Development of an exploratory mismatch negativity-based prognostic nomogram for consciousness recovery in patients...

Prolonged disorders of consciousness (pDOC) pose significant clinical and societal challenges. Evaluating the prognosis of patients with pDOC is of a great concern for clinicians. This derivation study aimed to establish a nomogram based on mismatch negativity (MMN) to predict the recovery of consciousness in patients with pDOC.

This is a single-center retrospective derivation study. From September 2021 to June 2023, demographic and clinical information and MMN results of patients with pDOC were collected. The prognosis of patients who were admitted to the hospital for 6 months was assessed using the Glasgow Outcome Scale, categorized as "unfavorable prognosis" and "favorable prognosis." In this study, Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were used to select the most relevant predictors and create the nomogram. Receiver Operating Characteristic (ROC), calibration curves and Decision Curves Analysis (DCA) in the nomogram explained the predictive efficacy and clinical utility of the patients.

101 patients with pDOC were included, with 57 and 44 having unfavorable and favorable prognose. Univariate and LASSO regression analysis indicated that the MMN amplitude at Fz, Coma Recovery Scale-Revised scores, disease duration, and multiple intensive care unit admissions were the independent factors that were used to develop the exploration nomogram. ROC curves, calibration curves, and DCA showed good predictive power (area under the ROC curve: 0.821), with DCA suggested potential net benefit within clinically relevant decision-probability ranges.

In this study, an exploratory nomogram developed based on MMN predicted the 6-month outcome of patients with pDOC. This exploratory, internally validated model may support prognostic assessment.