A pilot project informing the design of a web-based dynamic nomogram in order to predict survival one year after hip fracture surgery

Background: Hip fracture is associated with high mortality. Identification of individual risk informs anaesthetic and surgical decision making and can reduce the risk of death. However, interpretation of mathematical models and application to clinical practice can be difficult, and there is a need to simplify risk indices for clinicians and lay-people alike.

Objective: Our primary objective was to develop a web-based nomogram for prediction of survival up to 365 days after fracture hip surgery.

Methods: We collected data from 329 patients. Our variables included sex, age, BMI, white cell count, lactate, creatinine, hemoglobin, C-reactive protein, ASA status, socio-economic 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 (CPH) model of survival 365 days after hip fracture surgery, logistic regression models 30-, 120- and 365-days after surgery and a binomial model. In order to present models on a laptop, tablet or phone in a user-friendly way, we built any app using Shiny (RStudio). The app consisted of a drop-down box for model selection, horizontal sliders for data entry, model summaries, and prediction and survival plots. A slider represents patient follow-up over 365 days.

Results: Twenty-four patients died within 30 days, 65 (19.8%) within 120 days and 94 (28.6%) within 365 days of surgery. For all models, independent predictors of mortality were: age, BMI, creatinine and lactate. The logistic model also incorporated WCC. For example, using the CPH model, mortality differed as follows: age 80 yr vs 60 yr, HR 0.6 (0.3 to 1.1); plasma lactate levels of 2 mmol.L-1 vs 1 mmol.L-1, HR 2.4 (1.5 - 3.9); and plasma creatinine levels 60 vs 90 mol.L-1, HR 2.3 (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 CPH and logistic models model showed good discrimination (c-indices 0.732 and 0.781 respectively).