Abstract
Background/Aim: Cerebral edema is common in patients with sepsis-associated encephalopathy (SAE) and is a major cause of elevated intracranial pressure (ICP); however, the relationship between elevated ICP and SAE is unclear. The aim of this study was to investigate the association between optic nerve sheath diameter (ONSD), a surrogate of ICP, and the incidence of SAE. Patients and Methods: A prospective observational study was performed in a medical–surgical adult intensive care unit (ICU). All patients in the ICU who were consecutively diagnosed with sepsis during the study period were evaluated for eligibility. Ultrasound measurements of ONSD were performed within 6 h of enrollment and every two days thereafter until the patient developed SAE. Clinical and blood test data were collected throughout this period. Patients underwent a daily conscious and cognitive assessment. SAE was diagnosed as delirium or Glasgow Coma Scale (GCS) <15 points. Multivariate modified Poisson regression analysis was performed to identify risk factors for SAE. Results: A total of 123 patients with sepsis were included in the analysis. 58 patients (47.2%) developed SAE. The levels of ONSD0 (the first measured value) and ONSDmax (the maximum measured value) in the SAE group were significantly higher than those in the non-SAE group (5.23±0.52 mm vs. 5.85±0.54 mm for ONSD0 and 5.41±0.46 mm vs. 6.09±0.58 mm for ONSDmax, respectively; all p-values <0.001). The area under the curves (AUCs) for the ONSD0 and ONSDmax values in predicting SAE were 0.801 (95%CI=0.723-0.880, p<0.001) and 0.829 (95%CI=0.754-0.903, p<0.001), respectively. A higher ONSD0 level was significantly associated with an increased risk of SAE (adjusted risk ratio 3.241; 95%CI=1.686-6.230, p<0.001). Conclusion: The levels of ONSD correlate with risk of SAE, indicating that increased ICP level is an independent risk factor for the development of SAE. Dynamic monitoring of ONSD/ICP has a high predictive value for SAE. Measures to prevent increases in ICP are helpful to reduce the incidence of SAE in sepsis patients.
Sepsis-associated encephalopathy (SAE) is a diffuse brain dysfunction caused by sepsis, which is not due to central nervous system infection (1, 2), and it is the most common cause of encephalopathy in critically ill patients (3). The neurological anomalies of SAE vary from sickness behavior to delirium and coma (1). SAE is associated with many adverse intensive care unit (ICU) outcomes (4-8) and long-term cognitive impairment (9). However, the pathophysiology of SAE remains incompletely understood, and there is no definitive statement of risk factors for this encephalopathy and no targeted pharmacological treatment.
Intracranial hypertension is a common cause of consciousness disorders. Patients with sepsis can present one or more pathophysiological changes that can cause intracranial hypertension due to cerebral edema (10-12), intraperitoneal hypertension (13), and fever. Assessing the impact of elevated intracranial pressure (ICP) on SAE will be particularly promising offering the possibility of targeted prevention and intervention in the occurrence and development of SAE. The correlation between ICP and SAE has been investigated in several studies (14-16), but elevated ICP level has not been proven to be a risk factor for SAE. Therefore, we conducted this prospective cohort study to evaluate the relationship between ICP and the risk of SAE using ultrasonographic (USG) measurement of optic nerve sheath diameter (ONSD), a surrogate of ICP, as USG is a non-invasive technique of monitoring ICP that is easily accessible at the bedside.
Patients and Methods
This study was undertaken with the permission of the local authority and the Medical Ethics Committee of the People’s Hospital of Beihai. The Ethics Committee of the Hospital reviewed and approved the study on August 18, 2019 (Approval number: 2019002). All experiments were performed in accordance with the ethical standards of the 1995 Declaration of Helsinki, as revised in Tokyo (2004). A written informed consent form for all patients enrolled in this study was prepared. This study has been structured following the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) guidelines for cohort studies (17).
Settings and patients. This prospective observational cohort study was conducted in a 20-bed medical–surgical adult ICU of an academic tertiary level hospital. The recruitment period was from June 2020 until April 2022. Patients (18 to 89 years of age) diagnosed with sepsis were screened for eligibility. Sepsis was diagnosed according to the criteria from the 2016 International Sepsis Definitions Conference (18). Informed consent was obtained from eligible patients or guardians who were willing to participate in the study. The exclusion criteria: (i) Pre-existing or current suffering from mental, cognitive, or consciousness disorders, including encephalopathy of other causes, dementia, psychosis, sleep disorders, drug addiction, alcohol withdrawal delirium and other; (ii) Average daily intake of alcohol greater than 30 g; and (iii) Having central nervous system infection. The withdrawal criteria: (i) Inability to obtain a clear image of the ONSD because the eye was injured, or the eyeballs were significantly sunken or other anatomical variations; (ii) Some baseline data unavailable or missing; (iii) Patients were persistently deeply sedated during the follow-up period and could not be identified as having SAE; and (iv) Developed encephalopathy due to other or unknown causes during the follow-up period. The sample size estimation was based on the incidence of SAE in sepsis patients and the principle of 10 outcome events per variable (19-21). According to the previous reports on the incidence (6-8, 22) and the possible risks (4, 5, 22) of SAE, we presumed that four confounders should be included, and the incidence of SAE would be 50%, we aimed to enroll 100 sepsis patients and 50 ICU patients with SAE.
USG measurement of ONSD. ONSD was performed by experienced operators who only knew the ONSD measurement protocol using a Myriad M7 ultrasound (Shenzhen Mindray Bio-Medical Electronics Co., Ltd., Shenzhen, Guangdong, PR China). The patient was in a supine position with the head of the bed raised 30° above the horizontal line. A piece of transparent protective film was applied on the patient’s eyeball after closing the eyes. The ONSD was measured at the retrobulbar 3 mm position using B-scan ultrasound with a linear array probe at 7.5 Hz (Shenzhen Mindray Bio-Medical Electronics Co., Ltd.). Both eyes were measured twice horizontally and vertically. The ONSD of two eyeballs was measured 8 times in total, and the average value was taken, accurate to 0.1 mm.
Image requirements for USG ONSD (23, 24): (i) Sonographic contrast between the optic nerve and the arachnoid must be obvious; (ii) Ideal views of the nerve (single low echogenic band) demonstrating the point of its penetration into the vitreous (circular hypoechoic region) without the interposition of a thick echogenic layer of the posterior sclera, that is, “dark meets dark”; (iii) The outer edge of the arachnoid (retrobulbar hyperechoic striped bands) must be identifiable. The optic nerve sheath was measured as the distance between the outer edge of the arachnoid or the optic nerve to the transition of the hyperechoic retrobulbar fat.
Data collection. Baseline data on patients were collected at enrollment, including demographics, type of ICU admission, chronic underlying conditions, medication history, and presence or absence of maintenance hemodialysis. The ONSD was first measured within 6 h of enrollment, while vital signs at that time and the recent hematological data within 24 h were recorded. Subsequently, the ONSD was reviewed every other day. The first measured ONSD was recorded as ONSD0, and the highest ONSD during the follow-up period was recorded as ONSDmax. Data collected within 24 h of enrollment included: modified acute physiology score and chronic health evaluation (APACHE) II score (excluding neurological scores), modified sequential organ failure assessment (SOFA) score (excluding the neurological component), and organs in failure. Organ failure was defined as a score >2 for each component of the SOFA scale. The site of infection, pathogenic microorganisms, and treatment measures such as analgesia and sedation, blood transfusions, mechanical ventilation, vasopressors, and renal replacement were collected during the follow-up period. Deep sedation was defined as the use of sedative or analgesic, anesthetic drugs resulting in a Richmond Agitation-Sedation Scale (RASS) score of −3 to −5. All patients were asked to implement an early mobilization strategy. The follow-up period was defined from inclusion to the onset of SAE or departure from ICU (including transfer to the general ward, discharge, or death).
Outcomes. The outcome was whether SAE occurred during the ICU stay. SAE was defined as delirium or GCS <15 points. Delirium was defined as any positive Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) examination (25) during the ICU stay. GCS score and RASS score were evaluated every 8 h in patients who did not use sedative or analgesic drugs. CAM-ICU screening was performed when the RASS score fluctuated within 24 h and was ≥−2. A positive result was diagnosed as delirium. Patients on sedative and analgesic drugs were scored hourly for RASS. When the RASS score fluctuated, the influence of analgesic and sedative drugs and other causes on the RASS score should be excluded before performing the GCS score and delirium assessment. Patients whose consciousness or mental status was affected by drugs or other factors were not included in the final analysis.
Statistical analysis. Statistical analysis was conducted using SPSS version 26.0 (IBM Inc. Armonk, NY, USA). Receiver operating characteristic (ROC) curve analysis was used to assess the effectiveness of ONSD0 and ONSDmax in predicting SAE and to determine a cut-off value with optimal sensitivity and specificity. ONSD0 and ONSDmax were classified into two levels according to their cut-off values, respectively: lower level (equal to or below the cutoff value) and higher level (above the cutoff value). Continuous variables are presented as mean±standard deviation (SD) or median (interquartile range). The independent Student’s t-test was used for normally distributed continuous variables, and the nonparametric Mann–Withney U-test was used for abnormally distributed continuous variables. Categorical variables were compared with the Pearson Chi-square test or Chi-square test continuity correction or Fisher exact test. To assess the impact of increased ICP on SAE, multivariate modified Poisson regression and Logistic regression model were performed, adjusting for confounders (probable causes of both exposure and outcome). The pre-specified candidate confounders in the models were based on the literature on the likely risk factors for SAE and our clinical experience. The results of the previous studies suggest that possible risk factors (4, 5, 22) for SAE include: acute renal failure, hypoglycemia, hyperglycemia, hypercapnia, hypernatremia, Staphylococcus aureus infection, higher heart rate, blood lactate level, lower platelet count, serum sodium level, serum albumin level, pH value, APACHE II score, and age ≥65 years, shortness of breath, and thrombocytopenia (26, 27). Confounders were screened from candidate variables, baseline, and follow-up variables via the following process: (i) Comparison the difference between the two ONSD0 levels for each variable, and if the difference was statistically significant at the 0.05 alpha level, the variable was selected; (ii) The assumption of linearity between the logit (p) value of the outcome and the continuous variables was assessed using the Box-Tidwell test. If the linearity assumption was not met, the continuous variables were transformed into categorical variables. Univariate analyses (modified Poisson regression) were performed with each variable and the outcome. Variables were selected if they were significant at a 0.1 alpha level; and (iii) Variables that were statistically significant in both step one and step two were retained as confounders.
Multicollinearity was assessed by checking the Variance Inflation Factor on a multiple regression model. If there were two or more variables with higher correlation, we chose one of them. The endpoint was analyzed in a multivariate modified Poisson regression model and logistic regression model with a calculation of the adjusted risk ratio (aRR) and the adjusted odds ratio (aOR) of SAE, after adjusting confounders.
Results
The final dataset included 175 sepsis patients who met our inclusion criteria, and 141 matched the selection criteria. Of the eligible patients, 137 consented to participate in the study. Fourteen patients were withdrawn during the follow-up. The final study samples consisted of the remaining 123 patients, 58 of whom developed SAE, resulting in an SAE incidence of 47.2% (58/123) (Figure 1).
Flowchart of this study. The number of enrolled cases according to diagnosis. Details are given in the text. ICU: Intensive care unit; ONSD: optic nerve sheath diameter; SAE: sepsis-associated encephalopathy.
Among patients who developed SAE, the median time to diagnosis of SAE was 3.9±2.7 days after enrollment. In 77.6% of SAE cases (45/58), SAE occurred within 2 days after ONSDmax. The levels of ONSD0 (the first measured value) and ONSDmax (the maximum measured value) in the SAE group were significantly higher than those in the non-SAE group (5.23±0.52 mm vs. 5.85±0.54 mm for ONSD0 and 5.41±0.46 mm vs. 6.09±0.58 mm for ONSDmax, respectively, p<0.001). ROC curve analysis showed that both ONSD0 and ONSDmax were good predictors of SAE with area under the curve (AUC)=0.801, 95%CI=0.723-0.880, p<0.001, and AUC=0.829, 95%CI=0.754-0.903, p<0.001, respectively (Figure 2). For the cut-off value of ONSD0 5.4 mm, we found a sensitivity of 84.5% and a specificity of 64.6%; for the cut-off value of ONSDmax 5.8 mm, the sensitivity and specificity were 74.1% and 81.5%, respectively.
Receiver operating characteristic (ROC) curve analysis for the first measured value of optic nerve sheath diameter (ONSD0) (green line) and ONSDmax (black line). The ROC curves were established based on the levels of ONSD0 and the maximum measured value of ONSD (ONSDmax) in 123 participating patients with sepsis. The area under the curve (AUC) was compared between 58 cases with SAE and 65 cases without to estimate the sensitivities and specificities of the ONSD levels. The results of ROC curves suggest that both ONSD0 and ONSDmax are good predictors of SAE with AUCs=0.801 and 0.829, respectively.
ONSD0 was divided into lower ONSD0 level (ONSD0 ≤5.4 mm) and higher ONSD0 level (ONSD0 >5.4 mm) according to the cut-off value of 0.54. There were 57 patients (57/123, 46.3%) in the lower ONSD0 level group, 12 of whom were diagnosed with SAE during ICU (21.1%), and 66 patients (66/123, 53.7%) in the higher ONSD0 level group, 46 of whom were diagnosed with SAE during ICU (69.7%) (Figure 3). The median [IQR] age in this cohort was 64 (53-75) years, with 71.5% (88/123) of patients being male. Demographics (including age, sex, and BMI) and underlying disease were similar between groups with different ONSD0 levels (Table I). C-reactive protein (CRP), blood sodium, the partial pressure of carbon dioxide (PCO2) 35-45 mmHg, deep sedation treatment, use of benzodiazepines, use of morphine, and mechanical ventilation were statistically different between the two groups. Other baseline laboratory values and follow-up period variables were similar (Table I). The ONSDmax level was classified as ≤5.8 mm and >5.8 mm according to the cut-off value of 0.58. Seventy-two patients with ONSDmax ≤5.8 mm and 51 patients with >5.8 mm. The incidence of SAE was significantly higher in patients with higher levels of both ONSD0 and ONSDmax (both p-values <0.001) (Figure 3).
Relationship between optic nerve sheath diameter (ONSD) levels and the incidence of sepsis-associated encephalopathy (SAE). ONSD0: the first measured value of ONSD; ONSDmax: the maximum measured value of ONSD.
Characteristics and outcomes of patients according to the cutoff value of the first measured value of optic nerve sheath diameter (ONSD0).
Of all variables screened, male, respiratory failure (respiration score of SOFA score >2), the partial pressure of oxygen (PO2) <60 mmHg, oxygenation index (PO2/FiO2 ratio) <200 mmHg, blood sodium ≥135 mmol/l, use of benzodiazepines, use of morphine, deep sedation, and mechanical ventilation were significantly associated with SAE using univariate modified Poisson regression analysis, p<0.10 (Table II). Since the variables of male, respiratory failure, PO2 <60 mmHg, oxygenation index <200 mmHg, and blood sodium ≥135 mmol/l did not differ significantly between ONSD0 levels, they did not become confounders. The final variables of use of benzodiazepines, use of morphine, deep sedation, and mechanical ventilation were confounders. Multicollinearity tests showed no collinearity between these variables. They were included in the multivariate modified Poisson regression analysis along with ONSD0 (Model 1). The aRR was 3.241, 95%CI=1.686-6.230, p<0.001. Other variables were not statistically significant (Table III).
Univariate modified Poisson regression of baseline and follow-up period variables with sepsis-associated encephalopathy (SAE).
Multivariate analysis adjusting for different variables.
Sensitivity analysis. First, using a multivariate logistic regression model, we analyzed whether the association between ONSD0 and SAE changes after adjusting for the confounders in Model 1. The aOR for ONSD0 was 9.623, 95%CI=3.921-23.616, p<0.001. The association indicating that ONSD0 is a risk factor for SAE remained unchanged. Second, variables that were not included in Model 1, such as sex, respiratory failure, PO2, oxygenation index, and blood sodium, were built into the model along with ONSD0, and multivariate modified Poisson regression and logistic regression analyses were performed. ONSD0 was still an independent risk factor of SAE (Table III). Additionally, respiratory failure, PO2 <60 mmHg, and blood sodium ≥135 mmol/l were found to be risk factors for SAE (Table III).
Discussion
In the present study, we showed that sepsis patients were independently associated with an increased risk of SAE after adjusting for confounders such as deep sedation, use of benzodiazepines, morphine, and mechanical ventilation. The cut-off value of ONSD0 5.4 mm and ONSDmax 5.8 mm can be used to predict the occurrence of SAE. SAE occurred within 2 days after ONSDmax measurement in 77.6% of patients in this study. We confirmed that elevated levels of ONSD, a surrogate of ICP, are an independent risk factor of SAE.
Currently there is no unified diagnostic standard for SAE, which is mainly determined based on clinical manifestations and the exclusion of encephalopathy caused by other disorders. Therefore, to ensure the accuracy of diagnosis, we set strict inclusion and exclusion criteria according to the SAE definition in this study. Delirium and GCS scores less than 15 include most symptoms of encephalopathy in terms of changes in consciousness level and content. Therefore, this study used delirium and GCS score as the diagnostic criteria. The incidence of SAE in this study was 47.2%, and it is similar to the results (43-57%) of previous studies using the same diagnostic criteria (7, 22).
The pathophysiology of SAE is still not fully understood, and several studies have explored the correlation between ICP and SAE, but there is lack of population studies for the potential impact of elevated ICP on SAE. Since the difficulty and complications of invasive ICP measurements, ONSD measured using ultrasound is now commonly used as an alternative to invasive ICP. Yang et al. (15) found that the ONSD of patients with SAE is significantly wider than that of patients without SAE or the patients in the SAE recovery period. Because that study was a cross-sectional study, it failed to demonstrate the causal relationship between the elevated ICP level and SAE in sepsis patients. The results of an animal study also showed (16) that the ONSD of the SAE group increases over time and is significantly wider than that of the control group. ONSD is positively correlated with biomarkers of brain injury, such as myeloperoxidase, neuro-specific enolase, and S100B in the SAE group. AUCs for diagnosing SAE based on the ONSD values were 0.864, 0.957, and 0.877, respectively.
Similar findings were found in humans in the present study. To minimize confounding bias, a large number of baseline and follow-up variables were screened for confounders, and we showed that elevated ICP increased the risk of SAE by both modified Poisson regression and logistic regression analyses. It has been shown that benzodiazepine use can increase the risk of delirium in critically ill patients (26-28), but its impact on SAE remains unclear. In this study, the use of benzodiazepines was statistically significant in the univariate modified Poisson regression analysis, but not in the multivariate analysis adjusted for ONSD0. In addition, we found that respiratory failure, PO2 <60 mmHg, and blood sodium ≥135 mmol/l were also risk factors for SAE in our study. These factors may be part of pathological mechanisms causing SAE besides increasing ICP.
In sepsis patients, the elevated ICP is mostly caused by vascular and cellular brain edema resulting from disruption of the blood-brain barrier and neuroinflammation. In addition, other causes and disorders can also lead ICP increase, including increased abdominal and thoracic pressure, fever, excessive infusion, cerebrovascular hypoperfusion, and hyper-perfusion. Besides the use of anti-infection measures to reduce systemic inflammatory response, measures to prevent ICP elevation in response to these triggers may reduce the incidence of SAE. Because our investigation was an observational study, future experimental studies are necessary to further validate whether increased ICP is a risk factor for SAE. For example, after taking measures to prevent increased ICP, observe whether the incidence of SAE can be reduced, and whether taking measures to decrease ICP can improve symptoms in SAE patients with widened ONSD. The results of these studies may help change the prevention strategy for SAE and enhance the prognosis of sepsis patients.
The main limitations of this study are that (i) it was a single-center study with small sample size that may have potential selection bias, and (ii) we did not observe the outcome of SAE and changes of ONSD after SAE occurred. However, Yang’s study shows that ONSD in SAE patients is smaller in the recovery period than that in the acute phase. Therefore, further research investigations are needed to determine whether the degree of change in ONSD is synchronized in all SAE patients.
Conclusion
In this study, we showed that the levels of ONSD correlate with risk of SAE, suggesting that increased ICP level is an independent risk factor for the development of SAE. Dynamic monitoring of ONSD/ICP has a high predictive value for SAE. Measures to prevent increases in ICP are helpful to reduce the incidence of SAE in sepsis patients.
Acknowledgements
The Authors would like to express our sincere gratitude to all staff members in the Department of Critical Care Medicine, Beihai People’s Hospital. This study was supported by a grant from the Science and Technology Plan Project of Beihai City (No. 202082047). The funding agency had no role in study design, data analysis, decision to publish, or preparation of the manuscript.
Footnotes
Authors’ Contributions
YL and HY equally contributed to this work. YL and HY designed the research. YL searched the literature and wrote the first draft. WY and WZ performed the clinical study and data acquisition. HY and MZ analyzed data and provided feedback for the first draft. YL, HY, and QQL conceived the project, interpreted data, and revised the article. YL obtained the funding. All Authors met the authorship criteria and have read and approved the final manuscript.
Conflicts of Interest
The Authors declare that they have no competing interests in relation to this study.
- Received June 26, 2023.
- Revision received August 1, 2023.
- Accepted August 2, 2023.
- Copyright © 2023, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).