Risk factors and clinical prediction models for osteoporosis in pre-dialysis chronic kidney disease patients.

BACKGROUND: Osteoporosis in pre-dialysis chronic kidney disease (CKD) patients has been overlooked, and the risk factors of osteoporosis in these patients have not been adequately studied. OBJECTIVE: To identify risk factors for osteoporosis in pre-dialysis CKD patients and develop predictive models to estimate the likelihood of osteoporosis. METHODS: Dual-energy X-ray absorptiometry was used to measure bone mineral density, and clinical examination results were collected from 326 pre-dialysis CKD patients. Binary logistic regression was employed to explore the risk factors associated with osteoporosis and develop predictive models. RESULTS: In this cohort, 53.4% (n = 174) were male, 46.6% (n = 152) were female, and 21.8% (n = 71) were diagnosed with osteoporosis. Among those diagnosed with osteoporosis, 67.6% (n = 48) were female and 32.4% (n = 23) were male. Older age and low 25-(OH)-Vitamin D levels were identified as risk factors for osteoporosis in males. For females, older age, being underweight, higher bone alkaline phosphatase (NBAP), and advanced CKD (G5) were significant risk factors, while higher iPTH was protective. Older age, being underweight, and higher NBAP were risk factors for osteoporosis in the G1-4 subgroup. In the G5 subgroup, older age and higher NBAP increased the risk, while high 25-(OH)-Vitamin D or iPTH had protective effects. Nomogram models were developed to assess osteoporosis risk in pre-dialysis patients based on gender and renal function stage. CONCLUSION: Risk factors for osteoporosis vary by gender and renal function stages. The nomogram clinical prediction models we constructed may aid in the rapid screening of patients at high risk of osteoporosis.

Establishment and evaluation of a nomogram prediction model for the risk of vascular calcification in stage 5 chronic kidney disease patients.

Vascular calcification (VC) is a common complication of chronic kidney disease (CKD) that has a detrimental effect on patients' survival and prognosis. The aim of this study was to develop and validate a practical and reliable prediction model for VC in CKD5 patients. The medical records of 544 CKD5 patients were reviewed retrospectively. Multivariate logistic regression analysis was used to identify the independent risk factors for vascular calcification in patients with CKD5 and then created a nomogram prediction model. The area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow test, and decision curve analysis (DCA) were used to assess model performance. The patients were split into groups with normal and high serum uric acid levels, and the factors influencing these levels were investigated. Age, BUN, SUA, P and TG were independent risk factors for vascular calcification in CKD5 patients in the modeling group (P < 0.05). In the internal validation, the results of model showed that the AUC was 0.917. No significant divergence between the predicted probability of the nomogram and the actual incidence rate (x2 = 5.406, P = 0.753) was revealed by the calibration plot and HL test, thus confirming that the calibration was satisfactory. The external validation also showed good discrimination (AUC = 0.973). The calibration chart and HL test also demonstrated good consistency. Besides, the correlation analysis of serum uric acid levels in all CKD5 patients revealed that elevated uric acid levels may be related to gender, BUN, P, and TG.

The impact of statin use before intensive care unit admission on patients with acute kidney injury after cardiac surgery.

Background: Cardiac surgery-associated acute kidney injury (CSA-AKI) is a common and serious complication after cardiac surgery. The influence of statin use before surgery on the renal outcome of patients undergoing cardiac surgery is controversial. The purpose of this study was to evaluate the effect of statins on postoperative renal outcomes in patients undergoing cardiac surgery. Methods: We included CSA-AKI patients in the Medical Information Mart for Intensive Care (MIMIC)-IV database and were divided into statin group and non-statin group according to whether they used statins before entering intensive care units (ICU). The main outcomes were hospitalization and 30-day mortality, and the secondary outcomes were 60-day mortality and 90-day mortality. We used propensity score matching (PSM) to adjust for confounding factors. The 95% confidence interval (CI) and risk ratio (RO) were calculated by the COX proportional regression model. At the same time, stratified analysis was used to explore whether the relationship between the statins use before intensive care units and mortality was different in each subgroup and whether the relationship between different doses of Atorvastatin and mortality was different. Result: We identified 675 pre-ICU statin users and 2095 non-statin users. In the COX proportional regression model, pre-ICU statin use was associated with decreased in-hospital (HR = 0.407, 95%confidence interval 0.278-0.595, p < 0.001) and 30-day mortality (HR = 0.407, 95%CI 0.279-0.595, p < 0.001). The survival rate of patients who took statins before entering ICU was significantly higher than that of those who did not use statins at 30 days, 60 days and 90 days. There is a significant interaction between patients with aged>65 years (HR = 0.373, 95%CI 0.240-0.581, p < 0.001), Acute kidney injury grade I (HR = 0.244, 95%CI 0.118-0.428, p < 0.001), and without post-myocardial infarction syndrome (HR = 0.344, 95%CI 0.218-0.542, p < 0.001). The mortality in hospital and 60 days of CSA-AKI patients treated with ≥80 mg Atorvastatin before operation was significantly reduced (p < 0.05). Conclusion: The pre-ICU statin use was significantly associated with decreased risk in hospital and 30-day mortality. The preoperative use of ≥80 mg Atorvastatin may improve the prognosis of CSA-AKI.

Aspirin reduces the mortality risk of sepsis-associated acute kidney injury: an observational study using the MIMIC IV database.

Introduction: Sepsis-associated acute kidney injury (SA-AKI) is a complication of sepsis and is characterized by high mortality. Aspirin affects cyclooxygenases which play a significant role in inflammation, hemostasis, and immunological regulation. Sepsis is an uncontrolled inflammatory and procoagulant response to a pathogen, but aspirin can inhibit platelet function to attenuate the inflammatory response, thus improving outcomes. Several studies have generated contradictory evidence regarding the effect of aspirin on patients with sepsis-associated acute kidney injury (SA-AKI). We conducted an analysis of the MIMIC IV database to investigate the correlation between aspirin utilization and the outcomes of patients with SA-AKI, as well as to determine the most effective dosage for aspirin therapy. Materials and methods: SA-AKI patients' clinical data were extracted from MIMIC-IV2.1. Propensity score matching was applied to balance the baseline characteristics between the aspirin group and the non-user group. Subsequently, the relationship between aspirin and patient death was analyzed by Kaplan-Meier method and Cox proportional hazard regression models. Results: 12,091 patients with SA-AKI were extracted from the MIMIC IV database. In the propensity score-matched sample of 7,694 individuals, lower 90-day mortality risks were observed in the aspirin group compared to the non-users group (adjusted HR: 0.722; 95%CI: 0.666, 0.783) by multivariable cox proportional hazards analysis. In addition, the Kaplan-Meier survival curves indicated a superior 90-day survival rate for aspirin users compared to non-users (the log-rank test p-value was 0.001). And the median survival time of patients receiving aspirin treatment was significantly longer than those not receiving (46.47 days vs. 24.26 days). In the aspirin group, the average ICU stay length was shorter than non-users group. (5.19 days vs. 5.58 days, p = 0.006). There was no significant association between aspirin and an increased risk of gastrointestinal hemorrhage (p = 0.144). Conclusion: Aspirin might reduce the average ICU stay duration and the 30-day or 90-day mortality risks of SA-AKI patients. No statistically significant difference in the risk of gastrointestinal hemorrhage was found between the aspirin group and the control group.