Iron Overload in a Murine Model of Hereditary Hemochromatosis Is Associated with Accelerated Progression of Osteoarthritis Under Mechanical Stress

OBJECTIVE: Hereditary hemochromatosis (HH) is a disease caused by mutations in the Hfe gene characterised by systemic iron overload and associated with an increased prevalence of osteoarthritis (OA) but the role of iron overload in the development of OA is still undefined. To further understand the molecular mechanisms involved we have used a murine model of HH and studied the progression of experimental OA under mechanical stress. DESIGN: OA was surgically induced in the knee joints of 10-week-old C57BL6 (wild-type) mice and Hfe-KO mice. OA progression was assessed using histology, micro CT, gene expression and immunohistochemistry at 8 weeks after surgery. RESULTS: Hfe-KO mice showed a systemic iron overload and an increased iron accumulation in the knee synovial membrane following surgery. The histological OA score was significantly higher in the Hfe-KO mice at 8 weeks after surgery. Micro CT study of the proximal tibia revealed increased subchondral bone volume and increased trabecular thickness. Gene expression and immunohistochemical analysis showed a significant increase in the expression of matrix metallopeptidase 3 (MMP-3) in the joints of Hfe-KO mice compared with control mice at 8 weeks after surgery. CONCLUSIONS: HH was associated with an accelerated development of OA in mice. Our findings suggest that synovial iron overload has a definite role in the progression of HH-related OA

Modeling in-Hospital Patient Survival During the First 28 Days After Intensive Care Unit Admission: a Prognostic Model for Clinical Trials in General Critically Ill Patients

OBJECTIVE: The objective of the study was to develop a model for estimating patient 28-day in-hospital mortality using 2 different statistical approaches. DESIGN: The study was designed to develop an outcome prediction model for 28-day in-hospital mortality using (a) logistic regression with random effects and (b) a multilevel Cox proportional hazards model. SETTING: The study involved 305 intensive care units (ICUs) from the basic Simplified Acute Physiology Score (SAPS) 3 cohort. PATIENTS AND PARTICIPANTS: Patients (n = 17138) were from the SAPS 3 database with follow-up data pertaining to the first 28 days in hospital after ICU admission. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: The database was divided randomly into 5 roughly equal-sized parts (at the ICU level). It was thus possible to run the model-building procedure 5 times, each time taking four fifths of the sample as a development set and the remaining fifth as the validation set. At 28 days after ICU admission, 19.98% of the patients were still in the hospital. Because of the different sampling space and outcome variables, both models presented a better fit in this sample than did the SAPS 3 admission score calibrated to vital status at hospital discharge, both on the general population and in major subgroups. CONCLUSIONS: Both statistical methods can be used to model the 28-day in-hospital mortality better than the SAPS 3 admission model. However, because the logistic regression approach is specifically designed to forecast 28-day mortality, and given the high uncertainty associated with the assumption of the proportionality of risks in the Cox model, the logistic regression approach proved to be superior.

Acute Kidney Injury after Pediatric Cardiac Surgery: Risk Factors and Outcomes. Proposal for a Predictive Model

Objectives: To characterize the epidemiology and risk factors for acute kidney injury (AKI) after pediatric cardiac surgery in our center, to determine its association with poor short-term outcomes, and to develop a logistic regression model that will predict the risk of AKI for the study population. Methods: This single-center, retrospective study included consecutive pediatric patients with congenital heart disease who underwent cardiac surgery between January 2010 and December 2012. Exclusion criteria were a history of renal disease, dialysis or renal transplantation. Results: Of the 325 patients included, median age three years (1 day---18 years), AKI occurred in 40 (12.3%) on the first postoperative day. Overall mortality was 13 (4%), nine of whom were in the AKI group. AKI was significantly associated with length of intensive care unit stay, length of mechanical ventilation and in-hospital death (p<0.01). Patients’ age and postoperative serum creatinine, blood urea nitrogen and lactate levels were included in the logistic regression model as predictor variables. The model accurately predicted AKI in this population, with a maximum combined sensitivity of 82.1% and specificity of 75.4%. Conclusions: AKI is common and is associated with poor short-term outcomes in this setting. Younger age and higher postoperative serum creatinine, blood urea nitrogen and lactate levels were powerful predictors of renal injury in this population. The proposed model could be a useful tool for risk stratification of these patients.