ePoster

Association of insulin-like growth factor 1 with post-traumatic brain injury sleep disorders: A longitudinal study

Kai-Yun Chenand 3 co-authors
FENS Forum 2024 (2024)
Messe Wien Exhibition & Congress Center, Vienna, Austria

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Association of insulin-like growth factor 1 with post-traumatic brain injury sleep disorders: A longitudinal study poster preview

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Abstract

Mild traumatic brain injury (mTBI) poses a significant public health concern due to its association with psychiatric complications, including anxiety, depression, and sleep disturbances. Insulin-like growth factor 1 (IGF-1), known for its implications in acromegaly and cancer, has been linked to metabolic syndrome in patients with obstructive sleep apnea. This study aimed to investigate the relationship between IGF-1 and post-TBI sleep disorders and its predictive value for sleep disorder onset. Fifty-nine mTBI patients underwent a 1-year follow-up assessment, among whom 20 individuals aged 41–60 reported poor sleep quality based on evaluations using the Pittsburgh Sleep Quality Index (PSQI), Beck Anxiety Inventory (BAI), and Beck Depression Inventory (BDI). IGF-1 levels were measured within two weeks post-injury. Receiver operating characteristic curve analysis demonstrated area under the curve (AUC) values of 0.665 for age, 0.792 for PSQI, 0.829 for BAI, 0.629 for BDI scores, and 0.703 for IGF-1 levels. Seventeen models were constructed, combining these risk factors with four potential cutoff point sets. A risk profile comprising age, sex, and IGF-1 ratio yielded an AUC value of 0.885. Subsequently, a cutoff point with a sensitivity of 0.895 and specificity of 0.75 was selected. Further analysis revealed that adults aged ≥50 years, male, and with an IGF-1 ratio ≥1.16 were at high risk of poor sleep quality one-year post-injury. This risk profile provides insights into mTBI, facilitating early prediction of poor sleep quality at 1-year assessment. Identifying mTBI patients at high risk for poor sleep quality enables targeted interventions to improve patient outcomes.

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