Epidemiology of Sepsis-Associated Acute Kidney Injury in Beijing, China: A Descriptive Analysis

An early warning model to predict acute kidney injury in sepsis patients with prior hypertension

Background

In the context of sepsis patients, hypertension has a significant impact on the likelihood of developing sepsis-associated acute kidney injury (S-AKI), leading to a considerable burden. Moreover, sepsis is responsible for over 50 % of cases of acute kidney injuries (AKI) and is linked to an increased likelihood of death during hospitalization. The objective of this research is to develop a dependable and strong nomogram framework, utilizing the variables accessible within the first 24 h of admission, for the anticipation of S-AKI in sepsis patients who have hypertension.

Methods

In this study that looked back, a total of 462 patients with sepsis and high blood pressure were identified from Nanfang Hospital. These patients were then split into a training set (consisting of 347 patients) and a validation set (consisting of 115 patients). A multivariate logistic regression analysis and a univariate logistic regression analysis were performed to identify the factors that independently predict S-AKI. Based on these independent predictors, the model was constructed. To evaluate the efficacy of the designed nomogram, several analyses were conducted, including calibration curves, receiver operating characteristics curves, and decision curve analysis.

Results

The findings of this research indicated that diabetes, prothrombin time activity (PTA), thrombin time (TT), cystatin C, creatinine (Cr), and procalcitonin (PCT) were autonomous prognosticators for S-AKI in sepsis individuals with hypertension. The nomogram model, built using these predictors, demonstrated satisfactory discrimination in both the training (AUC = 0.823) and validation (AUC = 0.929) groups. The S-AKI nomogram demonstrated superior predictive ability in assessing S-AKI within the hypertension grade I (AUC = 0.901) set, surpassing the hypertension grade II (AUC = 0.816) and III (AUC = 0.810) sets. The nomogram exhibited satisfactory calibration and clinical utility based on the calibration curve and decision curve analysis.

Conclusion

In patients with sepsis and high blood pressure, the nomogram that was created offers a dependable and strong evaluation for predicting S-AKI. This evaluation provides valuable insights to enhance individualized treatment, ultimately resulting in improved clinical outcomes.

Amazonia Phytotherapy Reduces Ischemia and Reperfusion Injury in the Kidneys

Acute kidney injury (AKI) is defined as a sudden decrease in kidney function. Phytomedicines have shown positive effects in the treatment of AKI worldwide. The aim of this study was to evaluate the effect of Abuta grandifolia on the renal function of rats submitted to AKI. A phytochemical study of the plant was performed through liquid chromatography coupled with mass spectrometry (CL-EM) and DPPH and ABTS antioxidant tests. Renal function tests were performed in 20 male adult Wistar rats weighing from 250 to 300 g distributed in the following groups: SHAM (submitted to laparotomy with simulation of renal ischemia); ABUTA (animals that received 400 mg/kg of AG, orally-VO, once a day, for 5 days, with simulation of renal ischemia); I/N (animals submitted to laparotomy for clamping of bilateral renal pedicles for 30 min, followed by reperfusion); ABUTA + I/R (animals that received AG-400 mg/kg, 1× per day, VO, for 5 days, submitted to renal ischemia after treatment with herbal medicine). The results suggest that the consumption of Abuta grandifolia promoted renoprotection, preventing the reduction of renal function induced by ischemia, oxidizing activity, and deleterious effects on the renal tissue, confirmed by the decrease of oxidative metabolites and increase of antioxidants in the animals' organisms.

Analysis of factors associated with postoperative acute kidney injury in patients with colorectal cancer and the development of a risk prediction model: a retrospective study

BACKGROUND

To investigate the factors associated with acute kidney injury (AKI) in postoperative colorectal cancer (CRC) patients and develop a risk prediction model.

METHODS

The clinical data of 389 CRC patients were retrospectively analyzed. The patients were divided into AKI (n = 30) and non-AKI groups (n = 359) according to KDIGO diagnostic criteria. Demographic data, the presence of underlying diseases, perioperative conditions and related examination results were compared between the two groups. Binary logistic regression was used to analyze the independent risk factors for postoperative AKI, and a risk prediction model was established. And a verification group (94 patients) was used to verify the model.

RESULTS

30 patients (7.71%) with CRC had postoperative AKI. Binary logistic regression analysis showed that preoperative combined hypertension, preoperative anemia, inadequate intraoperative crystalloid infusion, low intraoperative minimum mean arterial pressure (MAP) and moderate to severe postoperative decline in hemoglobin (Hb) levels were independent risk factors. The risk prediction model developed was expressed as Logit P = - 0.853 + 1.228 * preoperative combined hypertension + 1.275 *preoperative anemia - 0.002 * intraoperative crystalloid infusion (ml) - 0.091 * intraoperative minimum MAP (mmHg) + 1.482 * moderate to severe postoperative decline in Hb levels. In Hosmer-Lemeshow test, χ² = 8.157, P = 0.718 showed that the fitting effect was good. The area under ROC curve was 0.776 (95% CI 0.682-0.871, P < 0.001), with a prediction threshold of 1.570, a sensitivity of 63.3% and a specificity of 88.9%. The sensitivity and specificity of the verification group were 65.8% and 86.1%.

CONCLUSIONS

Preoperative combined hypertension, preoperative anemia, inadequate intraoperative crystalloid infusion, low intraoperative minimum MAP, and moderate to severe postoperative decline in Hb levels were independent risk factors for AKI development in CRC patients. The prediction model can effectively predict the occurrence of postoperative AKI in patients with CRC.

No sex differences in the incidence, risk factors and clinical impact of acute kidney injury in critically ill patients with sepsis

Background

Sex-stratified medicine is an important aspect of precision medicine. We aimed to compare the incidence and risk factors of acute kidney injury (AKI) for critically ill men and women with sepsis. Furthermore, the short-term mortality was compared between men and women with sepsis associated acute kidney injury (SA-AKI).

Method

This was a retrospective study based on the Medical Information Mart for Intensive Care IV database. We used the multivariable logistic regression analysis to evaluate the independent effect of sex on the incidence of SA-AKI. We further applied three machine learning methods (decision tree, random forest and extreme gradient boosting) to screen for the risk factors associated with SA-AKI in the total, men and women groups. We finally compared the intensive care unit (ICU) and hospital mortality between men and women with SA-AKI using propensity score matching.

Results

A total of 6463 patients were included in our study, including 3673 men and 2790 women. The incidence of SA-AKI was 83.8% for men and 82.1% for women. After adjustment for confounders, no significant association was observed between sex and the incidence of SA-AKI (odds ratio (OR), 1.137; 95% confidence interval (CI), 0.949-1.361; p=0.163). The machine learning results revealed that body mass index, Oxford Acute Severity of Illness Score, diuretic, Acute Physiology Score III and age were the most important risk factors of SA-AKI, irrespective of sex. After propensity score matching, men had similar ICU and hospital mortality to women.

Conclusions

The incidence and associated risk factors of SA-AKI are similar between men and women, and men and women with SA-AKI experience comparable rates of ICU and hospital mortality. Therefore, sex-related effects may play a minor role in developing SA-AKI. Our study helps to contribute to the knowledge gap between sex and SA-AKI.