Published online Dec 27, 2024. doi: 10.4240/wjgs.v16.i12.3818
Revised: September 5, 2024
Accepted: October 22, 2024
Published online: December 27, 2024
Processing time: 228 Days and 17.4 Hours
Acute gastrointestinal injury (AGI) is common in intensive care unit (ICU) and worsens the prognosis of critically ill patients. The four-point grading system proposed by the European Society of Intensive Care Medicine is subjective and lacks specificity. Therefore, a more objective method is required to evaluate and determine the grade of gastrointestinal dysfunction in this patient population. Digital continuous monitoring of bowel sounds and some biomarkers can change in gastrointestinal injuries. We aimed to develop a model of AGI using continuous monitoring of bowel sounds and biomarkers.
To develop a model to discriminate AGI by monitoring bowel sounds and biomarker indicators.
We conducted a prospective observational study with 75 patients in an ICU of a tertiary-care hospital to create a diagnostic model for AGI. We recorded their bowel sounds, assessed AGI grading, collected clinical data, and measured biomarkers. We evaluated the model using misjudgment probability and leave-one-out cross-validation.
Mean bowel sound rate and citrulline level are independent risk factors for AGI. Gastrin was identified as a risk factor for the severity of AGI. Other factors that correlated with AGI include mean bowel sound rate, amplitude, interval time, Sequential Organ Failure Assessment score, Acute Physiology and Chronic Health Evaluation II score, platelet count, total protein level, blood gas potential of hydrogen (pH), and bicarbonate (HCO3-) level. Two discriminant models were constructed with a misclassification probability of < 0.1. Leave-one-out cross-validation correctly classified 69.8% of the cases.
Our AGI diagnostic model represents a potentially effective approach for clinical AGI grading and holds promise as an objective diagnostic standard for AGI.
Core Tip: We developed a model to discriminate acute gastrointestinal injury (AGI) by continuous monitoring of bowel sounds and biomarker indicators. The study found that mean bowel sound rate and citrulline level are independent risk factors for AGI. Gastrin was identified as a risk factor for the severity of AGI. Two discriminant models were constructed with a misclassification probability of < 0.1. Our AGI diagnostic model represents a potentially effective approach for clinical AGI grading and holds promise as an objective diagnostic standard for AGI.