Academic Journal
Construction and validation of a risk prediction model for postoperative nausea and vomiting in craniotomy patients: A cohort study.
| Τίτλος: | Construction and validation of a risk prediction model for postoperative nausea and vomiting in craniotomy patients: A cohort study. |
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| Συγγραφείς: | Wu L; Nursing Department, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China., Pan H, Xu Y, Ding S |
| Πηγή: | Medicine [Medicine (Baltimore)] 2026 Aug 21; Vol. 105 (34), pp. e50193. |
| Τύπος έκδοσης: | Journal Article; Validation Study |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 2985248R Publication Model: Print Cited Medium: Internet ISSN: 1536-5964 (Electronic) Linking ISSN: 00257974 NLM ISO Abbreviation: Medicine (Baltimore) Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Hagerstown, Md : Lippincott Williams & Wilkins |
| Ιατρικοί όροι (MeSH): | Craniotomy*/adverse effects , Postoperative Nausea and Vomiting*/epidemiology , Postoperative Nausea and Vomiting*/etiology, Risk Assessment/methods ; Humans ; Female ; Middle Aged ; Male ; Adult ; Retrospective Studies ; Risk Factors ; ROC Curve ; Cohort Studies ; Incidence ; Prediction Algorithms ; Aged |
| Περίληψη: | Postoperative nausea and vomiting (PONV) is one of the most distressing symptoms experienced by patients. The incidence is high, and complications are dangerous. Therefore, it is important to construct a prediction model to enhance the risk assessment strategies. This study included developmental and validation cohorts. The development cohort consisted of patients who underwent craniotomy between January 1, 2021, and December 31, 2022. Data were retrospectively collected to identify the factors associated with PONV events and to construct a risk prediction model. The validation cohort comprised patients from September 1, 2023, to December 22, 2023, at the same hospital. We collected data prospectively, compared the forecasted outcomes with the actual outcomes, and assessed the external validation performance of the model using model evaluation metrics, such as the area under the receiver operating characteristic curve (AUROC), Brier score, and calibration curves. The incidence of PONV within 24 hours after surgery was 27.2% (181 patients). The independent predictors of PONV after craniotomy were sex, age, preoperative sodium level, surgical site, and postoperative intracranial air accumulation. The predictive model had an AUROC of 0.862 (95% confidence interval = 0.829-0.894, P < .001), a sensitivity of 73.5%, a specificity of 86.8%, and an accuracy of 83.2%. External validation revealed an AUROC of 0.832 (95% confidence interval = 0.744-0.920), a sensitivity of 73.2%, a specificity of 90.3%, and an accuracy of 83.5%. Its reliability has been demonstrated in various clinical settings. We successfully developed a risk prediction model for PONV in patients who underwent craniotomy. This tool has been validated to have good predictive efficacy, which is helpful in helping healthcare professionals identify high-risk patients with PONV after craniotomy at an early stage and lays the foundation for the precise prevention of PONV. (Copyright © 2026 the Author(s). Published by Wolters Kluwer Health, LLC.) |
| Competing Interests: | The authors have no conflicts of interest to declare. |
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| Contributed Indexing: | Keywords: craniotomy; neurosurgery; postoperative nausea and vomiting (PONV); prediction model; risk factors |
| Entry Date(s): | Date Created: 20260822 Date Completed: 20260822 Latest Revision: 20260918 |
| Update Code: | 20260918 |
| PubMed Central ID: | PMC13502832 |
| DOI: | 10.1097/MD.0000000000050193 |
| PMID: | 42629685 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1536-5964 |
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| DOI: | 10.1097/MD.0000000000050193 |