Objective:To explore the predictive value of platelet aggregation function for acute kidney injury (AKI) in sepsis patients based on decision curve.Methods:A retrospective study was conducted to collect and analyze the clinical data of 120 sepsis patients admitted to the Affiliated Hospital of Jiangnan University from January 2021 to December 2023. According to the incidence of AKI during hospitalization, they were divided into AKI group (37 cases) and non-AKI group (83 cases). The general data, platelet aggregation function index (platelet aggregation rate) and other laboratory indexes of the two groups were collected and compared. Logistic regression model was used to analyze the relationship between AKI and main indexes of platelet aggregation function in patients with sepsis. The area under the curve (AUC) was obtained by drawing the receiver operating characteristic (ROC) curve, and the predictive value of platelet aggregation function on AKI in patients with sepsis was analyzed. R language software was used to construct a nomogram model of platelet aggregation function combined with other main indicators to predict AKI in patients with sepsis. Based on the decision curve, the predictive efficacy of the model on AKI in patients with sepsis was analyzed.Results:The platelet aggregation rate in the AKI group was lower than that in the non-AKI group: (56.23 ± 7.86)% vs. (68.79 ± 8.54)%, and the thrombin time was longer than that in the non-AKI group: 17.00 (16.50, 18.00) s vs. 16.00 (15.00, 17.00) s. The levels of D-dimer, C-reactive protein and procalcitonin were higher than those in the non-AKI group: (1.55 ± 0.45) mg/L vs. (1.32 ± 0.41) mg/L, (107.53 ± 18.41) mg/L vs. (99.86 ± 17.25) mg/L, (3.10 ± 0.46) μg/L vs. (2.88 ± 0.42) μg/L, and the differences were statistically significant ( P<0.05). The results of constructing a Logistic regression model showed that AKI in sepsis patients may be related to abnormal levels of platelet aggregation rate, thrombin time, C-reactive protein and procalcitonin ( P<0.05). The ROC curve was drawn to obtain the corresponding AUC: the AUC of platelet aggregation rate predicting sepsis complicated with AKI was 0.860 (95% CI 0.789 to 0.931), which had certain predictive value. When the platelet aggregation rate was set to 62.84%, the best predictive value can be obtained, with sensitivity, specificity, and Jorden index of 83.80%, 80.70%, and 0.645, respectively. The nomogram model of platelet aggregation function assisting other major indicators in predicting AKI in sepsis patients had a C-index of 0.904 (95% CI 0.851 to 0.957), indicating good discrimination of the model. Through decision curve analysis of the clinical net benefit of the model, the results showed that the clinical net benefit of the model was higher than that of platelet aggregation rate and other major indicators when applied alone. When the risk threshold was within the range of 0 to 0.81 and 0.97 to 1.00, the model could provide a significant increase in clinical net benefit rate. Conclusions:Platelet aggregation function (platelet aggregation rate) can serve as an early auxiliary predictive indicator for the risk of AKI in sepsis patients, and can assist other major indicators to improve the predictive value of AKI in sepsis patients.

Objective:To explore the predictive value of platelet aggregation function for acute kidney injury (AKI) in sepsis patients based on decision curve.Methods:A retrospective study was conducted to collect and analyze the clinical data of 120 sepsis patients admitted to the Affiliated Hospital of Jiangnan University from January 2021 to December 2023. According to the incidence of AKI during hospitalization, they were divided into AKI group (37 cases) and non-AKI group (83 cases). The general data, platelet aggregation function index (platelet aggregation rate) and other laboratory indexes of the two groups were collected and compared. Logistic regression model was used to analyze the relationship between AKI and main indexes of platelet aggregation function in patients with sepsis. The area under the curve (AUC) was obtained by drawing the receiver operating characteristic (ROC) curve, and the predictive value of platelet aggregation function on AKI in patients with sepsis was analyzed. R language software was used to construct a nomogram model of platelet aggregation function combined with other main indicators to predict AKI in patients with sepsis. Based on the decision curve, the predictive efficacy of the model on AKI in patients with sepsis was analyzed.Results:The platelet aggregation rate in the AKI group was lower than that in the non-AKI group: (56.23 ± 7.86)% vs. (68.79 ± 8.54)%, and the thrombin time was longer than that in the non-AKI group: 17.00 (16.50, 18.00) s vs. 16.00 (15.00, 17.00) s. The levels of D-dimer, C-reactive protein and procalcitonin were higher than those in the non-AKI group: (1.55 ± 0.45) mg/L vs. (1.32 ± 0.41) mg/L, (107.53 ± 18.41) mg/L vs. (99.86 ± 17.25) mg/L, (3.10 ± 0.46) μg/L vs. (2.88 ± 0.42) μg/L, and the differences were statistically significant ( P<0.05). The results of constructing a Logistic regression model showed that AKI in sepsis patients may be related to abnormal levels of platelet aggregation rate, thrombin time, C-reactive protein and procalcitonin ( P<0.05). The ROC curve was drawn to obtain the corresponding AUC: the AUC of platelet aggregation rate predicting sepsis complicated with AKI was 0.860 (95% CI 0.789 to 0.931), which had certain predictive value. When the platelet aggregation rate was set to 62.84%, the best predictive value can be obtained, with sensitivity, specificity, and Jorden index of 83.80%, 80.70%, and 0.645, respectively. The nomogram model of platelet aggregation function assisting other major indicators in predicting AKI in sepsis patients had a C-index of 0.904 (95% CI 0.851 to 0.957), indicating good discrimination of the model. Through decision curve analysis of the clinical net benefit of the model, the results showed that the clinical net benefit of the model was higher than that of platelet aggregation rate and other major indicators when applied alone. When the risk threshold was within the range of 0 to 0.81 and 0.97 to 1.00, the model could provide a significant increase in clinical net benefit rate. Conclusions:Platelet aggregation function (platelet aggregation rate) can serve as an early auxiliary predictive indicator for the risk of AKI in sepsis patients, and can assist other major indicators to improve the predictive value of AKI in sepsis patients.