Use of Penalized Count Regression to Determine Factors Affecting the Length of Stay of Trauma Patients in the Intensive Care Unit

Trauma is considered an important issue in most countries. Identification of the factors affecting the length of stay (LOS) in the intensive care unit (ICU) plays a crucial role in controlling the costs and complications of prolonged hospitalization.

This study aimed to identify the factors affecting the LOS of trauma patients in the ICU using stepwise and new penalized variable selection methods in count data regression.

The patients’ information was evaluated in Emtiaz Hospital and Shahid Rajaee trauma center in Shiraz from March 2016 to September 2017. Count regression model was used to determine the factors affecting the LOS of patients in the ICU using penalized variable selection including, Enet, Snet, and Mnet.

The mean age of the patients (n=382) was obtained at 36.7±16.7 years, and the majority (88.4%) of the patients were male. The mean LOS in the ICU was determined at 6.2±6.6 days. Mnet with a negative binomial distribution outperformed the other penalized variable selection methods. A Glasgow Coma Scale (GCS) of less than 9 (IRR=1.7), blunt brain trauma (IRR=1.8), chest trauma (IRR=2.2), and oxygen saturation of less than 90 (IRR=1.2) increased the LOS of trauma patients in the ICU.

Penalized variable selection methods effectively ignore or control the existing correlations between predictors. Amongst the penalized models, Mnet provided more acceptable results with smaller Akaike information criterion and fewer predictors. According to this penalty, the most important factors affecting the length of stay were chest trauma, blunt brain trauma, GCS, and oxygen saturation rate. Most clinical studies on trauma have also shown the importance of these factors.