Correlation between cuproptosis-related proteins and postoperative delirium in cardiac valve replacement: a prospective, observational study

Correlation between cuproptosis-related proteins and postoperative delirium in cardiac valve replacement: a prospective, observational study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Correlation between cuproptosis-related proteins and postoperative delirium in cardiac valve replacement: a prospective, observational study Zheng Zhang, Qiuran Zheng, Yangyang Ye, Qin Shi, Weiqin Li, Jingzheng Zeng, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7608169/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Postoperative delirium (POD) is a common neurological complication following cardiac valve replacement. Although cuproptosis, a novel form of copper-dependent cell death, has been implicated in neurological disorders, its relationship with POD remains unclear. This study aimed to investigate the association between perioperative changes in cuproptosis-related biomarkers and POD incidence. Methods This prospective observational study enrolled patients undergoing cardiac valve replacement. Serum levels of copper ion (Cu²⁺), ferredoxin 1 (FDX1), and lipoic acid (LA) were measured at four time points: before anesthesia induction (T1), at cardiopulmonary bypass (CPB) initiation (T2), at CPB cessation (T3), and immediately after surgery (T4). POD was assessed twice daily from postoperative days 1 to 7 using the Richmond Agitation-Sedation Scale (RASS) and the Confusion Assessment Method for the ICU (CAM-ICU). Propensity score matching (PSM) was applied to compare POD and non-POD groups in a 1:1 ratio. Results Among 126 analyzed patients, 58 (46.0%) developed POD. After PSM (34 pairs), FDX1 levels at T4 were significantly higher in the POD group (18.6 vs. 14.9 ng/mL, P < 0.05), while LA levels were lower at T1, T2, and T4 (all P < 0.05). Multivariate analysis showed that each unit increase in FDX1 change (ΔT4–T1) and LA change during CPB (ΔT3–T2) was associated with a 70% (OR = 1.7, P = 0.018) and 60% (OR = 1.6, P = 0.044) increase in POD risk, respectively. Conclusions Perioperative increases in FDX1 and decreases in LA are independently associated with higher POD risk, suggesting that cuproptosis-related pathways may represent potential mechanisms and therapeutic targets for POD. Trial registration Chinese Clinical Trial Registry, ChiCTR2400088024. Registered on August 9, 2024. Postoperative delirium Cardiac valve replacement Cuproptosis Ferredoxin 1 Lipoic acid Propensity score matching Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Postoperative delirium (POD) is an acute neurological disorder characterized by fluctuating disturbances in attention and cognition, typically occurring within the first week after surgery[ 1 ]. It affects approximately 27% of patients following major cardiac procedures such as valve replacement[ 2 , 3 ]. Although perioperative neuroprotection has gained increasing attention, the precise mechanisms underlying POD remain incompletely understood[ 4 ]. Current hypotheses implicate neuroinflammation, oxidative stress, neurotransmitter imbalances, and cerebrovascular dysregulation as key contributors[ 5 , 6 , 7 ]. Major risk factors include surgical trauma, anesthetic exposure, cardiopulmonary bypass (CPB), advanced age, preexisting cognitive impairment, and comorbidities[ 8 , 9 ]. Cuproptosis is a recently identified form of regulated cell death triggered by excessive intracellular copper accumulation, leading to lipoylated protein aggregation and iron-sulfur cluster destabilization in mitochondria[ 10 ]. Copper is an essential cofactor for enzymes involved in energy production, antioxidant defense, and neuronal maintenance[ 11 , 12 ]. Dysregulated copper homeostasis has been linked to cognitive impairment through oxidative stress and neuroinflammatory pathways[ 13 , 14 ]. Anesthesia, surgery, and CPB may promote cuproptosis, suggesting a potential mechanistic link to POD[ 15 , 16 , 17 ]. However, clinical evidence regarding this association is lacking. This study aimed to investigate the relationship between perioperative changes in cuproptosis-related biomarkers—copper ion (Cu²⁺), ferredoxin 1 (FDX1), and lipoic acid (LA)—and the incidence of POD in patients undergoing cardiac valve replacement. Methods Study Design This prospective, observational, single-center cohort study was conducted at the General Hospital of Western Theater Command. The study was approved by the hospital’s Ethics Committee (No. 2024EC4-ky010) and registered with the Chinese Clinical Trial Registry (ChiCTR2400088024). All participants provided written informed consent. Study population Adult patients (aged ≥ 18 years) scheduled for elective cardiac valve replacement under general anesthesia with cardiopulmonary bypass (CPB) between August 2024 and July 2025 were included.Exclusion criteria comprised: emergency surgery; inability to communicate preoperatively; Mini-Mental State Examination (MMSE) score < 24; history of neurological or psychiatric disorders; copper metabolism abnormalities; abnormal coagulation; severe hepatic, renal, or pulmonary impairment; and cases with missing data. A total of 140 patients were enrolled and provided informed consent(Fig. 1). Data collection and Variable definitions The occurrence of postoperative delirium (POD) was assessed twice daily from postoperative days 1 to 7 using the Richmond Agitation-Sedation Scale (RASS) and the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Various patient-related, anesthesia-related, and surgery-related factors were analyzed, including gender, body mass index (BMI), American Society of Anesthesiologists (ASA) classification, Mini-Mental State Examination (MMSE) score, smoking history, alcohol abuse, comorbidities (hypertension, diabetes mellitus, coronary artery disease), cardiac function classification, left ventricular ejection fraction (LVEF), fractional shortening (FS), hemoglobin concentration, liver and renal function indicators, cardiopulmonary bypass (CPB) duration, total volume of intravenous fluids administered, intraoperative urine output, volume of blood transfused, type of surgery, duration of surgery, and intraoperative blood loss. To evaluate perioperative changes in cuproptosis activity, central venous blood samples were collected at four time points: before induction of anesthesia (T1), at initiation of CPB (T2), at end of CPB (T3), and immediately after surgery (T4). Serum concentrations of copper ions (Cu²⁺), FDX1, and lipoic acid were measured using commercial enzyme-linked immunosorbent assay (ELISA) kits. All POD assessments were performed by trained staff members who were blinded to group assignments and biomarker results. Anesthetic Management In accordance with standard preoperative fasting guidelines, all patients abstained from oral intake for 8 hours prior to surgery. Following the establishment of peripheral intravenous access, ultrasound-guided cannulation of the left radial artery and right deep vein was performed to enable continuous arterial and central venous pressure monitoring, as well as central venous catheterization.General anesthesia was induced using intravenous midazolam (0.03 mg/kg), etomidate (0.3 mg/kg), and sufentanil (0.5 µg/kg). Upon loss of the eyelash reflex, cisatracurium (0.2 mg/kg) was administered to facilitate neuromuscular blockade prior to endotracheal intubation. Mechanical ventilation was conducted in Pressure Controlled Ventilation–Volume Guaranteed (PCV-VG) mode with the following parameters: tidal volume 6–8 mL/kg, FiO₂ 100%, inspiratory-to-expiratory ratio of 1:2, and end-tidal CO₂ maintained at 35–45 mmHg through adjustment of respiratory rate and tidal volume.Anesthesia was maintained with a continuous infusion of dexmedetomidine (0.5 µg/kg/h) and inhaled sevoflurane at a minimum alveolar concentration (MAC) ≥ 0.6. Supplemental intravenous boluses of cisatracurium (0.08 mg/kg) and sufentanil (0.5 µg/kg) were administered as needed to maintain a bispectral index (BIS) value between 40 and 60. Hemodynamic stability was supported through the judicious use of vasoactive agents, including norepinephrine, dobutamine, milrinone, nitroglycerin, and isoproterenol.During cardiopulmonary bypass (CPB), core temperature was maintained at 28–30°C, pump flow was set at 2.0–2.4 L/(min·m²), and mean arterial pressure (MAP) was targeted between 50 and 80 mmHg. Prior to weaning from CPB, patients were rewarmed to 36–37°C.Postoperative analgesia was provided via a patient-controlled intravenous analgesia (PCIA) system containing sufentanil (100 µg), butorphanol tartrate (5 mg), and ondansetron (16 mg), diluted to 100 mL with normal saline and infused at a basal rate of 3 mL/h. All patients were transferred to the intensive care unit (ICU) with the endotracheal tube in place. Sedation and analgesia in the ICU were maintained with remimazolam and remifentanil, respectively, until extubation criteria were met and the endotracheal tube was removed. Sample size Based on a literature-derived POD incidence of 27% and a target relative risk of 2.5[ 26 ]., a sample size of 126 patients was estimated using PASS 15.0, with α = 0.05 and power = 0.9. Accounting for a 10% dropout rate, 140 patients were planned for enrollment. Statistical analysis Data analysis was performed using IBM SPSS Statistics for Windows, Version 27.0 (IBM Corp., Armonk, NY, USA). Nominal categorical variables (e.g., gender, smoking history, hypertension comorbidity) were presented as frequencies (percentages). Intergroup comparisons were conducted using Pearson's chi-square test or Fisher's exact test (when expected frequencies were < 5). Ordinal categorical variables (e.g., cardiac function classification, ASA physical status classification) were presented as median (interquartile range, IQR). Comparisons between two groups were performed using the Mann-Whitney U test. Continuous variables (e.g., CPB duration, age, MMSE score, serum substance concentrations) were first assessed for distribution normality using the Kolmogorov-Smirnov test. Normally distributed continuous variables were expressed as mean ± standard deviation (SD), and intergroup comparisons were made using the independent samples t-test. Non-normally distributed continuous variables were expressed as median (IQR), and comparisons between two groups were performed using the Mann-Whitney U test. Intergroup comparisons of baseline characteristics and intraoperative variables prior to matching were conducted according to the principles outlined above: Normally distributed continuous variables (age, BMI, MMSE score, LVEF, FS, Hb) were compared using the independent samples t-test.Non-normally distributed continuous variables (CPB duration, fluid infusion volume, blood transfusion volume, operation duration, blood loss) and ordinal categorical variables (ASA classification, cardiac function classification) were compared using the Mann-Whitney U test.Nominal binary categorical variables (gender, smoking history, alcohol abuse history, hypertension, diabetes, coronary heart disease, liver function, renal function) were compared using the chi-square test. To control for potential confounding factors, a 1:1 Propensity Score Matching (PSM) method was employed using the Nearest Neighbor Matching algorithm, with a caliper width set to 0.05. Matching variables encompassed all baseline characteristics and intraoperative variables (total of 22 variables): gender, age, BMI, ASA classification, MMSE score, smoking history, alcohol abuse history, hypertension, diabetes, coronary heart disease, cardiac function classification, LVEF, FS, Hb, liver function, renal function, CPB duration, fluid infusion volume, urine output, blood transfusion volume, operation duration, and blood loss. Biomarker Data Presentation and Derived Variables: Serum concentrations of Cu²⁺, FDX1, and lipoic acid were recorded and analyzed at four time points: pre-anesthesia (T1), initiation of cardiopulmonary bypass (CPB) (T2), cessation of CPB (T3), and immediately post-operation (T4). The following derived concentration difference indices were calculated and analyzed: Pre- to post-operative concentration difference (T4 - T1, ΔT4-T1); Pre- to post-CPB concentration difference (T3 - T2, ΔT3-T2). Preliminary Screening (Differential Expression Analysis): All 18 concentration indices (3 proteins at 6 time points/differences: T1, T2, T3, T4, ΔT4-T1, ΔT3-T2) in the matched sample were analyzed. Log2 Fold Change (Log2FC) was calculated for concentrations in the POD group relative to the non-POD group. Differences in each concentration index between the POD and non-POD groups were compared using the independent samples t-test. Statistical significance for differential expression was defined as |Log2FC| > log2(1.2) (indicating a 1.2-fold change) and P < 0.05. Volcano plots were generated to visualize the differential analysis results. Multivariable Conditional Logistic Regression Analysis: To assess the independent association between cuproptosis biomarkers and POD risk while controlling for the matched-pair design and important covariates, conditional logistic regression analysis was performed. Dependent variable: Occurrence of POD (binary variable). Independent variables: The 6 significantly differential protein indices identified in the preliminary screening were included in the model. Adjustment variables: Considering the matched design and clinical importance, the model was forced to adjust for the matching factor (implicitly handled by the conditional logistic regression), age, MMSE score, and CPB duration. Results were expressed as Odds Ratios (OR) with corresponding 95% Confidence Intervals (95% CI). All hypothesis tests were two-tailed. A P-value < 0.05 was considered statistically significant. Results A total of 152 patients scheduled for cardiac valve replacement between August 2024 and July 2025 were screened. Of these, 2 declined participation and 10 were excluded based on predetermined criteria: preoperative communication barriers (n = 2), MMSE scores < 24 (n = 4), history of neurological or psychiatric disorders (n = 1), abnormal coagulation function (n = 1), and severe hepatic, renal, or pulmonary impairment (n = 2). The remaining 140 patients met the inclusion criteria and provided informed consent (Fig. 1). During the follow-up period, 14 participants were lost to attrition. Consequently, 126 patients completed the entire study and were included in the final analysis. Among them, 58 (46.0%) developed postoperative delirium (POD group), while 68 (54.0%) did not (non-POD group). The study flowchart is presented in Fig. 1. This study included 126 patients who underwent cardiac valve surgery. Pre-matching baseline data analysis (Table 1) revealed significant differences between the POD and non-POD groups in age, MMSE score, and prevalence of coronary heart disease (CHD) (all P < 0.05). Specifically, the POD group was older ( P = 0.028), had lower baseline MMSE scores (indicating poorer baseline cognitive function, P = 0.017), and had a higher proportion of CHD ( P = 0.034). No significant differences were observed in other demographic characteristics, comorbidities, NYHA functional class, LVEF, FS, Hb, or hepatic and renal function indicators (all P > 0.05). Baseline characteristics of patients before PSM are summarized in Table 1. Analysis of surgical and perioperative indicators is presented in Table 2. The cardiopulmonary bypass (CPB) time was significantly longer in the POD group than in the non-POD group ( P = 0.009), and intraoperative urine output was significantly lower ( P = 0.022). No significant differences were found in other intraoperative indicators, including duration of surgery, blood loss, fluid infusion volume, or transfusion volume (all P > 0.05). To control for baseline confounding factors, PSM was performed to balance 22 variables, including baseline characteristics (age, gender, BMI, ASA grade, MMSE score, smoking history, alcohol abuse, hypertension, diabetes, CHD, NYHA class, LVEF, FS, Hb, hepatic and renal function) and surgical parameters (CPB time, fluid infusion volume, urine output, transfusion volume, duration of surgery, and blood loss). A caliper value of 0.05 was used with 1:1 nearest-neighbor matching. After PSM, 34 matched pairs were successfully formed (34 in the POD group and 34 in the non-POD control group). After PSM, all 22 matched variables were well-balanced between the groups, including the previously significant factors such as age, MMSE score, and CPB duration (all P > 0.05)., indicating successful matching and comparability. PSM results are presented in Table 3. Serum concentrations of ferredoxin 1 (FDX1), lipoic acid (LA), and copper ions (Cu²⁺) were measured via ELISA at four perioperative time points: T1 (pre-anesthesia), T2 (CPB initiation), T3 (CPB cessation), and T4 (immediately after surgery). Two change values were calculated: ΔT4–T1 (reflecting change over the entire procedure) and ΔT3–T2 (reflecting change during CPB), resulting in a total of 18 biomarker concentration indicators (3 biomarkers × [4 time points + 2 Δ values]). After PSM, the following analyses were performed on the matched cohort of 68 patients(34 pairs). Independent samples t-tests were performed to compare these 18 indicators between the POD and non-POD groups. The POD group showed significantly higher serum FDX1 concentration at T4 (18.6 vs. 14.9 ng/mL). Serum LA levels were significantly lower in the POD group at T1 (19.6 vs. 23.9 µg/L), T2 (11.3 vs. 15.0 µg/L), and T4 (6.7 vs. 9.1 µg/L). No consistent differences were observed in copper ion levels. Dynamic changes in concentrations of lipoic acid, copper ions, and ferredoxin 1 during cardiopulmonary bypass are shown in Figs. 2 to 4. Further analysis using log₂fold change (FC, POD/non-POD ratio) combined with independent samples t-tests was conducted. With a significance threshold of |log₂FC| ≥ log₂(1.2) (i.e., ≥ 1.2-fold or ≤ 0.83-fold change) and P < 0.05, volcano plot analysis (Fig. 5) identified six biomarkers significantly associated with POD. Compared to the non-POD group, the POD group exhibited: Significantly greater increases in FDX1 over the entire procedure (ΔT4–T1) and during CPB (ΔT3–T2). Significantly lower LA levels at T1, T2, T4, and a reduced increase (or greater decrease) in LA during CPB (ΔT3–T2). Notably, no significant differences were observed in copper ion (Cu²⁺) levels at any time point or in Δ values (all P > 0.05). The volcano plot illustrating significantly altered biomarkers is displayed in Fig. 5. To evaluate the independent association of the differentially expressed biomarkers with POD risk while controlling for potential residual confounders (particularly age, baseline MMSE score, and CPB time), conditional logistic regression analysis adjusted for these factors was performed on the PSM-matched sample (34 pairs) (Table 4 and Fig. 6). The results showed: Each unit increase in FDX1 ΔT4–T1 (change over the entire procedure) was associated with a 70% increase in POD risk (adjusted OR = 1.7, 95% CI: 1.1–2.5, P = 0.018). Each unit increase in LA ΔT3–T2 (change during CPB) was associated with a 60% increase in POD risk (adjusted OR = 1.60, 95% CI: 1.1–2.4, P = 0.044). The other four biomarkers that showed significant differences in initial screening (FDX1 ΔT3–T2, LA T1, LA T2, LA T4) did not demonstrate independent significant associations with POD risk after adjusting for age, MMSE score, CPB time, and the matched-pair design (all P > 0.05).Results of the multivariate regression analysis are provided in Table 4 and Fig. 6. Discussion Postoperative delirium (POD) is an acute organic brain syndrome of unclear etiology, characterized by acutely onset cognitive impairment and inattention within a short period after surgery (typically within 7 days), often accompanied by confusion and perceptual disturbances, with fluctuating symptoms[ 27 ]. Cuproptosis is a novel form of regulated cell death triggered by excessive intracellular copper accumulation or dysregulated copper metabolism, leading to mitochondrial lipoylated protein aggregation and destabilization of iron-sulfur cluster proteins[ 28 ]. This study is the first to reveal an association between dynamic changes in key proteins of the cuproptosis pathway during the perioperative period of cardiac valve surgery and the occurrence of POD. After controlling for confounders using propensity score matching, we found that the cumulative increase in FDX1 throughout the surgery (ΔT4–T1) and the exaggerated consumption of lipoic acid during cardiopulmonary bypass (ΔT3–T2) were independent risk factors for POD (OR = 1.7, P = 0.018; OR = 1.6, P = 0.044, respectively). These findings provide new insights into the molecular mechanisms of POD and highlight potential interventional targets. The cumulative increase in FDX1, a key driver of cuproptosis, suggests a neurotoxic mechanism underlying POD. Elevated FDX1 levels directly promote copper-dependent lipoylated protein aggregation within mitochondria. In this study, POD patients showed significantly increased FDX1 levels throughout surgery—particularly at T4 (end of surgery)—and a strong positive correlation was observed between ΔT4–T1 and POD risk, which is consistent with recent cuproptosis theory. As a critical initiator of cuproptosis, FDX1 may induce neuronal damage via mitochondrial proteotoxicity. FDX1 overexpression can suppress iron-sulfur cluster biosynthesis and disrupt the tricarboxylic acid (TCA) cycle, leading to neuronal ATP depletion[ 29 ]. Ischemia-reperfusion injury during cardiac surgery may amplify this process, causing an energy crisis in the hippocampus and impairing cognitive function. Furthermore, animal studies have confirmed that cuproptosis can lead to neuronal apoptosis through oxidative and lipid damage, disrupt synaptic plasticity, and impair CREB pathway-mediated memory formation, resulting in memory deficits and cognitive decline [ 30 , 31 ]. FDX1 upregulation can activate the NLRP3 inflammasome and promote IL-1β release[ 32 ]. Prolonged CPB time (P = 0.009 in the POD group) may enhance endothelial FDX1 activation via shear stress, aggravating systemic inflammation and its transmission to the central nervous system. Real-time intraoperative monitoring of FDX1 dynamics may help identify patients at high risk of POD. Furthermore, targeting FDX1 has emerged as a potential neuroprotective strategy, suggesting that FDX1 inhibition could be a promising therapeutic approach to mitigate POD risk, warranting further investigation[ 33 ], suggesting a promising direction for future interventional studies. Concurrently, the observed depletion of lipoic acid, a physiological antagonist of cuproptosis, reflects exhaustion of antioxidant reserves counteracting this pathway. Significantly lower lipoic acid levels in POD patients at T1, T2, and T4, and its change during CPB (ΔT3–T2) was independently associated with POD risk. One study found that copper-exposed mice showed elevated glutamate, malondialdehyde, and caspase-3 levels in the frontal cortex and hippocampus, along with reduced glutathione (GSH) and impaired Y-maze attention scores[ 31 ]. This suggests that copper induces apoptosis in the hippocampus and frontal cortex via glutamate and oxidative stress pathways, leading to impaired learning and memory. Lipoic acid helps maintain redox balance by regenerating GSH and vitamin E[ 34 ]. Its depletion exposes neurons to cuproptosis-related lipid peroxidation, causing direct synaptic damage[ 35 ]. The lower baseline MMSE scores in the POD group (P = 0.017) further indicate preoperative susceptibility to oxidative stress. Moreover, lipoic acid has been shown to support the PINK1/Parkin pathway [ 36 ]; its deficiency may therefore hinder the clearance of damaged mitochondria, leading to accumulated reactive oxygen species (ROS) that further activate FDX1, creating a vicious cycle of “cuproptosis–oxidative stress”[ 36 ]. The independent predictive value of lipoic acid ΔT3–T2 highlights the CPB period as a critical window of consumption. This is directly related to hemodilution and free radical burst during CPB, suggesting that supplementing lipoic acid analogues in the CPB circuit may offer neuroprotective potential. Notably, the absence of significant differences in copper ion (Cu²⁺) levels at any time point carries scientific meaning, implying that cuproptosis is driven by abnormal copper localization (mitochondrial accumulation) rather than total serum copper levels. FDX1 and lipoic acid, as functional molecules, more accurately reflect pathway activity than copper ions alone. This finding aligns with the concept of “functional cuproptosis biomarkers”, underscoring a therapeutic strategy focused on regulating key proteins rather than mere copper chelation. Collectively, these findings hold significant clinical translational value. The combination of FDX1 ΔT4–T1 and lipoic acid ΔT3–T2 may form a novel biomarker panel for immediate postoperative identification of high-risk patients. Targeted interventions can be designed based on the temporal patterns of FDX1 elevation (end of surgery) and lipoic acid depletion (during CPB). Ultimately, developing FDX1 inhibitors or lipoic acid nanodelivery systems may help disrupt the cuproptosis–neuroinflammation axis, opening new avenues for preventing and treating POD. Limitations Several limitations of this study should be acknowledged. First, as a single-center observational study, although propensity score matching was applied to minimize confounding, residual bias may persist due to unmeasured variables. Second, the generalizability of our findings is limited to patients undergoing cardiac valve replacement with cardiopulmonary bypass, and may not extend to other surgical populations or clinical settings. Third, the biomarkers measured in peripheral blood may not directly reflect changes within the central nervous system, limiting mechanistic interpretation. Finally, the moderate sample size after matching (34 pairs) may have reduced statistical power to detect more subtle associations or interactions. Conclusion The dynamic activation of the cuproptosis pathway during cardiac valve surgery represents a key mechanism underlying postoperative delirium (POD). The cumulative increase in FDX1 and progressive depletion of lipoic acid collectively contribute to neuronal injury, with their respective changes (Δ values) serving as independent predictors. Future studies should focus on validating brain protection strategies targeting this pathway—such as FDX1 antagonism and lipoic acid supplementation—to improve neurocognitive outcomes in patients undergoing cardiac surgery. Abbreviations POD Postoperative Delirium Cuproptosis Copper-dependent cell death FDX1 Ferredoxin 1 CPB Cardiopulmonary Bypass PSM Propensity Score Matching RASS Richmond Agitation-Sedation Scale CAM-ICU Confusion Assessment Method for the Intensive Care Unit MMSE Mini-Mental State Examination ASA American Society of Anesthesiologists BMI Body Mass Index CHD Coronary Heart Disease LVEF Left Ventricular Ejection Fraction FS Fractional Shortening ELISA Enzyme-Linked Immunosorbent Assay ROS Reactive Oxygen Species TCA Tricarboxylic Acid Cycle GSH Glutathione CREB cAMP-response Element Binding Protein OR Odds Ratio CI Confidence Interval SD Standard Deviation IQR Interquartile Range Log2FC Log2 Fold Change Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of the General Hospital of Western Theater Command (Approval No. 2024EC4-ky010). All procedures performed in this study involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Written informed consent was obtained from all individual participants included in the study. Consent for publication Written informed consent for publication was obtained from all individual participants included in the study. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author (Dr. Gu Gong, Email: [email protected] ) on reasonable request. Data requests will be evaluated to ensure they comply with the ethical obligations and participant confidentiality established by the Ethics Committee of the General Hospital of Western Theater Command. Competing interests None declared. Funding This study was supported by the Hospital Management Project of the General Hospital of the Western Theatre Command (grant number 2021-XZYG-A10) and the Joint Key Project (grant number 2021-XZYG-C25). The funders had no role in the design of the study; collection, analysis, or interpretation of data; or in writing the manuscript. Authors' contributions ZZ conceived the study and led the proposal development under the supervision and suggestions of GG and QH. ZZ and QZ contributed to study design and to development of the proposal. QS and WL wrote the statistical analysis plan and estimated the sample size. YY and JZ was the lead trial methodologist. ZZ drafted the manuscript with QH. All authors read and approved the final manuscript. ZZ is the guarantor. Acknowledgements We would like to thank Editage (www.editage.com) for English language editing Author information Authors and Affiliations Zheng Zhang 1,2 , Qiuran Zheng 1 , Yangyang Ye 2,3 , Qin Shi 2 , Weiqin Li 2 , Jingzheng Zeng 2 , Qingqing Huang 2,4* , Gu Gong 1,2* 1 Department of Anesthesiology, The Affiliated Hospital, Southwest Medical University, Luzhou, China 2 Department of Anesthesiology, The General Hospital of Western Theater Command, Chengdu, China 3 College of Medicine, North Sichuan Medical College, Nanchong, China 4 College of Medicine, Southwest Jiaotong University, Chengdu, China *These authors contributed equally to this work Corresponding author Correspondence to Dr Gu Gong and Dr QingQing Huang. References Chaput AJ, Bryson GL. Postoperative delirium: risk factors and management: continuing professional development. Can J Anaesth. 2012;59(3):304–20. 10.1007/s12630-011-9658-4 . Fu M, Yuan Q, Yang Q, et al. Risk factors and incidence of postoperative delirium after cardiac surgery in children: a systematic review and meta-analysis. Ital J Pediatr. 2024;50(1):24. 10.1186/s13052-024-01603-2 . Published 2024 Feb 8. Mattimore D, Fischl A, Christophides A, et al. Delirium after cardiac surgery-a narrative review. Brain Sci. 2023;13(12):1682. 10.3390/brainsci13121682 . Published 2023 Dec 7. Xiao M, Liu C, Zhou L, Yang Y, Wang Y. Postoperative delirium, neuroinflammation, and influencing factors of postoperative delirium: a review. Med (Baltimore). 2023;102(8):e32991. 10.1097/MD.0000000000032991 . Pang Y, Li Y, Zhang Y, Wang H, Lang J, Han L, Liu H, Xiong X, Gu L, Wu X. Effects of inflammation and oxidative stress on postoperative delirium in cardiac surgery. Front Cardiovasc Med. 2022;9:1049600. 10.3389/fcvm.2022.1049600 . Wang Y, Shen X. Postoperative delirium in the elderly: the potential neuropathogenesis. Aging Clin Exp Res. 2018;30(11):1287–95. 10.1007/s40520-018-1008-8 . Sampaolesi C, Casarotta E, Gresti G, Mariotti G, Pisani L, Veccia D, Di Eusanio M, Malvindi PG, Donati A, Münch CM. The association between cerebral blood flow variations during on-pump coronary artery bypass grafting surgery and postoperative delirium. Perfusion. 2025;40(2):440–9. 10.1177/02676591241239823 . Othman SMA, Aziz MAA, Sriwayyapram C, Xu Q. Systematic literature review on early detection of postoperative delirium in adult patients after cardiac surgery. J Cardiothorac Surg. 2024;19(1):678. 10.1186/s13019-024-03173-0 . Published 2024 Dec 21. Fatehi Hassanabad A, Bahrami N, Novick RJ, Ali IS. Delirium and depression in cardiac surgery: a comprehensive review of risk factors, pathophysiology, and management. J Card Surg. 2021;36(8):2876–89. 10.1111/jocs.15610 . Gromadzka G, Tarnacka B, Flaga A, Adamczyk A. Copper dyshomeostasis in neurodegenerative diseases-therapeutic implications. Int J Mol Sci. 2020;21(23):9259. 10.3390/ijms21239259 . Published 2020 Dec 4. Scheiber I, Dringen R, Mercer JF. Copper: effects of deficiency and overload. Met Ions Life Sci. 2013;13:359–87. 10.1007/978-94-007-7500-8_11 . Mezzaroba L, Alfieri DF, Colado Simão AN, Vissoci Reiche EM. The role of zinc, copper, manganese and iron in neurodegenerative diseases. Neurotoxicology. 2019;74:230–41. 10.1016/j.neuro.2017.07.007 . Zhao R, Sukocheva O, Tse E, Neganova M, Aleksandrova Y, Zheng Y, Gu H, Zhao D, Madhunapantula SV, Zhu X, Liu J, Fan R. Cuproptosis, the novel type of oxidation-induced cell death in thoracic cancers: can it enhance the success of immunotherapy? Cell Commun Signal. 2024;22:379. 10.1186/s12964-024-01743-2 . Ruiz LM, Libedinsky A, Elorza AA. Role of copper on mitochondrial function and metabolism. Front Mol Biosci. 2021;8:711227. 10.3389/fmolb.2021.711227 . Published 2021 Aug 24. Sensi SL, Granzotto A, Siotto M, Squitti R. Copper and zinc dysregulation in Alzheimer's disease. Trends Pharmacol Sci. 2018;39(12):1049–63. 10.1016/j.tips.2018.10.001 . Huat TJ, Camats-Perna J, Newcombe EA, Valmas N, Kitazawa M, Medeiros R. Metal toxicity links to Alzheimer's disease and neuroinflammation. J Mol Biol. 2019;431(9):1843–68. 10.1016/j.jmb.2019.01.018 . Nzengue Y, Steiman R, Rachidi W, Favier A, Guiraud P. Oxidative stress induced by cadmium in the C6 cell line: role of copper and zinc. Biol Trace Elem Res. 2012;146(3):410–9. 10.1007/s12011-011-9265-9 . Wang B, Mu C, Tang X et al. The relationship between mild cognitive impairment and postoperative delirium undergoing total knee arthroplasty: the PNDABLE study. Front Aging Neurosci. 2022;14:959510. Published 2022 Sep 29. 10.3389/fnagi.2022.959510 Thedim M, Vacas S. Postoperative delirium and the older adult: untangling the confusion. J Neurosurg Anesthesiol. 2024;36(3):184–9. 10.1097/ANA.0000000000000971 . Berger M, Terrando N, Smith SK, Browndyke JN, Newman MF, Mathew JP. Neurocognitive function after cardiac surgery: from phenotypes to mechanisms. Anesthesiology. 2018;129(4):829–51. 10.1097/ALN.0000000000002194 . O'Neal JB, Shaw AD. Predicting, preventing, and identifying delirium after cardiac surgery. Perioper Med (Lond). 2016. 10.1186/s13741-016-0032-5 . 5:7. Published 2016 Apr 26. Chen H, Mo L, Hu H, Ou Y, Luo J. Risk factors of postoperative delirium after cardiac surgery: a meta-analysis. J Cardiothorac Surg. 2021;16(1):113. Published 2021 Apr 26. 10.1186/s13019-021-01496-w Lewis CA, de Jersey S, Seymour M, Hopkins G, Hickman I, Osland E. Iron, vitamin B12, folate and copper deficiency after bariatric surgery and the impact on anaemia: a systematic review. Obes Surg. 2020;30(11):4542–91. 10.1007/s11695-020-04872-y . Langley A, Dameron CT. Copper and anesthesia: clinical relevance and management of copper related disorders. Anesthesiol Res Pract. 2013;2013:750901. 10.1155/2013/750901 . Kaur A, Gupta KK, Deep G, Thakur S. Wilson disease - challenge for safe anesthesia! Saudi J Anaesth. 2019;13(4):384–5. 10.4103/sja.SJA_12_19 . Tse L, Schwarz SK, Bowering JB, Moore RL, Barr AM. Incidence of and risk factors for delirium after cardiac surgery at a quaternary care center: a retrospective cohort study. J Cardiothorac Vasc Anesth. 2015;29(6):1472–9. 10.1053/j.jvca.2015.06.018 . Aldecoa C, Bettelli G, Bilotta F, Sanders RD, Audisio R, Borozdina A, Cherubini A, Jones C, Kehlet H, MacLullich A, Radtke F, Riese F, Slooter AJ, Veyckemans F, Kramer S, Neuner B, Weiss B, Spies CD. European Society of Anaesthesiology evidence-based and consensus-based guideline on postoperative delirium. Eur J Anaesthesiol. 2017;34(4):192–214. 10.1097/EJA.0000000000000594 . Chen L, Min J, Wang F. Copper homeostasis and cuproptosis in health and disease. Signal Transduct Target Ther. 2022;7(1):378. 10.1038/s41392-022-01229-y . Tsvetkov P, Coy S, Petrova B, Dreishpoon M, Verma A, Abdusamad M, Rossen J, Joesch-Cohen L, Humeidi R, Spangler RD, Eaton JK, Frenkel E, Kocak M, Corsello SM, Lutsenko S, Kanarek N, Santagata S, Golub TR. Copper induces cell death by targeting lipoylated TCA cycle proteins. Science. 2022;375(6586):1254–61. 10.1126/science.abf0529 . Zhang Y, Zhou Q, Lu L et al. Copper induces cognitive impairment in mice via modulation of cuproptosis and CREB signaling. Nutrients. 2023;15(4):972. Published 2023 Feb 15. 10.3390/nu15040972 Kalita J, Kumar V, Misra UK, Bora HK. Memory and learning dysfunction following copper toxicity: biochemical and immunohistochemical basis. Mol Neurobiol. 2018;55(5):3800–11. 10.1007/s12035-017-0619-y . Cai D, Li J, Peng Z, Fu R, Chen C, Liu F, Li Y, Su Y, Li C, Chen W. Interplay of ferroptosis, cuproptosis, autophagy and pyroptosis in male infertility: molecular crossroads and therapeutic opportunities. Int J Mol Sci. 2025;26(8):3496. 10.3390/ijms26083496 . Yang S, Li X, Yan J, Jiang F, Fan X, Jin J, Zhang W, Zhong D, Li G. Disulfiram downregulates ferredoxin 1 to maintain copper homeostasis and inhibit inflammation in cerebral ischemia/reperfusion injury. Sci Rep. 2024;14(1):15175. 10.1038/s41598-024-64981-x . Packer L, Witt EH, Tritschler HJ. alpha-Lipoic acid as a biological antioxidant. Free Radic Biol Med. 1995;19(2):227–50. 10.1016/0891-5849(95)00017-r . Parsanathan R. Copper's dual role: unravelling the link between copper homeostasis, cuproptosis, and cardiovascular diseases. Hypertens Res. 2024;47(5):1440–2. 10.1038/s41440-024-01636-4 . Shen C, Chen X, Cao Y, Du Y, Xu X, Wu Q, Lin L, Qin Y, Meng R, Gan L, Zhang J. Alpha-lipoic acid protects against chronic alcohol consumption-induced cardiac damage by the aldehyde dehydrogenase 2-associated PINK/parkin pathway. J Cardiovasc Pharmacol. 2023;82(5):407–18. 10.1097/FJC.0000000000001480 . Tables Tables 1 to 4 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files floatimage2.png Table 1 floatimage3.png Table 1 floatimage4.png Table 2 floatimage5.png Table 3 floatimage10.jpeg Table 4 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7608169","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":534368264,"identity":"626ca54f-4b60-4e72-9bb9-f255eca74342","order_by":0,"name":"Zheng Zhang","email":"","orcid":"","institution":"The Affiliated Hospital of Southwest Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zheng","middleName":"","lastName":"Zhang","suffix":""},{"id":534368265,"identity":"4d698656-60bf-4e75-96b8-c320e0386ce1","order_by":1,"name":"Qiuran Zheng","email":"","orcid":"","institution":"The Affiliated Hospital of Southwest Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qiuran","middleName":"","lastName":"Zheng","suffix":""},{"id":534368266,"identity":"79158433-5760-410b-baca-f2ae8168db70","order_by":2,"name":"Yangyang Ye","email":"","orcid":"","institution":"The General Hospital of Western Theater Command","correspondingAuthor":false,"prefix":"","firstName":"Yangyang","middleName":"","lastName":"Ye","suffix":""},{"id":534368268,"identity":"beb7636f-5e90-45d7-812f-19a56661667a","order_by":3,"name":"Qin Shi","email":"","orcid":"","institution":"The General Hospital of Western Theater Command","correspondingAuthor":false,"prefix":"","firstName":"Qin","middleName":"","lastName":"Shi","suffix":""},{"id":534368270,"identity":"db4f1a56-a9e2-4640-86d7-80debb99fbbe","order_by":4,"name":"Weiqin Li","email":"","orcid":"","institution":"The General Hospital of Western Theater Command","correspondingAuthor":false,"prefix":"","firstName":"Weiqin","middleName":"","lastName":"Li","suffix":""},{"id":534368271,"identity":"8b8b2829-dda3-4ddf-8a0d-2b4722e396ec","order_by":5,"name":"Jingzheng Zeng","email":"","orcid":"","institution":"The General Hospital of Western Theater Command","correspondingAuthor":false,"prefix":"","firstName":"Jingzheng","middleName":"","lastName":"Zeng","suffix":""},{"id":534368273,"identity":"f43dd27e-f584-4ab1-b01d-c027eb90a7dd","order_by":6,"name":"Qingqing Huang","email":"","orcid":"","institution":"The General Hospital of Western Theater Command","correspondingAuthor":false,"prefix":"","firstName":"Qingqing","middleName":"","lastName":"Huang","suffix":""},{"id":534368274,"identity":"05af8028-8b7a-4a64-ab39-386a35230539","order_by":7,"name":"Gu Gong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwklEQVRIiWNgGAWjYPACGzl+ZubDD0jRkmYs2c6WZkCKlkOJG87zKEgQpVbevffwy69tB4yND/MwGDDU2EQT1GJ45lyatWzbHTmzw7wHHjAcS8ttIKhlRo6ZsWTbM2Ozw3wJBowNh4nWcjhxczOPgQRRWuQlcowffgRq2cBMrBYDnjNmzAzn0owlDgMDOYEYv8i39xh//FEGjMr+w4cffKixIcKWAwxs0jwwXgIh5WBbGhiYP/4gRuUoGAWjYBSMXAAAGVRBA/T5ossAAAAASUVORK5CYII=","orcid":"","institution":"The Affiliated Hospital of Southwest Medical University","correspondingAuthor":true,"prefix":"","firstName":"Gu","middleName":"","lastName":"Gong","suffix":""}],"badges":[],"createdAt":"2025-09-13 15:08:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7608169/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7608169/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":94663257,"identity":"cae4ba79-4026-4d5d-84f0-f0ece0684d13","added_by":"auto","created_at":"2025-10-29 12:09:00","extension":"doc","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":491056,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.doc","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/e2e93c9fba5959e620460abd.doc"},{"id":94663276,"identity":"170b7795-6fe1-4a18-a0b2-e9e4854813be","added_by":"auto","created_at":"2025-10-29 12:09:01","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":9546,"visible":true,"origin":"","legend":"","description":"","filename":"c443895ef7d14b6ab33b0e49bb64fafe.json","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/39b687210e2c3efc9e17e8dd.json"},{"id":94663194,"identity":"779a4265-76d9-48f7-a6a3-3875a56c59db","added_by":"auto","created_at":"2025-10-29 12:08:59","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":109146,"visible":true,"origin":"","legend":"","description":"","filename":"c443895ef7d14b6ab33b0e49bb64fafe1enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/05a907068a8f1723f34abb5c.xml"},{"id":94663186,"identity":"152e8ad4-4e06-4d00-90d6-21ec38d69be6","added_by":"auto","created_at":"2025-10-29 12:08:59","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":52510,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/788e0917653956ca0bb227b4.png"},{"id":94673441,"identity":"580c2538-cc29-49fe-abce-c46af536d9ba","added_by":"auto","created_at":"2025-10-29 13:41:23","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":37820,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/7699e5efdeb0475970bdbe39.png"},{"id":94663282,"identity":"6fa77c17-c01e-42f1-b6fa-ab7594d8afb5","added_by":"auto","created_at":"2025-10-29 12:09:02","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":38607,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/4d97ef2f1521afc2d3211a42.png"},{"id":94663292,"identity":"d56a2621-f3ff-4df3-8d10-13f1b31be089","added_by":"auto","created_at":"2025-10-29 12:09:03","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":37376,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/78cf16dec8562cf6686b8afc.png"},{"id":94663287,"identity":"55588182-45d3-499a-9dbe-2f095757fefc","added_by":"auto","created_at":"2025-10-29 12:09:02","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":17707,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/9b637f97e555d5cbf676f30e.png"},{"id":94672616,"identity":"6ea652a5-f713-4e29-8990-8279d7acc59d","added_by":"auto","created_at":"2025-10-29 13:40:46","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":22903,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/3d192d74e7c1f5660df38545.png"},{"id":94663293,"identity":"0f0ae351-20ea-4b64-8f0b-c07250685f56","added_by":"auto","created_at":"2025-10-29 12:09:03","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":118797,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/c1674e94e74ddf5c4af621ec.png"},{"id":94663267,"identity":"9da3f937-f17c-4965-b05c-c5632c699e1d","added_by":"auto","created_at":"2025-10-29 12:09:00","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":22155,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/d48b69a8ac33ce4b768050c6.png"},{"id":94663288,"identity":"3e17e0a5-1fbc-4d98-a567-c97a447a6623","added_by":"auto","created_at":"2025-10-29 12:09:02","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5015,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/01c43b7f2a3b4c43e83f6166.png"},{"id":94663281,"identity":"f966bc1c-6d06-44bd-b655-33b2a8d8b2c2","added_by":"auto","created_at":"2025-10-29 12:09:02","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":14853,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/12566983d6bc837d0890e9e4.png"},{"id":94663256,"identity":"6d566ccf-9193-4e6c-9da7-1fe84a7ccb93","added_by":"auto","created_at":"2025-10-29 12:09:00","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5450,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/021bb27ea7929f68a258c105.png"},{"id":94663201,"identity":"e9a6bddf-0999-4a2a-823f-819a1d990efb","added_by":"auto","created_at":"2025-10-29 12:09:00","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":12570,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/9e552f1e8ad98febb68eb50c.png"},{"id":94663289,"identity":"1267a889-5c6f-4c95-b9f2-67be3863a0f6","added_by":"auto","created_at":"2025-10-29 12:09:02","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":12934,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/3abc3cba9dde3c433d5d7f6f.png"},{"id":94672382,"identity":"e179b7eb-52cb-4958-8a30-c5a754f71c92","added_by":"auto","created_at":"2025-10-29 13:40:25","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":13777,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/25c572c34f66cc2983b90c83.png"},{"id":94663283,"identity":"3285ed4b-8215-4f01-a43f-5adea5befb20","added_by":"auto","created_at":"2025-10-29 12:09:02","extension":"png","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":7301,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/910493ebdc70fbfb4efffea0.png"},{"id":94663299,"identity":"35ee3c46-1724-42d0-8864-8971496c1560","added_by":"auto","created_at":"2025-10-29 12:09:03","extension":"xml","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":105623,"visible":true,"origin":"","legend":"","description":"","filename":"c443895ef7d14b6ab33b0e49bb64fafe1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/1906da24af8b9fcb7d4adccc.xml"},{"id":94663295,"identity":"14baa7d1-2748-4da5-a40c-ce7a88f317f8","added_by":"auto","created_at":"2025-10-29 12:09:03","extension":"html","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":119025,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/4e5d04818eb6d2359948c0b5.html"},{"id":94663279,"identity":"576cfde8-9a92-4bcc-ab53-c6af8028814e","added_by":"auto","created_at":"2025-10-29 12:09:02","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":118900,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/0941780276ee3c0cd2f44fb8.jpg"},{"id":94663294,"identity":"24c72455-b898-4696-9d7d-86ae6645eab3","added_by":"auto","created_at":"2025-10-29 12:09:03","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":51174,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/bf323baedc64e6705f517aaa.jpg"},{"id":94672568,"identity":"0da1848d-2690-43a8-a8b1-f0372cd13886","added_by":"auto","created_at":"2025-10-29 13:40:43","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":53302,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/96d86a9e18600626b8736244.jpg"},{"id":94663199,"identity":"ecf15d88-4ed9-4256-bd9b-3e3aefcb83e7","added_by":"auto","created_at":"2025-10-29 12:09:00","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":48629,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/f0280a050704a656f80ac686.jpg"},{"id":94673194,"identity":"41cde5bb-3f29-4c02-86aa-15b3ba24e91b","added_by":"auto","created_at":"2025-10-29 13:41:16","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":19514,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/45481911ed660298007d5542.jpg"},{"id":94663260,"identity":"cbaa4a3e-2715-4873-b4ee-fb3bd36ddbe5","added_by":"auto","created_at":"2025-10-29 12:09:00","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":25627,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/261eb83e12f604174ce8bf6d.jpg"},{"id":100239885,"identity":"766ce50a-3698-484f-b50e-a1f0f01f6d31","added_by":"auto","created_at":"2026-01-14 13:10:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":954989,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/b3c982a4-28b1-4e29-ae83-37d3987e9f62.pdf"},{"id":94663278,"identity":"128f4c95-1221-4726-87e2-bca2a14228b5","added_by":"auto","created_at":"2025-10-29 12:09:01","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":53930,"visible":true,"origin":"","legend":"\u003cp\u003eTable 1\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/443d74e9a60b9a077d8ff341.png"},{"id":94663286,"identity":"96c11833-8f0a-4dd0-8795-5f1bdf6d3c71","added_by":"auto","created_at":"2025-10-29 12:09:02","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":11671,"visible":true,"origin":"","legend":"\u003cp\u003eTable 1\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/62109c6ea0150964f5704c78.png"},{"id":94663195,"identity":"5fc18c15-8fdd-4c62-a5ad-0dd2c914d0e5","added_by":"auto","created_at":"2025-10-29 12:08:59","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":34400,"visible":true,"origin":"","legend":"\u003cp\u003eTable 2\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/49d1bf45137209e6d88ed95c.png"},{"id":94663230,"identity":"61bf233e-cb65-4f09-9714-3b0bad0b31fd","added_by":"auto","created_at":"2025-10-29 12:09:00","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":13969,"visible":true,"origin":"","legend":"\u003cp\u003eTable 3\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/edff3b5f07e96df74ef6b3cc.png"},{"id":94663297,"identity":"cb0df313-be69-4056-b8a0-8de34326428f","added_by":"auto","created_at":"2025-10-29 12:09:03","extension":"jpeg","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":197424,"visible":true,"origin":"","legend":"\u003cp\u003eTable 4\u003c/p\u003e","description":"","filename":"floatimage10.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7608169/v1/171461f8603fef9b511ed0a5.jpeg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Correlation between cuproptosis-related proteins and postoperative delirium in cardiac valve replacement: a prospective, observational study","fulltext":[{"header":"Background","content":"\u003cp\u003ePostoperative delirium (POD) is an acute neurological disorder characterized by fluctuating disturbances in attention and cognition, typically occurring within the first week after surgery[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It affects approximately 27% of patients following major cardiac procedures such as valve replacement[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Although perioperative neuroprotection has gained increasing attention, the precise mechanisms underlying POD remain incompletely understood[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Current hypotheses implicate neuroinflammation, oxidative stress, neurotransmitter imbalances, and cerebrovascular dysregulation as key contributors[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Major risk factors include surgical trauma, anesthetic exposure, cardiopulmonary bypass (CPB), advanced age, preexisting cognitive impairment, and comorbidities[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCuproptosis is a recently identified form of regulated cell death triggered by excessive intracellular copper accumulation, leading to lipoylated protein aggregation and iron-sulfur cluster destabilization in mitochondria[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Copper is an essential cofactor for enzymes involved in energy production, antioxidant defense, and neuronal maintenance[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Dysregulated copper homeostasis has been linked to cognitive impairment through oxidative stress and neuroinflammatory pathways[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Anesthesia, surgery, and CPB may promote cuproptosis, suggesting a potential mechanistic link to POD[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, clinical evidence regarding this association is lacking.\u003c/p\u003e\u003cp\u003eThis study aimed to investigate the relationship between perioperative changes in cuproptosis-related biomarkers\u0026mdash;copper ion (Cu\u0026sup2;⁺), ferredoxin 1 (FDX1), and lipoic acid (LA)\u0026mdash;and the incidence of POD in patients undergoing cardiac valve replacement.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design\u003c/h2\u003e\u003cp\u003eThis prospective, observational, single-center cohort study was conducted at the General Hospital of Western Theater Command. The study was approved by the hospital\u0026rsquo;s Ethics Committee (No. 2024EC4-ky010) and registered with the Chinese Clinical Trial Registry (ChiCTR2400088024). All participants provided written informed consent.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003eAdult patients (aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years) scheduled for elective cardiac valve replacement under general anesthesia with cardiopulmonary bypass (CPB) between August 2024 and July 2025 were included.Exclusion criteria comprised: emergency surgery; inability to communicate preoperatively; Mini-Mental State Examination (MMSE) score\u0026thinsp;\u0026lt;\u0026thinsp;24; history of neurological or psychiatric disorders; copper metabolism abnormalities; abnormal coagulation; severe hepatic, renal, or pulmonary impairment; and cases with missing data. A total of 140 patients were enrolled and provided informed consent(Fig.\u0026nbsp;1).\u003c/p\u003e\n\u003ch3\u003eData collection and Variable definitions\u003c/h3\u003e\n\u003cp\u003eThe occurrence of postoperative delirium (POD) was assessed twice daily from postoperative days 1 to 7 using the Richmond Agitation-Sedation Scale (RASS) and the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Various patient-related, anesthesia-related, and surgery-related factors were analyzed, including gender, body mass index (BMI), American Society of Anesthesiologists (ASA) classification, Mini-Mental State Examination (MMSE) score, smoking history, alcohol abuse, comorbidities (hypertension, diabetes mellitus, coronary artery disease), cardiac function classification, left ventricular ejection fraction (LVEF), fractional shortening (FS), hemoglobin concentration, liver and renal function indicators, cardiopulmonary bypass (CPB) duration, total volume of intravenous fluids administered, intraoperative urine output, volume of blood transfused, type of surgery, duration of surgery, and intraoperative blood loss. To evaluate perioperative changes in cuproptosis activity, central venous blood samples were collected at four time points: before induction of anesthesia (T1), at initiation of CPB (T2), at end of CPB (T3), and immediately after surgery (T4). Serum concentrations of copper ions (Cu\u0026sup2;⁺), FDX1, and lipoic acid were measured using commercial enzyme-linked immunosorbent assay (ELISA) kits. All POD assessments were performed by trained staff members who were blinded to group assignments and biomarker results.\u003c/p\u003e\n\u003ch3\u003eAnesthetic Management\u003c/h3\u003e\n\u003cp\u003e In accordance with standard preoperative fasting guidelines, all patients abstained from oral intake for 8 hours prior to surgery. Following the establishment of peripheral intravenous access, ultrasound-guided cannulation of the left radial artery and right deep vein was performed to enable continuous arterial and central venous pressure monitoring, as well as central venous catheterization.General anesthesia was induced using intravenous midazolam (0.03 mg/kg), etomidate (0.3 mg/kg), and sufentanil (0.5 \u0026micro;g/kg). Upon loss of the eyelash reflex, cisatracurium (0.2 mg/kg) was administered to facilitate neuromuscular blockade prior to endotracheal intubation. Mechanical ventilation was conducted in Pressure Controlled Ventilation\u0026ndash;Volume Guaranteed (PCV-VG) mode with the following parameters: tidal volume 6\u0026ndash;8 mL/kg, FiO₂ 100%, inspiratory-to-expiratory ratio of 1:2, and end-tidal CO₂ maintained at 35\u0026ndash;45 mmHg through adjustment of respiratory rate and tidal volume.Anesthesia was maintained with a continuous infusion of dexmedetomidine (0.5 \u0026micro;g/kg/h) and inhaled sevoflurane at a minimum alveolar concentration (MAC)\u0026thinsp;\u0026ge;\u0026thinsp;0.6. Supplemental intravenous boluses of cisatracurium (0.08 mg/kg) and sufentanil (0.5 \u0026micro;g/kg) were administered as needed to maintain a bispectral index (BIS) value between 40 and 60. Hemodynamic stability was supported through the judicious use of vasoactive agents, including norepinephrine, dobutamine, milrinone, nitroglycerin, and isoproterenol.During cardiopulmonary bypass (CPB), core temperature was maintained at 28\u0026ndash;30\u0026deg;C, pump flow was set at 2.0\u0026ndash;2.4 L/(min\u0026middot;m\u0026sup2;), and mean arterial pressure (MAP) was targeted between 50 and 80 mmHg. Prior to weaning from CPB, patients were rewarmed to 36\u0026ndash;37\u0026deg;C.Postoperative analgesia was provided via a patient-controlled intravenous analgesia (PCIA) system containing sufentanil (100 \u0026micro;g), butorphanol tartrate (5 mg), and ondansetron (16 mg), diluted to 100 mL with normal saline and infused at a basal rate of 3 mL/h. All patients were transferred to the intensive care unit (ICU) with the endotracheal tube in place. Sedation and analgesia in the ICU were maintained with remimazolam and remifentanil, respectively, until extubation criteria were met and the endotracheal tube was removed.\u003c/p\u003e\n\u003ch3\u003eSample size\u003c/h3\u003e\n\u003cp\u003eBased on a literature-derived POD incidence of 27% and a target relative risk of 2.5[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]., a sample size of 126 patients was estimated using PASS 15.0, with α\u0026thinsp;=\u0026thinsp;0.05 and power\u0026thinsp;=\u0026thinsp;0.9. Accounting for a 10% dropout rate, 140 patients were planned for enrollment.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eData analysis was performed using IBM SPSS Statistics for Windows, Version 27.0 (IBM Corp., Armonk, NY, USA).\u003c/p\u003e\u003cp\u003eNominal categorical variables (e.g., gender, smoking history, hypertension comorbidity) were presented as frequencies (percentages). Intergroup comparisons were conducted using Pearson's chi-square test or Fisher's exact test (when expected frequencies were \u0026lt;\u0026thinsp;5). Ordinal categorical variables (e.g., cardiac function classification, ASA physical status classification) were presented as median (interquartile range, IQR). Comparisons between two groups were performed using the Mann-Whitney U test. Continuous variables (e.g., CPB duration, age, MMSE score, serum substance concentrations) were first assessed for distribution normality using the Kolmogorov-Smirnov test. Normally distributed continuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), and intergroup comparisons were made using the independent samples t-test. Non-normally distributed continuous variables were expressed as median (IQR), and comparisons between two groups were performed using the Mann-Whitney U test.\u003c/p\u003e\u003cp\u003eIntergroup comparisons of baseline characteristics and intraoperative variables prior to matching were conducted according to the principles outlined above:\u003c/p\u003e\u003cp\u003eNormally distributed continuous variables (age, BMI, MMSE score, LVEF, FS, Hb) were compared using the independent samples t-test.Non-normally distributed continuous variables (CPB duration, fluid infusion volume, blood transfusion volume, operation duration, blood loss) and ordinal categorical variables (ASA classification, cardiac function classification) were compared using the Mann-Whitney U test.Nominal binary categorical variables (gender, smoking history, alcohol abuse history, hypertension, diabetes, coronary heart disease, liver function, renal function) were compared using the chi-square test.\u003c/p\u003e\u003cp\u003eTo control for potential confounding factors, a 1:1 Propensity Score Matching (PSM) method was employed using the Nearest Neighbor Matching algorithm, with a caliper width set to 0.05. Matching variables encompassed all baseline characteristics and intraoperative variables (total of 22 variables): gender, age, BMI, ASA classification, MMSE score, smoking history, alcohol abuse history, hypertension, diabetes, coronary heart disease, cardiac function classification, LVEF, FS, Hb, liver function, renal function, CPB duration, fluid infusion volume, urine output, blood transfusion volume, operation duration, and blood loss.\u003c/p\u003e\u003cp\u003eBiomarker Data Presentation and Derived Variables: Serum concentrations of Cu\u0026sup2;⁺, FDX1, and lipoic acid were recorded and analyzed at four time points: pre-anesthesia (T1), initiation of cardiopulmonary bypass (CPB) (T2), cessation of CPB (T3), and immediately post-operation (T4). The following derived concentration difference indices were calculated and analyzed: Pre- to post-operative concentration difference (T4 - T1, ΔT4-T1); Pre- to post-CPB concentration difference (T3 - T2, ΔT3-T2).\u003c/p\u003e\u003cp\u003ePreliminary Screening (Differential Expression Analysis): All 18 concentration indices (3 proteins at 6 time points/differences: T1, T2, T3, T4, ΔT4-T1, ΔT3-T2) in the matched sample were analyzed. Log2 Fold Change (Log2FC) was calculated for concentrations in the POD group relative to the non-POD group. Differences in each concentration index between the POD and non-POD groups were compared using the independent samples t-test. Statistical significance for differential expression was defined as |Log2FC| \u0026gt; log2(1.2) (indicating a 1.2-fold change) and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Volcano plots were generated to visualize the differential analysis results.\u003c/p\u003e\u003cp\u003eMultivariable Conditional Logistic Regression Analysis: To assess the independent association between cuproptosis biomarkers and POD risk while controlling for the matched-pair design and important covariates, conditional logistic regression analysis was performed. Dependent variable: Occurrence of POD (binary variable). Independent variables: The 6 significantly differential protein indices identified in the preliminary screening were included in the model. Adjustment variables: Considering the matched design and clinical importance, the model was forced to adjust for the matching factor (implicitly handled by the conditional logistic regression), age, MMSE score, and CPB duration. Results were expressed as Odds Ratios (OR) with corresponding 95% Confidence Intervals (95% CI).\u003c/p\u003e\u003cp\u003eAll hypothesis tests were two-tailed. A P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 152 patients scheduled for cardiac valve replacement between August 2024 and July 2025 were screened. Of these, 2 declined participation and 10 were excluded based on predetermined criteria: preoperative communication barriers (n\u0026thinsp;=\u0026thinsp;2), MMSE scores\u0026thinsp;\u0026lt;\u0026thinsp;24 (n\u0026thinsp;=\u0026thinsp;4), history of neurological or psychiatric disorders (n\u0026thinsp;=\u0026thinsp;1), abnormal coagulation function (n\u0026thinsp;=\u0026thinsp;1), and severe hepatic, renal, or pulmonary impairment (n\u0026thinsp;=\u0026thinsp;2). The remaining 140 patients met the inclusion criteria and provided informed consent (Fig.\u0026nbsp;1). During the follow-up period, 14 participants were lost to attrition. Consequently, 126 patients completed the entire study and were included in the final analysis. Among them, 58 (46.0%) developed postoperative delirium (POD group), while 68 (54.0%) did not (non-POD group). The study flowchart is presented in Fig.\u0026nbsp;1.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThis study included 126 patients who underwent cardiac valve surgery. Pre-matching baseline data analysis (Table\u0026nbsp;1) revealed significant differences between the POD and non-POD groups in age, MMSE score, and prevalence of coronary heart disease (CHD) (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Specifically, the POD group was older (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028), had lower baseline MMSE scores (indicating poorer baseline cognitive function, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017), and had a higher proportion of CHD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.034). No significant differences were observed in other demographic characteristics, comorbidities, NYHA functional class, LVEF, FS, Hb, or hepatic and renal function indicators (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Baseline characteristics of patients before PSM are summarized in Table\u0026nbsp;1.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAnalysis of surgical and perioperative indicators is presented in Table\u0026nbsp;2. The cardiopulmonary bypass (CPB) time was significantly longer in the POD group than in the non-POD group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009), and intraoperative urine output was significantly lower (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022). No significant differences were found in other intraoperative indicators, including duration of surgery, blood loss, fluid infusion volume, or transfusion volume (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo control for baseline confounding factors, PSM was performed to balance 22 variables, including baseline characteristics (age, gender, BMI, ASA grade, MMSE score, smoking history, alcohol abuse, hypertension, diabetes, CHD, NYHA class, LVEF, FS, Hb, hepatic and renal function) and surgical parameters (CPB time, fluid infusion volume, urine output, transfusion volume, duration of surgery, and blood loss). A caliper value of 0.05 was used with 1:1 nearest-neighbor matching. After PSM, 34 matched pairs were successfully formed (34 in the POD group and 34 in the non-POD control group). After PSM, all 22 matched variables were well-balanced between the groups, including the previously significant factors such as age, MMSE score, and CPB duration (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05)., indicating successful matching and comparability. PSM results are presented in Table\u0026nbsp;3.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSerum concentrations of ferredoxin 1 (FDX1), lipoic acid (LA), and copper ions (Cu\u0026sup2;⁺) were measured via ELISA at four perioperative time points: T1 (pre-anesthesia), T2 (CPB initiation), T3 (CPB cessation), and T4 (immediately after surgery). Two change values were calculated: ΔT4\u0026ndash;T1 (reflecting change over the entire procedure) and ΔT3\u0026ndash;T2 (reflecting change during CPB), resulting in a total of 18 biomarker concentration indicators (3 biomarkers \u0026times; [4 time points\u0026thinsp;+\u0026thinsp;2 Δ values]). After PSM, the following analyses were performed on the matched cohort of 68 patients(34 pairs). Independent samples t-tests were performed to compare these 18 indicators between the POD and non-POD groups. The POD group showed significantly higher serum FDX1 concentration at T4 (18.6 vs. 14.9 ng/mL). Serum LA levels were significantly lower in the POD group at T1 (19.6 vs. 23.9 \u0026micro;g/L), T2 (11.3 vs. 15.0 \u0026micro;g/L), and T4 (6.7 vs. 9.1 \u0026micro;g/L). No consistent differences were observed in copper ion levels. Dynamic changes in concentrations of lipoic acid, copper ions, and ferredoxin 1 during cardiopulmonary bypass are shown in Figs.\u0026nbsp;2 to 4.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFurther analysis using log₂fold change (FC, POD/non-POD ratio) combined with independent samples t-tests was conducted. With a significance threshold of |log₂FC| \u0026ge; log₂(1.2) (i.e., \u0026ge;\u0026thinsp;1.2-fold or \u0026le;\u0026thinsp;0.83-fold change) and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, volcano plot analysis (Fig.\u0026nbsp;5) identified six biomarkers significantly associated with POD. Compared to the non-POD group, the POD group exhibited: Significantly greater increases in FDX1 over the entire procedure (ΔT4\u0026ndash;T1) and during CPB (ΔT3\u0026ndash;T2). Significantly lower LA levels at T1, T2, T4, and a reduced increase (or greater decrease) in LA during CPB (ΔT3\u0026ndash;T2). Notably, no significant differences were observed in copper ion (Cu\u0026sup2;⁺) levels at any time point or in Δ values (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The volcano plot illustrating significantly altered biomarkers is displayed in Fig.\u0026nbsp;5.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo evaluate the independent association of the differentially expressed biomarkers with POD risk while controlling for potential residual confounders (particularly age, baseline MMSE score, and CPB time), conditional logistic regression analysis adjusted for these factors was performed on the PSM-matched sample (34 pairs) (Table\u0026nbsp;4 and Fig.\u0026nbsp;6). The results showed: Each unit increase in FDX1 ΔT4\u0026ndash;T1 (change over the entire procedure) was associated with a 70% increase in POD risk (adjusted OR\u0026thinsp;=\u0026thinsp;1.7, 95% CI: 1.1\u0026ndash;2.5, P\u0026thinsp;=\u0026thinsp;0.018). Each unit increase in LA ΔT3\u0026ndash;T2 (change during CPB) was associated with a 60% increase in POD risk (adjusted OR\u0026thinsp;=\u0026thinsp;1.60, 95% CI: 1.1\u0026ndash;2.4, P\u0026thinsp;=\u0026thinsp;0.044). The other four biomarkers that showed significant differences in initial screening (FDX1 ΔT3\u0026ndash;T2, LA T1, LA T2, LA T4) did not demonstrate independent significant associations with POD risk after adjusting for age, MMSE score, CPB time, and the matched-pair design (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).Results of the multivariate regression analysis are provided in Table\u0026nbsp;4 and Fig.\u0026nbsp;6.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePostoperative delirium (POD) is an acute organic brain syndrome of unclear etiology, characterized by acutely onset cognitive impairment and inattention within a short period after surgery (typically within 7 days), often accompanied by confusion and perceptual disturbances, with fluctuating symptoms[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Cuproptosis is a novel form of regulated cell death triggered by excessive intracellular copper accumulation or dysregulated copper metabolism, leading to mitochondrial lipoylated protein aggregation and destabilization of iron-sulfur cluster proteins[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study is the first to reveal an association between dynamic changes in key proteins of the cuproptosis pathway during the perioperative period of cardiac valve surgery and the occurrence of POD. After controlling for confounders using propensity score matching, we found that the cumulative increase in FDX1 throughout the surgery (ΔT4\u0026ndash;T1) and the exaggerated consumption of lipoic acid during cardiopulmonary bypass (ΔT3\u0026ndash;T2) were independent risk factors for POD (OR\u0026thinsp;=\u0026thinsp;1.7, P\u0026thinsp;=\u0026thinsp;0.018; OR\u0026thinsp;=\u0026thinsp;1.6, P\u0026thinsp;=\u0026thinsp;0.044, respectively). These findings provide new insights into the molecular mechanisms of POD and highlight potential interventional targets.\u003c/p\u003e\u003cp\u003eThe cumulative increase in FDX1, a key driver of cuproptosis, suggests a neurotoxic mechanism underlying POD. Elevated FDX1 levels directly promote copper-dependent lipoylated protein aggregation within mitochondria. In this study, POD patients showed significantly increased FDX1 levels throughout surgery\u0026mdash;particularly at T4 (end of surgery)\u0026mdash;and a strong positive correlation was observed between ΔT4\u0026ndash;T1 and POD risk, which is consistent with recent cuproptosis theory. As a critical initiator of cuproptosis, FDX1 may induce neuronal damage via mitochondrial proteotoxicity. FDX1 overexpression can suppress iron-sulfur cluster biosynthesis and disrupt the tricarboxylic acid (TCA) cycle, leading to neuronal ATP depletion[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Ischemia-reperfusion injury during cardiac surgery may amplify this process, causing an energy crisis in the hippocampus and impairing cognitive function. Furthermore, animal studies have confirmed that cuproptosis can lead to neuronal apoptosis through oxidative and lipid damage, disrupt synaptic plasticity, and impair CREB pathway-mediated memory formation, resulting in memory deficits and cognitive decline [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. FDX1 upregulation can activate the NLRP3 inflammasome and promote IL-1β release[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Prolonged CPB time (P\u0026thinsp;=\u0026thinsp;0.009 in the POD group) may enhance endothelial FDX1 activation via shear stress, aggravating systemic inflammation and its transmission to the central nervous system. Real-time intraoperative monitoring of FDX1 dynamics may help identify patients at high risk of POD. Furthermore, targeting FDX1 has emerged as a potential neuroprotective strategy, suggesting that FDX1 inhibition could be a promising therapeutic approach to mitigate POD risk, warranting further investigation[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], suggesting a promising direction for future interventional studies.\u003c/p\u003e\u003cp\u003eConcurrently, the observed depletion of lipoic acid, a physiological antagonist of cuproptosis, reflects exhaustion of antioxidant reserves counteracting this pathway. Significantly lower lipoic acid levels in POD patients at T1, T2, and T4, and its change during CPB (ΔT3\u0026ndash;T2) was independently associated with POD risk. One study found that copper-exposed mice showed elevated glutamate, malondialdehyde, and caspase-3 levels in the frontal cortex and hippocampus, along with reduced glutathione (GSH) and impaired Y-maze attention scores[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This suggests that copper induces apoptosis in the hippocampus and frontal cortex via glutamate and oxidative stress pathways, leading to impaired learning and memory. Lipoic acid helps maintain redox balance by regenerating GSH and vitamin E[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Its depletion exposes neurons to cuproptosis-related lipid peroxidation, causing direct synaptic damage[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The lower baseline MMSE scores in the POD group (P\u0026thinsp;=\u0026thinsp;0.017) further indicate preoperative susceptibility to oxidative stress. Moreover, lipoic acid has been shown to support the PINK1/Parkin pathway [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]; its deficiency may therefore hinder the clearance of damaged mitochondria, leading to accumulated reactive oxygen species (ROS) that further activate FDX1, creating a vicious cycle of \u0026ldquo;cuproptosis\u0026ndash;oxidative stress\u0026rdquo;[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The independent predictive value of lipoic acid ΔT3\u0026ndash;T2 highlights the CPB period as a critical window of consumption. This is directly related to hemodilution and free radical burst during CPB, suggesting that supplementing lipoic acid analogues in the CPB circuit may offer neuroprotective potential.\u003c/p\u003e\u003cp\u003eNotably, the absence of significant differences in copper ion (Cu\u0026sup2;⁺) levels at any time point carries scientific meaning, implying that cuproptosis is driven by abnormal copper localization (mitochondrial accumulation) rather than total serum copper levels. FDX1 and lipoic acid, as functional molecules, more accurately reflect pathway activity than copper ions alone. This finding aligns with the concept of \u0026ldquo;functional cuproptosis biomarkers\u0026rdquo;, underscoring a therapeutic strategy focused on regulating key proteins rather than mere copper chelation.\u003c/p\u003e\u003cp\u003eCollectively, these findings hold significant clinical translational value. The combination of FDX1 ΔT4\u0026ndash;T1 and lipoic acid ΔT3\u0026ndash;T2 may form a novel biomarker panel for immediate postoperative identification of high-risk patients. Targeted interventions can be designed based on the temporal patterns of FDX1 elevation (end of surgery) and lipoic acid depletion (during CPB). Ultimately, developing FDX1 inhibitors or lipoic acid nanodelivery systems may help disrupt the cuproptosis\u0026ndash;neuroinflammation axis, opening new avenues for preventing and treating POD.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eSeveral limitations of this study should be acknowledged. First, as a single-center observational study, although propensity score matching was applied to minimize confounding, residual bias may persist due to unmeasured variables. Second, the generalizability of our findings is limited to patients undergoing cardiac valve replacement with cardiopulmonary bypass, and may not extend to other surgical populations or clinical settings. Third, the biomarkers measured in peripheral blood may not directly reflect changes within the central nervous system, limiting mechanistic interpretation. Finally, the moderate sample size after matching (34 pairs) may have reduced statistical power to detect more subtle associations or interactions.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe dynamic activation of the cuproptosis pathway during cardiac valve surgery represents a key mechanism underlying postoperative delirium (POD). The cumulative increase in FDX1 and progressive depletion of lipoic acid collectively contribute to neuronal injury, with their respective changes (Δ values) serving as independent predictors. Future studies should focus on validating brain protection strategies targeting this pathway\u0026mdash;such as FDX1 antagonism and lipoic acid supplementation\u0026mdash;to improve neurocognitive outcomes in patients undergoing cardiac surgery.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePOD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePostoperative Delirium\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCuproptosis\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCopper-dependent cell death\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFDX1\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eFerredoxin 1\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCPB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCardiopulmonary Bypass\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePSM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePropensity Score Matching\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRASS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRichmond Agitation-Sedation Scale\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCAM-ICU\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfusion Assessment Method for the Intensive Care Unit\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMMSE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMini-Mental State Examination\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eASA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAmerican Society of Anesthesiologists\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBody Mass Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCHD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCoronary Heart Disease\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLVEF\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLeft Ventricular Ejection Fraction\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eFractional Shortening\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eELISA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEnzyme-Linked Immunosorbent Assay\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eROS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eReactive Oxygen Species\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTCA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTricarboxylic Acid Cycle\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGSH\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGlutathione\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCREB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ecAMP-response Element Binding Protein\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eOdds Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence Interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStandard Deviation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInterquartile Range\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLog2FC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLog2 Fold Change\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of the General Hospital of Western Theater Command (Approval No. 2024EC4-ky010). All procedures performed in this study involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Written informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent for publication was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author (Dr. Gu Gong, Email: [email protected]) on reasonable request. Data requests will be evaluated to ensure they comply with the ethical obligations and participant confidentiality established by the Ethics Committee of the General Hospital of Western Theater Command.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003cbr\u003e\u003c/strong\u003eNone declared.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003cbr\u003e\u003c/strong\u003eThis study was supported by the Hospital Management Project of the General Hospital of the Western Theatre Command (grant number 2021-XZYG-A10) and the Joint Key Project (grant number 2021-XZYG-C25). The funders had no role in the design of the study; collection, analysis, or interpretation of data; or in writing the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003cbr\u003e\u003c/strong\u003eZZ conceived the study and led the proposal development under the supervision and suggestions of GG and QH. ZZ and QZ contributed to study design and to development of the proposal. QS and WL wrote the statistical analysis plan and estimated the sample size. YY and JZ was the lead trial methodologist. ZZ drafted the manuscript with QH. All authors read and approved the final manuscript. ZZ is the guarantor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003cbr\u003e\u003c/strong\u003eWe would like to thank Editage (www.editage.com) for English language editing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZheng Zhang\u003csup\u003e1,2\u003c/sup\u003e, Qiuran Zheng\u003csup\u003e1\u003c/sup\u003e , Yangyang Ye\u003csup\u003e2,3\u003c/sup\u003e, Qin Shi\u003csup\u003e2\u003c/sup\u003e, Weiqin Li\u003csup\u003e2\u003c/sup\u003e, Jingzheng Zeng\u003csup\u003e2\u003c/sup\u003e, Qingqing Huang\u003csup\u003e2,4*\u003c/sup\u003e, Gu Gong\u003csup\u003e1,2*\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eDepartment of Anesthesiology, The Affiliated Hospital, Southwest Medical University, Luzhou, China\u003cbr\u003e\u003csup\u003e2\u003c/sup\u003eDepartment of Anesthesiology, The General Hospital of Western Theater Command, Chengdu, China\u003cbr\u003e\u003csup\u003e3\u003c/sup\u003eCollege of Medicine, North Sichuan Medical College, Nanchong, China\u003cbr\u003e\u003csup\u003e4\u003c/sup\u003eCollege of Medicine, Southwest Jiaotong University, Chengdu, China\u003c/p\u003e\n\u003cp\u003e*These authors contributed equally to this work\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Dr Gu Gong and Dr QingQing Huang.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChaput AJ, Bryson GL. Postoperative delirium: risk factors and management: continuing professional development. Can J Anaesth. 2012;59(3):304\u0026ndash;20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s12630-011-9658-4\u003c/span\u003e\u003cspan address=\"10.1007/s12630-011-9658-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFu M, Yuan Q, Yang Q, et al. Risk factors and incidence of postoperative delirium after cardiac surgery in children: a systematic review and meta-analysis. Ital J Pediatr. 2024;50(1):24. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13052-024-01603-2\u003c/span\u003e\u003cspan address=\"10.1186/s13052-024-01603-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Published 2024 Feb 8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMattimore D, Fischl A, Christophides A, et al. Delirium after cardiac surgery-a narrative review. Brain Sci. 2023;13(12):1682. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/brainsci13121682\u003c/span\u003e\u003cspan address=\"10.3390/brainsci13121682\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Published 2023 Dec 7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXiao M, Liu C, Zhou L, Yang Y, Wang Y. Postoperative delirium, neuroinflammation, and influencing factors of postoperative delirium: a review. Med (Baltimore). 2023;102(8):e32991. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/MD.0000000000032991\u003c/span\u003e\u003cspan address=\"10.1097/MD.0000000000032991\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePang Y, Li Y, Zhang Y, Wang H, Lang J, Han L, Liu H, Xiong X, Gu L, Wu X. Effects of inflammation and oxidative stress on postoperative delirium in cardiac surgery. Front Cardiovasc Med. 2022;9:1049600. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fcvm.2022.1049600\u003c/span\u003e\u003cspan address=\"10.3389/fcvm.2022.1049600\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang Y, Shen X. Postoperative delirium in the elderly: the potential neuropathogenesis. Aging Clin Exp Res. 2018;30(11):1287\u0026ndash;95. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s40520-018-1008-8\u003c/span\u003e\u003cspan address=\"10.1007/s40520-018-1008-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSampaolesi C, Casarotta E, Gresti G, Mariotti G, Pisani L, Veccia D, Di Eusanio M, Malvindi PG, Donati A, M\u0026uuml;nch CM. The association between cerebral blood flow variations during on-pump coronary artery bypass grafting surgery and postoperative delirium. Perfusion. 2025;40(2):440\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/02676591241239823\u003c/span\u003e\u003cspan address=\"10.1177/02676591241239823\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOthman SMA, Aziz MAA, Sriwayyapram C, Xu Q. Systematic literature review on early detection of postoperative delirium in adult patients after cardiac surgery. J Cardiothorac Surg. 2024;19(1):678. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13019-024-03173-0\u003c/span\u003e\u003cspan address=\"10.1186/s13019-024-03173-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Published 2024 Dec 21.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFatehi Hassanabad A, Bahrami N, Novick RJ, Ali IS. Delirium and depression in cardiac surgery: a comprehensive review of risk factors, pathophysiology, and management. J Card Surg. 2021;36(8):2876\u0026ndash;89. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/jocs.15610\u003c/span\u003e\u003cspan address=\"10.1111/jocs.15610\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGromadzka G, Tarnacka B, Flaga A, Adamczyk A. Copper dyshomeostasis in neurodegenerative diseases-therapeutic implications. Int J Mol Sci. 2020;21(23):9259. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms21239259\u003c/span\u003e\u003cspan address=\"10.3390/ijms21239259\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Published 2020 Dec 4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eScheiber I, Dringen R, Mercer JF. Copper: effects of deficiency and overload. Met Ions Life Sci. 2013;13:359\u0026ndash;87. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/978-94-007-7500-8_11\u003c/span\u003e\u003cspan address=\"10.1007/978-94-007-7500-8_11\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMezzaroba L, Alfieri DF, Colado Sim\u0026atilde;o AN, Vissoci Reiche EM. The role of zinc, copper, manganese and iron in neurodegenerative diseases. Neurotoxicology. 2019;74:230\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neuro.2017.07.007\u003c/span\u003e\u003cspan address=\"10.1016/j.neuro.2017.07.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao R, Sukocheva O, Tse E, Neganova M, Aleksandrova Y, Zheng Y, Gu H, Zhao D, Madhunapantula SV, Zhu X, Liu J, Fan R. Cuproptosis, the novel type of oxidation-induced cell death in thoracic cancers: can it enhance the success of immunotherapy? Cell Commun Signal. 2024;22:379. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12964-024-01743-2\u003c/span\u003e\u003cspan address=\"10.1186/s12964-024-01743-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRuiz LM, Libedinsky A, Elorza AA. Role of copper on mitochondrial function and metabolism. Front Mol Biosci. 2021;8:711227. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fmolb.2021.711227\u003c/span\u003e\u003cspan address=\"10.3389/fmolb.2021.711227\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Published 2021 Aug 24.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSensi SL, Granzotto A, Siotto M, Squitti R. Copper and zinc dysregulation in Alzheimer's disease. Trends Pharmacol Sci. 2018;39(12):1049\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.tips.2018.10.001\u003c/span\u003e\u003cspan address=\"10.1016/j.tips.2018.10.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuat TJ, Camats-Perna J, Newcombe EA, Valmas N, Kitazawa M, Medeiros R. Metal toxicity links to Alzheimer's disease and neuroinflammation. J Mol Biol. 2019;431(9):1843\u0026ndash;68. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jmb.2019.01.018\u003c/span\u003e\u003cspan address=\"10.1016/j.jmb.2019.01.018\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNzengue Y, Steiman R, Rachidi W, Favier A, Guiraud P. Oxidative stress induced by cadmium in the C6 cell line: role of copper and zinc. Biol Trace Elem Res. 2012;146(3):410\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s12011-011-9265-9\u003c/span\u003e\u003cspan address=\"10.1007/s12011-011-9265-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang B, Mu C, Tang X et al. The relationship between mild cognitive impairment and postoperative delirium undergoing total knee arthroplasty: the PNDABLE study. Front Aging Neurosci. 2022;14:959510. Published 2022 Sep 29. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fnagi.2022.959510\u003c/span\u003e\u003cspan address=\"10.3389/fnagi.2022.959510\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThedim M, Vacas S. Postoperative delirium and the older adult: untangling the confusion. J Neurosurg Anesthesiol. 2024;36(3):184\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/ANA.0000000000000971\u003c/span\u003e\u003cspan address=\"10.1097/ANA.0000000000000971\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBerger M, Terrando N, Smith SK, Browndyke JN, Newman MF, Mathew JP. Neurocognitive function after cardiac surgery: from phenotypes to mechanisms. Anesthesiology. 2018;129(4):829\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/ALN.0000000000002194\u003c/span\u003e\u003cspan address=\"10.1097/ALN.0000000000002194\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eO'Neal JB, Shaw AD. Predicting, preventing, and identifying delirium after cardiac surgery. Perioper Med (Lond). 2016. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13741-016-0032-5\u003c/span\u003e\u003cspan address=\"10.1186/s13741-016-0032-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. 5:7. Published 2016 Apr 26.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen H, Mo L, Hu H, Ou Y, Luo J. Risk factors of postoperative delirium after cardiac surgery: a meta-analysis. J Cardiothorac Surg. 2021;16(1):113. Published 2021 Apr 26. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13019-021-01496-w\u003c/span\u003e\u003cspan address=\"10.1186/s13019-021-01496-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLewis CA, de Jersey S, Seymour M, Hopkins G, Hickman I, Osland E. Iron, vitamin B12, folate and copper deficiency after bariatric surgery and the impact on anaemia: a systematic review. Obes Surg. 2020;30(11):4542\u0026ndash;91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11695-020-04872-y\u003c/span\u003e\u003cspan address=\"10.1007/s11695-020-04872-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLangley A, Dameron CT. Copper and anesthesia: clinical relevance and management of copper related disorders. Anesthesiol Res Pract. 2013;2013:750901. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2013/750901\u003c/span\u003e\u003cspan address=\"10.1155/2013/750901\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKaur A, Gupta KK, Deep G, Thakur S. Wilson disease - challenge for safe anesthesia! Saudi J Anaesth. 2019;13(4):384\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/sja.SJA_12_19\u003c/span\u003e\u003cspan address=\"10.4103/sja.SJA_12_19\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTse L, Schwarz SK, Bowering JB, Moore RL, Barr AM. Incidence of and risk factors for delirium after cardiac surgery at a quaternary care center: a retrospective cohort study. J Cardiothorac Vasc Anesth. 2015;29(6):1472\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1053/j.jvca.2015.06.018\u003c/span\u003e\u003cspan address=\"10.1053/j.jvca.2015.06.018\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAldecoa C, Bettelli G, Bilotta F, Sanders RD, Audisio R, Borozdina A, Cherubini A, Jones C, Kehlet H, MacLullich A, Radtke F, Riese F, Slooter AJ, Veyckemans F, Kramer S, Neuner B, Weiss B, Spies CD. European Society of Anaesthesiology evidence-based and consensus-based guideline on postoperative delirium. Eur J Anaesthesiol. 2017;34(4):192\u0026ndash;214. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/EJA.0000000000000594\u003c/span\u003e\u003cspan address=\"10.1097/EJA.0000000000000594\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen L, Min J, Wang F. Copper homeostasis and cuproptosis in health and disease. Signal Transduct Target Ther. 2022;7(1):378. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41392-022-01229-y\u003c/span\u003e\u003cspan address=\"10.1038/s41392-022-01229-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTsvetkov P, Coy S, Petrova B, Dreishpoon M, Verma A, Abdusamad M, Rossen J, Joesch-Cohen L, Humeidi R, Spangler RD, Eaton JK, Frenkel E, Kocak M, Corsello SM, Lutsenko S, Kanarek N, Santagata S, Golub TR. Copper induces cell death by targeting lipoylated TCA cycle proteins. Science. 2022;375(6586):1254\u0026ndash;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1126/science.abf0529\u003c/span\u003e\u003cspan address=\"10.1126/science.abf0529\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang Y, Zhou Q, Lu L et al. Copper induces cognitive impairment in mice via modulation of cuproptosis and CREB signaling. Nutrients. 2023;15(4):972. Published 2023 Feb 15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/nu15040972\u003c/span\u003e\u003cspan address=\"10.3390/nu15040972\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKalita J, Kumar V, Misra UK, Bora HK. Memory and learning dysfunction following copper toxicity: biochemical and immunohistochemical basis. Mol Neurobiol. 2018;55(5):3800\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s12035-017-0619-y\u003c/span\u003e\u003cspan address=\"10.1007/s12035-017-0619-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCai D, Li J, Peng Z, Fu R, Chen C, Liu F, Li Y, Su Y, Li C, Chen W. Interplay of ferroptosis, cuproptosis, autophagy and pyroptosis in male infertility: molecular crossroads and therapeutic opportunities. Int J Mol Sci. 2025;26(8):3496. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms26083496\u003c/span\u003e\u003cspan address=\"10.3390/ijms26083496\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang S, Li X, Yan J, Jiang F, Fan X, Jin J, Zhang W, Zhong D, Li G. Disulfiram downregulates ferredoxin 1 to maintain copper homeostasis and inhibit inflammation in cerebral ischemia/reperfusion injury. Sci Rep. 2024;14(1):15175. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-024-64981-x\u003c/span\u003e\u003cspan address=\"10.1038/s41598-024-64981-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePacker L, Witt EH, Tritschler HJ. alpha-Lipoic acid as a biological antioxidant. Free Radic Biol Med. 1995;19(2):227\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/0891-5849(95)00017-r\u003c/span\u003e\u003cspan address=\"10.1016/0891-5849(95)00017-r\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eParsanathan R. Copper's dual role: unravelling the link between copper homeostasis, cuproptosis, and cardiovascular diseases. Hypertens Res. 2024;47(5):1440\u0026ndash;2. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41440-024-01636-4\u003c/span\u003e\u003cspan address=\"10.1038/s41440-024-01636-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShen C, Chen X, Cao Y, Du Y, Xu X, Wu Q, Lin L, Qin Y, Meng R, Gan L, Zhang J. Alpha-lipoic acid protects against chronic alcohol consumption-induced cardiac damage by the aldehyde dehydrogenase 2-associated PINK/parkin pathway. J Cardiovasc Pharmacol. 2023;82(5):407\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/FJC.0000000000001480\u003c/span\u003e\u003cspan address=\"10.1097/FJC.0000000000001480\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 4 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Postoperative delirium, Cardiac valve replacement, Cuproptosis, Ferredoxin 1, Lipoic acid, Propensity score matching","lastPublishedDoi":"10.21203/rs.3.rs-7608169/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7608169/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003ePostoperative delirium (POD) is a common neurological complication following cardiac valve replacement. Although cuproptosis, a novel form of copper-dependent cell death, has been implicated in neurological disorders, its relationship with POD remains unclear. This study aimed to investigate the association between perioperative changes in cuproptosis-related biomarkers and POD incidence.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis prospective observational study enrolled patients undergoing cardiac valve replacement. Serum levels of copper ion (Cu\u0026sup2;⁺), ferredoxin 1 (FDX1), and lipoic acid (LA) were measured at four time points: before anesthesia induction (T1), at cardiopulmonary bypass (CPB) initiation (T2), at CPB cessation (T3), and immediately after surgery (T4). POD was assessed twice daily from postoperative days 1 to 7 using the Richmond Agitation-Sedation Scale (RASS) and the Confusion Assessment Method for the ICU (CAM-ICU). Propensity score matching (PSM) was applied to compare POD and non-POD groups in a 1:1 ratio.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAmong 126 analyzed patients, 58 (46.0%) developed POD. After PSM (34 pairs), FDX1 levels at T4 were significantly higher in the POD group (18.6 vs. 14.9 ng/mL, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while LA levels were lower at T1, T2, and T4 (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Multivariate analysis showed that each unit increase in FDX1 change (ΔT4\u0026ndash;T1) and LA change during CPB (ΔT3\u0026ndash;T2) was associated with a 70% (OR\u0026thinsp;=\u0026thinsp;1.7, P\u0026thinsp;=\u0026thinsp;0.018) and 60% (OR\u0026thinsp;=\u0026thinsp;1.6, P\u0026thinsp;=\u0026thinsp;0.044) increase in POD risk, respectively.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003ePerioperative increases in FDX1 and decreases in LA are independently associated with higher POD risk, suggesting that cuproptosis-related pathways may represent potential mechanisms and therapeutic targets for POD.\u003c/p\u003e\u003ch2\u003eTrial registration\u003c/h2\u003e\u003cp\u003eChinese Clinical Trial Registry, ChiCTR2400088024. Registered on August 9, 2024.\u003c/p\u003e","manuscriptTitle":"Correlation between cuproptosis-related proteins and postoperative delirium in cardiac valve replacement: a prospective, observational study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-29 12:08:45","doi":"10.21203/rs.3.rs-7608169/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5de17f66-ce48-495e-aa7c-2f930c4d5ec1","owner":[],"postedDate":"October 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-14T13:08:42+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-29 12:08:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7608169","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7608169","identity":"rs-7608169","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}