A hematoma location-based nomogram for individualized prediction of thalamic pain after spontaneous thalamic hemorrhage.

OBJECTIVE: To identify predictors of thalamic pain (TP) within 6 months after spontaneous thalamic hemorrhage (STH), develop and internally validate a prediction model, and explore the association between hematoma location and pain severity. METHODS: We retrospectively analyzed 410 patients with STH (training, n = 287; validation, n = 123). Predictors were selected using LASSO and multivariable logistic regression to construct a nomogram. Discrimination, calibration, and net benefit were assessed using AUC, calibration curves, and decision curve analysis. Interaction and subgroup analyses assessed whether the association between hematoma location and TP varied with modified Graeb score (mGS). Among patients with TP, differences in maximum NRS scores across hematoma locations and the correlation between initial hematoma volume and maximum NRS score were examined. RESULTS: TP occurred in 27.87% of the training cohort and 38.21% of the validation cohort. The nomogram, incorporating hematoma location, mGS score, and body temperature, showed AUCs of 0.852 and 0.870 in the training and validation cohorts, respectively, with good calibration and favorable net benefit. The association between hematoma location and TP appeared more pronounced at lower mGS scores. Among 127 patients with TP, maximum NRS scores differed significantly across hematoma locations (P < 0.001), with lateral bleed showing the highest pain intensity. Initial hematoma volume was not correlated with maximum NRS score (ρ = 0.030, P = 0.736). CONCLUSION: The nomogram estimates TP risk after STH. Hematoma location may be particularly informative at lower mGS scores and is associated with pain severity, supporting risk stratification using routine clinical and CT features.