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Association of postoperative delirium with serum and cerebrospinal fluid proteomic profiles: a prospective cohort study in older hip fracture patients

GeroScience, 2024

Lozano-Vicario L., Muñoz-Vázquez ?., Ramírez-Vélez R., Galbete-Jiménez A., Fernández-Irigoyen J., Santamaría E., Cedeno-Veloz B., Zambom-Ferraresi F., Van Munster B., Ortiz-Gómez J., Hidalgo-Ovejero ?., Romero-Ortuno R., Izquierdo M., Martínez-Velilla N.

Disease areaApplication areaSample typeProducts
Neurology
Aging
Patient Stratification
Serum
CSF
O

Olink Target 48

Abstract

Postoperative delirium (POD) is a common neuropsychiatric complication in geriatric inpatients after hip fracture surgery and its occurrence is associated with poor outcomes. The purpose of this study was to investigate the relationship between preoperative biomarkers in serum and cerebrospinal fluid (CSF) and the development of POD in older hip fracture patients, exploring the possibility of integrating objective methods into future predictive models of delirium. Sixty hip fracture patients were recruited. Blood and CSF samples were collected at the time of spinal anesthesia when none of the subjects had delirium. Patients were assessed daily using the 4AT scale, and based on these results, they were divided into POD and non-POD groups. The Olink® platform was used to analyze 45 cytokines. Twenty-one patients (35%) developed POD. In the subsample of 30 patients on whom proteomic analyses were performed, a proteomic profile was associated with the incidence of POD. Chemokine (C-X-C motif) ligand 9 (CXCL9) had the strongest correlation between serum and CSF samples in patients with POD (rho = 0.663; p < 0.05). Although several cytokines in serum and CSF were associated with POD after hip fracture surgery in older adults, there was a significant association with lower preoperative levels of CXCL9 in CSF and serum. Despite the small sample size, this study provides preliminary evidence of the potential role of molecular biomarkers in POD, which may provide a basis for the development of new delirium predictive models.

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