Researchers developed and validated a dynamic nomogram prediction model to identify the early need for tracheotomy (TT) in patients with supratentorial deep-seated intracranial hemorrhage (SDICH). The model showed that key clinical variables such as Glasgow Coma Score, white blood cell count, platelet count, and heart rate were reliable markers for early TT need. Using retrospective data from 1,046 patients treated between January 1, 2019, and January 1, 2023, at two hospitals in China, the model was trained on 667 cases and externally validated on 379 cases. The model demonstrated strong predictive performance, with an area under the curve of 0.817 in the training group and 0.768 in the validation group. Among all the patients, 19.02% underwent early TT. Calibration and decision curve analyses confirmed there was close alignment between the predicted and observed outcomes. “The dynamic nomogram provides an efficient and accessible tool for clinicians, supporting timely decision-making for early TT,” the study authors conclude.