ABSTRACT
BACKGROUND: Hip fracture is associated with high mortality. Identification of individual risk informs anesthetic and surgical decision-making and can reduce the risk of death. However, interpreting mathematical models and applying them in clinical practice can be difficult. There is a need to simplify risk indices for clinicians and laypeople alike. OBJECTIVE: Our primary objective was to develop a web-based nomogram for prediction of survival up to 365 days after hip fracture surgery. METHODS: We collected data from 329 patients. Our variables included sex; age; BMI; white cell count; levels of lactate, creatinine, hemoglobin, and C-reactive protein; physical status according to the American Society of Anesthesiologists Physical Status Classification System; socioeconomic status; duration of surgery; total time in the operating room; side of surgery; and procedure urgency. Thereafter, we internally calibrated and validated a Cox proportional hazards model of survival 365 days after hip fracture surgery; logistic regression models of survival 30, 120, and 365 days after surgery; and a binomial model. To present the models on a laptop, tablet, or mobile phone in a user-friendly way, we built an app using Shiny (RStudio). The app showed a drop-down box for model selection and horizontal sliders for data entry, model summaries, and prediction and survival plots. A slider represented patient follow-up over 365 days. RESULTS: Of the 329 patients, 24 (7.3%) died within 30 days of surgery, 65 (19.8%) within 120 days, and 94 (28.6%) within 365 days. In all models, the independent predictors of mortality were age, BMI, creatinine level, and lactate level. The logistic model also incorporated white cell count as a predictor. The Cox proportional hazards model showed that mortality differed as follows: age 80 vs 60 years had a hazard ratio (HR) of 0.6 (95% CI 0.3-1.1), a plasma lactate level of 2 vs 1 mmol/L had an HR of 2.4 (95% CI 1.5-3.9), and a plasma creatinine level of 60 vs 90 mol/L had an HR of 2.3 (95% CI 1.3-3.9). CONCLUSIONS: In conclusion, we provide an easy-to-read web-based nomogram that predicts survival up to 365 days after hip fracture. The Cox proportional hazards model and logistic models showed good discrimination, with concordance index values of 0.732 and 0.781, respectively.
ABSTRACT
Recent fate-mapping studies in mice have provided substantial evidence that mature adult hepatocytes are a major source of new hepatocytes after liver injury. In other systems, integrin αvß8 has a major role in activating transforming growth factor (TGF)-ß, a potent inhibitor of hepatocyte proliferation. We hypothesized that depletion of hepatocyte integrin αvß8 would increase hepatocyte proliferation and accelerate liver regeneration after injury. Using Itgb8flox/flox;Alb-Cre mice to deplete hepatocyte αvß8, after partial hepatectomy, hepatocyte proliferation and liver-to-body weight ratio were significantly increased in Itgb8flox/flox;Alb-Cre mice compared with control mice. Antibody-mediated blockade of hepatocyte αvß8 in vitro, with assessment of TGF-ß signaling pathways by real-time quantitative PCR array, supported the hypothesis that integrin αvß8 inhibition alters hepatocyte TGF-ß signaling toward a pro-regenerative phenotype. A diethylnitrosamine-induced model of hepatocellular carcinoma, used to examine the possibility that this pro-proliferative phenotype might be oncogenic, revealed no difference in either tumor number or size between Itgb8flox/flox;Alb-Cre and control mice. Immunohistochemistry for integrin αvß8 in healthy and injured human liver demonstrated that human hepatocytes express integrin αvß8. Depletion of hepatocyte integrin αvß8 results in increased hepatocyte proliferation and accelerated liver regeneration after partial hepatectomy in mice. These data demonstrate that targeting integrin αvß8 may represent a promising therapeutic strategy to drive liver regeneration in patients with a broad range of liver diseases.
