Predictive value of ANE-SS combined with ferritin and DIC scores for mortality Risk in children with acute necrotizing encephalopathy

Introduction

Acute necrotizing encephalopathy (ANE) in children is a rare neurological disorder induced by infection, with a mortality rate of up to 30% (1-3). The disease has an abrupt onset and can progress rapidly, making it a significant cause of mortality and disability in children following influenza or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections (4,5). Early identification of prognostic risk factors and timely intervention are crucial for reducing mortality rates and mitigating long-term neurological impairment. However, there is still lack of clarity surrounding ANE, and reliable prognostic indicators are yet to be sufficiently defined.

In 2015, Yamamoto et al. introduced the Acute Necrotizing Encephalopathy Severity Score (ANE-SS) (6), which consists of five components: age, shock, brainstem involvement, platelet count, and cerebrospinal fluid protein levels. This score was developed to aid in risk stratification for ANE. Subsequently, Lim et al. demonstrated that a high ANE-SS was closely associated with increased mortality and severe disability rates (7). However, another study indicated that the overall accuracy of the ANE-SS in predicting mortality was lower compared to that of shock when used as an independent predictor (8). This suggests that the other components of the score do not substantially enhance mortality risk prediction.

Recent studies have identified additional high-risk factors affecting ANE prognosis (9-12), such as procalcitonin (PCT), ferritin and elevated levels of various pro-inflammatory cytokines, including interleukin (IL)-6, tumor necrosis factor-alpha (TNF-α), IL-10, IL-15, and Interferon-gamma (IFN-γ). These markers may play significant roles in the disease’s pathogenesis and prognosis. Furthermore, elevated serum transaminase levels, reduced platelet counts (PLT), and coagulation dysfunction are also commonly associated with poor outcomes (13,14).

Despite the established significance of these markers in assessing ANE severity and prognosis of ANE, it remains unclear whether combining them with the ANE-SS can improve predictive accuracy. Therefore, this study aims to evaluate the mortality risk factors in children with ANE and their predictive value, while also exploring the potential benefits of integrating the ANE-SS with clinical indicators to enhance prognostic accuracy. We present this article in accordance with the STROBE reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-24-416/rc).

Methods

Patient population

A retrospective analysis was conducted on children diagnosed with ANE who were admitted to the Pediatric Intensive Care Unit (PICU) of Beijing Children’s Hospital, affiliated to Capital Medical University, between January 2016 and May 2024. The diagnosis of ANE was made according to the criteria established by Mizuguchi et al. (1).

Inclusion criteria were as follows: (I) patients aged between 29 days and 18 years; (II) acute encephalopathy following a febrile illness, characterized by rapid deterioration in consciousness and the onset of convulsions; (III) cranial imaging consistently revealing symmetric, multifocal brain lesions, predominantly involving the bilateral thalami, with possible extension to the cerebral periventricular white matter, internal capsule, putamen, upper brainstem tegmentum, and cerebellar medulla; (IV) cerebrospinal fluid (CSF) analysis typically showing elevated protein levels without pleocytosis; (V) elevated serum aminotransferases observed to varying degrees, but no hyperammonemia; (VI) exclusion of other resembling diseases. Children with incomplete basic information, missing clinical data, or those lost to follow-up were excluded from the study. The patients were then divided into two groups based on their 28-day survival outcomes: survival and non-survival groups.

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study protocol was reviewed and approved by the Ethics Committee of Beijing Children’s Hospital (No. 2019-k-198) and informed consent was taken from all the patients’ parents.

Data collection

Demographic data, clinical manifestations, laboratory results, neuroimaging findings, treatment modalities, and clinical outcomes were obtained from the medical records system. Inflammatory markers within 12 hours of admission, including PCT, IL-6, C-reactive protein (CRP), and ferritin, were recorded. CSF analysis, coagulation parameters—such as D-dimer (DD), activated partial thromboplastin time (APTT), prothrombin time (PT), fibrinogen (Fib), and thrombin time (TT) - along with liver enzyme levels, were also collected. The ANE-SS and DIC scores were assessed at admission, and the 28-day prognosis was documented.

The primary therapeutic strategies for ANE included high-dose methylprednisolone combined with intravenous immunoglobulin (IVIG), with some patients receiving plasma exchange (PE) therapy. Pulsed steroid therapy was defined as an initial dose of ≥20 mg/kg/day, while the IVIG dose was 2 g/kg, administered via intravenous infusion over 2 to 5 days.

Related definition standards

ANE-SS: The ANE-SS scoring system, which ranges from 0 to 9 points, categorizes patients into three risk groups (6): low risk (0–1 points), medium risk (2–4 points), and high risk (5–9 points). The weighted scores of individual items are detailed in Table 1.

Diagnosis of DIC: According to the Chinese Disseminated Intravascular Coagulation Scoring System (CDSS), a score of 7 or higher is diagnostic for DIC (15). The criteria of CDSS is described in Table 2.

Shock was defined as persistent hypotension despite fluid administration, requiring initiation of vasoactive therapy (16).

Statistical analysis

Statistical analysis was conducted using SPSS 27.0 software (IBM Corp., Armonk, NY, USA). Continuous variables were presented as median (interquartile range), and group comparisons were conducted using the Mann-Whitney U test. Categorical variables were analyzed using the Chi-squared test or Fisher’s exact test. Multivariate logistic regression analysis was applied to identify independent risk factors for mortality. The predictive value of each indicator was evaluated using receiver operating characteristic (ROC) curves, determining the area under the curve (AUC), optimal cutoff values, sensitivity, and specificity. A P value of <0.05 was considered statistically significant.

Results

Methods for selecting enrolled pediatric patients

A total of 89 children with clinical manifestations of ANE were admitted during the study period. Among these, 3 cases lacked imaging examination or typical imaging changes, 13 cases did not undergo cerebrospinal fluid examination, and 2 cases suspected of having inherited metabolic diseases were excluded. Additionally, 15 patients were excluded because of missing laboratory data within the first 12 hours of admission. Ultimately, 56 patients with confirmed ANE were included in the study (Figure 1).

Figure 1 Screening flowchart for the enrollment of children with acute necrotizing encephalopathy. PICU, pediatric intensive care unit.

Comparison of clinical characteristics between the two groups

Based on the 28-day post-discharge outcomes, the patients were divided into a survival group (n=27) and a non-survival group (n=29), reaching in an overall mortality rate of 51.8%. The clinical characteristics of ANE patients with different outcomes are compared in Table 3. In this study, 80.4% (45/56) of the patients tested positive for respiratory pathogen antigen or nucleic acid, with the predominant infections being influenza A virus (39.3%) and SARS-CoV-2 (30.4%). Genetic testing was performed in 25 patients, revealing Ran Binding Protein 2 (RANBP2) mutation in 5 cases (20%). There were no significant differences in age, gender, or pathogen between the two groups (P>0.05). However, the non-survival group had a significantly higher proportion of patients with shock, DIC, and multiple organ dysfunction syndrome (MODS) at admission compared to the survival group (P<0.05). Brainstem involvement was observed in 32 patients (57.1%), with no statistically significant difference between these two groups (69% vs. 44.4%, P=0.06). The immunotherapy regimens received by both groups were largely consistent.

Univariate analysis of prognostic factors

At admission, the median score of ANE-SS (5 vs. 3) and DIC (6 vs. 3) were significantly higher in the non-survival group (P<0.001) (Table 3). Laboratory examination results showed that the levels of ferritin, PCT, IL-6, APTT, PT, DD, and CSF protein were significantly elevated in the non-survival group (P<0.05). There were no significant differences in the levels of CRP, PLT, AST and ALT between the two groups (P>0.05) (Table 4).

Multivariate analysis of prognostic variables

To avoid interaction between variables, ferritin, PCT, IL-6, ANE-SS, and DIC scores were ultimately included in the multivariate analysis. ROC curve analysis was performed to determine the optimal cutoff values for ferritin (≥2,109 vs. <2,109 ng/mL), PCT (≥4.1 vs. <4.1 ng/mL), IL-6 (≥14.1 vs. <14.1 pg/mL), ANE-SS (≥4.5 vs. <4.5), and DIC scores (≥5.5 vs. <5.5) (Figure 2). These predictors were then converted into binary variables based on the optimal cutoff values and included in a multivariate regression model, which identified ferritin, ANE-SS, and DIC scores as independent risk factors for mortality (Table 5).

Figure 2 The AUC and the best cut-off value of the variables for predicting 28-day mortality. AUC, area under the curve; CI, confidence interval; DIC, disseminated intravascular coagulation; ANE-SS, Acute Necrotizing Encephalopathy Severity Score; PCT, procalcitonin; IL-6, interleukin-6.

Analysis of predictive performance of independent risk factors and combined ANE-SS indicators

Table 6 presents the AUC, sensitivity, and specificity for ferritin, DIC scores, ANE-SS, and their combined indicators in predicting outcomes. All predictor variables had an AUC greater than 0.7, with significant differences (P<0.05). Among individual predictors, ferritin had the highest AUC (0.827, 95% CI: 0.657–0.997) for predicting 28-day mortality in ANE patients, exhibiting higher sensitivity and specificity compared to ANE-SS and DIC scores. In pairwise combinations, ANE-SS combined with ferritin had the highest sensitivity, while ANE-SS combined with DIC scores displayed the highest specificity. When combining ferritin, DIC scores, and ANE-SS to predict 28-day mortality in ANE patients, the AUC reached 0.99 (95% CI: 0.965–1.000), with a sensitivity of 92.3% and a specificity of 100%. This result demonstrates superior predictive performance compared to individual or pairwise combinations of these indicators.

Discussion

This study systematically evaluated the high-risk factors associated with mortality in children with ANE, with univariate analysis revealing that IL-6, PCT, ferritin, APTT, PT, DD, CSF, and DIC scores were linked to an increased risk of death. Multivariate analysis identified ferritin, ANE-SS, and DIC scores as independent predictors of mortality in ANE, with areas under the ROC curve of 0.827, 0.782, and 0.773, respectively. Compared to ANE-SS (sensitivity 75.9%, specificity 66.7%) and DIC scores (sensitivity 60.7%, specificity 81.5%), ferritin exhibited the highest sensitivity (84.6%) and specificity (87.5%). The combination of ANE-SS with ferritin and DIC scores yielded an AUC of 0.990, demonstrating superior predictive performance compared to individual indicators.

As an important indicator of iron storage and inflammatory status, ferritin levels are closely associated with conditions such as sepsis, systemic inflammatory response syndrome (SIRS), MODS, and macrophage activation syndrome (MAS) (17,18). Ferritin levels in critically ill patients correlate with the severity of underlying conditions and their prognosis (19). In pediatric patients with severe sepsis, Garcia et al. demonstrated that ferritin levels above 500 ng/mL increase the risk of death by threefold (20). For critically ill COVID-19 patients, ferritin levels exceeding 3,000 ng/mL are associated with a 16-fold increase in the risk of death (21). Similarly, Lee et al. reported that ferritin may serve as a potential prognostic marker in ANE patients, with levels exceeding 1,823 ng/mL associated with an approximately eightfold increased risk of poor neurological outcomes (10). In this study, the average ferritin level in children with ANE was 1,270.5 ng/mL, with significantly higher levels in the non-survival group compared to the survival group. Additionally, ROC curve analysis identified 2,109 ng/mL as the optimal cutoff value for ferritin levels, indicating that the level above 2,109 ng/mL is associated with approximately a tenfold increased risk of death (OR=10.15, 95% CI: 1.64–62.76).

Various pro-inflammatory cytokines, such as IL-6, TNF-α, IL-1β, IL-12, and IFN-γ, could stimulate excessive activation of hepatocytes, Kupffer cells, macrophages, and T cells, leading to ferritin synthesis (22). Elevated ferritin levels not only directly promote excessive cytokine secretion, but also indirectly act on macrophages by activating signaling pathways, such as NF-κB, increasing circulating cytokine concentrations and exacerbating the inflammatory response (23). Therefore, hyperferritinemia is not only a consequence of the cytokine storm but may also further contribute to its progression (24). In the current study, more than half (69%) of ANE patients exhibited elevated ferritin levels (>500 ng/mL), and approximately one-third (34.5%) had ferritin levels >3,000 ng/mL, indicating a “hyperferritinemia syndrome”. This finding suggests that ferritin may serve as a key indicator for predicting the severity of the cytokine storm in ANE. It is worth noting that hyperferritinemia (≥500 ng/mL) is also a crucial diagnostic criterion for HLH, and cases of HLH combined with ANE have been reported in previous studies (25,26). In our study, none of the patients met the diagnostic criteria for HLH (27). Despite its rarity, clinicians should exercise caution in distinguishing mixed cases of ANE and HLH.

Coagulation system dysfunction is a critical pathophysiological feature of ANE. Prognostic studies of ANE have shown that as levels of DD, APTT, and PT increase, so does the mortality rate, which is consistent with the results of this study (13,28). The current study found that 67.9% of ANE patients exhibited coagulation disorders, with 28.6% experiencing thrombocytopenia early in the disease course. A platelet count below 100,000/uL is commonly considered a predictor of poor prognosis in ANE (6). However, in this study, platelet levels at admission did not significantly differ between the two groups, suggesting that the initial platelet count may have limited predictive value for assessing mortality risk in ANE. Further research is needed to assess the role of dynamic platelet levels in disease assessment and prognosis.

The study identified DIC scores as a valuable tool for assessing prognosis in children with ANE. DIC scores above 5.5 were associated with relative risk of death of 7.9 (1.58 to 39.76, P=0.012). The pathophysiological mechanisms of ANE-related DIC are likely multifactorial, with virus-induced cytokine storms being a key contributor to the hypercoagulable state. In addition to the activation of coagulation and inhibition of fibrinolysis, activated leukocytes, platelets, and vascular endothelial cells also exacerbate inflammation and coagulation disorders, contributing to the thrombus formation process (29). Therefore, for ANE patients with high-risk coagulation dysfunction, early aggressive anticoagulant therapy may be an effective measure to reduce mortality. According to Japanese “Guidelines for the Diagnosis and Treatment of Acute Encephalopathy in Childhood” (30), heparin 100 to 150 IU/kg/day is administered with continuous infusion until the end of methylprednisolone pulse therapy to prevent thrombus formation due to hypercoagulation. In our study, approximately 75% of patients received prophylactic anticoagulation upon admission. Although there was no significant difference in mortality between children who received anticoagulation and those who did not (52.4% vs. 42.9%, P=0.758), we emphasize the potential significance of anticoagulation in ANE management and advocate for future research to provide stronger evidence to guide clinical practice.

This study further confirmed that ANE-SS serves as an independent predictor of mortality in ANE. When ANE-SS exceeds 4.5, the relative risk of mortality increases by 4.4 times. ANE-SS is a widely used comprehensive predictive score in clinical practice and is theoretically more reliable than single indicators. However, its ability to predict mortality risk is relatively lower compared to ferritin and DIC scores. Additionally, while combining ANE-SS with ferritin or DIC scores results in a higher AUC for predicting mortality risk compared to individual measures, sensitivity and specificity decline to varying degrees. Nevertheless, the combination of all three compensates for the limitations of individual predictors, likely due to the consideration of both inflammatory and coagulation mechanisms involved in ANE.

The limitations of this study include a relatively small sample size, lacking some data due to its retrospective design, and a narrow range of clinical predictive indicators, which may have led to the underestimation of some laboratory parameters. Additionally, this study only focused on disease status at admission and did not account for dynamic changes that may occur during hospitalization. Future studies should aim to increase the sample size and continuously monitor inflammatory and coagulation markers to better assess the prognosis and treatment response in ANE.

Conclusions

The current study found that the combination of ANE-SS score, ferritin and DIC scores holds significant predictive value for the prognosis of ANE. The concurrent evaluation of these three indicators enhances the predictive efficacy for the prognosis of children with ANE.

Acknowledgments

Funding: This work was supported by Capital’s Funds for Health Improvement and Research of Beijing Children’s Hospital, Capital Medical University (No. 2020-2-2094) and Beijing Research Ward Project (No. BCRW202101).

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-24-416/rc

Data Sharing Statement: Available at https://tp.amegroups.com/article/view/10.21037/tp-24-416/dss

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-24-416/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-24-416/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study protocol was reviewed and approved by the Ethics Committee of Beijing Children’s Hospital (No. 2019-k-198) and informed consent was taken from all the patients’ parents.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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