| 1. |
- Yang, Yang, et al.
(author)
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The association of patient age with postoperative morbidity and mortality following resection of intracranial tumors.
- 2021
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In: Brain & spine. - : Elsevier BV. - 2772-5294. ; 1
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Journal article (peer-reviewed)abstract
- The postoperative functional status of patients with intracranial tumors is influenced by patient-specific factors, including age.This study aimed to elucidate the association between age and postoperative morbidity or mortality following the resection of brain tumors.A multicenter database was retrospectively reviewed. Functional status was assessed before and 3-6 months after tumor resection by the Karnofsky Performance Scale (KPS). Uni- and multivariable linear regression were used to estimate the association of age with postoperative change in KPS. Logistic regression models for a ≥10-point decline in KPS or mortality were built for patients ≥75 years.The total sample of 4864 patients had a mean age of 56.4±14.4 years. The mean change in pre-to postoperative KPS was -1.43. For each 1-year increase in patient age, the adjusted change in postoperative KPS was -0.11 (95% CI -0.14 - - 0.07). In multivariable analysis, patients ≥75 years had an odds ratio of 1.51 to experience postoperative functional decline (95%CI 1.21-1.88) and an odds ratio of 2.04 to die (95%CI 1.33-3.13), compared to younger patients.Patients with intracranial tumors treated surgically showed a minor decline in their postoperative functional status. Age was associated with this decline in function, but only to a small extent.Patients ≥75 years were more likely to experience a clinically meaningful decline in function and about two times as likely to die within the first 6 months after surgery, compared to younger patients.
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| 2. |
- Staartjes, Victor E, et al.
(author)
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Development and external validation of a clinical prediction model for functional impairment after intracranial tumor surgery.
- 2021
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In: Journal of neurosurgery. - 1933-0693. ; 134, s. 1743-1750
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Journal article (peer-reviewed)abstract
- Decision-making for intracranial tumor surgery requires balancing the oncological benefit against the risk for resection-related impairment. Risk estimates are commonly based on subjective experience and generalized numbers from the literature, but even experienced surgeons overestimate functional outcome after surgery. Today, there is no reliable and objective way to preoperatively predict an individual patient's risk of experiencing any functional impairment.The authors developed a prediction model for functional impairment at 3 to 6 months after microsurgical resection, defined as a decrease in Karnofsky Performance Status of ≥ 10 points. Two prospective registries in Switzerland and Italy were used for development. External validation was performed in 7 cohorts from Sweden, Norway, Germany, Austria, and the Netherlands. Age, sex, prior surgery, tumor histology and maximum diameter, expected major brain vessel or cranial nerve manipulation, resection in eloquent areas and the posterior fossa, and surgical approach were recorded. Discrimination and calibration metrics were evaluated.In the development (2437 patients, 48.2% male; mean age ± SD: 55 ± 15 years) and external validation (2427 patients, 42.4% male; mean age ± SD: 58 ± 13 years) cohorts, functional impairment rates were 21.5% and 28.5%, respectively. In the development cohort, area under the curve (AUC) values of 0.72 (95% CI 0.69-0.74) were observed. In the pooled external validation cohort, the AUC was 0.72 (95% CI 0.69-0.74), confirming generalizability. Calibration plots indicated fair calibration in both cohorts. The tool has been incorporated into a web-based application available at https://neurosurgery.shinyapps.io/impairment/.Functional impairment after intracranial tumor surgery remains extraordinarily difficult to predict, although machine learning can help quantify risk. This externally validated prediction tool can serve as the basis for case-by-case discussions and risk-to-benefit estimation of surgical treatment in the individual patient.
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