Abstract
Objective: This study aimed to survey the prevalence of delirium in the pediatric intensive care unit (PICU) and explore the associated risk factors. Design: A retrospective case-control study. Setting: Two PICUs within a tertiary-A general hospital. Patients: Patients aged from 1 month to 7 years who stayed in either PICU for at least 1 day were included. Methods: A total of 639 patients admitted to PICU of a tertiary-A general hospital from December 2018 to August 2019 were enrolled. Demographic, clinical, laboratory data and length of stay in the PICU were collected. The patients were screened twice a day with the Chinese version of Cornell Assessment of Pediatric Delirium (CAPD), and were divided into the delirium group and the non-delirium group. A risk factor analysis was conducted, with ICU pediatric delirium as primary outcome, by performing a multivariable logistic regression analysis. Results: Of the 639 patients, the prevalence of ICU pediatric delirium was 31.30%. Of the 200 children with delirium across 3703 study days, 36% children were hyperactive, 41% were hypoactive, and 23% displayed the mixed type of delirium. Univariate analysis and multivariate logistic regression analysis showed that age, PRISM IV score (OR, 2.20; 95% CI, 1.42-3.41), hypoxia (OR, 2.69; 95% CI, 1.53-4.71), metabolic dis-function (OR, 3.73; 95% CI, 2.08-6.71), duration of infection (OR, 1.22; 95% CI, 1.10-1.36), and mechanical ventilation (OR, 3.78; 95% CI, 2.25-6.35) were statistically correlated with ICU pediatric delirium. The ROC curve analysis shows the combination CRP with duration of infection has good predictive performance. Conclusions: Age, PRISM IV score, ICU retention time, metabolic dis-function, duration of infection, hypoxia, CRP and mechanical ventilation were the independent risk factors for ICU pediatric delirium. We suggest that active preventive measures should be taken to reduce the occurrence of ICU pediatric delirium.
Keywords: Pediatric, children, critical care, delirium, risk factor
Introduction
Delirium refers to an acute fluctuating change in the state of consciousness, which is defined by impairment of cognition, attention, and behavior [1]. The specific features of pediatric delirium include delayed responses, sustained agitation, abnormal and implacable crying along with many other types of changes in psychomotor activity. In ICU settings, pediatric delirium was linked with increased hospital mortality, prolonged mechanical ventilation and length of hospital stay. Pediatric patients may be at risk of exposure to both short-term and long-term hazards [2-4]. Meanwhile, guardians of children suffering from delirium in PICU often have to afford higher healthcare costs [5]. A longer duration with ICU pediatric delirium is reported to be linked to worse outcomes [6].
Reported prevalence rates of pediatric delirium in critically ill children ranged from 12% to 47% [7-15], and in a recent study were even up to 56% in children below 2 years of age [8]. Children at a young age (< 2 years), disease severity, infectious diseases, inflammation, mechanical ventilation, and antiepileptic drugs were identified as important risk factors for ICU pediatric delirium [10,16,17]. It is vital to carefully identify the specific independent risk factors linked to pediatric delirium as later this information can help to develop significant and effective preventive strategies in patients.
According to Maldonado [18,19], the development of delirium in patients is thought to be based on at least six pathophysiology and seven neuro-pathogenesis theories. Based on the neuroinflammation hypothesis represented by Cerejeira [20], infection may introduce specific triggering factors that may then provoke the inflammatory cascade activation, which would include hypoxia, blood transfusions, elevated hormone levels, and so on. These neuroinflammatory changes lead to the destruction of the permeability of the blood-brain barrier, and then result in neurobehavioral and cognitive symptoms of delirium [21]. Systemic inflammation, which may be caused by injury (including surgical injury) or infection, has been widely known as a triggering cause of delirium [19]. However, few studies have examined C-reactive protein (CRP), one of the most common markers for systemic inflammation, as a risk factor for pediatric delirium. The aim of this research was to survey the prevalence of delirium in PICU and explore the associated risk factors.
Material and methods
Study approval
Informed consent was obtained from parents/guardians of all patients in accordance with a protocol reviewed and approved by the institutional ethical review board of Xinhua Hospital Ethics Committee Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China (Approved No. of ethic committee: XHEC-C-2018-097).
Patient population
This retrospective observational study was conducted in 2 PICUs at Xinhua Hospital affiliated to Shanghai Jiao Tong University, which is a tertiary-A general hospital in Shanghai, China. Patients admitted to PICU from Dec. 2018 to Aug. 2019 were included. The inclusion criteria were as follows: 1) ICU check-in time was more than 24 hours; 2) Age was between 1 month and 7 years; 3) Informed consent was obtained from the parent/guardian. The exclusion criteria were as follows: 1) After being admitted, patients were in a coma or deep sedation with Richmond agitation sedation scale (RASS) < -3; 2) Patients had delirium before admission; 3) Patients had previously undergone neurosurgery or neurological surgery; 4) Patients had been diagnosed with mental illness or developmental delay and continued to be administered antipsychotic drugs; 5) Patients presented with hearing or visual impairment; 6) Patients had missed or incomplete delirium score; 7) Patients were non-Chinese or non-English language users.
Data collection
The PICU responsible nurses explained this research to the children’s legal guardians and gave detailed instructions on what it would involve. Participants would be included after their legal guardians signed an informed consent form containing detailed information about the research. The study was registered in the Chinese Clinical Trial Registry (Registration number: ChiCTR1800019825 http://www.chictr.org.cn/showproj.aspx?proj= 33238).
Each patient, 1 month-7 years of age, was screened for delirium twice daily by the researchers using the Cornell Assessment of Pediatric Delirium (CAPD). The CAPD score > 9 and RASS > -3 were considered as ICU pediatric delirium positive and a child who has been assessed as delirium positive at least once during his/her stay in PICU was defined as pediatric delirium. Meanwhile, we identified a priori-defined, non-mutually exclusive phenotypes of delirium per the presence of hypoxia, sepsis, sedative exposure, or metabolic (e.g., renal) dysfunction. Delirium in the absence of hypoxia, sepsis, sedation, and metabolic dysfunction was considered to be unclassified. In addition, the data were collected by the researcher herself and PICU nurses, and the researchers were authorized by the scale inventor and the translator for the Chinese version. The CAPD was validated for use in children and was reliable for detecting delirium in children of all ages (including infants) in PICU. The pilot experiment (n = 20) in this study measured Cronbach’s α of CAPD as 0.97. Severity of illness was measured by Pediatric Risk of Mortality IV (PRISM IV) [22] within 4 hours of being admitted to PICU. The higher the score, the more severe the condition. Demographic and clinical indicators were extracted from the Hospital Information System, including gender, age, duration of mechanical ventilation and sedative drug, CRP and length of PICU etc.
When a patient’s arterial blood oxygen pressure (PaO2) was less than 80 mmHg, the patient was judged to be hypoxia. When a patient’s white blood cell count, neutrophil ratio, and daily maximum body temperature were out of the normal range, the patient was judged to be infected. In addition, sepsis data were obtained from Nosocomial Infection Monitoring System (NIM).
Statistical analysis
SPSS 22.0 statistical software was used to analyze and process the data. First, Univariate analysis (Chi-squared test) was conducted to examine the distributions of selected characteristics for cases and controls. Moreover, univariate model analysis and multivariate conditional logistic regressions were used to examine whether delirium was with different clinical phenotypes. The associations were presented as odds ratios (ORs) with 95% confidence intervals (CIs). Two-sided P values < 0.05 were considered statistically significant. The area under the ROC curve (AUC) was used to determine the diagnostic performance, and values > 0.75 were considered to represent good performance.
Results
Description of delirium
A total of 639 patients met the criteria and were finally admitted to this study. Among 3703 study days (the sum of the enrollment days of all patients), delirium occurred in 581 (15.69%) study days. It was found that 36% of patients with delirium were hyperactive, 41% were hypoactive and 23% showed a mix of the types. The average age was 19.51±23.58 months. The prevalence rate of pediatric delirium in PICU settings was 31.30%. Among the 200 children with delirium, the first onset of pediatric delirium occurred within the first seven admission days to PICU. Among them, 176 cases (88%) of delirium occurred for the first time within 72 hours of admission to PICU, 148 cases (74%) occurred for the first time within 48 hours of admission, 95 cases (47.5%) occurred for the first time within 24 hours of admission of PICU. Moreover, 107 cases (53.5%) were pediatric delirium with duration of 1 day. The average was 1.79 (SD = 1.49) days for duration of ICU pediatric delirium, and the median was 1 day. The longest duration was 9 days, while the shortest was 1 day.
Descriptions of patient population
Demographics and clinical characteristics of the study population are shown in Table 1. Pediatric delirium occurred in 200 of 639 patients (31.3%) after PICU admission. There were no statistically significant differences in the distribution of sex, gestational age, surgery or not, pain, head injury, opioid exposure between the case group and the control group (P > 0.05), but the differences in the distribution of age, admission diagnosis, emergency check-in, mechanically ventilated, restrict, benzodiazepine or dexmedetomidine exposure, LOS, PRISM IV score, duration of infection or hypoxia, and CRP were statistically significant (P < 0.05).
Table 1.
Demographics and clinical characteristics of the study population (n = 639)
| Characteristic | Never deliriums (n = 439), N (%) | Ever deliriums (n = 200), n (%) | Overall Cohort (n = 639), N (%) | P Value |
|---|---|---|---|---|
| Age (month) | ||||
| < 6 M | 194 (44.2) | 98 (49.0) | 292 (45.7) | 0.001** |
| 6-12 M | 88 (20.0) | 57 (28.5) | 145 (22.7) | |
| 13-36 M | 62 (14.1) | 25 (12.5) | 87 (13.6) | |
| > 37 M | 95 (21.6) | 20 (10.0) | 115 (18.0) | |
| Sex | ||||
| male | 238 (54.2) | 110 (55.0) | 348 (54.5) | 0.461 |
| female | 201 (45.8) | 90 (45.0) | 291 (45.5) | |
| Gestational | ||||
| Preterm | 37 (8.4) | 21 (10.5) | 58 (9.1) | 0.241 |
| No preterm | 401 (91.3) | 179 (89.5) | 581 (90.9) | |
| Admission diagnosis | ||||
| Sepsis/ARDS | 78 (17.8) | 63 (31.5) | 141 (22.1) | 0.008** |
| Surgery | 264 (60.1) | 102 (51.0) | 366 (57.3) | |
| Asthma, other pulmonary disease | 31 (7.1) | 12 (6.0) | 43 (6.7) | |
| Congestive heart failure, myocardial infarction, or cardiogenic shock | 6 (1.4) | 3 (1.5) | 9 (1.4) | |
| Airway protection | 17 (3.9) | 7 (3.5) | 24 (3.8) | |
| Other | 43 (9.8) | 13 (6.5) | 56 (8.8) | |
| Pain | ||||
| Yes | 178 (89.00) | 398 (90.66) | 576 (90.01) | 0.510 |
| No | 22 (11.00) | 41 (9.34) | 65 (10.17) | |
| Head injury | ||||
| Yes | 3 (1.50) | 4 (0.91) | 7 (1.10) | 0.510 |
| No | 197 (98.50) | 435 (99.09) | 632 (98.90) | |
| Emergency check-in | ||||
| Yes | 90 (20.5) | 55 (27.5) | 145 (22.7) | 0.033* |
| No | 349 (79.5) | 145 (72.5) | 494 (77.3) | |
| Mechanically ventilated | ||||
| Yes | 45 (10.3) | 93 (46.5) | 138 (21.6) | 0.000** |
| No | 394 (89.7) | 107 (53.5) | 501 (78.4) | |
| Restrict | ||||
| Yes | 385 (87.7) | 192 (96.0) | 577 (90.3) | 0.000** |
| No | 54 (12.3) | 8 (4.0) | 62 (9.7) | |
| Opioid exposure | ||||
| Yes | 16 (3.6) | 12 (6.0) | 28 (4.4) | 0.128 |
| No | 423 (96.4) | 188 (94.0) | 611 (95.6) | |
| Dexmedetomidineor exposure | ||||
| Yes | 18 (4.1) | 22 (11.0) | 40 (6.3) | 0.001** |
| No | 421 (95.9) | 178 (89.0) | 599 (93.7) | |
| Benzodiazepine exposure | ||||
| Yes | 72 (16.4) | 66 (33.0) | 138 (21.6) | 0.000** |
| No | 367 (83.6) | 134 (67.0) | 501 (78.4) | |
| LOS | 0.000** | |||
| 1-2 | 183 (41.7) | 32 (16.0) | 215 (33.6) | |
| 3-4 | 120 (27.3) | 48 (24.0) | 168 (26.3) | |
| 5-6 | 69 (15.7) | 29 (14.5) | 98 (15.3) | |
| > 7 | 67 (15.3) | 91 (45.5) | 158 (24.7) | |
| PRISM IV Score | 0.000** | |||
| 1-6 | 376 (86.4) | 93 (46.7) | 469 (74.0) | |
| 7-11 | 53 (12.2) | 86 (43.2) | 139 (21.9) | |
| ≥ 12 | 6 (14.0) | 20 (10.1) | 26 (4.1) | |
| CRP (mg/L) | 0.001** | |||
| < 10 | 143 (32.6) | 40 (20.0) | 183 (28.6) | |
| 10-50 | 261 (59.5) | 131 (65.5) | 392 (61.3) | |
| > 50 | 35 (8.0) | 29 (14.5) | 64 (10.0) | |
| Duration of Infection | 0.81±1.86 | 4.4±7.60 | 0.000** | |
| Duration of Hypoxia | 0.53±1.46 | 3.14±6.19 | 0.000** |
P < 0.05;
P < 0.01.
CRP: C-reactive protein; LOS: Length of stay; PRISM IV Score: Pediatric Risk of Mortality IV Score; Duration of Hypoxia: Sum of days of hypoxia during ICU stay; Duration of Infection: Sum of days of infection during ICU stay.
Risk factors
As shown in Table 2, a single delirium phenotype was present in only 51 (25.5%) of the 200 children with ICU delirium, two phenotypes account for 42%, whereas three or more phenotypes were present among 47 (23.5%) delirium patients. Hypoxic delirium was the most common type (61%).
Table 2.
Univariate analysis of delirium with different clinical phenotypes (n = 639)
| Clinical Phenotype | Overall Cohort (n = 639) n (%) | Never deliriums (n = 439) n (%) | Ever deliriums (n = 200) n (%) | F | P Value |
|---|---|---|---|---|---|
| Hypoxic1 | 100.28 | 0.000** | |||
| No | 426 (66.7) | 348 (79.3) | 78 (39.0) | ||
| Yes | 213 (33.3) | 91 (20.7) | 122 (61.0) | ||
| Septic2 | 16.01 | 0.000** | |||
| No | 532 (83.3) | 383 (87.2) | 149 (74.5) | ||
| Yes | 107 (16.7) | 56 (12.8) | 51 (25.5) | ||
| Metabolic3 | |||||
| No | 463 (72.5) | 369 (84.1) | 94 (47.0) | 94.53 | 0.000** |
| Yes | 176 (27.5) | 70 (15.9) | 106 (53.0) | ||
| Sedative-associated4 | |||||
| None | 367 (57.4) | 273 (62.2) | 94 (47.0) | 23.18 | 0.000** |
| No benzodiazepines | 134 (21.0) | 94 (21.4) | 40 (20.0) | ||
| Benzodiazepines | 138 (21.6) | 72 (16.4) | 66 (33.0) | ||
| co-exist | 140.15 | 0.000** | |||
| 1 type | 235 (36.8) | 184 (41.9) | 51 (25.5) | ||
| 2 types | 142 (22.2) | 58 (13.2) | 84 (42.0) | ||
| 3-4 types | 73 (11.4) | 26 (5.9) | 47 (23.5) | ||
| unclassified | 189 (29.6) | 171 (39.0) | 18 (9.0) |
P < 0.01.
Hypoxia (PaO2 < 80 mmHg) or shock.
Known sepsis or systemic inflammatory response syndrome criteria.
Blood urea nitrogen > 6.4 mmol/L or serum creatinine > 62 μmol/L.
Receipt of benzodiazepine or propofol or dexmedetomidine.
Multivariable logistic regression model for risk factors of ICU pediatric delirium is shown in Table 3. The risk of ICU delirium in critically ill children with mechanical ventilation is 3.78 times that of non-mechanical ventilation (95% CI, 2.25-6.35), and the risk of delirium in children with metabolic dysfunction is 3.73 times that of metabolic function (95% CI, 2.08-6.71). The risk of delirium in PICU patients with high PRISM IV score is 2.2 times that of children with low PRISM IV score (95% CI, 1.42-3.41). Additionally, age of children, hypoxia (OR, 2.69; 95% CI, 1.53-4.71), duration of infection (OR, 1.22; 95% CI, 1.10-1.36), LOS and CRP are independent risk factors.
Table 3.
Multivariate logistic regression result of risk factors (n = 639)
| Variable | B | S.E, | Wald | P Value | OR | 95% C.I. | |
|---|---|---|---|---|---|---|---|
|
| |||||||
| lower limit | upper limit | ||||||
| Age | -0.37 | 0.11 | 12.11 | 0.001** | 0.69 | 0.56 | 0.85 |
| Mechanically ventilated | 1.33 | 0.26 | 25.32 | 0.000** | 3.78 | 2.25 | 6.35 |
| LOS | 0.09 | 0.03 | 12.99 | 0.000** | 1.10 | 1.04 | 1.16 |
| Hypoxia | 0.99 | 0.29 | 11.90 | 0.001** | 2.69 | 1.53 | 4.71 |
| Metabolic dysfunction | 1.32 | 0.30 | 19.36 | 0.000** | 3.73 | 2.08 | 6.71 |
| PRISM IV Score | 0.79 | 0.22 | 12.49 | 0.000** | 2.20 | 1.42 | 3.41 |
| CRP | 0.01 | 0.00 | 8.60 | 0.003** | 1.01 | 1.00 | 1.02 |
| Duration of Infection | 0.20 | 0.05 | 13.83 | 0.000** | 1.22 | 1.10 | 1.36 |
| constant | -3.38 | 0.59 | 33.04 | 0.000 | 0.03 | ||
P < 0.01.
CRP: c-reactive protein; LOS: Length of stay; PRISM IV Score: Pediatric Risk of Mortality IV Score; Duration of Infection: Sum of days of infection during ICU stay.
Figure 1 shows the area under an ROC curve for combination CRP with duration of infection. ROC curve analysis revealed that the area under ROC curve (AUC) of combination CRP with duration of infection on predicting delirium occurrence was 0.81, when the cut-off value was over 0.28, the sensitivity was 75%, and the specificity was 76%. The predicted results of the independent risk factors were in good agreement with the actual occurrence of ICU pediatric delirium. The combination CRP with duration of infection had good predictive performance.
Figure 1.
Predictive efficacy of duration of infection and CRP for delirium. AUC: 0.81; Sensitivity: 0.75; Specificity: 0.76.
Discussion
Delirium is caused by a significantly large range of brain dysfunctions rather than specific local brain disorders. It is a reversible response of brain tissue to hypoxia, infection, metabolic and endocrine imbalances, and certain drugs. The study results showed that age, mechanically ventilated, LOS, hypoxia, metabolic dysfunction, PRISM IV score, CRP, and duration of infection were the risk factors for ICU pediatric delirium.
Hypoxia was one of the major risk factors for delirium in ICU [1]. Despite the association of hypoxia with pediatric delirium has not been fully explored in children, studies in adults have reported conflicting effects of hypoxia on both the occurrence and the development of delirium [23-26]. Lopez et al. [27] found that hypoxia was not an independent risk factor for postoperative delirium, while intraoperative hypoxia cerebral reperfusion was a risk factor. Hypoxia is able to cause edema, brain tissue damage and central nervous system disability, which can result in a decrease in the synthesis and release of acetylcholine, and an increase in dopamine concentration and delirium.
Multivariable logistic regression analysis indicated that elevated c-reactive protein and duration of infection were independent risk factors for PICU delirium. The neuroinflammatory hypothesis represented by Cerejeira et al. [20] reported that the peripheral inflammatory response caused by infection or surgery could induce the activation of brain parenchymal cells, promote the expression of inflammatory markers in the central nervous system, and lead to neuronal and synaptic dysfunction, which in turn led to delirium. Hoogland et al. included a systematic review [28] of 51 animal experiments, and their conclusions supported this hypothesis. Among critically ill children suffering from infectious or inflammatory diseases, it was found that PICU patients had the highest prevalence of delirium [10]. Nevertheless, Dechnik et al. [29] found that there was no association between CRP levels and ICU pediatric delirium. In addition, delirium was also thought to be secondary complication of systemic infection [30] and regarded as a result of neuroinflammation in the brain with associated release of brain cytokines causing direct neuronal damage [18]; infection may lead to inflammation stress, and finally increases the prevalence of delirium.
The severity of the illness affected the occurrence of ICU pediatric delirium. In this study, the scores were divided into three groups: safe observation group (1-6), boundary risk group (7-11), high risk group (more than 11). Higher PRISM IV scores showed trends towards more delirium (OR, 2.02; 95% CI, 1.42-3.41; P = 0.000). The reason for this result may be that as the PRISM IV score of ICU patients increases, the function of various organs decreases, including a decline in central cognitive function and executive ability. In addition, the critically ill children have excessive stress response, which leads to neuro-endocrine disorders and developes ICU pediatric delirium. Therefore, the management of critically ill children should be strengthened and improved. Intervention and treatment of the primary disease should take place as soon as possible to improve the functional status of key organs and minimize the risk of delirium [26].
There are some limitations in the research. First, it’s a retrospective observational study and can only suggest an association and not establish causality. While reporting the independent risk factors of ICU pediatric delirium, we did not present intraoperative cerebral oxygenation, the degree of hypoxia, infection and metabolic dysfunction. Therefore, the relationship should be further examined in future studies. Second, there’re some other factors that may lead to the occurrence of delirium, such as sleep disturbance and deprivation, sedative and analgesia drugs, and family members visiting, which are not included in our study. Finally, the study was conducted in a single hospital in Shanghai, so the conclusions may not be widely generalizable. Multi-location studies are needed to validate the independent risk factors of ICU pediatric delirium.
Conclusions
In conclusion, this study demonstrated that age, PRISM IV score, ICU retention time, metabolic dis-function, duration of infection, hypoxia, and mechanical ventilation were the independent risk factors for ICU pediatric delirium. These important and notable findings deserve more consideration when it comes to pathophysiology and the treatment that will determine its practical and clinical benefit in critical care pediatric patients. We suggest that active preventive measures should be taken to reduce the occurrence of PICU delirium.
Acknowledgements
Clinical Trial Registry Number: ChiCTR1800019825 (date of clinical registration: 30/11/2018). This research was conducted at Xinhua Hospital of Shanghai Jiao Tong University. We would like to thank the patients and their families who participated in the investigation and acknowledge all PICU staffs of Xinhua Hospital for the data collection. This research received support from Foundation of Shanghai Municipal Education Commission-Gaoyuan Nursing Grant (Hlgy1804dxk). The funding bodies played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. This study was approved by the Ethics Committee of Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine (approval number: XHEC-C-2018-097). All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee, as well as the 1964 Helsinki declaration and its subsequent amendments or comparable ethical standard. The guardians of enrolled children gave written informed consents to participate this research project.
Disclosure of conflict of interest
None.
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