Paediatric Delirium After Cardiac Surgery:Prevalence and Predictive Risk Factor Analysis

Paediatric Delirium After Cardiac Surgery:Prevalence and Predictive Risk Factor Analysis | 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 Article Paediatric Delirium After Cardiac Surgery:Prevalence and Predictive Risk Factor Analysis Sophia Schumann, Gerhard Schön, Ida Hüners, Daniel Biermann, Lena Christine Siebel, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6214736/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Jun, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract With increasing focus on neurodevelopment in children with congenital heart disease (CHD), early predictive markers are crucial to intervene and improve neurodevelopmental outcome. As postoperative delirium (PD) is known to have a long-term impact on neurocognitive function in adults, investigations into the prevalence and identification of modifiable risk factors of PD offer new perspectives. We conducted a retrospective, single-centre study screening for PD using the Cornell Assessment of Pediatric Delirium (CAPD). We distinguished it from the iatrogenic withdrawal syndrome (IWS) using the withdrawal assessment tool 1 (WAT-1). An explorative, multivariate regression analysis included various pre-, intra-, and postoperative variables. With screening compliance of 95% in 311 patients, PD prevalence was 40.2%, and 46.4% developed IWS. Infants were at highest risk for PD (OR 2.9, p = 0.05). Prolonged mechanical ventilation > 100hours (OR 7.4, p = 0.003), infusion therapy with ketamine (OR 3.3, p = 0.009), IWS (mild: OR 7.7, p = < 0.001, severe: OR 17.0, p = < 0.001) and low cardiac output syndrome (LCOS) (OR 3.9, p = 0.02) were significant predictive risk factors for PD. Overall, PD and IWS are highly prevalent in paediatric cardiac intensive care unit (pCICU), especially in infants and children with prolonged ventilation duration, demand for multiple sedatives, and LCOS as a newly described risk factor. Health sciences/Medical research/Paediatric research Health sciences/Diseases/Cardiovascular diseases/Congenital heart defects Health sciences/Diseases/Neurological disorders/Disorders of consciousness Paediatric Delirium Cornell Assessment of Pediatric Delirium (CAPD) Neurodevelopment Congenital Heart Disease (CHD) Iatrogenic Withdrawal Syndrome (IWS) Paediatric Cardiac Intensive Care Unit (pCICU) Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Congenital heart disease (CHD) remains the most common form of birth defect worldwide, with a prevalence of 18 per 1000 live births, and is responsible for 4% of neonatal deaths 1 . Fortunately, mortality has been significantly reduced in recent decades 2 . Therefore, investigation on morbidity and long-term outcomes such as neurodevelopment come into focus. While one-third of children who undergo cardiac surgery for CHD suffer from developmental delays that involve either one or combined areas of motor, language, or cognitive skills 3 , the degree of impairment is linked to the severity of CHD 4 . Furthermore, each postoperative day a child spends in the paediatric cardiac intensive care unit (pCICU) equates to losing one point in the intelligence quotient 5 . At the same time, pCICU length of stay, in particular, negatively correlates with the development of motor skills 6 . Besides neurodevelopmental outcomes, psychological disorders of children after cardiac surgery, such as anxiety, posttraumatic disorders, or depression, are frequent and affect the quality of life (QoL) of patients as well as their families to a variable degree 7 , 8 . While two-thirds of the patients do not suffer from neurological impairment, the key question is how to identify those who will have neurodevelopmental delays later on as early as possible so that patients and families can be supported. While there are established assessment tools for infants and toddlers, such as the Bayley Scales of Infant Development, the link to early predictors of developmental delay remains under evaluation, as the use of postoperative neuromonitoring as a possible predictive tool is very heterogeneous, according to an extensive European survey 9 . In some studies, pre- and postoperative neuroimaging is used to identify complications such as stroke, white matter injury, or reduction in brain volume in CHD patients and correlate these findings to neurodevelopment 10 – 12 . Biomarkers indicating neurological damage, such as glial fibrillary acidic protein, which rises during and after bypass surgery, in children 13 , seem to be a promising component to predict neurodevelopment 14 . Another not thoroughly investigated perspective towards a link to neurodevelopment is the data from the perioperative course of children undergoing cardiac surgery. While technical appliances of neuromonitoring such as near-infrared spectroscopy (NIRS) and amplitude-integrated electroencephalograms (aEEG) are more and more frequently used in pCICUs and being correlated to neurodevelopmental outcomes 15 , 16 , simply assessing the postoperative clinical presentation of neuropsychological dysfunction might be another key component. In particular, these scoring tools are comparably cost-effective and do not need structural requirements such as neuroimaging or laboratory testing. Screening for paediatric delirium (PD), even in neonates and infants, who represent the vast majority of pCICU patients, has recently become possible with the development of the Cornell assessment of pediatric delirium (CAPD) 17 . CAPD is in excellent concordance with the Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5) criteria 18 and has been validated for the German language 19 . International guidelines recommend its use 20 , 21 . Nevertheless, in an extensive survey, only 44% of centres have implemented regular delirium screening in paediatric ICUs (PICUs) 22 . Delirium is defined as a neuropsychiatric disorder and is associated with disturbances of consciousness and attention, alteration of perception, disorganised thinking, acute onset, and fluctuating course. The pathophysiology of delirium has not been yet fully understood. Hypotheses are based on an imbalance of the neurotransmitters in the central nervous system (CNS) and a dysfunction of neuronal networks. Contributing factors are the presence of a neuroinflammatory component 23 , 24 , whereas proinflammatory cytokines lead to an increased permeability of the blood-brain barrier (BBB) 25 , thus increasing the vulnerability of the CNS, resulting in the so-called “failure of the system integration hypothesis” 26 . Various risk factors for delirium have been described in the elderly population, such as infection, drug withdrawal, endocrine disorders, trauma, CNS pathology, hypoxia, vitamin deficiencies, acute vascular disorders, medications, and heavy metal exposure 27 . Many of these risk factors apply to CHD patients, in particular to their perioperative course, implicating a high-risk profile to develop delirium in this cohort. Postoperative delirium in adults is generally associated with an unfavourable outcome and occurs with a high prevalence in the intensive care unit, especially after major or cardiac surgery 28 , 29 . Meta-analyses have demonstrated that postoperative delirium goes along with neurological impairment as well as psychological disorders 28 , 30 – 32 . Since the development of the CAPD, studies have emerged to evaluate the prevalence of PD in different paediatric intensive care settings. A one-day, multipoint-prevalence study on twenty-seven pCICUs and PICUs demonstrated a prevalence of 40% 33 . These results are conclusive, with a pooled prevalence in a recent review 34 . The highest risk occurs in paediatric patients treated with extracorporeal membrane oxygenation (ECMO) 35 . Nevertheless, prevalence is highly variable between different monocentric studies, ranging from 25% to almost 68% 36–39 , most likely due to different treatment variables between the centres implicating the possibility of jet unknown modifiable risk factors. To date, only patient age and duration of mechanical ventilation have been identified as definite s risk factors for PD. At the same time, developmental delay, cyanotic heart disease, cardiopulmonary bypass time (CPBT), and elevated pain scores are likely to be associated with PD 34 . The high prevalence of delirium in the postoperative paediatric population and long-term results in the adult population implicate that PD might either be causal for developmental delay in CHD patients or at least be a surrogate parameter for perioperative neurological damage and may act as an early predictor for impaired neurodevelopment. Methods To evaluate PD prevalence and potential risk factors in our cohort, we conducted a monocentric retrospective observational cohort study over 15 months from March 2023 to June 2024. All children from birth to 18 years were included that were being treated in the pCICU after cardiac surgery with or without cardiopulmonary bypass. Exclusion criteria include ICU admission for minor procedures such as central venous catheter (CVC) or pleural drain placement with short-acting sedation or admission for non-post-cardiac-surgery conditions. The study adhered to the Helsinki Declaration and due to the retrospective nature of the study, the Hamburg Medical Association Ethics Committee waived the need of obtaining informed consent (waiver 2023-300407-WF). Sample Size Calculation The study's primary endpoint was to estimate the prevalence of PD using the CAPD screening tool. A 95% confidence interval not greater than ± 6% was considered clinically relevant. We assumed the prevalence to be between 40% and 50%. To comply with this confidence interval, 40% prevalence would require n = 271 cases, and for 50% prevalence, n = 281 cases would be required. We planned conservatively and decided on n = 281 cases, which must be available for evaluation. With an assumed dropout of 2%, n = 287 people must therefore be included in the study. Patients’ Characteristics The authors’ pCICU is located within a large tertiary centre with a variety of treated cardiac malformations, ranging from simple up to complex univentricular heart defects with the possibility for veno-arterial (VA)- and veno-venous (VV)-ECMO treatment when needed. Since the introduction of fast-track protocols 40 in our centre in 2018, more than half of all patients have either been extubated in the theatre or on the same day of surgery in the pCICU. Nearly all postoperative patients are first-line sedated with dexmedetomidine (0.5–1.4µg/kg/h), while additional continuous sedation with ketamine or midazolam is avoided whenever possible according to guideline recommendation. Muscle relaxation (rocuronium 0.6-1.0mg/kg/h) is only used in cases of high ventilation settings to prevent barotrauma. First-line analgetic treatment in our centre is either by single dose opioids (morphine or piritramide 0.1mg/kg/dose) when the patient is extubated or remifentanil infusion (0.05-2.0µg/kg/min) when short time ventilation is expected. In challenging treatment courses due to increasing tolerance, drug cycling to morphine (30–100µg/kg/h) or sufentanil (0.3–1.3µg/kg/h) perfusion becomes necessary. Weaning protocols after prolonged sedation and opioid exposure are standardised and guided by scoring for patient comfort (COMFORT behaviour (COMFORT-B)) and withdrawal (withdrawal assessment tool 1 (WAT-1)). Patient Assessment for Pain, Iatrogenic Withdrawal Syndrome and Postoperative Delirium PD was screened using the CAPD and differentiated from symptoms of iatrogenic withdrawal syndrome (IWS) using the WAT-1 41 only when patients were awake, as classified by a Richmond agitation and sedation score (RASS) 42 of ≥ -2. Comfort and pain were assessed using the COMFORT-B scale. All scores were performed eight hourly by pCICU nurses and doctors. The CAPD is structured around the DSM-5 criteria and includes eight questions scored from 0 to 4 points, yielding a total score of 0 to 32 points, with delirium indicated by a score of ≥ 9. To address staff variability in recognising delirium in pCICU patients, “development anchor points” were established for children up to 2 years, outlining normal versus atypical behaviours by age 19 . The WAT-1 score includes 11 questions, scored from 0–2 points with a total score of 12 points. We divided the score into ≥ 3 points, indicating mild and ≥ 7 points as severe IWS. COMFORT-B comprises six questions, scoring from 0–5 points, with a total score of 30 points. A range between 11–22 points is considered an adequate sedation and pain treatment, while 22 points under-sedated patient 43 . Data Collection Data was extracted from the electronic medical record (EMR) Integrated Care Management (ICM, version 13.02 by Drägerwerk AG&Co. KGaA) using the software ICMiq (version 1.5.0, by Drägerwerk AG&Co. KGaA). Before analysis, a trustee pseudonymised all records, which the Data Integration Centre then provided. Besides RASS, CAPD, WAT-1, and COMFORT-B, perioperative risk factors related to postoperative delirium were determined after an extensive literature review, including known factors in the paediatric and elderly population. Baseline characteristics included patient age at the point of surgery divided into four groups: 1) neonates (0–1 month), 2) infants (1–12 months), 3) toddlers (1–6 years), and 4) school children/adolescents (7–18 years), risk stratification of type of surgery defined as per Risk Adjustment for Congenital Heart Surgery (RACHS-1) score 44 or univentricular physiology. Intraoperative data collected was time on cardiopulmonary bypass, divided into intervals of 30 minutes. Data on postoperative variables was obtained up to the point when the child presented with signs of delirium, as stated above. Postoperative variables included eight variables: 1) hypoxia (transcutaneous saturation (SaO2) of 250mg/dl in blood gas analysis (BGA)), 3) lactatemia (> 2mmol/l over six consecutive hours in BGA), 4) postoperative fever (> 38.5°C for more than three consecutive hours) 5) signs of postoperative infection (postoperative fever and secondary rise in c-reactive protein (CrP) not due to second surgery and/or pathologic microbiological finding in blood, tracheal or urinary samples and/or restart of antibiotic treatment due to clinical presentation of infection), 6) postoperative use of hydrocortisone to enhance inotropic effect and stabilise hemodynamics due to signs of systemic inflammatory response syndrome (SIRS) and 8) time on ventilation divided into four groups: i) on table extubation (OTE), ii) fast track (0–10 hours (h), iii) short term ventilation (> 10-100h) and iv) long term ventilation. For subgroup analysis, patient data was obtained for patients that remained ventilated on pCICU (ventilation groups 2–4) concerning the COMFORT-B scale and use of three different sedative infusions: 1) dexmedetomidine, 2) ketamine, and 3) midazolam. To differentiate between lactatemia type A, defined as resulting from inadequate delivery of oxygen and tissue hypoxia, and type B from metabolic uncoupling after bypass, 45 , 46 data for subgroup analysis was extracted, including: 1) arterio-venous difference in O 2 -concentration (avDO2) > 40% and 2) difference of central to peripheral temperature (ΔT) > 4°C. Statistical Analysis Throughout this article, we have used parametric statistics measures, such as arithmetic mean and standard deviation or categorical variables, frequencies, and proportions. The p-values in the descriptive statistics are based on t-tests or Chi²-tests. For multivariate modelling, we calculated logistic regression models and reported the odds ratio, the confidence interval of the odds ratio, and the p-values. All calculations and figures were made using the statistical program R (version 4.4.1, by the R Foundation for Statistical Computing, Vienna, Austria) 47 . Results In the period from March 2023 to June 2024, a total of 387 patients were treated for surgical and medical conditions in pCICU. After excluding patients treated for medical conditions and short-term procedures, 311 patients treated after heart surgery with or without CPB remained. With a compliance rate of 94.2%, CAPD and WAT-1 were performed in 293 of these 311 patients (Table 1 ). Delirium occurred in 118 (40.2%), IWS occurred in 136 (46.4%) cases, whereas 109 had mild and 27 had severe symptoms of IWS. The average duration of delirium was 53 hours, with the majority of cases presenting directly after extubation but also later on, partially with a fluctuating course, as demonstrated in the box plot in Fig. 1 . In multivariate regression analysis of 293 patients (Fig. 2 ), when controlling for age, school children and adolescents had the lowest delirium rates (OR 0.3, p = 0.1), and infants had the highest delirium rates (OR 2.9, p = 0.05) when compared to neonates. RACHS-1 (OR 1.0, p = 0.8) and CPBT (OR 0.9, p = 0.4) did not correlate with delirium with a narrow confidence interval and a precise effect size. The presence of IWS was a robust predictor for PD, categorised as mild IWS (OR 7.7, p = < 0.001) and severe IWS (OR 17.0, p = < 0.001). Delirium rates increased with length of ventilation compared to OTE, particularly for long-term ventilated children (OR 7.4, p = 0.003). Patients who had an elevated lactate level for a consecutive time of more than 6 hours had substantially higher delirium rates (OR 2.7, p = 0.05). No trend was identified for hypoxic or univentricular patients. Metabolic derailment, postoperative fever, signs of infection, and the postoperative use of hydrocortisone did not predict delirium. A total of 187 patients remained ventilated after transfer to pCICU. COMFORT-B scores were performed every shift (8 hours). Because the fast-track protocol was carried out for some of these patient before scoring, only 154 patients had a COMFORT-B score before extubation. As demonstrated in Fig. 3 , all patients that remained ventilated with a low COMFORT-B score < 11 had a lower delirium rate after extubation (OR 0.4, p = 0.08) compared to patients with a COMFORT-B score 11–22. Nearly all postoperative patients received dexmedetomidine infusion in our centre, even if extubated in the operating room, to modulate pain perception and reduce the need for opioids. If the patient required additional sedation to achieve an adequate sedation level (COMFORT-B 11–22) and remained tube-tolerant, ketamine or midazolam was added as an infusion therapy if a single bolus therapy was not sufficient. Figure 4 demonstrates that escalating to ketamine infusion therapy significantly increases delirium rates (OR 3.3, p = 0.009). This is also the case for escalation to midazolam infusion therapy, though the increase is insignificant (OR 2.84, p = 0.07). Due to the substantial correlation between postoperative lactatemia and delirium (Fig. 2 ), we conducted a subgroup analysis of all 83 patients with consecutive lactatemia over more than six hours (Fig. 5 ) to distinguish whether the elevated lactate was attributable to low cardiac output (LCO) (lactate acidosis type A) or to metabolic derailment (lactate acidosis type B). Patients with signs of low cardiac output (n = 19), defined as lactatemia for more than 6 hours, AVDO2 > 40%, and a core-to-peripheral temperature gradient of > 4°C, had a significantly higher delirium rate (OR 3.9, p = 0.02) than patients with metabolic decoupling, defined as lactatemia and a blood glucose level > 250mg/l. Discussion With a CAPD implementation rate approaching 95%, we determined a well-founded prevalence of delirium of 40.2 % . This corresponds with a pooled prevalence in pCICUs of 39% 34 and a prevalence of 40% in the only multicentre study to date 33 . According to a systematic review, the pooled prevalence in pCICUs, 53% (four studies), is higher than in PICUs (23%, 17 studies) 48 . Patients Age and Duration of Mechanical Ventilation Predicts Delirium In our study, infants had the highest (OR 2.9, p = 0.05), and young children/adolescents had the lowest risk (OR 0.3, p = 0.11) of developing PD. This is consistent with previous studies that identified children younger than 2 years 37 or less than 1 year 36 to have a significantly higher risk of developing PD. Our study confirms that mechanical ventilation duration is associated with increased rates of PD and a significantly increased risk in those with more than 100 hours of ventilation (OR 7.3, p = 0.003). These results are consistent with the current literature 33 , 37 , 49 and most likely reflect the cumulative effects of various variables contributing to a longer ventilation time. Of note is that compared to patients with OTE, even patients on fast-track protocols (0–10 hours, OR 2.0, p = 0.12) or ventilated for 10–100 hours (OR 2.4, p = 0.06) had a substantially higher risk of developing PD. This might reflect the benefits of the differences in pain and sedation management by anaesthetists in theatres compared to management in pCICU, and further evaluation is needed. Overall, this outlines the importance of OTE, which, in our experience, is not pursued in all cases possible due to logistical issues in theatres. Severity of Cardiac Surgery and Time of Cardiopulmonary Bypass Does Not Predict Delirium in Our Cohort Inconclusive with other studies, RACHS-1 did not predict PD in our cohort. While Patel et al. found a significant difference in delirium prevalence between RACHS-1 groups 1 and 2 compared to groups 3 and 4 37 , our study shows no correlation (OR 1.0 p = 0.82, CI of 0.73 to 1.48). Köditz et al. did also not find a correlation between RACHS-1 and CAPD, but the vast majority either had a RACHS-1 score of 2 or 3 50 , so the comparison might not be feasible. Alvarez et al. did not use the RACHS-1 score to assess surgical complexity in their study, but the alternative STS-EACTS (Society of Thoracic Surgeons and European Association for Cardio-Thoracic Surgery) scale, which showed a significant correlation with delirium 36 . Mao et al., on the other hand, focused on the general severity of illness and used the PRISM (Pediatric Risk of Mortality) III score, which also found a significant association with delirium 49 . Compared to Alvarez et al. 36 , CPBT per 30-minute interval did not predict delirium in our cohort (OR 0.94, CI 0.79–1.12, p = 0.46). The multicentre study by Staveski et al. 33 and the final multivariate analysis by Mao et al. 49 did also not demonstrate a significant correlation. Further research is needed to analyse the details of perfusion and surgical techniques regarding the prevalence of delirium. The current literature's inconsistency may indicate further, possibly modifiable risk factors. Sedation Strategy and Patient Comfort Impact Delirium, While the Presence of Iatrogenic Withdrawal Syndrome is the Strongest Predictor for Delirium A comfort scale of less than 11, usually classifying patients as over-sedated 43 , was protective for delirium (OR 0.49, p 0.08). However, the COMFORT-B Score comprises several aspects. On one hand, it recognises pain, which has been identified as a possible link to delirium 51 . Consequently, children with high potent analgetic on short-term sedation have a significantly lower rate of delirium 52 . On the other hand, oversedation, measured by EEG during anaesthesia for paediatric cardiac surgery, was shown to promote delirium 50 . Continuous EEG Monitoring was not implemented in our pCICU during the study period. So no further information can be provided. Assuming that a COMFORT-B < 11 points does not necessarily equate to a complete suppression pattern in EEG monitoring, there may be optimal sedation and analgetic depth to reduce delirium rates that are below the standard range COMFORT-B scale of 11–22 points, but still far from postoperative EEG suppression pattern. Further research is needed to evaluate this relationship. Of note, CAPD scoring was only performed during the pCICU stay. Therefore, due to individual pharmacokinetics, patients with a comfort score < 11, while intubated, might have developed delirium after transfer from pCICU, as fluctuating and late-onset delirium courses were observed during pCICU stay (Fig. 1 ). As to guidelines recommendation, we used a standardised protocol of single-dose opioids and dexmedetomidine infusion and only used ketamine and midazolam infusion as second- and third-line treatments. Nevertheless, long-time ventilation and increasing drug tolerance sometimes require an escalation. Benzodiazepine exposure is a known risk factor for delirium in the adult population 53 and for pCICU patients 36 . The subgroup analysis for ventilated patients demonstrated a favourable delirium rate if dexmedetomidine was the only sedative used compared to a combination with ketamine (OR 3,3 p = 0.009) or midazolam infusion (OR 2.84, p = 0.07). These findings are conclusive with data from postoperative children with congenital heart disease and pulmonary hypertension (PAH) 54 as well as in large randomised trials in the adult population 55 . Without scoring tools, IWS can be misinterpreted as delirium, although the two syndromes significantly differ in aetiology and symptoms. Current international guidelines suggest clinical evaluation should include IWS and delirium scoring 20 . Our study also emphasises this differentiation. In our study, IWS was identified with high statistical significance (mild IWS OR 7.7, p = < 0.001 and severe IWS OR 17.0, p = < 0.001) as a predictive factor for the occurrence of postoperative delirium. To date, these results have only been described in the multicentre 1-day study by Staveski et al.. WAT-1 levels at the time of diagnosing delirium were significantly higher, and the patient had a higher WAT-1 Score twenty-four hours before diagnosing delirium 33 . A methodological limitation lies in the overlap of the diagnostic question “Is the child restless?” within the two scoring questionnaires, WAT-1 and CAPD. This question, which occurs in both scores, could lead to diagnostic overlap and, thus, a potential distortion of the differential diagnosis between IWS and delirium. However, since withdrawal is a well-known risk factor in the elderly population 27 , the predictive value remains evident from our point of view. These results might lead to new preventive approaches. Using more potent analgetics during ventilation to reduce pain and optimising weaning protocols to prevent IWS might be key components. Minimising the use of midazolam or ketamine should play an important role, and further development of fast-track protocols in anaesthesia and intensive care could further reduce delirium rates in children after cardiac surgery. Postoperative Low Cardiac Output but not Hypoxia Predicts Delirium Although lactate was not identified as a significant risk factor in multivariate analysis (OR 2.7, p = 0.05), and this variable was not investigated in previous studies in the pCICU cohorts, data in the adult population demonstrated a significant correlation between lactatemia and postoperative delirium 56 . The origins of lactatemia were differentiated 57 using additional signs of low cardiac output syndrome (LCOS), such as AvDO2 > 40% and core to peripheral temperature difference > 4°C to circumscribe the LCOS definition. We found LCOS (Hyperlactatemia type A) but not metabolic uncoupling (Hyperlactatemia type B) to be a significant predictor of postoperative delirium after cardiac surgery (OR 3.9, p = 0.02). Mao et al. found secondary thoracic closure to be predictive of delirium 49 . Oftentimes, delayed sternal closure is due to a certain state of LCOS, which points out a possible correlation. While prolonged hypoxia or univentricular physiology were not significant predictors in our multivariate analysis, Liu et al. demonstrated a preventive effect for delirium by optimising regional cerebral oxygen saturation 58 . Real-time NIRS monitoring is available for all our patients. Still, due to technical compatibilities, it is not documented in sufficient detail in the EMR, and thus, this effect cannot be demonstrated in our analysis. Fever, Infection, and Use of Steroids Seem Not to Predict Delirium In contrast to a previous study by Meyburg et al. in a PCCU cohort 59 in our study, postoperative fever and infections were no significant risk factors for the occurrence of delirium. However, antipyretic pain medication (paracetamol and metamizole) is administered per standard protocol six hourly for every patient in our cohort. Active temperature control systems are used for patients with signs of LCOS, and in 1/3 of all patients, postoperative hydrocortisone is administered. Therefore, our data is likely not consistent enough to answer the question of how the immune system influences the occurrence of postoperative delirium. Generally, the role of neuroinflammation has been described in the literature 23 , 24 . Further research is needed to characterise better the influence of neuroinflammatory processes on the development of delirium in the context of postoperative care in this specific patient population. Study Strengths and Limitations With 311 patients and a compliance of nearly 95%, we recorded an accurate result of the prevalence in our cohort and, therefore, a detailed risk factor analysis. Compared to previous studies, an evaluation every 8 hours is more precise in detecting fluctuating forms of delirium. Nevertheless, there are some limitations. As a single-centre observational cohort study, our data cannot be widely generalised, and no causality can be drawn from it. We did not determine delirium subtypes (hypo-, hyperactive or mixed). CAPD and WAT-1 scoring were not continued after transfer from pCICU, so there might have been a number of missed cases due to late appearance. In addition, children with a positive delirium score were treated immediately for ethical reasons (environmental modifications and, in rare cases, use of antipsychotic medication), which could potentially have influenced the course and duration of the delirium. While a number of predictive risk factors were identified in our study, there are certainly other, jet unknown postoperative and intraoperative risk factors that were not recorded in our analysis and may play a role in delirium. These limitations emphasise the need for further studies. Conclusion PD and IWS have a high prevalence after paediatric cardiac surgery, and screening should be part of standard care. While non-modifiable risk factors such as patient’s age play an important role in risk stratification, possibly modifiable risk factors such as duration of mechanical ventilation emphasise the further development of fast-track protocols. While patients with LCOS have an increased risk, neuromonitoring should aim to optimise for cerebral tissue perfusion. Especially IWS, as a powerful predictor for delirium, demands not only well-considered sedation and pain management, avoiding ketamine and benzodiazepine use, but also sophisticated weaning protocols. Overall, further research is needed to determine the predictive value of postoperative delirium in neurodevelopment, as infants have the highest prevalence, and data in the adult population is predictive. Declarations Data availability The dataset used and/or analysed during the present study is available from the corresponding author upon reasonable request. Authors Contributions S.S. and S.H.H. designed the study and carried out the sample collection, G.S. performed the data analysis, S.S., S.H.H., I.H. and D.B. wrote and reviewed the manuscript, L.C.S., I.H., F.J., U.G., C.G.-N., J.De., J.Dr., D.B., S.D., M.H., R.K-F. supported the clinical aspect in sample collection. All authors read and approved the final manuscript. References Wu, W. L., He, J. X. & Shao, X. B. Incidence and mortality trend of congenital heart disease at the global, regional, and national level, 1990-2017. Medicine 99 (2020). https://doi.org:10.1097/MD.0000000000020593 Liu, Y. J. et al. 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Association of intraoperative circulating-brain injury biomarker and neurodevelopmental outcomes at 1 year among neonates who have undergone cardiac surgery. J Thorac Cardiov Sur 157 , 1996-2002 (2019). https://doi.org:10.1016/j.jtcvs.2019.01.040 Latal, B., Wohlrab, G., Brotschi, B., Beck, I., Knirsch, W. & Bernet, V. Postoperative Amplitude-Integrated Electroencephalography Predicts Four-Year Neurodevelopmental Outcome in Children with Complex Congenital Heart Disease. J Pediatr 178 , 55-60.e51 (2016). https://doi.org:10.1016/j.jpeds.2016.06.050 Simons, J., Sood, E. D., Derby, C. D. & Pizarro, C. Predictive value of near-infrared spectroscopy on neurodevelopmental outcome after surgery for congenital heart disease in infancy. J Thorac Cardiovasc Surg 143 , 118-125 (2012). https://doi.org:10.1016/j.jtcvs.2011.09.007 Traube, C. et al. Cornell Assessment of Pediatric Delirium: A Valid, Rapid, Observational Tool for Screening Delirium in the PICU. Crit Care Med 42 , 656-663 (2014). https://doi.org:10.1097/CCM.0b013e3182a66b76 Silver, G. et al. Detecting pediatric delirium: development of a rapid observational assessment tool. Intens Care Med 38 , 1025-1031 (2012). https://doi.org:10.1007/s00134-012-2518-z Dill, M. L. v. H. R. T., C.; , Silver G.; Meyburg, J. Diagnosis of delirium in pediatric intensive care patients.Prospective study to establish the German version of the CAPD. Monatszeitschrift Kinderheilkunde 164 , 308-317 (2016). Smith, H. A. B. et al. 2022 Society of Critical Care Medicine Clinical Practice Guidelines on Prevention and Management of Pain, Agitation, Neuromuscular Blockade, and Delirium in Critically Ill Pediatric Patients With Consideration of the ICU Environment and Early Mobility. Pediatr Crit Care Me 23 , E74-E110 (2022). https://doi.org:10.1097/Pcc.0000000000002873 Harris, J. et al. Clinical recommendations for pain, sedation, withdrawal and delirium assessment in critically ill infants and children: an ESPNIC position statement for healthcare professionals. Intens Care Med 42 , 972-986 (2016). https://doi.org:10.1007/s00134-016-4344-1 Ista, E. et al. ABCDEF Bundle Practices for Critically Ill Children: An International Survey of 161 PICUs in 18 Countries*. Crit Care Med 50 , 114-125 (2022). https://doi.org:10.1097/Ccm.0000000000005168 O'Neal, J. B. & Shaw, A. D. Predicting, preventing, and identifying delirium after cardiac surgery. Perioper Med (Lond) 5 , 7 (2016). https://doi.org:10.1186/s13741-016-0032-5 Peng, L., Xu, L. & Ouyang, W. Role of peripheral inflammatory markers in postoperative cognitive dysfunction (POCD): a meta-analysis. PLoS One 8 , e79624 (2013). https://doi.org:10.1371/journal.pone.0079624 Taylor, J. et al. Postoperative delirium and changes in the blood-brain barrier, neuroinflammation, and cerebrospinal fluid lactate: a prospective cohort study. Br J Anaesth 129 , 219-230 (2022). https://doi.org:10.1016/j.bja.2022.01.005 Maldonado, J. R. Delirium pathophysiology: An updated hypothesis of the etiology of acute brain failure. Int J Geriatr Psychiatry 33 , 1428-1457 (2018). https://doi.org:10.1002/gps.4823 Gower, L. E., Gatewood, M. O. & Kang, C. S. Emergency department management of delirium in the elderly. West J Emerg Med 13 , 194-201 (2012). https://doi.org:10.5811/westjem.2011.10.6654 Saczynski, J. S. et al. Cognitive trajectories after postoperative delirium. N Engl J Med 367 , 30-39 (2012). https://doi.org:10.1056/NEJMoa1112923 Janssen, T. L. et al. Risk factors for postoperative delirium after elective major abdominal surgery in elderly patients: A cohort study. Int J Surg 71 , 29-35 (2019). https://doi.org:10.1016/j.ijsu.2019.09.011 Goldberg, T. E. et al. Association of Delirium With Long-term Cognitive Decline: A Meta-analysis. JAMA Neurology 77 , 1373-1381 (2020). https://doi.org:10.1001/jamaneurol.2020.2273 Tsui, A. et al. The effect of baseline cognition and delirium on long-term cognitive impairment and mortality: a prospective population-based study. Lancet Health Longev 3 , E232-E241 (2022). https://doi.org:10.1016/S2666-7568(22)00013-7 Drews, T. et al. Postoperative delirium is an independent risk factor for posttraumatic stress disorder in the elderly patient: a prospective observational study. Eur J Anaesthesiol 32 , 147-151 (2015). https://doi.org:10.1097/eja.0000000000000107 Staveski, S. L. et al. Prevalence of ICU Delirium in Postoperative Pediatric Cardiac Surgery Patients. Pediatr Crit Care Me 22 , 68-78 (2021). https://doi.org:10.1097/Pcc.0000000000002591 Fu, M. L. et al. Risk factors and incidence of postoperative delirium after cardiac surgery in children: a systematic review and meta-analysis. Italian Journal of Pediatrics 50 (2024). https://doi.org:10.1186/s13052-024-01603-2 Patel, A. K., Biagas, K. V., Clark, E. C. & Traube, C. Delirium in the Pediatric Cardiac Extracorporeal Membrane Oxygenation Patient Population: A Case Series. Pediatr Crit Care Me 18 , E621-E624 (2017). https://doi.org:10.1097/Pcc.0000000000001364 Alvarez, R. V. et al. Delirium is a Common and Early Finding in Patients in the Pediatric Cardiac Intensive Care Unit. J Pediatr-Us 195 , 206-212 (2018). https://doi.org:10.1016/j.jpeds.2017.11.064 Patel, A. K. et al. Delirium in Children After Cardiac Bypass Surgery. Pediatr Crit Care Me 18 , 165-171 (2017). https://doi.org:10.1097/Pcc.0000000000001032 Semple, D., Howlett, M. M., Strawbridge, J. D., Breatnach, C. & Hayden, J. C. A Systematic Review and Pooled Prevalence of Delirium in Critically Ill Children*. Crit Care Med 50 , 317-328 (2022). https://doi.org:10.1097/Ccm.0000000000005260 Michel, J., Schepan, E., Hofbeck, M., Engel, J., Simma, A. & Neunhoeffer, F. Implementation of a Delirium Bundle for Pediatric Intensive Care Patients. Frontiers in Pediatrics 10 (2022). https://doi.org:10.3389/fped.2022.826259 Howard, F., Brown, K. L., Garside, V., Walker, I. & Elliott, M. J. Fast-track paediatric cardiac surgery: the feasibility and benefits of a protocol for uncomplicated cases. Eur J Cardiothorac Surg 37 , 193-196 (2010). https://doi.org:10.1016/j.ejcts.2009.06.039 Franck, L. S., Scoppettuolo, L. A., Wypij, D. & Curley, M. A. Q. Validity and generalizability of the Withdrawal Assessment Tool-1 (WAT-1) for monitoring iatrogenic withdrawal syndrome in pediatric patients. Pain 153 , 142-148 (2012). https://doi.org:10.1016/j.pain.2011.10.003 Ely, E. W. et al. Monitoring sedation status over time in ICU patients - Reliability and validity of the Richmond Agitation-Sedation Scale (RASS). Jama-J Am Med Assoc 289 , 2983-2991 (2003). https://doi.org:10.1001/jama.289.22.2983 Ista, E., van Dijk, M., Tibboel, D. & de Hoog, M. Assessment of sedation levels in pediatric intensive care patients can be improved by using the COMFORT "behavior" scale. Pediatr Crit Care Med 6 , 58-63 (2005). https://doi.org:10.1097/01.Pcc.0000149318.40279.1a Jenkins, K. J. Risk adjustment for congenital heart surgery: the RACHS-1 method. Semin Thorac Cardiovasc Surg Pediatr Card Surg Annu 7 , 180-184 (2004). https://doi.org:10.1053/j.pcsu.2004.02.009 Palermo, R. A. et al. Metabolic Uncoupling Following Cardiopulmonary Bypass. Congenital Heart Disease 10 , E250-E257 (2015). https://doi.org:10.1111/chd.12285 Stephens, E. H., Epting, C. L., Backer, C. L. & Wald, E. L. Hyperlactatemia: An Update on Postoperative Lactate. World J Pediatr Cong 11 , 316-324 (2020). https://doi.org:10.1177/2150135120903977 R: A Language and Environment for Statistical Computing v. R version 4.4.1 (R Foundation for Statistical Computing. Vienna, Austria, 2024). Ista, E. et al. Factors Associated With Delirium in Children: A Systematic Review and Meta-Analysis. Pediatr Crit Care Med 24 , 372-381 (2023). https://doi.org:10.1097/pcc.0000000000003196 Mao, D., Fu, L. & Zhang, W. Risk Factors and Nomogram Model of Postoperative Delirium in Children with Congenital Heart Disease: A Single-Center Prospective Study. Pediatr Cardiol 45 , 68-80 (2024). https://doi.org:10.1007/s00246-023-03297-5 Köditz, H., Drouche, A., Dennhardt, N., Schmidt, M., Schultz, M. & Schultz, B. Depth of anesthesia, temperature, and postoperative delirium in children and adolescents undergoing cardiac surgery. Bmc Anesthesiol 23 , 148 (2023). https://doi.org:10.1186/s12871-023-02102-3 Fu, M. et al. Risk factors and incidence of postoperative delirium after cardiac surgery in children: a systematic review and meta-analysis. Ital J Pediatr 50 , 24 (2024). https://doi.org:10.1186/s13052-024-01603-2 Xu, N., Chen, Q., Huang, S. T., Sun, K. P. & Cao, H. Sufentanil Reduces Emergence Delirium in Children Undergoing Transthoracic Device Closure of VSD After Sevoflurane-Based Cardiac Anesthesia. Braz J Cardiov Surg 35 , 660-665 (2020). https://doi.org:10.21470/1678-9741-2019-0334 Pandharipande, P. P. et al. Effect of sedation with dexmedetomidine vs lorazepam on acute brain dysfunction in mechanically ventilated patients - The MENDS randomized controlled trial. Jama-J Am Med Assoc 298 , 2644-2653 (2007). https://doi.org:DOI 10.1001/jama.298.22.2644 Jiang, L. et al. A Retrospective Comparison of Dexmedetomidine Versus Midazolam for Pediatric Patients with Congenital Heart Disease Requiring Postoperative Sedation. Pediatric Cardiology 36 , 993-999 (2015). https://doi.org:10.1007/s00246-015-1110-z Riker, R. R. et al. Dexmedetomidine vs midazolam for sedation of critically ill patients: a randomized trial. Jama 301 , 489-499 (2009). https://doi.org:10.1001/jama.2009.56 Qian, X., Sheng, Y., Jiang, Y. & Xu, Y. Associations of serum lactate and lactate clearance with delirium in the early stage of ICU: a retrospective cohort study of the MIMIC-IV database. Front Neurol 15 , 1371827 (2024). https://doi.org:10.3389/fneur.2024.1371827 Palermo, R. A. et al. Metabolic Uncoupling Following Cardiopulmonary Bypass. Congenit Heart Dis 10 , E250-257 (2015). https://doi.org:10.1111/chd.12285 Liu, J. F., Zhou, S. J., Chen, X. H., Cao, H. & Chen, Q. Effect of Optimizing Regional Cerebral Oxygen Saturation during Infant Cardiac Surgery on the Incidence of Postoperative Delirium: A Retrospective Study. Ann Thorac Cardiovasc Surg 30 (2024). https://doi.org:10.5761/atcs.oa.23-00057 Meyburg, J. et al. Risk Factors for the Development of Postoperative Delirium in Pediatric Intensive Care Patients. Pediatr Crit Care Med 19 , e514-e521 (2018). https://doi.org:10.1097/pcc.0000000000001681 Table 1 Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.docx Cite Share Download PDF Status: Published Journal Publication published 20 Jun, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 28 Apr, 2025 Reviews received at journal 24 Apr, 2025 Reviews received at journal 20 Apr, 2025 Reviewers agreed at journal 11 Apr, 2025 Reviewers agreed at journal 24 Mar, 2025 Reviewers invited by journal 21 Mar, 2025 Editor assigned by journal 21 Mar, 2025 Editor invited by journal 21 Mar, 2025 Submission checks completed at journal 19 Mar, 2025 First submitted to journal 12 Mar, 2025 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. 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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-6214736","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":432053981,"identity":"ce184488-0e67-479b-9ad4-8a29ad75fbd6","order_by":0,"name":"Sophia Schumann","email":"","orcid":"","institution":"University Medical Center Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Sophia","middleName":"","lastName":"Schumann","suffix":""},{"id":432053982,"identity":"388b5050-b426-4f2b-9b78-c8d714f20473","order_by":1,"name":"Gerhard Schön","email":"","orcid":"","institution":"University Medical Center 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20:23:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6214736/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6214736/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-04927-z","type":"published","date":"2025-06-20T15:57:38+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79175378,"identity":"705839eb-6d54-40ce-bc44-693234bcb46c","added_by":"auto","created_at":"2025-03-25 09:54:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2777485,"visible":true,"origin":"","legend":"\u003cp\u003eDuration of delirium in all delirious patients (n =118). Patients screened positive for delirium when the CPAD score was ≥ 9 points for the first time (time of delirium hour 0). CAPD was performed as soon as the patient was awake (RASS ≥-2). CAPD: Cornell Assessment of Pediatric Delirium, RASS: Richmond Agitation and Sedation Scale.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6214736/v1/86f50dccf0983b7b7bd35384.png"},{"id":79175299,"identity":"eedce903-1130-4141-97f2-90965d78f43d","added_by":"auto","created_at":"2025-03-25 09:54:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5818770,"visible":true,"origin":"","legend":"\u003cp\u003eMultivariate logistic regression model predicting postoperative delirium in children after cardiac surgery with or without bypass (n =293). OR: Odds Ratio, CI: Confidence Interval, WAT-1: Withdrawal Assessment Tool 1, IWS: Iatrogenic Withdrawal Syndrome, OTE: On Table Extubation, RACHS-1: Risk Adjustment for Congenital Heart Surgery, CPBT: Cardiopulmonary Bypass Time.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6214736/v1/00f6dc76ff2abf13d762f265.png"},{"id":79175277,"identity":"94a5da43-018d-4735-acbe-a8eafc54a7ea","added_by":"auto","created_at":"2025-03-25 09:54:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1560933,"visible":true,"origin":"","legend":"\u003cp\u003eCOMFORT-B scores for patients that were transferred intubated to pCICU (n=154). The reference COMFORT-B 11-22 points indicates an adequate level of sedation while intubated. With less than 11 points, the patient is considered over-, with more than 22 points under-sedated. OR: Odds Ratio, CI: Confidence Interval\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6214736/v1/70308f40ff7cf99c8bcfa3d4.png"},{"id":79176611,"identity":"97ed0483-4d9e-41fd-96a4-236dc4ee4ca6","added_by":"auto","created_at":"2025-03-25 10:02:10","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1497044,"visible":true,"origin":"","legend":"\u003cp\u003eDifferent continuous infusion therapies predict delirium in children who remained ventilated after cardiac surgery (n=146). Dex: Dexmedetomidine, OR: Odds Ratio, CI: Confidence Interval\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6214736/v1/417063c068b68b3fc713f938.png"},{"id":79175273,"identity":"6abf3ccb-22e0-4e21-a3f3-6ae04b66bacf","added_by":"auto","created_at":"2025-03-25 09:54:09","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2013639,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup analysis of patients with different causality for postoperative lactatemia and delirium (n=83) OR: Odds Ratio, CI: Confidence Interval\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6214736/v1/5e316d9ef80bbb3ccc8cc783.png"},{"id":85231351,"identity":"42ed415a-954e-4019-a0e0-a54817705d71","added_by":"auto","created_at":"2025-06-23 16:06:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":14603020,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6214736/v1/0e06ff98-84df-4857-8aa6-5ee9ba7e95da.pdf"},{"id":79175309,"identity":"e78e515b-2da1-4787-82d5-2eda96d2639e","added_by":"auto","created_at":"2025-03-25 09:54:11","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":6593999,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6214736/v1/81aa7a4262c06c5319183847.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003ePaediatric Delirium After Cardiac Surgery:Prevalence and Predictive Risk Factor Analysis\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCongenital heart disease (CHD) remains the most common form of birth defect worldwide, with a prevalence of 18 per 1000 live births, and is responsible for 4% of neonatal deaths \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Fortunately, mortality has been significantly reduced in recent decades \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Therefore, investigation on morbidity and long-term outcomes such as neurodevelopment come into focus.\u003c/p\u003e \u003cp\u003eWhile one-third of children who undergo cardiac surgery for CHD suffer from developmental delays that involve either one or combined areas of motor, language, or cognitive skills \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, the degree of impairment is linked to the severity of CHD \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Furthermore, each postoperative day a child spends in the paediatric cardiac intensive care unit (pCICU) equates to losing one point in the intelligence quotient \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. At the same time, pCICU length of stay, in particular, negatively correlates with the development of motor skills \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBesides neurodevelopmental outcomes, psychological disorders of children after cardiac surgery, such as anxiety, posttraumatic disorders, or depression, are frequent and affect the quality of life (QoL) of patients as well as their families to a variable degree \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWhile two-thirds of the patients do not suffer from neurological impairment, the key question is how to identify those who will have neurodevelopmental delays later on as early as possible so that patients and families can be supported.\u003c/p\u003e \u003cp\u003eWhile there are established assessment tools for infants and toddlers, such as the Bayley Scales of Infant Development, the link to early predictors of developmental delay remains under evaluation, as the use of postoperative neuromonitoring as a possible predictive tool is very heterogeneous, according to an extensive European survey \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. In some studies, pre- and postoperative neuroimaging is used to identify complications such as stroke, white matter injury, or reduction in brain volume in CHD patients and correlate these findings to neurodevelopment \u003csup\u003e\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Biomarkers indicating neurological damage, such as glial fibrillary acidic protein, which rises during and after bypass surgery, in children \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, seem to be a promising component to predict neurodevelopment \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAnother not thoroughly investigated perspective towards a link to neurodevelopment is the data from the perioperative course of children undergoing cardiac surgery. While technical appliances of neuromonitoring such as near-infrared spectroscopy (NIRS) and amplitude-integrated electroencephalograms (aEEG) are more and more frequently used in pCICUs and being correlated to neurodevelopmental outcomes \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, simply assessing the postoperative clinical presentation of neuropsychological dysfunction might be another key component. In particular, these scoring tools are comparably cost-effective and do not need structural requirements such as neuroimaging or laboratory testing. Screening for paediatric delirium (PD), even in neonates and infants, who represent the vast majority of pCICU patients, has recently become possible with the development of the Cornell assessment of pediatric delirium (CAPD) \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. CAPD is in excellent concordance with the Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5) criteria \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e and has been validated for the German language \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. International guidelines recommend its use \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Nevertheless, in an extensive survey, only 44% of centres have implemented regular delirium screening in paediatric ICUs (PICUs) \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDelirium is defined as a neuropsychiatric disorder and is associated with disturbances of consciousness and attention, alteration of perception, disorganised thinking, acute onset, and fluctuating course. The pathophysiology of delirium has not been yet fully understood. Hypotheses are based on an imbalance of the neurotransmitters in the central nervous system (CNS) and a dysfunction of neuronal networks. Contributing factors are the presence of a neuroinflammatory component \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, whereas proinflammatory cytokines lead to an increased permeability of the blood-brain barrier (BBB) \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, thus increasing the vulnerability of the CNS, resulting in the so-called \u0026ldquo;failure of the system integration hypothesis\u0026rdquo; \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eVarious risk factors for delirium have been described in the elderly population, such as infection, drug withdrawal, endocrine disorders, trauma, CNS pathology, hypoxia, vitamin deficiencies, acute vascular disorders, medications, and heavy metal exposure \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Many of these risk factors apply to CHD patients, in particular to their perioperative course, implicating a high-risk profile to develop delirium in this cohort.\u003c/p\u003e \u003cp\u003ePostoperative delirium in adults is generally associated with an unfavourable outcome and occurs with a high prevalence in the intensive care unit, especially after major or cardiac surgery \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Meta-analyses have demonstrated that postoperative delirium goes along with neurological impairment as well as psychological disorders \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSince the development of the CAPD, studies have emerged to evaluate the prevalence of PD in different paediatric intensive care settings. A one-day, multipoint-prevalence study on twenty-seven pCICUs and PICUs demonstrated a prevalence of 40% \u003csup\u003e33\u003c/sup\u003e. These results are conclusive, with a pooled prevalence in a recent review \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. The highest risk occurs in paediatric patients treated with extracorporeal membrane oxygenation (ECMO) \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Nevertheless, prevalence is highly variable between different monocentric studies, ranging from 25% to almost 68% \u003csup\u003e36\u0026ndash;39\u003c/sup\u003e, most likely due to different treatment variables between the centres implicating the possibility of jet unknown modifiable risk factors.\u003c/p\u003e \u003cp\u003eTo date, only patient age and duration of mechanical ventilation have been identified as definite s risk factors for PD. At the same time, developmental delay, cyanotic heart disease, cardiopulmonary bypass time (CPBT), and elevated pain scores are likely to be associated with PD \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe high prevalence of delirium in the postoperative paediatric population and long-term results in the adult population implicate that PD might either be causal for developmental delay in CHD patients or at least be a surrogate parameter for perioperative neurological damage and may act as an early predictor for impaired neurodevelopment.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eTo evaluate PD prevalence and potential risk factors in our cohort, we conducted a monocentric retrospective observational cohort study over 15 months from March 2023 to June 2024. All children from birth to 18 years were included that were being treated in the pCICU after cardiac surgery with or without cardiopulmonary bypass. Exclusion criteria include ICU admission for minor procedures such as central venous catheter (CVC) or pleural drain placement with short-acting sedation or admission for non-post-cardiac-surgery conditions. The study adhered to the Helsinki Declaration and due to the retrospective nature of the study, the Hamburg Medical Association Ethics Committee waived the need of obtaining informed consent (waiver 2023-300407-WF).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSample Size Calculation\u003c/h2\u003e \u003cp\u003eThe study's primary endpoint was to estimate the prevalence of PD using the CAPD screening tool. A 95% confidence interval not greater than \u0026plusmn;\u0026thinsp;6% was considered clinically relevant. We assumed the prevalence to be between 40% and 50%. To comply with this confidence interval, 40% prevalence would require n\u0026thinsp;=\u0026thinsp;271 cases, and for 50% prevalence, n\u0026thinsp;=\u0026thinsp;281 cases would be required. We planned conservatively and decided on n\u0026thinsp;=\u0026thinsp;281 cases, which must be available for evaluation. With an assumed dropout of 2%, n\u0026thinsp;=\u0026thinsp;287 people must therefore be included in the study.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePatients’ Characteristics\u003c/h3\u003e\n\u003cp\u003eThe authors\u0026rsquo; pCICU is located within a large tertiary centre with a variety of treated cardiac malformations, ranging from simple up to complex univentricular heart defects with the possibility for veno-arterial (VA)- and veno-venous (VV)-ECMO treatment when needed. Since the introduction of fast-track protocols \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e in our centre in 2018, more than half of all patients have either been extubated in the theatre or on the same day of surgery in the pCICU. Nearly all postoperative patients are first-line sedated with dexmedetomidine (0.5\u0026ndash;1.4\u0026micro;g/kg/h), while additional continuous sedation with ketamine or midazolam is avoided whenever possible according to guideline recommendation. Muscle relaxation (rocuronium 0.6-1.0mg/kg/h) is only used in cases of high ventilation settings to prevent barotrauma. First-line analgetic treatment in our centre is either by single dose opioids (morphine or piritramide 0.1mg/kg/dose) when the patient is extubated or remifentanil infusion (0.05-2.0\u0026micro;g/kg/min) when short time ventilation is expected. In challenging treatment courses due to increasing tolerance, drug cycling to morphine (30\u0026ndash;100\u0026micro;g/kg/h) or sufentanil (0.3\u0026ndash;1.3\u0026micro;g/kg/h) perfusion becomes necessary. Weaning protocols after prolonged sedation and opioid exposure are standardised and guided by scoring for patient comfort (COMFORT behaviour (COMFORT-B)) and withdrawal (withdrawal assessment tool 1 (WAT-1)).\u003c/p\u003e\n\u003ch3\u003ePatient Assessment for Pain, Iatrogenic Withdrawal Syndrome and Postoperative Delirium\u003c/h3\u003e\n\u003cp\u003ePD was screened using the CAPD and differentiated from symptoms of iatrogenic withdrawal syndrome (IWS) using the WAT-1 \u003csup\u003e41\u003c/sup\u003e only when patients were awake, as classified by a Richmond agitation and sedation score (RASS) \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e of \u0026ge; -2. Comfort and pain were assessed using the COMFORT-B scale. All scores were performed eight hourly by pCICU nurses and doctors.\u003c/p\u003e \u003cp\u003eThe CAPD is structured around the DSM-5 criteria and includes eight questions scored from 0 to 4 points, yielding a total score of 0 to 32 points, with delirium indicated by a score of \u0026ge;\u0026thinsp;9. To address staff variability in recognising delirium in pCICU patients, \u0026ldquo;development anchor points\u0026rdquo; were established for children up to 2 years, outlining normal versus atypical behaviours by age \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. The WAT-1 score includes 11 questions, scored from 0\u0026ndash;2 points with a total score of 12 points. We divided the score into \u0026ge;\u0026thinsp;3 points, indicating mild and \u0026ge;\u0026thinsp;7 points as severe IWS. COMFORT-B comprises six questions, scoring from 0\u0026ndash;5 points, with a total score of 30 points. A range between 11\u0026ndash;22 points is considered an adequate sedation and pain treatment, while\u0026thinsp;\u0026lt;\u0026thinsp;11 points indicate an over-sedated and \u0026gt;\u0026thinsp;22 points under-sedated patient \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eData was extracted from the electronic medical record (EMR) \u003cem\u003eIntegrated Care Management\u003c/em\u003e (ICM, version 13.02 by Dr\u0026auml;gerwerk AG\u0026amp;Co. KGaA) using the software ICMiq (version 1.5.0, by Dr\u0026auml;gerwerk AG\u0026amp;Co. KGaA). Before analysis, a trustee pseudonymised all records, which the Data Integration Centre then provided.\u003c/p\u003e \u003cp\u003eBesides RASS, CAPD, WAT-1, and COMFORT-B, perioperative risk factors related to postoperative delirium were determined after an extensive literature review, including known factors in the paediatric and elderly population. Baseline characteristics included patient age at the point of surgery divided into four groups: 1) neonates (0\u0026ndash;1 month), 2) infants (1\u0026ndash;12 months), 3) toddlers (1\u0026ndash;6 years), and 4) school children/adolescents (7\u0026ndash;18 years), risk stratification of type of surgery defined as per Risk Adjustment for Congenital Heart Surgery (RACHS-1) score \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e or univentricular physiology. Intraoperative data collected was time on cardiopulmonary bypass, divided into intervals of 30 minutes. Data on postoperative variables was obtained up to the point when the child presented with signs of delirium, as stated above. Postoperative variables included eight variables: 1) hypoxia (transcutaneous saturation (SaO2) of \u0026lt;\u0026thinsp;92% for more than six consecutive hours), 2) metabolic derailment (blood glucose level\u0026thinsp;\u0026gt;\u0026thinsp;250mg/dl in blood gas analysis (BGA)), 3) lactatemia (\u0026gt;\u0026thinsp;2mmol/l over six consecutive hours in BGA), 4) postoperative fever (\u0026gt;\u0026thinsp;38.5\u0026deg;C for more than three consecutive hours) 5) signs of postoperative infection (postoperative fever and secondary rise in c-reactive protein (CrP) not due to second surgery and/or pathologic microbiological finding in blood, tracheal or urinary samples and/or restart of antibiotic treatment due to clinical presentation of infection), 6) postoperative use of hydrocortisone to enhance inotropic effect and stabilise hemodynamics due to signs of systemic inflammatory response syndrome (SIRS) and 8) time on ventilation divided into four groups: i) on table extubation (OTE), ii) fast track (0\u0026ndash;10 hours (h), iii) short term ventilation (\u0026gt;\u0026thinsp;10-100h) and iv) long term ventilation.\u003c/p\u003e \u003cp\u003eFor subgroup analysis, patient data was obtained for patients that remained ventilated on pCICU (ventilation groups 2\u0026ndash;4) concerning the COMFORT-B scale and use of three different sedative infusions: 1) dexmedetomidine, 2) ketamine, and 3) midazolam. To differentiate between lactatemia type A, defined as resulting from inadequate delivery of oxygen and tissue hypoxia, and type B from metabolic uncoupling after bypass, \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e data for subgroup analysis was extracted, including: 1) arterio-venous difference in O\u003csub\u003e2\u003c/sub\u003e-concentration (avDO2)\u0026thinsp;\u0026gt;\u0026thinsp;40% and 2) difference of central to peripheral temperature (ΔT)\u0026thinsp;\u0026gt;\u0026thinsp;4\u0026deg;C.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eThroughout this article, we have used parametric statistics measures, such as arithmetic mean and standard deviation or categorical variables, frequencies, and proportions. The p-values in the descriptive statistics are based on t-tests or Chi\u0026sup2;-tests. For multivariate modelling, we calculated logistic regression models and reported the odds ratio, the confidence interval of the odds ratio, and the p-values. All calculations and figures were made using the statistical program R (version 4.4.1, by the R Foundation for Statistical Computing, Vienna, Austria) \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eIn the period from March 2023 to June 2024, a total of 387 patients were treated for surgical and medical conditions in pCICU. After excluding patients treated for medical conditions and short-term procedures, 311 patients treated after heart surgery with or without CPB remained. With a compliance rate of 94.2%, CAPD and WAT-1 were performed in 293 of these 311 patients (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Delirium occurred in 118 (40.2%), IWS occurred in 136 (46.4%) cases, whereas 109 had mild and 27 had severe symptoms of IWS. The average duration of delirium was 53 hours, with the majority of cases presenting directly after extubation but also later on, partially with a fluctuating course, as demonstrated in the box plot in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eIn multivariate regression analysis of 293 patients (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), when controlling for age, school children and adolescents had the lowest delirium rates (OR 0.3, p\u0026thinsp;=\u0026thinsp;0.1), and infants had the highest delirium rates (OR 2.9, p\u0026thinsp;=\u0026thinsp;0.05) when compared to neonates. RACHS-1 (OR 1.0, p\u0026thinsp;=\u0026thinsp;0.8) and CPBT (OR 0.9, p\u0026thinsp;=\u0026thinsp;0.4) did not correlate with delirium with a narrow confidence interval and a precise effect size.\u003c/p\u003e\n\u003cp\u003eThe presence of IWS was a robust predictor for PD, categorised as mild IWS (OR 7.7, p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and severe IWS (OR 17.0, p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Delirium rates increased with length of ventilation compared to OTE, particularly for long-term ventilated children (OR 7.4, p\u0026thinsp;=\u0026thinsp;0.003). Patients who had an elevated lactate level for a consecutive time of more than 6 hours had substantially higher delirium rates (OR 2.7, p\u0026thinsp;=\u0026thinsp;0.05). No trend was identified for hypoxic or univentricular patients. Metabolic derailment, postoperative fever, signs of infection, and the postoperative use of hydrocortisone did not predict delirium.\u003c/p\u003e\n\u003cp\u003eA total of 187 patients remained ventilated after transfer to pCICU. COMFORT-B scores were performed every shift (8 hours). Because the fast-track protocol was carried out for some of these patient before scoring, only 154 patients had a COMFORT-B score before extubation. As demonstrated in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, all patients that remained ventilated with a low COMFORT-B score\u0026thinsp;\u0026lt;\u0026thinsp;11 had a lower delirium rate after extubation (OR 0.4, p\u0026thinsp;=\u0026thinsp;0.08) compared to patients with a COMFORT-B score 11\u0026ndash;22.\u003c/p\u003e\n\u003cp\u003eNearly all postoperative patients received dexmedetomidine infusion in our centre, even if extubated in the operating room, to modulate pain perception and reduce the need for opioids. If the patient required additional sedation to achieve an adequate sedation level (COMFORT-B 11\u0026ndash;22) and remained tube-tolerant, ketamine or midazolam was added as an infusion therapy if a single bolus therapy was not sufficient. Figure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e demonstrates that escalating to ketamine infusion therapy significantly increases delirium rates (OR 3.3, p\u0026thinsp;=\u0026thinsp;0.009). This is also the case for escalation to midazolam infusion therapy, though the increase is insignificant (OR 2.84, p\u0026thinsp;=\u0026thinsp;0.07).\u003c/p\u003e\n\u003cp\u003eDue to the substantial correlation between postoperative lactatemia and delirium (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), we conducted a subgroup analysis of all 83 patients with consecutive lactatemia over more than six hours (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e) to distinguish whether the elevated lactate was attributable to low cardiac output (LCO) (lactate acidosis type A) or to metabolic derailment (lactate acidosis type B).\u003c/p\u003e\n\u003cp\u003ePatients with signs of low cardiac output (n\u0026thinsp;=\u0026thinsp;19), defined as lactatemia for more than 6 hours, AVDO2\u0026thinsp;\u0026gt;\u0026thinsp;40%, and a core-to-peripheral temperature gradient of \u0026gt;\u0026thinsp;4\u0026deg;C, had a significantly higher delirium rate (OR 3.9, p\u0026thinsp;=\u0026thinsp;0.02) than patients with metabolic decoupling, defined as lactatemia and a blood glucose level\u0026thinsp;\u0026gt;\u0026thinsp;250mg/l.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWith a CAPD implementation rate approaching 95%, we determined a well-founded prevalence of delirium of 40.2\u003cb\u003e%\u003c/b\u003e. This corresponds with a pooled prevalence in pCICUs of 39% \u003csup\u003e34\u003c/sup\u003e and a prevalence of 40% in the only multicentre study to date \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. According to a systematic review, the pooled prevalence in pCICUs, 53% (four studies), is higher than in PICUs (23%, 17 studies) \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003ePatients Age and Duration of Mechanical Ventilation Predicts Delirium\u003c/h3\u003e\n\u003cp\u003eIn our study, infants had the highest (OR 2.9, p\u0026thinsp;=\u0026thinsp;0.05), and young children/adolescents had the lowest risk (OR 0.3, p\u0026thinsp;=\u0026thinsp;0.11) of developing PD. This is consistent with previous studies that identified children younger than 2 years \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e or less than 1 year \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e to have a significantly higher risk of developing PD. Our study confirms that mechanical ventilation duration is associated with increased rates of PD and a significantly increased risk in those with more than 100 hours of ventilation (OR 7.3, p\u0026thinsp;=\u0026thinsp;0.003). These results are consistent with the current literature \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e and most likely reflect the cumulative effects of various variables contributing to a longer ventilation time. Of note is that compared to patients with OTE, even patients on fast-track protocols (0\u0026ndash;10 hours, OR 2.0, p\u0026thinsp;=\u0026thinsp;0.12) or ventilated for 10\u0026ndash;100 hours (OR 2.4, p\u0026thinsp;=\u0026thinsp;0.06) had a substantially higher risk of developing PD. This might reflect the benefits of the differences in pain and sedation management by anaesthetists in theatres compared to management in pCICU, and further evaluation is needed. Overall, this outlines the importance of OTE, which, in our experience, is not pursued in all cases possible due to logistical issues in theatres.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSeverity of Cardiac Surgery and Time of Cardiopulmonary Bypass Does Not Predict Delirium in Our Cohort\u003c/b\u003e \u003c/p\u003e \u003cp\u003eInconclusive with other studies, RACHS-1 did not predict PD in our cohort. While Patel et al. found a significant difference in delirium prevalence between RACHS-1 groups 1 and 2 compared to groups 3 and 4 \u003csup\u003e37\u003c/sup\u003e, our study shows no correlation (OR 1.0 p\u0026thinsp;=\u0026thinsp;0.82, CI of 0.73 to 1.48). K\u0026ouml;ditz et al. did also not find a correlation between RACHS-1 and CAPD, but the vast majority either had a RACHS-1 score of 2 or 3 \u003csup\u003e50\u003c/sup\u003e, so the comparison might not be feasible. Alvarez et al. did not use the RACHS-1 score to assess surgical complexity in their study, but the alternative STS-EACTS (Society of Thoracic Surgeons and European Association for Cardio-Thoracic Surgery) scale, which showed a significant correlation with delirium \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Mao et al., on the other hand, focused on the general severity of illness and used the PRISM (Pediatric Risk of Mortality) III score, which also found a significant association with delirium \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCompared to Alvarez et al. \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, CPBT per 30-minute interval did not predict delirium in our cohort (OR 0.94, CI 0.79\u0026ndash;1.12, p\u0026thinsp;=\u0026thinsp;0.46). The multicentre study by Staveski et al. \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e and the final multivariate analysis by Mao et al. \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e did also not demonstrate a significant correlation.\u003c/p\u003e \u003cp\u003eFurther research is needed to analyse the details of perfusion and surgical techniques regarding the prevalence of delirium. The current literature's inconsistency may indicate further, possibly modifiable risk factors.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSedation Strategy and Patient Comfort Impact Delirium, While the Presence of Iatrogenic Withdrawal Syndrome is the Strongest Predictor for Delirium\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA comfort scale of less than 11, usually classifying patients as over-sedated \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, was protective for delirium (OR 0.49, p 0.08). However, the COMFORT-B Score comprises several aspects. On one hand, it recognises pain, which has been identified as a possible link to delirium \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. Consequently, children with high potent analgetic on short-term sedation have a significantly lower rate of delirium \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. On the other hand, oversedation, measured by EEG during anaesthesia for paediatric cardiac surgery, was shown to promote delirium \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. Continuous EEG Monitoring was not implemented in our pCICU during the study period. So no further information can be provided. Assuming that a COMFORT-B\u0026thinsp;\u0026lt;\u0026thinsp;11 points does not necessarily equate to a complete suppression pattern in EEG monitoring, there may be optimal sedation and analgetic depth to reduce delirium rates that are below the standard range COMFORT-B scale of 11\u0026ndash;22 points, but still far from postoperative EEG suppression pattern. Further research is needed to evaluate this relationship. Of note, CAPD scoring was only performed during the pCICU stay. Therefore, due to individual pharmacokinetics, patients with a comfort score\u0026thinsp;\u0026lt;\u0026thinsp;11, while intubated, might have developed delirium after transfer from pCICU, as fluctuating and late-onset delirium courses were observed during pCICU stay (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e As to guidelines recommendation, we used a standardised protocol of single-dose opioids and dexmedetomidine infusion and only used ketamine and midazolam infusion as second- and third-line treatments. Nevertheless, long-time ventilation and increasing drug tolerance sometimes require an escalation. Benzodiazepine exposure is a known risk factor for delirium in the adult population \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e and for pCICU patients \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. The subgroup analysis for ventilated patients demonstrated a favourable delirium rate if dexmedetomidine was the only sedative used compared to a combination with ketamine (OR 3,3 p\u0026thinsp;=\u0026thinsp;0.009) or midazolam infusion (OR 2.84, p\u0026thinsp;=\u0026thinsp;0.07). These findings are conclusive with data from postoperative children with congenital heart disease and pulmonary hypertension (PAH) \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e as well as in large randomised trials in the adult population \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWithout scoring tools, IWS can be misinterpreted as delirium, although the two syndromes significantly differ in aetiology and symptoms. Current international guidelines suggest clinical evaluation should include IWS and delirium scoring \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Our study also emphasises this differentiation. In our study, IWS was identified with high statistical significance (mild IWS OR 7.7, p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and severe IWS OR 17.0, p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001) as a predictive factor for the occurrence of postoperative delirium. To date, these results have only been described in the multicentre 1-day study by Staveski et al.. WAT-1 levels at the time of diagnosing delirium were significantly higher, and the patient had a higher WAT-1 Score twenty-four hours before diagnosing delirium \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. A methodological limitation lies in the overlap of the diagnostic question \u0026ldquo;Is the child restless?\u0026rdquo; within the two scoring questionnaires, WAT-1 and CAPD. This question, which occurs in both scores, could lead to diagnostic overlap and, thus, a potential distortion of the differential diagnosis between IWS and delirium. However, since withdrawal is a well-known risk factor in the elderly population \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, the predictive value remains evident from our point of view.\u003c/p\u003e \u003cp\u003eThese results might lead to new preventive approaches. Using more potent analgetics during ventilation to reduce pain and optimising weaning protocols to prevent IWS might be key components. Minimising the use of midazolam or ketamine should play an important role, and further development of fast-track protocols in anaesthesia and intensive care could further reduce delirium rates in children after cardiac surgery.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePostoperative Low Cardiac Output but not Hypoxia Predicts Delirium\u003c/h2\u003e \u003cp\u003eAlthough lactate was not identified as a significant risk factor in multivariate analysis (OR 2.7, p\u0026thinsp;=\u0026thinsp;0.05), and this variable was not investigated in previous studies in the pCICU cohorts, data in the adult population demonstrated a significant correlation between lactatemia and postoperative delirium \u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. The origins of lactatemia were differentiated \u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e using additional signs of low cardiac output syndrome (LCOS), such as AvDO2\u0026thinsp;\u0026gt;\u0026thinsp;40% and core to peripheral temperature difference\u0026thinsp;\u0026gt;\u0026thinsp;4\u0026deg;C to circumscribe the LCOS definition. We found LCOS (Hyperlactatemia type A) but not metabolic uncoupling (Hyperlactatemia type B) to be a significant predictor of postoperative delirium after cardiac surgery (OR 3.9, p\u0026thinsp;=\u0026thinsp;0.02). Mao et al. found secondary thoracic closure to be predictive of delirium \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Oftentimes, delayed sternal closure is due to a certain state of LCOS, which points out a possible correlation. While prolonged hypoxia or univentricular physiology were not significant predictors in our multivariate analysis, Liu et al. demonstrated a preventive effect for delirium by optimising regional cerebral oxygen saturation \u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. Real-time NIRS monitoring is available for all our patients. Still, due to technical compatibilities, it is not documented in sufficient detail in the EMR, and thus, this effect cannot be demonstrated in our analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eFever, Infection, and Use of Steroids Seem Not to Predict Delirium\u003c/h2\u003e \u003cp\u003eIn contrast to a previous study by Meyburg et al. in a PCCU cohort \u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e in our study, postoperative fever and infections were no significant risk factors for the occurrence of delirium. However, antipyretic pain medication (paracetamol and metamizole) is administered per standard protocol six hourly for every patient in our cohort. Active temperature control systems are used for patients with signs of LCOS, and in 1/3 of all patients, postoperative hydrocortisone is administered. Therefore, our data is likely not consistent enough to answer the question of how the immune system influences the occurrence of postoperative delirium. Generally, the role of neuroinflammation has been described in the literature \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Further research is needed to characterise better the influence of neuroinflammatory processes on the development of delirium in the context of postoperative care in this specific patient population.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStudy Strengths and Limitations\u003c/h2\u003e \u003cp\u003eWith 311 patients and a compliance of nearly 95%, we recorded an accurate result of the prevalence in our cohort and, therefore, a detailed risk factor analysis. Compared to previous studies, an evaluation every 8 hours is more precise in detecting fluctuating forms of delirium. Nevertheless, there are some limitations. As a single-centre observational cohort study, our data cannot be widely generalised, and no causality can be drawn from it. We did not determine delirium subtypes (hypo-, hyperactive or mixed). CAPD and WAT-1 scoring were not continued after transfer from pCICU, so there might have been a number of missed cases due to late appearance. In addition, children with a positive delirium score were treated immediately for ethical reasons (environmental modifications and, in rare cases, use of antipsychotic medication), which could potentially have influenced the course and duration of the delirium. While a number of predictive risk factors were identified in our study, there are certainly other, jet unknown postoperative and intraoperative risk factors that were not recorded in our analysis and may play a role in delirium. These limitations emphasise the need for further studies.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePD and IWS have a high prevalence after paediatric cardiac surgery, and screening should be part of standard care. While non-modifiable risk factors such as patient\u0026rsquo;s age play an important role in risk stratification, possibly modifiable risk factors such as duration of mechanical ventilation emphasise the further development of fast-track protocols. While patients with LCOS have an increased risk, neuromonitoring should aim to optimise for cerebral tissue perfusion. Especially IWS, as a powerful predictor for delirium, demands not only well-considered sedation and pain management, avoiding ketamine and benzodiazepine use, but also sophisticated weaning protocols. Overall, further research is needed to determine the predictive value of postoperative delirium in neurodevelopment, as infants have the highest prevalence, and data in the adult population is predictive.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset used and/or analysed during the present study is available from the corresponding author upon reasonable request. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eS.S. and S.H.H. designed the study and carried out the sample collection, \u0026nbsp;G.S. performed the data analysis, S.S., S.H.H., I.H. and D.B. wrote and reviewed the manuscript, L.C.S., I.H., F.J., U.G., C.G.-N., J.De., J.Dr., D.B., S.D., M.H., R.K-F. supported the clinical aspect in sample collection. \u0026nbsp; All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWu, W. 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Assessment of sedation levels in pediatric intensive care patients can be improved by using the COMFORT \u0026quot;behavior\u0026quot; scale. \u003cem\u003ePediatr Crit Care Med\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 58-63 (2005). https://doi.org:10.1097/01.Pcc.0000149318.40279.1a\u003c/li\u003e\n\u003cli\u003eJenkins, K. J. Risk adjustment for congenital heart surgery: the RACHS-1 method. \u003cem\u003eSemin Thorac Cardiovasc Surg Pediatr Card Surg Annu\u003c/em\u003e \u003cstrong\u003e7\u003c/strong\u003e, 180-184 (2004). https://doi.org:10.1053/j.pcsu.2004.02.009\u003c/li\u003e\n\u003cli\u003ePalermo, R. A.\u003cem\u003e et al.\u003c/em\u003e Metabolic Uncoupling Following Cardiopulmonary Bypass. \u003cem\u003eCongenital Heart Disease\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, E250-E257 (2015). https://doi.org:10.1111/chd.12285\u003c/li\u003e\n\u003cli\u003eStephens, E. H., Epting, C. L., Backer, C. L. \u0026amp; Wald, E. L. Hyperlactatemia: An Update on Postoperative Lactate. \u003cem\u003eWorld J Pediatr Cong\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 316-324 (2020). https://doi.org:10.1177/2150135120903977\u003c/li\u003e\n\u003cli\u003eR: A Language and Environment for Statistical Computing v. R version 4.4.1 (R Foundation for Statistical Computing. Vienna, Austria, 2024).\u003c/li\u003e\n\u003cli\u003eIsta, E.\u003cem\u003e et al.\u003c/em\u003e Factors Associated With Delirium in Children: A Systematic Review and Meta-Analysis. \u003cem\u003ePediatr Crit Care Med\u003c/em\u003e \u003cstrong\u003e24\u003c/strong\u003e, 372-381 (2023). https://doi.org:10.1097/pcc.0000000000003196\u003c/li\u003e\n\u003cli\u003eMao, D., Fu, L. \u0026amp; Zhang, W. Risk Factors and Nomogram Model of Postoperative Delirium in Children with Congenital Heart Disease: A Single-Center Prospective Study. \u003cem\u003ePediatr Cardiol\u003c/em\u003e \u003cstrong\u003e45\u003c/strong\u003e, 68-80 (2024). https://doi.org:10.1007/s00246-023-03297-5\u003c/li\u003e\n\u003cli\u003eK\u0026ouml;ditz, H., Drouche, A., Dennhardt, N., Schmidt, M., Schultz, M. \u0026amp; Schultz, B. Depth of anesthesia, temperature, and postoperative delirium in children and adolescents undergoing cardiac surgery. \u003cem\u003eBmc Anesthesiol\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e, 148 (2023). https://doi.org:10.1186/s12871-023-02102-3\u003c/li\u003e\n\u003cli\u003eFu, M.\u003cem\u003e et al.\u003c/em\u003e Risk factors and incidence of postoperative delirium after cardiac surgery in children: a systematic review and meta-analysis. \u003cem\u003eItal J Pediatr\u003c/em\u003e \u003cstrong\u003e50\u003c/strong\u003e, 24 (2024). https://doi.org:10.1186/s13052-024-01603-2\u003c/li\u003e\n\u003cli\u003eXu, N., Chen, Q., Huang, S. T., Sun, K. P. \u0026amp; Cao, H. 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P.\u003cem\u003e et al.\u003c/em\u003e Effect of sedation with dexmedetomidine vs lorazepam on acute brain dysfunction in mechanically ventilated patients - The MENDS randomized controlled trial. \u003cem\u003eJama-J Am Med Assoc\u003c/em\u003e \u003cstrong\u003e298\u003c/strong\u003e, 2644-2653 (2007). https://doi.org:DOI 10.1001/jama.298.22.2644\u003c/li\u003e\n\u003cli\u003eJiang, L.\u003cem\u003e et al.\u003c/em\u003e A Retrospective Comparison of Dexmedetomidine Versus Midazolam for Pediatric Patients with Congenital Heart Disease Requiring Postoperative Sedation. \u003cem\u003ePediatric Cardiology\u003c/em\u003e \u003cstrong\u003e36\u003c/strong\u003e, 993-999 (2015). https://doi.org:10.1007/s00246-015-1110-z\u003c/li\u003e\n\u003cli\u003eRiker, R. R.\u003cem\u003e et al.\u003c/em\u003e Dexmedetomidine vs midazolam for sedation of critically ill patients: a randomized trial. \u003cem\u003eJama\u003c/em\u003e \u003cstrong\u003e301\u003c/strong\u003e, 489-499 (2009). https://doi.org:10.1001/jama.2009.56\u003c/li\u003e\n\u003cli\u003eQian, X., Sheng, Y., Jiang, Y. \u0026amp; Xu, Y. Associations of serum lactate and lactate clearance with delirium in the early stage of ICU: a retrospective cohort study of the MIMIC-IV database. \u003cem\u003eFront Neurol\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 1371827 (2024). https://doi.org:10.3389/fneur.2024.1371827\u003c/li\u003e\n\u003cli\u003ePalermo, R. A.\u003cem\u003e et al.\u003c/em\u003e Metabolic Uncoupling Following Cardiopulmonary Bypass. \u003cem\u003eCongenit Heart Dis\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, E250-257 (2015). https://doi.org:10.1111/chd.12285\u003c/li\u003e\n\u003cli\u003eLiu, J. F., Zhou, S. J., Chen, X. H., Cao, H. \u0026amp; Chen, Q. Effect of Optimizing Regional Cerebral Oxygen Saturation during Infant Cardiac Surgery on the Incidence of Postoperative Delirium: A Retrospective Study. \u003cem\u003eAnn Thorac Cardiovasc Surg\u003c/em\u003e \u003cstrong\u003e30\u003c/strong\u003e (2024). https://doi.org:10.5761/atcs.oa.23-00057\u003c/li\u003e\n\u003cli\u003eMeyburg, J.\u003cem\u003e et al.\u003c/em\u003e Risk Factors for the Development of Postoperative Delirium in Pediatric Intensive Care Patients. \u003cem\u003ePediatr Crit Care Med\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, e514-e521 (2018). https://doi.org:10.1097/pcc.0000000000001681\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Paediatric Delirium, Cornell Assessment of Pediatric Delirium (CAPD), Neurodevelopment, Congenital Heart Disease (CHD), Iatrogenic Withdrawal Syndrome (IWS), Paediatric Cardiac Intensive Care Unit (pCICU)","lastPublishedDoi":"10.21203/rs.3.rs-6214736/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6214736/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWith increasing focus on neurodevelopment in children with congenital heart disease (CHD), early predictive markers are crucial to intervene and improve neurodevelopmental outcome. As postoperative delirium (PD) is known to have a long-term impact on neurocognitive function in adults, investigations into the prevalence and identification of modifiable risk factors of PD offer new perspectives. We conducted a retrospective, single-centre study screening for PD using the Cornell Assessment of Pediatric Delirium (CAPD). We distinguished it from the iatrogenic withdrawal syndrome (IWS) using the withdrawal assessment tool 1 (WAT-1). An explorative, multivariate regression analysis included various pre-, intra-, and postoperative variables. With screening compliance of 95% in 311 patients, PD prevalence was 40.2%, and 46.4% developed IWS. Infants were at highest risk for PD (OR 2.9, p\u0026thinsp;=\u0026thinsp;0.05). Prolonged mechanical ventilation\u0026thinsp;\u0026gt;\u0026thinsp;100hours (OR 7.4, p\u0026thinsp;=\u0026thinsp;0.003), infusion therapy with ketamine (OR 3.3, p\u0026thinsp;=\u0026thinsp;0.009), IWS (mild: OR 7.7, p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001, severe: OR 17.0, p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and low cardiac output syndrome (LCOS) (OR 3.9, p\u0026thinsp;=\u0026thinsp;0.02) were significant predictive risk factors for PD. Overall, PD and IWS are highly prevalent in paediatric cardiac intensive care unit (pCICU), especially in infants and children with prolonged ventilation duration, demand for multiple sedatives, and LCOS as a newly described risk factor.\u003c/p\u003e","manuscriptTitle":"Paediatric Delirium After Cardiac Surgery:Prevalence and Predictive Risk Factor Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-25 09:53:44","doi":"10.21203/rs.3.rs-6214736/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-28T10:25:37+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-24T06:38:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-20T07:31:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"284407494569372217250873270760582028983","date":"2025-04-11T12:41:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269130583168631170193568288086547512513","date":"2025-03-24T11:15:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-21T10:40:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-21T10:36:34+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-03-21T05:52:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-19T14:15:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-12T20:08:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c82bf60c-339b-489c-b8ed-1d893b078afc","owner":[],"postedDate":"March 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46129042,"name":"Health sciences/Medical research/Paediatric research"},{"id":46129043,"name":"Health sciences/Diseases/Cardiovascular diseases/Congenital heart defects"},{"id":46129044,"name":"Health sciences/Diseases/Neurological disorders/Disorders of consciousness"}],"tags":[],"updatedAt":"2025-06-23T16:01:34+00:00","versionOfRecord":{"articleIdentity":"rs-6214736","link":"https://doi.org/10.1038/s41598-025-04927-z","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-06-20 15:57:38","publishedOnDateReadable":"June 20th, 2025"},"versionCreatedAt":"2025-03-25 09:53:44","video":"","vorDoi":"10.1038/s41598-025-04927-z","vorDoiUrl":"https://doi.org/10.1038/s41598-025-04927-z","workflowStages":[]},"version":"v1","identity":"rs-6214736","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6214736","identity":"rs-6214736","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}