Chinese Admission Warning Strategy for Predicting the Hospital Discharge Outcome in Patients with Traumatic Brain Injury

Abstract

Objective: To develop and validate an admission warning strategy that incorporates the general emergency department indicators for predicting the hospital discharge outcome of patients with traumatic brain injury (TBI) in China. Methods: This admission warning strategy was developed in a primary cohort that consisted of 605 patients with TBI who were admitted within 6 h of injury. The least absolute shrinkage and selection operator and multivariable logistic regression analysis were used to develop the early warning strategy of selected indicators. Two sub-cohorts consisting of 180 and 107 patients with TBI were used for the external validation. Results: Indicators of the strategy included three categories: baseline characteristics, imaging and laboratory indicators. This strategy displayed good calibration and good discrimination. A high C-index was reached in the internal validation. The multicenter external validation cohort still showed good discrimination C-indices. Decision curve analysis (DCA) showed the actual needs of this strategy when the possibility threshold was 0.01 for the primary cohort, and at thresholds of 0.02–0.83 and 0.01–0.88 for the two sub-cohorts, respectively. In addition, this strategy exhibited a significant prognostic capacity compared to the traditional single predictors, and this optimization was also observed in two external validation cohorts. Conclusions: We developed and validated an admission warning strategy that can be quickly deployed in the emergency department. This strategy can be used as an ideal tool for predicting hospital discharge outcomes and providing objective evidence for early informed consent of the hospital discharge outcome to the family members of TBI patients.

Combining bulk and scRNA‐seq to explore the molecular mechanisms governing the distinct efferocytosis activities of a macrophage subpopulation in PDAC

“…The present investigation has successfully discovered genes that have a statistically significant correlation with patient prognosis ( p < 0.05). To address the problem of multicollinearity among the genes, we performed further screening on these genes using LASSO regression (glmnet, version 4.1–6) 21–25 . The risk coefficients for each gene were subsequently estimated using multivariate Cox regression analysis.…”

“…To address the problem of multicollinearity among the genes, we performed further screening on these genes using LASSO regression (glmnet, version 4.1–6). 21 , 22 , 23 , 24 , 25 The risk coefficients for each gene were subsequently estimated using multivariate Cox regression analysis. The study incorporated survival analyses using the Kaplan–Meier technique, which was executed using the R package Survival (version 3.3–1).…”

An analysis of neutrophil-to-lymphocyte ratios and monocyte-to-lymphocyte ratios with six-month prognosis after cerebral contusions

“…On the other hand, an admission warning strategy which comprises 10 indicators, including baseline characteristics (age, GCS score, pupillary reactivity and hypotension), imaging indicators (midline shift, intracerebral hematoma, traumatic subarachnoid hematoma, and basal cistern), and laboratory indicators (glucose level and monocyte count), was developed and validated to predict the outcome of TBI patients. This warning system was proved to have a good discrimination with short-term outcomes ( 10 ).…”