Analysis of different trajectories of postoperative microinflammation in maintenance peritoneal dialysis patients and factors influencing them-A single-center retrospective study

Introduction Chronic Kidney Disease (CKD) has become a global chronic disease, and its incidence has been on the rise in recent years. It is another disease that seriously affects the health of the population after diabetes, cardiovascular diseases, tumors, and other diseases. Patients with chronic kidney disease commonly have symptoms of inflammation, malnutrition, and atherosclerosis, so they are collectively referred to as the malnutrition-inflammation-atherosclerosis syndrome. Inflammation is a key component in MIAS, and it is one of the main causes of adverse clinical outcomes in peritoneal dialysis patients. Therefore, the present study intends to explore the different trajectories of postoperative microinflammation in maintenance peritoneal dialysis patients and comparatively analyze their influencing factors to provide a direction for intervention in the malnutrition-inflammation-atherosclerosis syndrome in these patients. Methods This study was a retrospective longitudinal study. The study selected 503 peritoneal dialysis patients who were treated and followed up in the peritoneal dialysis center of the First Affiliated Hospital of Wenzhou Medical University from January 01, 2018, to December 2023, and collected microinflammation of the patients at five-time points: preoperative, 3 months postoperative, 6 months postoperative, 9 months postoperative, and 12 months postoperative. Groups were sequentially created through a nonlinear latent category growth model to analyze the characteristics and factors influencing the patients' different developmental trajectories. Results Microinflammatory states were present in patients at different time points, with a high preoperative micro inflammatory rate of 83.90% (3.76±2.47), which remained high and rebounded with the growth of peritoneal dialysis time in patients The nonlinear latent category growth analysis results in the final selection of the best number of categories for two categories: a low-level slow decline group and a high-level fast decline group. Statistical analysis of the various indicators of the two groups of patients showed that the differences in gender, systolic blood pressure, patient regression, white blood cell count, neutrophil count, lymphocyte count, platelet count, monocytes, and blood sodium were statistically significant in the two groups (P < 0.05). Conclusion During clinical treatment and care, attention needs to be paid to the relationship between the patient's gender, systolic blood pressure, and the patient's platelet count on inflammation in order to avoid complications such as malnutrition and atherosclerotic symptoms in the patient due to the prolonged microinflammatory state.