ≥ 6 points were classified into the poor gastrointestinal function group, while those scoring below 6 points were classified into the good gastrointestinal function group. Consequently, the modeling cohort was divided into 37 patients in the poor gastrointestinal function group and 49 in the good gastrointestinal function group; the validation cohort was divided into 16 patients in the poor gastrointestinal function group and 21 in the good gastrointestinal function group.

Statistical analysis

Data processing and analysis in this study were performed using SPSS 27.0 and R software. Normality distribution for continuous variables was first assessed using the Shapiro-Wilk test. Measurement data conforming to a normal distribution are presented as (mean ± SD) and were compared using the t-test. Count data are expressed as n (%). Unordered categorical count data were analyzed using the χ² test or Fisher’s exact probability test, while ordered categorical count data were analyzed using the Mann-Whitney U test. Binary logistic regression was employed to analyze influencing factors. A nomogram prediction model was constructed, and its accuracy was evaluated based on the discriminative ability of the validation set and the calibration plot. The predictive ability of the model was further assessed using the area under the receiver operating characteristic (ROC) curve area under the curve (AUC). The calibration curve (verified by the Hosmer-Lemeshow test) and decision curve analysis were used to validate the model’s consistency and evaluate its discriminative ability. A P < 0.05 was considered the criterion for statistical significance.

RESULTS

Baseline clinical characteristics

A total of 123 elderly patients with gallstones were included in the study, comprising 86 in the modeling cohort and 37 in the validation cohort. The mean age of the patients was 69.84 ± 7.98 years, with 56 (45.53%) males and 67 (54.47%) females. No statistically significant differences were observed in the baseline clinical characteristics between the two cohorts (P > 0.05), as shown in Table 1.

Table 1 Comparison of baseline clinical characteristics between the modeling cohort and the model validation cohort, mean ± SD/n (%).

Indicator		Modeling cohort (n = 86)	Model validation cohort (n = 37)	t/χ2	P value
Age (years)		69.62 ± 6.65	69.24 ± 5.66	0.3031	0.762
Gender	Female	54 (62.79)	26 (70.27)	0.6362	0.425
	Male	32 (37.21)	11 (29.73)
Body mass index	< 18.5 kg/m2	26 (30.23)	13 (35.14)	0.3622	0.834
	18.5-24.0 kg/m2	33 (38.37)	14 (37.84)
	> 24.0 kg/m2	27 (31.40)	10 (27.03)
History of alcohol consumption		45 (52.33)	19 (51.35)	0.0102	0.921
Breakfast habit		44 (51.16)	21 (56.76)	0.3252	0.569
Exercise habit		49 (56.98)	17 (45.95)	1.2662	0.261
Stone diameter	≤ 1 cm	48 (55.81)	19 (51.35)	0.1612	0.698
	> 1 cm	38 (44.19)	18 (48.65)
Stone number	1 stone	52 (60.47)	17 (45.95)	2.2142	0.137
	> 3 stone	34 (39.53)	20 (54.05)
TC (mmol/L)		5.03 ± 0.33	5.10 ± 0.311	1.1721	0.244
HDL-C (mmol/L)		1.31 ± 0.15	1.33 ± 0.15	0.8091	0.420
SII		493.75 ± 84.19	483.71 ± 42.35	0.6881	0.493
TC/HDL-C		3.93 ± 0.75	3.90 ± 0.60	0.1991	0.843
Gallbladder wall thickness	> 5 mm	34 (39.53)	15 (40.54)	16.3982	0.089
	≤ 5 mm	52 (60.47)	22 (59.46)
Operation time (minutes)		34.92 ± 6.99	36.84 ± 6.35	1.4341	0.154
Neutrophil count (× 109/L)		3.98 ± 0.62	3.79 ± 0.58	1.5891	0.115
Lymphocyte count (× 109/L)		1.49 ± 0.41	1.36 ± 0.45	1.5661	0.120
Platelet count (× 109/L)		198.46 ± 32.93	199.67 ± 35.82	0.1821	0.856
TG (mmol/L)		1.32 ± 0.17	1.39 ± 0.23	1.8751	0.063
LDL-C (mmol/L)		2.89 ± 0.35	3.02 ± 0.32	1.9371	0.055
Time to ambulation after surgery	< 1 day	53 (61.63)	23 (62.16)	0.0032	0.955
	≥ 1 days	33 (38.37)	14 (37.84)

¹t-test.

²χ² test.

TC: Total cholesterol; HDL-C: High-density lipoprotein cholesterol ratio; SII: Systemic immune-inflammation index; TG: Triglycerides; LDL-C: Low-density lipoprotein cholesterol.

Comparison of clinical data in the modeling cohort

No statistically significant differences were found in age, gender, body mass index, history of alcohol consumption, breakfast habits, or other baseline indicators between the two groups in the modeling cohort (P > 0.05). However, significant differences were observed in TC, SII, TC/HDL-C ratio, gallbladder wall thickness, operation time, neutrophil count, lymphocyte count, and time to ambulation after surgery. The levels of TC (5.16 ± 0.37 mmol/L), TC/HDL-C (4.16 ± 1.00), SII (494.04 ± 26.74), operation time (37.84 ± 9.92 minutes), neutrophil count (3.84 ± 0.43 × 10⁹/L), and lymphocyte count (1.44 ± 0.20 × 10⁹/L), as well as the proportions of patients with gallbladder wall thickness > 5 mm (62.16%) and time to ambulation after surgery ≥ 1 day (78.38%), were all significantly higher in the poor gastrointestinal function group than in the good gastrointestinal function group (P < 0.05), as shown in Table 2.

Table 2 Comparison of clinical data between the poor and good gastrointestinal function groups in the modeling cohort, mean ± SD/n (%).

Indicator		Poor GI function group (n = 37)	Good GI function group (n = 49)	t/χ2	P value
Age (years)		69.46 ± 7.20	69.73 ± 6.28	0.1851	0.853
Gender	Female	25 (67.57)	29 (59.18)	0.6342	0.426
	Male	12 (32.43)	20 (40.82)
Body mass index	< 18.5 kg/m2	12 (32.43)	14 (28.57)	0.1662	0.920
	18.5-24.0 kg/m2	14 (37.84)	19 (38.78)
	> 24.0 kg/m2	11 (29.73)	16 (32.65)
History of alcohol consumption		15 (40.54)	30 (61.22)	3.6162	0.057
Breakfast habit		16 (43.24)	28 (57.14)	1.6302	0.202
Exercise habit		19 (51.35)	30 (61.22)	0.8382	0.360
Stone diameter	≤ 1 cm	20 (54.05)	28 (57.14)	0.0822	0.775
	> 1 cm	17 (45.95)	21 (42.86)
Stone number	1 stone	24 (64.86)	28 (57.14)	0.5262	0.468
	> 3 stone	13 (35.14)	21 (42.86)
TC (mmol/L)		5.16 ± 0.37	4.94 ± 0.26	2.9311	0.005
HDL-C (mmol/L)		1.28 ± 0.19	1.32 ± 0.10	1.4091	0.165
SII		494.04 ± 26.74	450.89 ± 20.41	8.7701	0.000
TC/HDL-C		4.16 ± 1.00	3.75 ± 0.40	2.3751	0.022
Gallbladder wall thickness	> 5 mm	23 (62.16)	11 (22.45)	28.2172	0.002
	≤ 5 mm	14 (37.84)	38 (77.55)
Operation time (minutes)			32.71 ± 1.08	3.1281	0.003
Neutrophil count (× 109/L)			3.26 ± 0.24	7.9521	0.000
Lymphocyte count (× 109/L)			1.32 ± 0.21	2.6781	0.009
Platelet count (× 109/L)			188.83 ± 24.95	0.9121	0.364
TG (mmol/L)			1.29 ± 0.18	1.9031	0.060
LDL-C (mmol/L)			2.84 ± 0.37	1.6981	0.093
Time to ambulation after surgery	< 1 day	16 (43.24)	37 (75.51)	9.2822	0.002
	≥ 1 days	21 (56.76)	12 (24.49)

¹t-test.

²χ² test.

TC: Total cholesterol; HDL-C: High-density lipoprotein cholesterol ratio; SII: Systemic immune-inflammation index; TG: Triglycerides; LDL-C: Low-density lipoprotein cholesterol; GI: Gastrointestinal.

Logistic regression analysis of risk factors for poor postoperative gastrointestinal function in elderly patients with gallstones

Binary logistic regression analysis was conducted using postoperative gastrointestinal function as the dependent variable, where poor function = 1 and good function = 0. Independent variables included factors that demonstrated statistically significant differences in the univariate analysis (TC, SII, TC/HDL-C ratio, gallbladder wall thickness, operation time, neutrophil count, lymphocyte count, and time to ambulation after surgery). The results indicated that TC/HDL-C [odds ratio (OR) = 1.628, 95% confidence interval (CI): 1.378-1.869], SII (OR = 3.411, 95%CI: 1.763-5.509), gallbladder wall thickness (OR = 1.524, 95%CI: 1.167-1.881), operation time (OR = 2.406, 95%CI: 1.858-2.954), and time to ambulation after surgery (OR = 3.457, 95%CI: 1.109-5.805) were independent risk factors for poor postoperative gastrointestinal function in elderly patients with gallstones (Table 3).

Table 3 Logistic regression analysis of risk factors for poor postoperative gastrointestinal function in elderly gallstone patients.

Factor	β	SE	Wald χ2	P value	OR	95%CI
						Lower limit	Upper limit
TC	2.154	0.108	34.824	0.534	1.563	0.888	2.238
SII	0.245	0.371	18.996	0.003	3.411	1.763	5.059
TC/HDL-C	3.416	0.327	12.072	0.025	1.628	1.387	1.869
Gallbladder wall thickness	1.909	0.373	26.524	0.046	1.524	1.167	1.881
Operation time	0.638	0.524	6.927	0.019	2.406	1.858	2.954
Neutrophil count	-0.375	0.635	5.374	0.542	1.542	0.793	2.291
Lymphocyte count	0.547	0.024	46.698	0.457	0.937	0.573	1.301
Time to ambulation after surgery	1.527	0.846	17.051	0.008	3.457	1.109	5.805

TC: Total cholesterol; SII: Systemic immune-inflammation index; HDL-C: High-density lipoprotein cholesterol ratio; OR: Odds ratio; CI: Confidence interval.

Nomogram model for predicting poor postoperative gastrointestinal function in elderly patients with gallstones

Based on the independent risk factors identified through binary logistic regression analysis - TC/HDL-C ratio, SII, gallbladder wall thickness, operation time, and time to ambulation after surgery - a nomogram prediction model for poor postoperative gastrointestinal function in elderly patients with gallstones was developed using R software (Figure 1A). The total score ranged from 0 point to 250 points, corresponding to a predicted probability between 0.10 and 0.99. A higher total score indicated a greater risk of poor postoperative gastrointestinal function. In the training cohort, the model showed solid discriminative ability. The ROC curve yielded an AUC of 0.889 (95%CI: 0.805-0.973), reflecting strong predictive power (Figure 1B). The calibration plot (Figure 1C) confirmed good alignment between predicted risks and observed outcomes. The Hosmer-Lemeshow test gave a χ² of 5.832 with a P value of 0.666, suggesting no meaningful discrepancy between the predicted probabilities and the actual observations - a finding that points to satisfactory model calibration. As shown by the decision curve (Figure 1D), for threshold probabilities between roughly 5% and 85%, applying the nomogram to inform clinical decisions yielded a higher net benefit compared with strategies that either treated every patient or treated none. This finding supports the model’s real-world clinical value across that range.

Figure 1 Construction and validation of a nomogram model for predicting postoperative gastrointestinal dysfunction in elderly patients with cholelithiasis using a modeling cohort. A: Nomogram model construction; B: Receiver operating characteristic curve; C: Calibration curve; D: Decision curve analysis. SII: Systemic immune-inflammation index; TC: Total cholesterol; HDL-C: High-density lipoprotein cholesterol ratio; AUC: Area under the curve.

Validation of the nomogram model

The clinical data of patients in the validation cohort (n = 37; Table 4) were used to validate the previously established nomogram model. ROC curve analysis demonstrated that the AUC of the nomogram model in the validation cohort was 0.828 (95%CI: 0.731-0.924; Figure 2A), indicating good predictive accuracy. To test the earlier constructed nomogram, clinical information from the 37 patients in the validation set was applied (Table 4). ROC curve assessment yielded an AUC of 0.828 (95%CI: 0.731-0.924) for the nomogram within the validation cohort (Figure 2A), reflecting sound predictive performance. As displayed in Figure 2B, the calibration plot demonstrated a high level of concordance between forecasted and actual risk levels. Meanwhile, the Hosmer Leme test returned a χ² of 1.784 with a P value of 0.987, indicating that any deviation between predicted figures and real observations lacked statistical significance. This outcome speaks to superb calibration of the model. Further evidence came from the decision curve shown in Figure 2C. Across a threshold probability span of roughly 10 percent to 89 percent, deployment of the nomogram within the validation set produced a net clinical benefit superior to both the treat everyone and the treat no one approaches. Thus, the model’s dependable performance for guiding clinical choices was confirmed as shown in Table 4.

Figure 2 Verifies the validation of the nomogram model by the validation queue. A: Receiver operating characteristic curve; B: Calibration curve; C: Decision curve analysis. AUC: Area under the curve.

Table 4 Comparison of clinical data between the poor and good gastrointestinal function groups in the validation cohort, mean ± SD/n (%).

Indicator		Poor GI function group (n = 16)	Good GI function group (n = 21)	t/χ2	P value
Age (years)		70.06 ± 6.61	68.62 ± 4.90	0.7611	0.451
Gender	Female	11 (68.75)	15 (71.43)	0.0312	0.859
	Male	5 (31.25)	6 (28.57)
Body mass index	< 18.5 kg/m2	6 (37.50)	7 (33.33)	0.0892	0.957
	18.5-24.0 kg/m2	6 (37.50)	8 (38.10)
	> 24.0 kg/m2	4 (25.00)	6 (28.57)
History of alcohol consumption		6 (37.50)	13 (61.90)	2.1652	0.141
Breakfast habit		6 (37.50)	15 (71.43)	4.2592	0.052
Exercise habit		6 (37.50)	11 (52.38)	0.8102	0.368
Stone diameter	≤ 1 cm	8 (50.00)	11 (52.38)	0.0212	1.000
	> 1 cm	8 (50.00)	10 (47.62)
Stone number	1 stone	5 (31.25)	12 (57.14)	2.4512	0.185
	> 3 stone	11 (68.75)	9 (42.86)
TC (mmol/L)		5.37 ± 0.24	4.89 ± 0.15	7.3871	0.000
HDL-C (mmol/L)		1.29 ± 0.16	1.35 ± 0.14	1.2061	0.236
SII		488.90 ± 17.59	450.76 ± 18.93	6.2571	0.000
TC/HDL-C		4.22 ± 0.63	3.65 ± 0.45	3.1671	0.000
Gallbladder wall thickness	> 5 mm	10 (62.50)	5 (23.81)	5.6392	0.023
	≤ 5 mm	6 (37.50)	16 (76.19)
Operation time (minutes)		38.94 ± 8.93	35.37 ± 6.59	2.1871	0.031
Neutrophil count (× 109/L)		3.89 ± 0.34	3.68 ± 0.16	2.4981	0.017
Lymphocyte count (× 109/L)		1.58 ± 0.12	1.42 ± 0.28	2.1361	0.040
Platelet count (× 109/L)		191.32 ± 14.79	180.69 ± 19.83	1.7951	0.081
TG (mmol/L)		1.52 ± 0.27	1.37 ± 0.24	1.7621	0.087
LDL-C (mmol/L)		3.15 ± 0.26	3.02 ± 0.35	1.1631	0.253
Time to ambulation after surgery	< 1 day	6 (37.50)	17 (80.95)	7.2902	0.015
	≥ 1 days	10 (62.50)	4 (19.05)

¹t-test.

²χ² test.

TC: Total cholesterol; HDL-C: High-density lipoprotein cholesterol ratio; SII: Systemic immune-inflammation index; TG: Triglycerides; LDL-C: Low-density lipoprotein cholesterol; GI: Gastrointestinal.

DISCUSSION

Recent years have seen steady progress in medical technology, which has greatly enhanced the overall success rates of surgical procedures for gallstones[9]. Nonetheless, pulling or irritating the digestive tract during an operation can still lower bowel movement efficiency in certain individuals. Such effects may trigger multiple forms of postsurgical gut dysfunction, which in turn harm both nutrition levels and the healing process[10]. Older individuals face this issue more often because their bodily functions worsen as they grow older. As a result, poor gut recovery after surgery can greatly lower their life quality. The SII serves as a combined marker for both systemic inflammation and immune condition. Meanwhile, the TC to HDL-C ratio offers a broad view of lipid processing in the body. Used together, these two indexes can usefully capture a person’s overall metabolic state. However, their combined predictive value for postoperative gastrointestinal dysfunction in elderly patients with gallstones has not been fully elucidated. Therefore, this study investigated the predictive effects of preoperative SII and TC/HDL-C on postoperative gastrointestinal function recovery in elderly patients with gallstones and developed a nomogram model based on these indicators to provide a reference for individualized clinical assessment and management.

Results of this study showed that, in the modeling cohort, significant differences were observed between the two groups in TC/HDL-C, SII, operation time, gallbladder wall thickness, TC, neutrophil count, lymphocyte count, and time to ambulation after surgery. The poor gastrointestinal function group had higher values of TC/HDL-C, SII, operation time, TC, neutrophil count, and lymphocyte count, as well as a greater proportion of patients with gallbladder wall thickness > 5 mm and time to ambulation after surgery > 1 day, compared with the good gastrointestinal function group, while no significant differences were observed in the remaining indicators. Binary logistic regression analysis was performed using postoperative gastrointestinal function as the dependent variable (poor = 1, good = 0), and the variables that showed significant differences in univariate analysis as independent covariates. The results indicated that TC/HDL-C, SII, gallbladder wall thickness, operation time, and time to ambulation after surgery were independent risk factors for poor postoperative gastrointestinal function in elderly patients with gallstones. The observed outcomes point to a mixed origin for poor postsurgical gut function in this group, namely pre-existing disease states paired with the body’s reaction to surgical trauma. A thicker gallbladder wall signals more intense local inflammation within the gallbladder. This condition raises both the challenge and the amount of pulling and cutting needed during an operation. Furthermore, ongoing long-term inflammation may spread to nearby digestive tract tissues and disrupt their normal working order[11,12]. Extended operative duration indicates greater surgical complexity. Protracted anesthesia elevates systemic opioid levels, potentiates mu receptor binding in the gastrointestinal tract, and profoundly suppresses enteric neural activity. Sustained surgical stimulation activates the hypothalamic pituitary adrenal axis. This promotes catecholamine and cortisol release, which suppress gastrointestinal motility and reduce gut blood flow[13]. Advanced age and multiple comorbidities delay physical recovery in elderly patients. This results in later postoperative ambulation[14]. Extended bed rest induces venous pooling in lower extremities, reduces venous return, and lowers cardiac output. These changes worsen mucosal ischemia and compromise barrier function. Consequently, gastrointestinal motility recovery is delayed[15].

In this study, SII was found to be an independent risk factor for postoperative gastrointestinal dysfunction in the current work (OR = 3.411). He et al[16] reported SII as a predictive indicator for acute calculous cholecystitis and its severity, yielding an AUC of 0.73. In elderly cholelithiasis patients, elevated preoperative SII thus reflects both local gallbladder inflammation severity and a systemic chronic low grade inflammatory state. These conditions create an unfavorable environment for postoperative gastrointestinal recovery. Surgical trauma further amplifies the existing inflammatory response. This results in sustained release of inflammatory mediators including tumor necrosis factor alpha. These mediators directly target the enteric nervous system. Such mediator actions suppress acetylcholine output and increase inhibitory neurotransmitter secretion like nitric oxide. Signal transmission to gastrointestinal smooth muscle becomes impaired. Subsequent motility paralysis follows, commonly presenting as abdominal distension. Inflammatory mediators damage the intestinal mucosal barrier. They increase permeability and promote translocation of gut bacteria and lipopolysaccharides into circulation. This process amplifies systemic inflammation. A vicious cycle forms, persistently suppressing enteric neural activity and postponing gastrointestinal recovery[17]. Preoperative SII thus serves as a composite marker for local disease severity and systemic inflammatory load. Higher SII values signal greater vulnerability of the patient’s digestive tract to inflammation driven functional inhibition post surgery. Zhang et al[18] identified abnormal hepatic cholesterol metabolism as a core mechanism in cholesterol gallstone formation. All enrolled participants had cholelithiasis. The observed elevation in preoperative TC/HDL-C ratio thus directly corroborates the hepatic cholesterol dysregulation defect reported by Zhang et al[18]. This metabolic disturbance directly impairs gut function. It also worsens systemic inflammation through immune cell activation. A vicious cycle forms between metabolic disorder and inflammation. As an integrated metabolic parameter, the TC/HDL-C ratio offers a more precise reflection of cholesterol metabolic balance. A high TC/HDL-C ratio indicates relative TC excess alongside high density lipoprotein cholesterol deficiency. Low HDL-C levels drive nuclear factor kappa B pathway dysregulation. This causes adhesion molecule overexpression including vascular cell adhesion molecule 1 on vascular endothelial cells. Such changes enable neutrophil migration into tissues. Systemic inflammation worsens and gastrointestinal motility becomes suppressed[19,20]. Elevated TC serves as bile acid precursors. High TC levels cause abnormal bile acid metabolism and disturb gut microbiota balance. Short chain fatty acid production drops, slowing intestinal movement. Reduced short chain fatty acids suppress 5 hydroxytryptamine synthesis. Both central and enteric nervous system activity become impaired. Gastrointestinal motility weakens further[21,22]. Thus, the TC/HDL-C ratio and SII each stand as independent risk factors for poor postsurgical gastrointestinal outcomes in elderly gallstone patients. Routine measurement of these parameters enables early detection of high risk cases. Individualized perioperative care strategies can then be guided accordingly.

A nomogram prediction model was constructed in the present work to clarify the joint predictive value of SII and TC/HDL-C for postsurgical gastrointestinal dysfunction in elderly gallstone patients. In the derivation cohort, the nomogram yielded an AUC of 0.889. This value reflects strong discriminative ability and predictive power. The model then underwent testing in the validation cohort to estimate postoperative gastrointestinal dysfunction risk. High predictive accuracy persisted within this independent sample. Calibration curve analysis in the validation set revealed minimal deviation from the ideal reference line. The two curves nearly overlapped. This close alignment indicates strong concordance between predicted probabilities and observed outcomes, thereby affirming model reliability. Decision curve analysis in the validation cohort demonstrated substantial net clinical benefit. This finding supports the model’s utility for high risk patient identification and clinical decision guidance. Most predictors in the constructed nomogram are readily obtainable from routine preoperative blood work and imaging studies. Operative duration can be determined during surgery. Such practical accessibility enables clinicians to design and execute targeted perioperative intervention plans. These strategies improve patient outcomes and lower postsurgical complication rates. For example, patients with abnormally high SII and TC/HDL-C levels may receive enhanced preoperative nutritional support. For patients with expected long operative durations or sharply raised inflammatory markers, multimodal pain control regimens should take priority. Opioid doses require minimization to limit direct suppression of gastrointestinal motility. Incorporating predicted risks into postoperative recovery protocols allows creation of individualized early mobilization plans. These plans target high risk patients specifically. Thus, the model’s value rests on both predictive accuracy and the ability to convert predictions into actionable clinical actions. It offers a practical, evidence based tool for perioperative risk management.

CONCLUSION

To summarize, SII, TC/HDL-C, and the other identified factors each independently predicted postoperative gastrointestinal dysfunction in elderly gallstone patients. The proposed nomogram showed robust predictive performance across both derivation and validation cohorts. Calibration analysis revealed strong concordance between estimated and actual risks. Decision curve analysis further validated the model’s favorable clinical utility. This tool permits individualized risk evaluation. It also supplies a scientific foundation for targeted prevention design. Potential benefits include improved postoperative recovery quality and enhanced overall clinical outcomes. Nevertheless, this work held several limitations. It was a single center retrospective study with a relatively small sample size. Unmeasured variables like preoperative nutritional status and anesthesia technique were excluded. These omissions may restrict model comprehensiveness. Internal validation confirmed satisfactory model performance. External validation using multicenter data remains required. Future studies should enroll larger and more diverse patient populations. Such efforts will further refine the predictive model and enhance its generalizability.