Optimizing postoperative infection control strategies in gastrointestinal surgery via integrated disinfection, isolation measures, and risk prediction models

Abstract

This editorial critically evaluated the recent study by Wang et al, which systematically investigated the efficacy of perioperative disinfection and isolation measures (including preoperative povidone-iodine disinfection, intraoperative sterile barrier techniques, and postoperative intensive care) in reducing infection rates. The study further incorporated the surgical site infection risk prediction model (constructed via the least absolute shrinkage and selection operator algorithm, integrating patients' baseline characteristics, surgical indicators, and regional antibiotic-resistant bacterial data), and proposed a dynamic prevention and control system termed “disinfection protocols-predictive models–real-time monitoring”. The article highlighted that preoperative risk stratification, intraoperative personalized antibiotic selection, and postoperative multidimensional monitoring (encompassing inflammatory biomarkers, imaging, and microbiological testing) enabled the precise identification of high-risk patients and optimized intervention thresholds. Future research is deemed necessary to validate the synergistic effects of disinfection protocols and predictive models through large-scale multicenter studies, combined with advanced intraoperative rapid microbial detection technologies. This approach aims to establish standardized infection control protocols tailored for precision medicine and regional adaptability. Future research should prioritize validating the synergistic effects of disinfection protocols and predictive models via multi-center studies, while incorporating advanced rapid intraoperative microbial detection technologies to develop standardized infection prevention and control procedures. Such efforts will enhance the implementation of precise and regionally adaptive infection control strategies.

Key Words: Postoperative infection control; Perioperative; Gastrointestinal surgery; Disinfection and isolation measures; Risk prediction models

Core Tip: This article underscored the critical role of perioperative disinfection and isolation measures in mitigating postoperative infections following gastrointestinal surgeries. Furthermore, it advocated for the integration of these measures with surgical site infection risk prediction models to develop sophisticated strategies aimed at enhancing the precision and effectiveness of future postoperative infection prevention and control.

TO THE EDITOR

Gastrointestinal surgery represents a cornerstone in modern medical practice for treating digestive tract diseases and is widely utilized to address a range of conditions, such as gastrointestinal tumors, ulcers, and inflammatory bowel disease. However, despite remarkable advancements in surgical techniques, postoperative infections, including abdominal infections, incisional infections, and organ space infections, continue to be a leading complication affecting patient outcomes. Data from multiple studies consistently demonstrate that the incidence of postoperative infections ranges from 10% to 20%, indicating a significant proportion that requires further attention and intervention[1-3]. Postoperative infections not only significantly prolong patients' hospitalization duration and increase medical costs but also may lead to severe health complications, including systemic inflammatory response syndrome, which can further progress to multiple organ dysfunction syndrome or organ failure, thereby posing a substantial threat to patients’ survival and overall health[4-6]. The extensive use of antibiotics over the past decades has significantly reduced the incidence of postoperative infections and has solidified its role as a cornerstone in clinical infection prevention and management. However, with the increasing prevalence of drug-resistant bacterial strains, an exclusive reliance on antibiotics has become increasingly inadequate to meet contemporary clinical demands. For instance, the emergence of multidrug-resistant pathogens such as methicillin-resistant Staphylococcus aureus and carbapenem-resistant Enterobacteriaceae has markedly diminished the effectiveness of conventional antibiotic therapies. In addition, the overuse of antibiotics may disrupt the equilibrium of the human microbiota, thereby increasing the susceptibility to infections and complicating the development of effective treatment strategies. Thus, within the contemporary medical context, it is imperative to establish an integrated prevention and control framework that synergistically combines infection risk prediction with enhanced disinfection and isolation protocols. Developing a multi-faceted and systematic prevention and control system that seamlessly integrates infection risk assessment, rigorous disinfection and isolation measures, and advanced real-time monitoring technologies can more effectively mitigate the incidence of postoperative infections, optimize patient outcomes, and concurrently alleviate the burden on healthcare systems. This not only signifies an inevitable trajectory for the future evolution of gastrointestinal surgery but also constitutes a critical strategy for safeguarding patient safety.

In their study, Wang et al[7] performed a detailed comparative analysis of postoperative infection rates and biochemical indices between the observation group (which implemented enhanced disinfection and isolation protocols) and the control group (which received standard care). The results revealed that the observation group exhibited a significantly lower postoperative infection rate, reduced levels of inflammatory markers, and markedly improved hepatic and renal function indices (Table 1). These findings strongly corroborate the efficacy of comprehensive perioperative prevention and control measures. The primary innovation stems from the adoption of multidimensional intervention strategies, encompassing preoperative whole-body disinfection with 10% povidone-iodine, intraoperative activation of laminar airflow systems and aseptic barrier techniques, as well as postoperative intensive wound care supplemented with prophylactic antibiotic therapy. These interventions effectively minimized microbial load in the surgical area, disrupted pathogen colonization and dissemination pathways, and thereby significantly attenuated both localized and systemic inflammatory responses. Moreover, Wang et al[7] propose targeted prevention recommendations tailored to regional epidemiological characteristics, emphasizing the importance of personalized infection control strategies. Additionally, the research team conducted a thorough evaluation of the protective effects of infection prevention measures on organ function through dynamic monitoring of radiological and biochemical parameter changes, providing valuable reference evidence for multidimensional postoperative management. Notably, a nationwide prospective study encompassing 17353 gastrointestinal surgery cases developed a surgical site infection risk prediction model by leveraging the least absolute shrinkage and selection operator algorithm, thereby providing a robust tool for infection prevention and control[8]. This model systematically integrated multidimensional variables, including patient baseline characteristics, intraoperative parameters, and regional drug-resistant bacterial prevalence data, ensuring comprehensive risk assessment. Future research may incorporate the disinfection strategies validated by Wang et al[7] as additional variables into the predictive model, thereby enhancing its regional adaptability. Moreover, high-risk patients identified via the predictive model could be prioritized for enhanced disinfection and isolation protocols, including the administration of supplementary broad-spectrum antibiotics during surgery and the prolongation of postoperative monitoring periods. Additionally, through the integration of real-time pathogen detection data, the predictive model can dynamically refine the selection of intraoperative antibiotics and modulate postoperative isolation levels, ultimately promoting precise infection management.

Table 1 Key outcomes of enhanced perioperative disinfection measures.

Key indicators	Time period	Observation group (P value)	Control group (P value)
Incision infection	Postoperative day 1	10.42 (P < 0.05)	25.13 (P < 0.05)
	Postoperative day 3	4.17 (P < 0.05)	16.67 (P < 0.05)
	Postoperative day 7	4.17 (P < 0.05)	10.42 (P < 0.05)
	Postoperative day 1	9.25 ± 1.14 (P < 0.001)	12.04 ± 1.55 (P < 0.001)
WBCs	Postoperative day 3	7.82 ± 1.03 (P < 0.001)	11.02 ± 1.47 (P < 0.001)
	Postoperative day 7	6.41 ± 0.85 (P < 0.001)	9.67 ± 1.13 (P < 0.001)
	Postoperative day 1	4.83 ± 1.52 (P < 0.001)	11.03 ± 2.06 (P < 0.001)
CRP	Postoperative day 3	3.52 ± 1.06 (P < 0.001)	9.52 ± 2.51 (P < 0.001)
	Postoperative day 7	2.50 ± 0.73 (P < 0.001)	6.19 ± 1.55 (P < 0.001)

WBC: White blood cell; CRP: C-reactive protein.

Despite the progress achieved in existing studies, certain limitations remained apparent. First, Wang et al’s retrospective analysis[7] could have been susceptible to bias due to uncontrolled confounding factors, such as patient immune status and variations in surgical techniques. Moreover, this study was a single-center investigation with a relatively restricted sample size (48 cases per group), potentially limiting the generalizability of the findings and warranting cautious interpretation. Furthermore, the study inadequately addressed potential variations in infection risk between different surgical approaches (open vs laparoscopic). Previous research has demonstrated that open procedures typically carry higher infection risks compared to laparoscopic techniques, suggesting that future investigations should conduct stratified analyses to better evaluate the efficacy of disinfection measures across surgical modalities. Additionally, the predictive model omitted several critical variables, including surgical team experience (with junior surgeons demonstrating significantly prolonged operative durations) and specific disinfection protocol details, which may compromise predictive accuracy and introduce outcome bias. Therefore, we recommend multicenter validation studies to assess model robustness and generalizability. Subsequent research should incorporate standardized protocols (e.g., uniform disinfectant concentrations and strict operating room environmental controls) to minimize confounding effects, thereby enabling more precise evaluation of synergistic interactions between disinfection/isolation measures and predictive modeling frameworks[3]. Based on evidence-based findings, the intervention threshold for high-risk populations should be accurately defined, and a dynamic evaluation framework linking “disinfection protocols”, “predictive modeling”, and “clinical outcomes” should be developed. Moreover, by incorporating real-time monitoring technologies (e.g., rapid intraoperative microbial detection), the decision-making process can be systematically enhanced.

Future research could further explore federated learning techniques to enhance model generalizability through multi-center data utilization while ensuring institutional data privacy protection. Additionally, integrating explainable artificial intelligence with visualized key feature importance (e.g., individualized risk factors) and comparative analyses with similar clinical cases would strengthen clinicians’ confidence in model predictions, thereby facilitating the practical implementation and clinical translation of decision-support systems[9,10].

CONCLUSION

A comprehensive perioperative disinfection strategy can significantly reduce the postoperative infection rate in gastrointestinal surgery. This reduction is achieved by lowering microbial load, suppressing inflammatory responses, and safeguarding organ function. The integration of surgical site infection risk prediction models allows for the identification of high-risk populations and supports individualized interventions, such as enhanced disinfection protocols and adaptive antibiotic regimens. However, the present investigation exhibited limitations, including potential biases due to its single-center retrospective design, a relatively small sample size, and the lack of stratified analyses assessing the impact of different surgical procedures. Future research should focus on multi-center prospective studies to standardize disinfection parameters (e.g., concentration and duration) and integrate critical variables, such as surgeon experience and real-time pathogen data, thereby improving the clinical robustness of the model. Additionally, the establishment of a “prediction-intervention-evaluation” closed-loop system, utilizing artificial intelligence and real-time monitoring technologies, can enhance the precision of infection control and provide strong evidence-based support for global infection management in gastrointestinal surgery.