Analysis of Relevant Predictive Indicators for Postoperative Condition Change in Brain Tumor Patients

Abstract

Background: Novice nurse need more guidance and professional confidence. This study aimed to explore early relevant predictive indicators for postoperative condition changes in brain tumor patients, which can be used to map patients’ condition changes for novice nurses. Methods: The authors prospectively collected clinical data, including nursing records of cerebral tumor patients after operation from July 2020 to June 2021 in the Department of Neurosurgery. Univariant analysis and multivariable logistic regression analysis were performed to identify independent predictors, the satisfaction questionnaire for teaching nurses is used to evaluate the new nurse’s performance during perioperative period, psychometric scale is used to assess nurses’ psychological stress. Results: Nine hundred ninety-five cerebral tumor patients were enrolled in this study, and 115 (11.6%) patients’ conditions were changed. Relevant predictive indicators, including vision, myodynamia, urine volume, nausea, vomit, pain, Glasgow Coma Scale (GCS), and Modified Early Warning System (MEWS), among them GCS, MEWS, and vision can basically cover the above indicators through simulation and calculation of the integrated model was set as Z=22*vision+1*GCS+3*MEWS. The satisfaction rate of teaching nurses has increased from 78.125 to 86.25%. Novice nurses' psychological stress was dropped from 30.637% to 19.844%. Conclusions: GCS and MEWS. GCS, MEWS and vision can map patients’ condition change after cerebral tumor operation. The warning model has reduced their psychological stress, and the teaching nurse expressed that the effective evaluation of postoperative patient conditions by novice nurses reduces their nursing and teaching work greatly.