Factors Predicting Abnormal Postoperative Neurological Symptoms in The First 24 Hours Following Craniotomy in Patients with Primary Brain Tumor

Authors

  • Thanatip Pinchanchaiyuth Faculty of Nursing, Mahidol University
  • Prangtip Chayaput Faculty of Nursing, Mahidol University
  • Wallada Chanruangvanich Faculty of Nursing, Mahidol University
  • Bunpot Sittinamsuwan Faculty of Nursing, Mahidol University

Keywords:

Factor predicting, Abnormal postoperative neurological symptoms, Craniotomy, Primary brain tumor patients, Roy adaptation model

Abstract

This descriptive research aimed to determine predictors of abnormal neurological symptoms after the first 24 hours period of craniotomy among 385 primary brain tumor patients admitted to a single super tertiary hospital. Roy adaptation model was applied as a conceptual framework. The instruments used for data collection were demographic and clinical data record form, and abnormal neurological symptoms record form (sensitivity 0.722 and specificity 0.737). Chi–Square test and Relative Risk were employed for statistical analysis.

The study results noted that most of samples were females (71.2%), had a Meningioma (57.9%), and reported an incident of abnormal postoperative neurological symptoms during the first 24 hours after surgery (49.4%). The top-three abnormal neurological symptoms, most found, included cranial nerve function deficit (26.1%), motor deficit (22.6%), and postoperative seizure (10.6%), respectively. As for statistical analysis, the results showed that tumor size greater than or equal to 4 centimeters (RR=6.94; 95%CI 4.90-9.83, p<.001) and low levels of antiepileptic drugs (RR = 1.33; 95%CI 1.02–1.74, p<.05) could predict abnormal postoperative neurological symptoms significantly.

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Published

01-09-2023

How to Cite

1.
Pinchanchaiyuth T, Chayaput P, Chanruangvanich W, Sittinamsuwan B. Factors Predicting Abnormal Postoperative Neurological Symptoms in The First 24 Hours Following Craniotomy in Patients with Primary Brain Tumor. J Royal Thai Army Nurses [Internet]. 2023 Sep. 1 [cited 2024 Feb. 26];24(2):114-23. Available from: https://he01.tci-thaijo.org/index.php/JRTAN/article/view/260006

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Research Articles