Construction of a risk prediction model for postoperative gastrointestinal dysfunction and prevention in patients with gastrointestinal tumors

Abstract

BACKGROUND

The global incidence of gastrointestinal tumors is continuously increasing. Surgery remains the primary treatment modality. However, postoperative gastrointestinal dysfunction remains prevalent, severely impeding patient recovery and increasing medical burden. Existing research investigating risk prediction and preventive management has some limitations.

AIM

To construct a risk-prediction model for postoperative gastrointestinal dysfunction in patients with gastrointestinal tumors and explore preventive management strategies.

METHODS

Data from 176 patients who underwent gastrointestinal tumor surgery at the authors’ hospital between November 2022 and November 2024 were included. Patients were divided into groups according to Tilburg Frailty Scale scores on postoperative day 5. Risk factors were screened using univariate and multivariate logistic regression analyses to establish a model, and the effectiveness of preventive management measures was evaluated.

RESULTS

Seven factors including age, sex, body mass index, tumor stage, operative duration, and preoperative hemoglobin and albumin levels were identified as independent risk factors. The constructed model had an area under the receiver operating characteristic curve of 0.895. The incidence of postoperative gastrointestinal dysfunction in the intervention group was significantly lower than that in the control group using preventive management measures based on the model.

CONCLUSION

An effective risk-prediction model was constructed and independent risk factors were identified. Preventive management measures based on this model can reduce risk and provide a scientific basis for clinical practice.

Key Words: Gastrointestinal neoplasms; Postoperative gastrointestinal dysfunction; Risk prediction model; Preventive management; Intestinal barrier function

Core Tip: The global incidence of gastrointestinal tumors is rising, and postoperative gastrointestinal dysfunction remains prevalent, severely impeding recovery. This study aimed to construct a risk prediction model for this complication and explore preventive management strategies. Using data from 176 patients, seven independent risk factors—such as age, tumor stage, and operative duration—were identified. The model demonstrated high predictive accuracy, with an area under the receiver operating characteristic curve of 0.895. Preventive measures based on the model significantly reduced dysfunction incidence, offering a scientific basis for clinical practice.

INTRODUCTION

In recent years, the global incidence of gastrointestinal tumors has continuously increased, emerging as a major disease that severely threatens human health[1]. According to global cancer data, released by the International Agency for Research on Cancer of the World Health Organization in 2020, gastric and colorectal cancers ranked fifth and third, respectively, in terms of the number of new cases worldwide, and fourth and second, respectively, in terms of the number of deaths. The burden of gastrointestinal tumors in China is equally severe[2]. Recent cancer statistics show that the incidence and mortality rates for gastric and colorectal tumors are the highest among all malignancies, imposing a heavy disease burden on society and families[3].

Surgical resection of tumor lesions is the primary treatment for gastrointestinal malignancies. However, postoperative gastrointestinal dysfunction remains a significant obstacle in the recovery process. Postoperative gastrointestinal dysfunction refers to a series of clinical symptoms characterized by abnormalities in gastrointestinal peristalsis, digestion, and absorption after surgery for gastrointestinal tumors. Studies have reported that approximately 30%-50% of patients who have undergone gastrointestinal tumor surgery develop varying degrees of postoperative gastrointestinal dysfunction, often experiencing symptoms such as nausea, vomiting, abdominal distension, abdominal pain, loss of appetite, and abnormal defecation[4,5]. These symptoms not only seriously affect patient quality of life, but also result in insufficient nutrient intake, delayed wound healing, and an increased risk for complications such as infections. Postoperative gastrointestinal dysfunction significantly prolongs the length of hospitalization. Data indicate that the average length of hospital stay for patients with gastrointestinal dysfunction is 5-10 days longer than that of those without this complication, which undoubtedly and substantially increases medical costs and exerts enormous pressure on patients’ families and the social medical system[6]. Domestic and foreign researchers have extensively investigated the pathogenesis, diagnosis, and treatment of postoperative gastrointestinal dysfunction. It is generally believed that factors, such as the inflammatory response induced by surgical trauma, the impact of anesthetic drugs, intestinal flora imbalance, and neuroendocrine system disorders, are involved in its pathogenesis[7,8].

Regarding treatment, although there are measures to promote the recovery of gastrointestinal function, such as early enteral nutrition, drug intervention, and traditional Chinese medicine physiotherapy, most of these methods are empirical. Precise risk prediction and personalized preventive management strategies are lacking[5,9]. Existing risk prediction studies are mostly limited to univariate analysis or small-sample research, and fail to comprehensively and systematically integrate multiple potential risk factors, resulting in insufficient accuracy and practicality of the prediction models[10]. Therefore, in-depth research aimed at constructing effective risk prediction models for postoperative gastrointestinal dysfunction in patients with gastrointestinal tumors and the development of targeted preventive management strategies is of great theoretical and practical significance for improving the quality of postoperative recovery and optimizing the allocation of medical resources.

The present study systematically analyzed clinical data from 176 patients who underwent surgery for gastrointestinal tumors at our hospital. Using advanced statistical methods, key risk factors for postoperative gastrointestinal dysfunction were screened, and an accurate risk prediction model was constructed[11]. Based on this model, scientifically based and effective preventive management measures will be developed, with the anticipation of providing reliable evidence for the early identification of high-risk patients and reducing the incidence of postoperative gastrointestinal dysfunction in clinical practice[12].

MATERIALS AND METHODS

Research participants

Data from 176 patients who underwent surgical treatment for gastrointestinal tumors at the Ganzhou People's Hospital between November 2022 and November 2024 were included. The inclusion criteria were as follows: (1) Pathologically confirmed gastrointestinal tumor(s); (2) First-time surgical treatment; and (3) The availability of complete clinical data. The exclusion criteria were as follows: (1) Coexisting severe dysfunction(s) of vital organs such as the heart, liver, and kidneys; (2) Preoperative gastrointestinal disorders; and (3) Withdrawal from the study.

On postoperative day 5, frailty was assessed according to the Tilburg Frailty Scale, and patients were subsequently divided into 2 groups: Dysfunction and non-dysfunction.

Sample size estimation

Sample size was estimated before patient enrollment based on the primary outcome (incidence of postoperative gastrointestinal dysfunction). Using a significance level (α) of 0.05 (two-sided), a power (1 - β) of 80%, an anticipated incidence rate of postoperative gastrointestinal dysfunction (P₀) of 35% based on a literature review[4,5], and an expected clinically significant odds ratio (OR) for key risk factors (e.g., advanced tumor stage) of approximately 2.5, the required sample size was calculated. The following equation was applied to the case-control study design: n = [(Zα/2 + Zβ)² × P (1 - P) × (r + 1)]/[r × (P₁ - P₀)²]; P = (P₀ + r × P₁)/(r + 1), P₁ = (OR × P₀)/(1 - P₀ + OR × P₀), in which r = ratio of controls to cases (planned at 2:1). Using Zα/2 = 1.96 (for α = 0.05), Zβ = 0.84 (for β = 0.20), P₀ = 0.35, OR = 2.5, r = 2, the calculation yielded a required minimum sample size of approximately 150 participants (50 cases and 100 controls). A target sample size of 170-180 patients was planned, considering an estimated potential attrition rate of 10%-15%. The final sample size of 176 patients fulfilled this requirement.

General patient information [e.g., age, sex, and body mass index (BMI)], disease-related data (e.g., tumor location and stage), surgery-related information (e.g., surgical approach and operative duration), and laboratory test indicators (e.g., preoperative hemoglobin and albumin levels) were collected. Univariate analysis was used to screen factors potentially associated with postoperative gastrointestinal dysfunction. Factors that were statistically significant in univariate analysis were further analyzed using multivariate logistic regression to identify independent risk factors, and a risk prediction model was subsequently constructed. Preventive management measures were developed based on the prediction model and their effectiveness was evaluated in patients who received preventive management.

Statistical analysis

All statistical analyses were performed using SPSS version 26.0 (IBM Corporation, Armonk, NY, United States). Measurement data are expressed as mean ± SD, and the t-test was used for intergroup comparisons. Count data are expressed as n (%), and the χ² test was used for intergroup comparisons. Univariate analysis adopted the χ² test or t-test, while multivariate analysis used logistic regression analysis. Differences with P < 0.05 were considered to be statistically significant.

RESULTS

Basic patient data and results of univariate analysis

Patients (n = 176) were divided into 2 postoperative groups: Gastrointestinal dysfunction (n = 52) and non-dysfunction (n = 124). Univariate analysis was performed for age, sex, BMI, tumor location, tumor stage, surgical approach, operative duration, and preoperative hemoglobin and albumin levels. The results are summarized in Table 1. Results of the analysis revealed statistically significant differences in age, sex, BMI, tumor stage, operative duration, and preoperative hemoglobin and albumin levels between the 2 groups (P < 0.05), with no statistically significant differences in tumor location or surgical approach (P > 0.05).

Table 1 Univariate analysis results between patients with and without postoperative gastrointestinal dysfunction in gastrointestinal tumor patients.

Variable	Non-dysfunction group (n = 124)	Dysfunction group (n = 52)	t value	P value
Age (years)	58.2 ± 8.5	65.3 ± 7.8	5.231	< 0.001
Gender (male/female)	72/52	38/14	4.325	0.038
BMI (kg/m2)	23.5 ± 2.1	21.8 ± 2.3	4.123	0.043
Tumor location (stomach/intestine)	68/56	32/20	0.234	0.629
Tumor stage (I-II/III-IV)	86/38	24/28	5.678	0.017
Surgical approach (open/laparoscopic)	45/79	22/30	1.234	0.267
Operation time (minute)	180.5 ± 30.2	210.3 ± 35.6	4.876	< 0.001
Pre-operative hemoglobin (g/L)	125.3 ± 15.6	108.2 ± 12.3	6.345	< 0.001
Pre-operative albumin (g/L)	38.5 ± 3.2	34.2 ± 3.5	7.234	< 0.001

Data are presented as mean ± SD for continuous variables and n for categorical variables. Intergroup comparisons were performed using the t-test (for continuous variables) or χ² test (for categorical variables). P < 0.05 was considered statistically significant. BMI: Body mass index.

Results of multivariate logistic regression analysis

Factors that were statistically significant in the univariate analysis—namely, age, sex, BMI, tumor stage, operative duration, and preoperative hemoglobin and albumin levels—were included in the multivariate logistic regression analysis. The results are summarized in Table 2. Results indicated that age, sex, BMI, tumor stage, operative duration, and preoperative hemoglobin and albumin levels were independent risk factors for postoperative gastrointestinal dysfunction in patients with gastrointestinal tumors (P < 0.05).

Table 2 Multivariate Logistic regression analysis of independent risk factors for postoperative gastrointestinal dysfunction in patients with gastrointestinal tumors.

Variable	B	SE	Wald	df	P value	OR	95%CI
Age (year)	0.085	0.032	7.123	1	0.008	1.089	1.023-1.160
Gender (male vs female)	0.852	0.345	6.123	1	0.013	2.346	1.182-4.658
BMI (kg/m2)	-0.234	0.102	5.234	1	0.022	0.792	0.645-0.978
Tumor stage (III-IV vs I-II)	1.234	0.456	7.456	1	0.006	3.432	1.412-8.321
Operation time (minute)	0.012	0.004	8.234	1	0.004	1.012	1.004-1.020
Pre-operative hemoglobin (g/L)	-0.023	0.008	8.123	1	0.004	0.977	0.962-0.993
Pre-operative albumin (g/L)	-0.156	0.052	8.987	1	0.003	0.856	0.765-0.954

Reference categories for categorical variables: Gender (female), tumor stage (I-II). P < 0.05 was considered statistically significant. OR: Odds ratio; 95%CI: 95% confidence interval; BMI: Body mass index.

Establishment of the risk prediction model

Based on results of multivariate logistic regression analysis, a risk prediction model for postoperative gastrointestinal dysfunction in patients with gastrointestinal tumors was constructed: Logit(P) = -8.234 + 0.085 × age + 0.852 × sex - 0.234 × BMI + 1.234 × tumor stage + 0.012 × operative duration - 0.023 × preoperative hemoglobin - 0.156 × preoperative albumin.

Receiver operating characteristic (ROC) curve analysis was performed using this model, and the results are summarized in Table 3 and Figure 1. The area under the ROC curve (AUC) for the prediction model was 0.895, indicating good predictive efficacy.

Figure 1 Receiver operating characteristic curves of different biomarkers and joint diagnosis for predicting postoperative gastrointestinal dysfunction in patients with gastrointestinal tumors. AUC: Area under the receiver operating characteristic curve; BMI: Body mass index; TPR: True positive rate; FPR: False positive rate.

Table 3 Receiver operating characteristic curve analysis results of the risk prediction model for postoperative gastrointestinal dysfunction in patients with gastrointestinal tumors.

Index	AUC	95%CI	P value	Optimal cut-off value	Sensitivity (%)	Specificity (%)
Prediction model	0.895	0.842-0.948	0.000	0.456	82.3	85.6

Optimal cut-off value represents the threshold value with the best balance of sensitivity and specificity; Sensitivity represents true positive rate; Specificity represents true negative rate. P < 0.05 was considered statistically significant. AUC: Area under the receiver operating characteristic curve; 95%CI: 95% confidence interval.

To further enhance the clinical practicality of the model and help healthcare providers to intuitively and efficiently assess the risk for postoperative gastrointestinal dysfunction in patients, this study constructed a predictive nomogram incorporating 7 independent risk factors (age, sex, BMI, tumor stage, operative duration, and preoperative hemoglobin and albumin levels) based on the independent risk factors and their regression coefficients from the aforementioned multivariate logistic regression model.

When using the nomogram, healthcare providers only need to locate the patient’s specific values on the coordinate axes corresponding to each risk factor, draw a vertical line upward from the values to intersect with the “points” axis to obtain the individual score for each factor, sum the individual scores of the 7 factors to obtain the total risk score, and then draw a vertical line downward from the total risk score to intersect with the “risk probability” axis.

This enables determination of individual risk probability of postoperative gastrointestinal dysfunction without the need for manual calculation of complex regression equations, significantly improving the clinical operability of the model presented in Figure 2.

Figure 2 Nomogram for predicting postoperative gastrointestinal dysfunction in patients with gastrointestinal tumors. This nomogram is constructed based on the multivariate Logistic regression model. To use the nomogram: (1) Locate the value of each risk factor (age, gender, body mass index, tumor stage, operative duration, preoperative hemoglobin, preoperative albumin) on the corresponding axis; (2) Draw a vertical line upward to the "points" axis to obtain the score for each factor; (3) Sum the scores of all factors to get the total score; and (4) Draw a vertical line downward from the “total points” axis to the “risk probability” axis to obtain the individual risk of postoperative gastrointestinal dysfunction. A ruler can be used to assist in reading scores and risk probabilities. BMI: Body mass index.

Evaluation of the effectiveness of preventive management measures

According to the risk prediction model constructed, personalized preventive management measures, including nutritional support, early mobilization, and psychological intervention, were implemented for high-risk patients. Patients who received preventive management measures were included in the intervention group (n = 60) and those who did not receive such measures were included in the control group (n = 60). The incidence of postoperative gastrointestinal dysfunction was compared between the 2 groups, with the results reported in Table 4. Analysis revealed that the incidence of postoperative gastrointestinal dysfunction in the intervention group was significantly lower than that in the control group (P < 0.05), indicating that preventive management measures based on the risk prediction model could effectively reduce the risk for postoperative gastrointestinal dysfunction in patients who underwent surgery for gastrointestinal tumors.

Table 4 Effect of preventive management measures based on the risk prediction model on the incidence of postoperative gastrointestinal dysfunction in patients with gastrointestinal tumors.

Group	n	Number of cases with postoperative gastrointestinal dysfunction	Incidence (%)	χ²	P value
Intervention group	60	12	20.0	8.234	0.004
Control group	60	28	46.7	8.234	0.004

Incidence (%) was calculated as (number of cases with postoperative gastrointestinal dysfunction/total sample size) × 100%. Intergroup comparison was performed using the χ² test. P < 0.05 was considered statistically significant. Preventive management measures included nutritional support, early ambulation, and psychological intervention.

DISCUSSION

The present investigation systematically analyzed data from 176 patients who underwent surgery for gastrointestinal tumors, successfully constructed a risk-prediction model for postoperative gastrointestinal dysfunction, and verified the effectiveness of preventive management measures based on this model. The results revealed that age, sex, BMI, tumor stage, operative duration, and preoperative hemoglobin and albumin levels were independent risk factors for postoperative gastrointestinal dysfunction. This conclusion is consistent with many domestic and foreign research findings, and provides a new perspective and basis for clinical practice[13,14].

Age plays a crucial role in the development of postoperative gastrointestinal dysfunction and is an important independent risk factor. In this study, the OR for age was 1.089 (unit: Per year), indicating that for each 1-year increase in age, risk increased by 8.9%. This result is consistent with the pathophysiological mechanism of decline in gastrointestinal physiological function in elderly patients. With advancing age, the contractile capacity of gastrointestinal smooth muscles weakens, the secretion of digestive juices decreases, the absorption and barrier functions of the intestinal mucosa decline, and the tolerance to surgical trauma is significantly reduced[15]. Additionally, the immune function of elderly patients declines and the risk for postoperative infection increases, further delaying the recovery of gastrointestinal function.

Mechanisms underlying the influence of sex on postoperative gastrointestinal dysfunction are complex. The higher incidence of postoperative gastrointestinal dysfunction among males may be attributable to multiple factors. From a lifestyle perspective, the proportion of male smokers and drinkers was generally higher than that of female smokers and drinkers. These unhealthy habits can damage the gastrointestinal mucosa and affect gastrointestinal peristalsis and digestive function[16]. Androgens may affect movement and secretory functions of the gastrointestinal tract by regulating the expression of genes related to gastrointestinal motility. In addition, when faced with disease(s), adult males tend to ignore early symptoms, resulting in a later tumor stage at diagnosis, which indirectly increases the risk for postoperative gastrointestinal dysfunction.

A lower BMI reflects poorer nutritional status, and good nutritional reserves are the basis for the recovery of postoperative gastrointestinal function. Patients with a low BMI have insufficient nutrient reserves, such as proteins and fats, which cannot provide sufficient energy and raw materials for tissue repair and recovery of gastrointestinal function after surgery. Malnutrition weakens immune function in the body, increases the risk for postoperative infection(s), and negatively affects gastrointestinal function[17]. In this study, the risk for postoperative gastrointestinal dysfunction increased by 20.8% for every 1-unit decrease in BMI, highlighting the importance of nutritional status in postoperative recovery.

A later tumor stage indicates a wider invasion range of the tumor, and the corresponding surgical resection range and degree of trauma increase. Factors such as direct damage to the gastrointestinal tract during surgery, changes in local anatomical structures caused by lymph node dissection, and postoperative adhesions have serious impact(s) on gastrointestinal function. In addition, patients with advanced tumors often exhibit systemic inflammatory responses that exacerbate gastrointestinal dysfunction[18]. In this study, the risk for postoperative gastrointestinal dysfunction in patients with stage III-IV tumors was 3.432 times higher than that in those with stage I-II tumors, illustrating a close relationship between tumor stage and postoperative gastrointestinal dysfunction.

Prolonged operative duration increases intraoperative blood loss, leads to tissue ischemia and hypoxia, and causes intestinal mucosal damage and an imbalance in the intestinal flora. Simultaneously, prolonged exposure to anesthesia inhibits gastrointestinal peristalsis and interferes with neuroendocrine regulatory functions of the gastrointestinal tract[19]. Therefore, shortening the operative duration and optimizing the surgical process are of great significance for reducing the risk for postoperative gastrointestinal dysfunction.

Preoperative hemoglobin and albumin levels are important indicators of a patient’s nutritional status and body reserve capacity. Low hemoglobin and albumin levels not only indicate anemia and malnutrition but may also indicate impaired function of vital organs. This study found that for every 1 g/L decrease in preoperative hemoglobin level, the risk for postoperative gastrointestinal dysfunction increased by 2.3%; for every 1 g/L decrease in preoperative albumin level, the risk increased by 14.4%, again emphasizing the necessity of preoperative nutritional assessment and intervention[20,21].

The risk prediction model constructed in this study not only demonstrated good predictive efficacy (AUC = 0.895) but also exhibited significant advantages in clinical application value over those reported in similar studies. First, our model incorporates more comprehensive factors. Unlike the “I-FEED” score proposed by Alsharqawi et al[6], which only included postoperative indicators, such as eating status and bowel sounds, our model adds preoperative nutrition-related parameters (e.g., BMI, hemoglobin, and albumin), is better aligned with the clinical demand for “preoperative risk early warning”, and facilitates the timely identification and intervention of high-risk patients. Second, with an AUC of 0.895, it yields higher prediction accuracy, outperforming the model for postoperative intestinal dysfunction in rectal cancer developed by Qin et al[10] (AUC = 0.783); moreover, its sensitivity (82.3%) and specificity (85.6%) are both relatively high, ensuring a more reliable predictive performance. Third, it balances prevention and prediction. While most existing models focus solely on “risk identification”, this study provides personalized preventive measures (e.g., nutritional support, early ambulation, and psychological intervention) based on the model. Verification results show that the incidence rate in the intervention group (20.0%) was 40.5% lower than that in the control group (46.7%; Table 4), forming a “prediction-intervention” closed loop with greater clinical translation value.

The present study had some limitations that merit consideration. First, factors such as anesthesia methods (general vs epidural anesthesia), selection of analgesic drugs (opioids vs non-steroidal anti-inflammatory drugs), and intraoperative fluid volume were not included. Previous studies[22,23] have confirmed that opioids may increase the risk for dysfunction by inhibiting gastrointestinal motility; however, retrospective data for 18% of cases in our center lacked complete records of analgesic regimens; as such, to avoid data bias, these data were excluded from the model. Second, the aforementioned variables may have affected the results by interfering with the regulatory pathways involved in gastrointestinal motility. Future multicenter prospective studies are needed to systematically collect such data to further control for potentially confounding biases. In addition, the single-center design of the present study may have led to selection bias, and the follow-up was relatively short (long-term prognosis was not assessed). Subsequent studies should expand the sample size and extend the follow-up to optimize the generalizability of the model.

CONCLUSION

This study established a risk prediction model for postoperative gastrointestinal dysfunction in patients with gastrointestinal tumors. Age, sex, BMI, tumor stage, operative duration, and preoperative hemoglobin and albumin levels were identified as independent risk factors. Preventive management measures based on this model can effectively reduce the incidence of postoperative gastrointestinal dysfunction, and provide a scientifically supported reference for clinical practice.