{Reference Type}: Journal Article
{Title}: Prediction of prolonged length of stay on the intensive care unit in severely injured patients-a registry-based multivariable analysis.
{Author}: Lefering R;Waydhas C; ;
{Journal}: Front Med (Lausanne)
{Volume}: 11
{Issue}: 0
{Year}: 2024
{Factor}: 5.058
{DOI}: 10.3389/fmed.2024.1358205
{Abstract}: UNASSIGNED: Mortality is the primary outcome measure in severely injured trauma victims. However, quality indicators for survivors are rare. We aimed to develop and validate an outcome measure based on length of stay on the intensive care unit (ICU).
UNASSIGNED: The TraumaRegister DGU of the German Trauma Society (DGU) was used to identify 108,178 surviving patients with serious injuries who required treatment on ICU (2014-2018). In a first step, need for prolonged ICU stay, defined as 8 or more days, was predicted. In a second step, length of stay was estimated in patients with a prolonged stay. Data from the same trauma registry (2019-2022, n = 72,062) were used to validate the models derived with logistic and linear regression analysis.
UNASSIGNED: The mean age was 50 years, 70% were males, and the average Injury Severity Score was 16.2 points. Average/median length of stay on ICU was 6.3/2 days, where 78% were discharged from ICU within the first 7 days. Prediction of need for a prolonged ICU stay revealed 15 predictors among which injury severity (worst Abbreviated Injury Scale severity level), need for intubation, and pre-trauma condition were the most important ones. The area under the receiver operating characteristic curve was 0.903 (95% confidence interval 0.900-0.905). Length of stay prediction in those with a prolonged ICU stay identified the need for ventilation and the number of injuries as the most important factors. Pearson's correlation of observed and predicted length of stay was 0.613. Validation results were satisfactory for both estimates.
UNASSIGNED: Length of stay on ICU is a suitable outcome measure in surviving patients after severe trauma if adjusted for severity. The risk of needing prolonged ICU care could be calculated in all patients, and observed vs. predicted rates could be used in quality assessment similar to mortality prediction. Length of stay prediction in those who require a prolonged stay is feasible and allows for further benchmarking.