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INTENSIVE CARE MEDICINE / CLINICAL RESEARCH
Postoperative hyperglycemia in patients with traumatic brain injury: development of a prediction model
1
Department of Neurosurgery, Suzhou Hospital, Affiliated Hospital of Medical School, Nanjing University, Suzhou, China
2
Department of Neurosurgery, The 904th Hospital of the Joint Logistics Support Force of Chinese People’s Liberation Army, Wuxi, China
These authors had equal contribution to this work
Submission date: 2024-02-21
Final revision date: 2024-04-16
Acceptance date: 2024-04-27
Online publication date: 2024-06-06
Publication date: 2025-02-28
Corresponding author
Lichun Lu
Suzhou Hospital Affiliated Hospital of Medical School Nanjing University No. 1, Lijiang road Huqiu district Suzhou, Jiangsu province China Phone: 13613446618
Suzhou Hospital Affiliated Hospital of Medical School Nanjing University No. 1, Lijiang road Huqiu district Suzhou, Jiangsu province China Phone: 13613446618
Xianlan Meng
Suzhou Hospital Affiliated Hospital of Medical School Nanjing University No. 1, Lijiang road Huqiu district Suzhou, Jiangsu province China Phone: 13613446618
Suzhou Hospital Affiliated Hospital of Medical School Nanjing University No. 1, Lijiang road Huqiu district Suzhou, Jiangsu province China Phone: 13613446618
Arch Med Sci 2025;21(1):131-137
KEYWORDS
TOPICS
ABSTRACT
Introduction:
Blood glucose monitoring and management are very important for the prognosis of patients with traumatic brain injury (TBI). It is necessary to evaluate the status and influencing factors of hyperglycemia within 48 h after the operation in patients with TBI.
Material and methods:
Patients with TBI who received craniocerebral surgery between March 1, 2022, and October 31, 2023, were enrolled. We assessed the clinical characteristics of TBI patients with and without the development of postoperative hyperglycemia. To identify potential risk factors associated with postoperative hyperglycemia, we performed both univariate and multivariate logistic regression analyses. Utilizing the regression coefficients derived from each significant risk factor, we subsequently constructed a predictive model aimed at forecasting postoperative hyperglycemia.
Results:
A total of 216 TBI patients were included. The incidence of postoperative hyperglycemia was 31.48%. Correlation analysis indicated that age (r = 0.415), body mass index (BMI) (r = 0.441), diabetes (r = 0.513), Glasgow Coma Scale (GCS) score (r = 0.545) and length of hospital stay (r = 0.456) were all correlated with the postoperative hyperglycemia in TBI patients (all p < 0.05). Age ≥ 60 years (OR = 2.556, 95% CI: 1.831–3.641), BMI ≥ 24 kg/m2 (OR = 2.793, 95% CI: 2.305–3.679), diabetes (OR = 3.081, 95% CI: 2.326–3.811) and GCS score ≤ 8 (OR = 3.603, 95% CI: 1.956–4.086) were the independent factors influencing postoperative hyperglycemia in TBI patients (all p < 0.05). The area under the receiver operating characteristic curve and 95% CI were 0.795 (0.712, 0.849). The model had good discriminative ability to distinguish the occurrence of postoperative hyperglycemia in TBI patients (all p < 0.05).
Conclusions:
Postoperative hyperglycemia in patients with TBI is common. For TBI patients with a total score ≥ 6 in the prediction model, early interventions and care are needed to reduce the postoperative hyperglycemia.
Blood glucose monitoring and management are very important for the prognosis of patients with traumatic brain injury (TBI). It is necessary to evaluate the status and influencing factors of hyperglycemia within 48 h after the operation in patients with TBI.
Material and methods:
Patients with TBI who received craniocerebral surgery between March 1, 2022, and October 31, 2023, were enrolled. We assessed the clinical characteristics of TBI patients with and without the development of postoperative hyperglycemia. To identify potential risk factors associated with postoperative hyperglycemia, we performed both univariate and multivariate logistic regression analyses. Utilizing the regression coefficients derived from each significant risk factor, we subsequently constructed a predictive model aimed at forecasting postoperative hyperglycemia.
Results:
A total of 216 TBI patients were included. The incidence of postoperative hyperglycemia was 31.48%. Correlation analysis indicated that age (r = 0.415), body mass index (BMI) (r = 0.441), diabetes (r = 0.513), Glasgow Coma Scale (GCS) score (r = 0.545) and length of hospital stay (r = 0.456) were all correlated with the postoperative hyperglycemia in TBI patients (all p < 0.05). Age ≥ 60 years (OR = 2.556, 95% CI: 1.831–3.641), BMI ≥ 24 kg/m2 (OR = 2.793, 95% CI: 2.305–3.679), diabetes (OR = 3.081, 95% CI: 2.326–3.811) and GCS score ≤ 8 (OR = 3.603, 95% CI: 1.956–4.086) were the independent factors influencing postoperative hyperglycemia in TBI patients (all p < 0.05). The area under the receiver operating characteristic curve and 95% CI were 0.795 (0.712, 0.849). The model had good discriminative ability to distinguish the occurrence of postoperative hyperglycemia in TBI patients (all p < 0.05).
Conclusions:
Postoperative hyperglycemia in patients with TBI is common. For TBI patients with a total score ≥ 6 in the prediction model, early interventions and care are needed to reduce the postoperative hyperglycemia.
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| eISSN: | 1896-9151 |
| ISSN: | 1734-1922 |
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