A cost-sensitive multiclass machine learning framework for postoperative neurosurgical triage (Neuro-TACTIC)
Postoperative placement of patients into a regular ward, an intermediate-care unit (IMC), or an intensive care unit (ICU) is critical for balancing patient safety against resource constraints. Most existing models collapse this decision into a binary ICU versus non-ICU choice and lack a mechanism to...
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| Autores principales: | , , , , , , |
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| Formato: | Article (Journal) |
| Lenguaje: | inglés |
| Publicado: |
24 March 2026
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| In: |
Scientific reports
Year: 2026, Volumen: 16, Pages: 1-13 |
| ISSN: | 2045-2322 |
| DOI: | 10.1038/s41598-026-45092-1 |
| Acceso en línea: | Verlag, kostenfrei, Volltext: https://doi.org/10.1038/s41598-026-45092-1 Verlag, kostenfrei, Volltext: https://www.nature.com/articles/s41598-026-45092-1 
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| Notas de Autor: | Paul Vincent Naser, Maximilian Fischer, Roberto Diaz Peregrino, Martin Jakobs, Sandro Krieg, Peter Neher, Jan-Oliver Neumann |
| Sumario: | Postoperative placement of patients into a regular ward, an intermediate-care unit (IMC), or an intensive care unit (ICU) is critical for balancing patient safety against resource constraints. Most existing models collapse this decision into a binary ICU versus non-ICU choice and lack a mechanism to tune risk thresholds to local staffing ratios or definitions of ICU‐level events. We developed Neuro-TACTIC, a cost-sensitive machine learning framework that stratifies postoperative neurosurgical patients into three monitoring levels: regular ward, intermediate care unit, and intensive care unit. An XGBoost-based classifier was trained on 27 demographic, intraoperative, and imaging-derived features from a retrospective cohort of 1072 patients undergoing elective craniotomy. A tunable parameter ζ integrates resource-related and harm-related costs to adjust the balance between over- and under-triage. Generalization was assessed in an independent cohort. Across repeated cross-validation and bootstrap analyses, the framework demonstrated stable behavior across cost settings. At the operating point ζ = 0.975, performance was AUCμ = 0.67 ± 0.03 and weighted F1 = 0.49 ± 0.03 in the development cohort, and AUCμ = 0.60 ± 0.04 and weighted F1 = 0.44 ± 0.06 in the independent evaluation cohort (n = 81). Feature importance analyses identified operative duration, tumor volume, surgical position, body mass index, and patient age as the most influential predictors. This study demonstrates the feasibility of cost-sensitive, three-tier postoperative triage modeling in neurosurgical patients. Neuro-TACTIC is a methodological proof-of-concept; prospective validation and multicenter evaluation are required before clinical deployment. |
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| Notas: | Veröffentlicht: 24. März 2026 Gesehen am 30.04.2026 |
| Descripción Física: | Online Resource |
| ISSN: | 2045-2322 |
| DOI: | 10.1038/s41598-026-45092-1 |