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A novel online calculator predicting short-term postoperative outcomes in patients with metastatic brain tumors.
Khalafallah, Adham M; Jimenez, Adrian E; Patel, Palak; Huq, Sakibul; Azmeh, Omar; Mukherjee, Debraj.
Afiliación
  • Khalafallah AM; Department of Neurosurgery, Johns Hopkins University School of Medicine, 1800 Orleans St, Baltimore, MD, 21287, USA.
  • Jimenez AE; Department of Neurosurgery, Johns Hopkins University School of Medicine, 1800 Orleans St, Baltimore, MD, 21287, USA.
  • Patel P; Department of Neurosurgery, Johns Hopkins University School of Medicine, 1800 Orleans St, Baltimore, MD, 21287, USA.
  • Huq S; Department of Neurosurgery, Johns Hopkins University School of Medicine, 1800 Orleans St, Baltimore, MD, 21287, USA.
  • Azmeh O; Department of Neurosurgery, Johns Hopkins University School of Medicine, 1800 Orleans St, Baltimore, MD, 21287, USA.
  • Mukherjee D; Department of Neurosurgery, Johns Hopkins University School of Medicine, 1800 Orleans St, Baltimore, MD, 21287, USA. dmukher1@jhmi.edu.
J Neurooncol ; 149(3): 429-436, 2020 Sep.
Article en En | MEDLINE | ID: mdl-32964354
ABSTRACT

PURPOSE:

Establishing predictors of hospital length of stay (LOS), discharge deposition, and total hospital charges is essential to providing high-quality, value-based care. Though previous research has investigated these outcomes for patients with metastatic brain tumors, there are currently no tools that synthesize such research findings and allow for prediction of these outcomes on a patient-by-patient basis. The present study sought to develop a prediction calculator that uses patient demographic and clinical information to predict extended hospital length of stay, non-routine discharge disposition, and high total hospital charges for patients with metastatic brain tumors.

METHODS:

Patients undergoing surgery for metastatic brain tumors at a single academic institution were analyzed (2017-2019). Multivariate logistic regression was used to identify independent predictors of extended LOS (> 7 days), non-routine discharge, and high total hospital charges (> $ 46,082.63). p < 0.05 was considered statistically significant. C-statistics and the Hosmer-Lemeshow test were used to assess model discrimination and calibration, respectively.

RESULTS:

A total of 235 patients were included in our analysis, with a mean age of 62.74 years. The majority of patients were female (52.3%) and Caucasian (76.6%). Our models predicting extended LOS, non-routine discharge, and high hospital charges had optimism-corrected c-statistics > 0.7, and all three models demonstrated adequate calibration (p > 0.05). The final models are available as an online calculator ( https//neurooncsurgery.shinyapps.io/brain_mets_calculator/ ).

CONCLUSIONS:

Our models predicting postoperative outcomes allow for individualized risk-estimation for patients following surgery for metastatic brain tumors. Our results may be useful in helping clinicians to provide resource-conscious, high-value care.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Complicaciones Posoperatorias / Neoplasias Encefálicas / Procedimientos Neuroquirúrgicos Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Male / Middle aged Idioma: En Revista: J Neurooncol Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Complicaciones Posoperatorias / Neoplasias Encefálicas / Procedimientos Neuroquirúrgicos Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Male / Middle aged Idioma: En Revista: J Neurooncol Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos