This analysis identifies dysnatremia's effect on mortality in traumatic brain injury patients, revealing blood sugar as a key predictor.
Background: Dysnatremia is known to make hospitalized traumatic brain injury (TBI) patients vulnerable to morbidity and mortality. This investigation aimed at observing frequency of dysnatremia in the first 24 hours and its relationship with mortality in patients with traumatic brain injuries. Materials and Methods: This prospective descriptive-analytical study was conducted at Hashminejad Hospital in Mashhad from April 2023 to March 2024. The study sample included patients with severe traumatic brain injuries. Information about each patient, including age, sex, Glasgow coma score, blood pressure, plasma sodium, creatinine, serum sugar, calcium, potassium, blood urea nitrogen, and blood pressure at the beginning of admission. Results: A total of 81 patients with traumatic brain injuries, with an average age of 40.33 ± 19.47 years were included in the study; 85% were male and 15% were female. 32 patients (40%) died and the rest were discharged. Out of a total of 81 patients included in the study, 36 (44.5%) suffered from dysnatremia. 16 patients (19.8%) had hyponatremia and 20 (24.7%) had hypernatremia. The statistical results did not show any significant relationship between the sodium status of patients and their outcome. statistical analysis showed that the patient’s sodium level during hospitalization is not a predictor of mortality. Diastolic blood pressure and blood sugar in deceased patients were substantially higher than alive patients. the only factor that could predict the death of patients was blood sugar, so that every incremental rise in glucose level increased the chance of death by 1.018 times. Conclusion: The present study showed that although dysnatremia has no significant relationship with the outcome of brain trauma patients, it needs attention due to its high incidence rate (44.5%) in these patients. In addition, blood sugar was introduced as a factor that could predict the death of patients.
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Kakhki et al. (2025) studied this question.
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