Potential value of serum prealbumin and serum albumin in the identification of postoperative delirium in patients undergoing knee/hip replacement: an observational study and internal validation study

Abstract

Background: Postoperative delirium (POD) is a common postoperative neurological complication that can lead to a variety of postoperative complications. At present, the pathogenesis of POD is unclear. This study aims to explore the relationship between serum prealbumin and serum albumin and POD and whether serum prealbumin and serum albumin influence POD through POD core pathology.

Objective: We enrolled 500 Chinese Han patients between September 2020 to January 2023. We analyzed the risk and protective factors of POD using the multivariate logistic regression. We also assessed the predictive power of serum prealbumin, serum albumin, and both in combination with CSF POD biomarkers. We used Stata MP16.0. to examine whether the association between serum prealbumin and serum albumin and POD was mediated by CSF POD biomarkers, and conducted an internal validation study to verify the accuracy of the combination of serum prealbumin + serum albumin + CSF POD biomarkers for predicting POD. The model was visualized using ROC curve and decision curve analysis (DCA). DynNom and Shiny packages were used to create an online calculator. Ten patients who had POD occurring from February 2023 to October 2023 were selected for internal verification.

Results: Finally, a total of 364 patients were included in our study. Levels of serum prealbumin, serum albumin in the POD group were lower than those in the NPOD group. The lever of serum prealbumin, serum albumin were protective factors for POD. The relationship between serum prealbumin, serum albumin and POD was partially mediated by T-tau (12.28%) and P-tau (20.61%). The model combining serum prealbumin and serum albumin and POD biomarkers exhibited a relatively better discriminatory ability to predict POD. DCA also showed that the combination of serum prealbumin and serum albumin and POD biomarkers brought high predictive benefits to patients. The dynamic online calculator can accurately predict the occurrence of POD in the internal validation study.

Conclusion: Preoperative low serum prealbumin and serum albumin levels were the preoperative risk factors for POD, which is partly mediated by T-tau and P-tau. The model combining serum prealbumin and serum albumin and CSF POD biomarkers can accurately predict the occurrence of POD.

Clinical trial registration: http://www.clinicaltrials.gov, identifier ChiCTR2000033439.

Keywords: biomarkers; neurodegeneration; perioperative neurocognitive disorders; serum albumin; serum prealbumin.

Figure 1

The flow diagram showed the selection of eligible patients and the enrollment process.

Figure 2

Distribution of serum prealbumin and serum albumin and biomarker levels for participants with and without delirium during subsequent hospitalization.

Figure 3

Mediation analyses with postoperative delirium as the cognitive outcome. In the PNDABLE (Perioperative Neurocognitive Disorder And Biomarker LifestylE study), the relationship between serum prealbumin and serum albumin and postoperative delirium was mediated by amyloid pathology indicated by (A, F) amyloid β 42 (Aβ₄₂), (B, G) phosphorylated total-tau (P-tau), (C, H) Total-tau (T-tau), (D, I) amyloid β 42/phosphorylated total-tau (Aβ₄₂/P-tau), and (E, J) amyloid β 42/Total-tau (Aβ₄₂/T-tau). IE, indirect effect.

Figure 4

The ROC curve analysis of serum prealbumin, serum albumin, the combination of serum prealbumin and serum albumin and the combination of serum prealbumin and serum albumin and POD biomarkers showed that the combination of serum prealbumin and serum albumin and POD biomarkers had a high diagnostic value for POD.

Figure 5

The PRC curve analysis of serum prealbumin (A), serum albumin (B), the combination of serum prealbumin and serum albumin (C) and the combination of serum prealbumin and serum albumin and POD biomarkers (D) showed that the combination of serum prealbumin and serum albumin and POD biomarkers had a high diagnostic value for POD.

Figure 6

(A) Calibration curve presented prediction of POD after surgery between the prediction model and actual observation. The Hosmer-Lemeshow test indicated a good prediction of the nomogram. (B) Nomogram for predicting POD after surgery.

Figure 7

The clinical DCA was plotted using R software, and the results showed that the model of the combination of serum prealbumin and serum albumin and POD biomarkers brought a high benefit value to patients.

Figure 8

Visualization for predictive model. The online calculator translated from the nomogram for generating risk of POD by the internal verification. Users can submit values for the seven features into the corresponding text box of the web page through the computer or mobile phone for calculation (A). Once the output of the sample has been calculated, the results page will display the probability of POD, the 95% confidence interval, and the parameters of the model (B, C).