Prediction of Bleeding Risk After Gastrointestinal Surgery Combined with Spectral Analysis and Construction of Nursing Monitoring Model

Postoperative gastrointestinal bleeding is a key problem affecting prognosis, and traditional monitoring methods have limitations such as lag and insufficient sensitivity. In this study, Raman spectroscopy, near infrared spectroscopy (NIRS) and fluorescence spectroscopy were integrated to construct a dynamic risk prediction model (DRPM) and a graded nursing monitoring system to achieve active prevention and accurate management of postoperative bleeding. In this paper, the spectrum of 400-1000nm band near the anastomotic site was collected by the proximal endoscopic adaptive fiber probe, and the oxygen saturation (StO₂) and total hemoglobin (tHb) of mesenteric tissue were monitored by the distal percutaneous NIRS patch, and the key spectral parameters such as ΔHbT and HIR were extracted. DRPM model fuses spectral core indicators with clinical parameters such as preoperative coagulation function and anastomotic type, and uses adaptive weighted integration method to generate comprehensive risk score, and dynamically adjusts the weights of spectral factors, clinical factors and dynamic trend factors to optimize early warning efficiency. At the same time, a three-level early warning response mechanism was established, and differentiated monitoring and intervention (grade I observation, grade II alert and grade III intervention) were implemented according to the risk score, and the bleeding point was accurately identified by combining spatial positioning technology. The validation results showed that among 312 patients undergoing gastrointestinal surgery, the sensitivity (94.7%) and specificity (92.5%) of the DRPM model for grade II/III bleeding were significantly higher than those of traditional methods (68.4%, 84.6%), with a warning lead time of 4.8 ± 1.2 hours and a false alarm rate reduced to 7.4%; The incidence of bleeding in patients with grade III risk stratification is 100%, and the accuracy of spatial positioning error ≤ 2cm is 86.5%. In terms of clinical benefits, the experimental group's reoperation rate decreased by 69.7% and the average length of hospital stay was shortened by 23.9%, confirming that this model can improve the efficiency of bleeding warning, promote the transformation of postoperative management from passive treatment to active prevention, and provide a new paradigm for interdisciplinary and integrated complication management.

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Publication Details

Journal
International Journal of Biology and Life Sciences
Published
2025-08-27
DOI
https://doi.org/10.54097/t82s0v64
Primary Topic
Optical Imaging and Spectroscopy Techniques
Type
article
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article

Prediction of Bleeding Risk After Gastrointestinal Surgery Combined with Spectral Analysis and Construction of Nursing Monitoring Model

C. Shen
International Journal of Biology and Life Sciences
Optical Imaging and Spectroscopy Techniques
article

Prediction of Bleeding Risk After Gastrointestinal Surgery Combined with Spectral Analysis and Construction of Nursing Monitoring Model

C. Shen
article en

Abstract

Postoperative gastrointestinal bleeding is a key problem affecting prognosis, and traditional monitoring methods have limitations such as lag and insufficient sensitivity. In this study, Raman spectroscopy, near infrared spectroscopy (NIRS) and fluorescence spectroscopy were integrated to construct a dynamic risk prediction model (DRPM) and a graded nursing monitoring system to achieve active prevention and accurate management of postoperative bleeding. In this paper, the spectrum of 400-1000nm band near the anastomotic site was collected by the proximal endoscopic adaptive fiber probe, and the oxygen saturation (StO₂) and total hemoglobin (tHb) of mesenteric tissue were monitored by the distal percutaneous NIRS patch, and the key spectral parameters such as ΔHbT and HIR were extracted. DRPM model fuses spectral core indicators with clinical parameters such as preoperative coagulation function and anastomotic type, and uses adaptive weighted integration method to generate comprehensive risk score, and dynamically adjusts the weights of spectral factors, clinical factors and dynamic trend factors to optimize early warning efficiency. At the same time, a three-level early warning response mechanism was established, and differentiated monitoring and intervention (grade I observation, grade II alert and grade III intervention) were implemented according to the risk score, and the bleeding point was accurately identified by combining spatial positioning technology. The validation results showed that among 312 patients undergoing gastrointestinal surgery, the sensitivity (94.7%) and specificity (92.5%) of the DRPM model for grade II/III bleeding were significantly higher than those of traditional methods (68.4%, 84.6%), with a warning lead time of 4.8 ± 1.2 hours and a false alarm rate reduced to 7.4%; The incidence of bleeding in patients with grade III risk stratification is 100%, and the accuracy of spatial positioning error ≤ 2cm is 86.5%. In terms of clinical benefits, the experimental group's reoperation rate decreased by 69.7% and the average length of hospital stay was shortened by 23.9%, confirming that this model can improve the efficiency of bleeding warning, promote the transformation of postoperative management from passive treatment to active prevention, and provide a new paradigm for interdisciplinary and integrated complication management.

International Journal of Biology and Life SciencesVol. 11(2)
Kyungwoon University (KR)
Openalex Percentile: Top 69%
Optical Imaging and Spectroscopy Techniques
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