Interleukin-6, serum albumin levels, and acute kidney injury jointly predict in-hospital mortality in pediatric COVID-19 patients

Introduction

Since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic in late 2019, the number of infections worldwide has risen dramatically (1). Clinical data indicate that most children with COVID-19 experience mild or asymptomatic cases (2,3). However, some infected children may suffer disease progression, leading to critical illness. These severe cases are often associated with complications such as acute respiratory distress syndrome (ARDS), multisystem inflammatory syndrome in children (MIS-C), multi-organ failure, asthma, and acute kidney injury (AKI), with significant variations in severity and fatality risk (4).

Interleukin-6 (IL-6) is a key proinflammatory cytokine that, when excessively expressed in severe viral infections, can trigger a cytokine storm, leading to systemic inflammatory response syndrome (SIRS), organ dysfunction, and increased mortality. In COVID-19, IL-6 not only activates humoral immunity but also regulates various immune cells, often reaching elevated levels. It promotes the release of additional inflammatory factors, exacerbating immune overactivation and increasing the risk of multiple organ dysfunction syndrome (MODS) and death. High IL-6 levels are strongly correlated with disease severity and poor clinical outcomes, making it a critical predictor of severe disease progression (5,6).

Serum albumin (ALB) is a key marker of nutritional status, inflammation, and immune function. In COVID-19, inflammation shifts hepatic protein synthesis toward acute-phase proteins, reducing ALB production. Endothelial dysfunction increases vascular permeability, causing ALB leakage into tissues, exacerbating edema, and perpetuating a cycle of inflammation and capillary permeability dysfunction. Low ALB levels are associated with persistent systemic inflammation and a worse prognosis (7).

AKI is a common and severe complication of COVID-19, particularly in cytokine storm conditions. It arises from direct viral injury to renal tubular cells, hemodynamic disturbances, inflammation, and drug toxicity. AKI is strongly linked to MODS and poor outcomes, especially in pediatric patients, in whom it increases mortality risk (8,9).

IL-6 plays a central role in AKI pathogenesis by increasing vascular permeability, promoting renal ischemia-reperfusion injury, and suppressing ALB synthesis. Meanwhile, low ALB levels exacerbate AKI by reducing colloid osmotic pressure and enhancing renal tubular toxicity. AKI further fuels systemic inflammation by impairing toxin clearance, thus creating a vicious cycle that heightens mortality risk.

While IL-6, ALB, and AKI have been studied in adult COVID-19 patients, research in pediatric patients remains limited. Most studies have focused on single markers rather than their combined effects. We hypothesized that integrating IL-6, ALB, and AKI can improve early identification of severe pediatric COVID-19 cases. Through risk stratification (low-, medium-, and high-risk groups), we aimed to assess their collective impact on inpatient mortality.

In this study, we evaluated the combined effect of IL-6, ALB, and AKI on disease progression in children with COVID-19 via a retrospective multicenter cohort analysis. Additionally, we explored their predictive value for inpatient mortality. By integrating these biomarkers and establishing risk stratification models, we aimed to enhance early identification of high-risk pediatric patients, offering data-driven strategies for timely clinical intervention.

The identification and validation of such predictive models are fundamentally rooted in robust cohort study methodologies. Large-scale, longitudinal birth cohorts, such as those investigating the links between early-life antibiotic exposure and subsequent neuropsychiatric disorders or food allergy risk, have demonstrated the profound value of these designs in elucidating complex health outcomes in pediatric populations (10,11). While the present study utilizes a retrospective multicenter cohort to derive a novel risk stratification tool, the principles of rigorous cohort design align with these larger initiatives. Furthermore, the findings from this initial investigation highlight the necessity for future validation in similarly extensive, prospective cohorts to confirm the generalizability and clinical utility of the proposed biomarker panel across diverse populations and settings. We present this article in accordance with the STROBE reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-480/rc).

Methods

Study design and participant selection

This study was a multicenter, retrospective analysis of pediatric patients hospitalized in the Pediatric Departments of Qingdao University Affiliated Hospital and its alliance hospitals (comprising a total of 24 institutions) between December 2021 and January 2022. Ethical approval for this multicenter study was obtained from the lead center, the Medical Ethics Committee of The Affiliated Hospital of Qingdao University. This approval was recognized by all participating alliance hospitals within the network. The study protocol was approved by the Medical Ethics Committee of The Affiliated Hospital of Qingdao University (No. QYFY WZLL 29938). Given its retrospective nature, the requirement for written informed consent was waived. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study process is outlined in Figure S1.

The participants included children aged ≤14 years with a confirmed diagnosis of the COVID-19 Omicron variant via reverse transcription-polymerase chain reaction. Patients were excluded if they had hematological disorders, kidney disease, liver cirrhosis, or malignancies; were receiving immunosuppressive therapy; discontinued treatment or were discharged against medical advice; lacked cytokine, ALB, or other relevant laboratory test results; or had incomplete medical records.

A total of 142 pediatric COVID-19 cases were initially screened. After applying exclusion criteria (hematological disorders, n=3; pre-existing renal disease, n=5; missing biomarker data, n=15), 119 patients were included in the final analysis (Figure S1). The sample size was determined a priori, based on an anticipated mortality rate of 15% from prior pediatric cohorts. A minimum of 100 patients was required to achieve 80% power (α=0.05, two-sided) to detect a hazard ratio (HR) of >2.0 for key predictors.

Data collection

Baseline data were collected for all eligible patients, including demographic characteristics (age and sex), clinical data (medical history, symptoms, complications, comorbidities, and prognosis), and laboratory test results, particularly inflammatory markers, renal function tests, and ALB levels.

Statistical analysis

Categorical variables were presented as frequencies and percentages and compared using the Chi-squared test or Fisher’s exact test. Continuous variables were analyzed based on their distribution; normally distributed data were expressed as the mean ± standard deviation and compared using an independent t-test, whereas non-normally distributed data were presented as the median and interquartile range (IQR) and analyzed using the Mann-Whitney U test or the Kruskal-Wallis rank sum test. A complete-case analysis was performed by applying listwise deletion, excluding patients with any missing data for the key biomarkers of interest (IL-6, ALB, or creatinine). Patients were categorized into survivors and nonsurvivors, and features showing significant differences between the groups were analyzed using univariate logistic regression. Variables with a P<0.001 were further assessed using a multivariate Cox regression model to estimate their association with inpatient mortality, reported as HRs with 95% confidence intervals (CIs). The discriminative ability of the multivariate Cox regression model was assessed using the concordance index (C-index). The proportional hazards assumption for the Cox regression model was assessed using the Schoenfeld residual test, both globally and for each variable.

To assess mortality risk, patients were stratified into three groups based on IL-6, ALB, and AKI status: low-risk (0 points) if IL-6 <83.4 pg/mL, ALB ≥25 g/L, and no AKI; medium-risk (1 point) if one abnormal value was present; and high-risk (≥2 points) if two or more abnormalities were observed. The predictive ability of these biomarkers for hospital mortality was evaluated using receiver operating characteristic (ROC) curve analysis, while Kaplan-Meier survival curves were used to compare inpatient mortality rates across risk groups. A P<0.05 was considered statistically significant. All statistical analyses were performed using SPSS (version 28.0, IBM, USA).

Results

Characteristics of the study participants

This study included 119 pediatric patients with COVID-19, comprising 70 males and 49 females. The median age was 1.58 years (IQR, 0.53–6.17 years). The overall inpatient mortality rate was 14.3% (17/119).

Clinical differences between the survival and nonsurvival groups

Comparative analysis revealed that the nonsurvivors were significantly older than the survivors and exhibited higher incidences of AKI [47.1% (8/17) in nonsurvivors vs. 0% (0/102) in survivors], dyspnea/asphyxia, seizures, and lethargy (P<0.05, Table 1).

Distribution of molecular biomarkers

Baseline biomarker analysis showed significant differences between survivors and nonsurvivors. The nonsurvivor group had markedly abnormal levels of white blood cells, lymphocytes, hemoglobin, C-reactive protein, ferritin, D-dimer, creatinine, lactate dehydrogenase, IL-6, and ALB (P<0.001, Table 2).

Association between biomarkers and inpatient mortality rate

Significant variables identified in the survivor and nonsurvivor comparisons were subjected to univariate and multivariate Cox regression analysis. Multivariate analysis indicated that IL-6 was positively associated with mortality (HR: 1.003, 95% CI: 1.001–1.004), while ALB showed a negative correlation with mortality (HR: 0.839, 95% CI: 0.761–0.925). Creatinine was also significantly associated with mortality (HR: 1.010, 95% CI: 1.006–1.014). Thus, IL-6, low ALB, and elevated creatinine were identified as key risk factors for inpatient mortality (Table 3). The C-index for the multivariate Cox regression model was 0.958 (95% CI: 0.925–0.991), indicating excellent discriminative ability. The proportional hazards assumption was verified for the final model (Figure S2). Neither the global test (χ²=4.854, df=4, P=0.30) nor any covariate-specific tests (all P>0.05) provided evidence of violation (Table S1). ROC analysis demonstrated that IL-6 and creatinine effectively predicted inpatient mortality [IL-6, area under the curve (AUC): 0.897, sensitivity: 0.824, specificity: 0.922, Youden’s index: 0.745, P<0.001; creatinine, AUC: 0.885, sensitivity: 0.706, specificity: 0.990, Youden’s index: 0.696, P<0.001, Table S2].

Survival analysis across risk groups

Patients were stratified into three risk groups based on IL-6 level, ALB level, and AKI occurrence: high-risk (n=12), medium-risk (n=13), and low-risk (n=94). The IL-6 and creatinine levels increased with risk, whereas the ALB levels decreased. Significant differences were observed between the low- and medium-risk groups, as well as between the low-and high-risk groups (P<0.001, Figures 1-3). Kaplan-Meier survival analysis showed a significantly higher inpatient mortality rate in the high-risk group compared to the medium- and low-risk groups (P<0.001, Figure S3).

Figure 1 IL-6 levels across the low-, medium-, and high-risk groups. IL-6, interleukin-6.

Figure 2 ALB levels across the low-, medium-, and high-risk groups. ALB, albumin.

Figure 3 Creatinine levels across the low-, medium-, and high-risk groups.

Discussion

This study explored the predictive value of the IL-6 level, ALB serum level, and the occurrence of AKI for inpatient mortality in children with COVID-19, verifying their combined predictive capability. The findings demonstrate that an elevated IL-6 level, a low ALB level, and the presence of AKI significantly increase the risk of mortality. By integrating these three biomarkers, the patients were categorized into low-, moderate-, and high-risk groups, revealing significant differences in mortality rates among them. These results confirm the predictive value of individual biomarkers while highlighting the importance of a combined risk assessment model in managing critically ill pediatric COVID-19 patients.

IL-6 is a key mediator of the cytokine storm (12,13). Studies have shown that elevated IL-6 levels are associated with severe disease and poor outcomes in COVID-19 patients (5,14). Consistent with these findings, our study confirmed that IL-6 is an independent risk factor for severe COVID-19 in children, with significantly higher inpatient mortality among those with elevated IL-6 levels. This aligns with previous studies on adults, such as the research by Liu et al. (15). Clinically, targeted IL-6 therapies, such as tocilizumab, hold promise in the management of pediatric COVID-19 patients (16).

ALB is a critical marker of nutritional status and inflammation. COVID-19 infection triggers an inflammatory cascade that increases vascular permeability, leading to capillary leak syndrome and a decline in serum ALB levels, which has been linked to worse outcomes (17,18). Our study further confirmed that low ALB levels significantly correlate with increased mortality. These findings underscore the need for enhanced nutritional support and inflammation management in children with low ALB levels to improve their prognosis.

AKI, typically diagnosed based on the Kidney Disease-Improving Global Outcomes criteria, is a frequent and serious complication in severe COVID-19 cases (19,20). In pediatric settings, accurate urine output data can be challenging to obtain, making serum creatinine levels a widely used diagnostic marker, as supported by Chopra et al. (21). Our study confirmed that elevated serum creatinine is a significant risk factor for inpatient mortality, consistent with research by Leghrouz et al. (22). The pathophysiology of AKI in pediatric COVID-19 patients likely involves direct viral damage to renal tubular cells, systemic inflammation, and hemodynamic disturbances (23). AKI not only signifies multi-organ dysfunction but also exacerbates metabolic imbalances and electrolyte disturbances, further worsening disease severity (24). Early monitoring and protective interventions, such as avoiding nephrotoxic agents and optimizing fluid management, are crucial for reducing AKI incidence and improving outcomes (25).

IL-6, ALB, and AKI are interrelated in a pathogenic cycle. Elevated IL-6 damages endothelial cells, disrupts organ function, and exacerbates immune hyperactivation. By inhibiting hepatic ALB synthesis, it worsens hypoalbuminemia, leading to osmotic imbalances and immune dysfunction, which contribute to AKI. AKI, in turn, amplifies the inflammatory response, promoting further IL-6 release and creating a vicious cycle that accelerates MODS and increases mortality risk. Our study demonstrated that risk stratification using IL-6, ALB, and AKI effectively predicts disease severity.

Previous studies have established the link between elevated IL-6 and severe disease outcomes in adults with COVID-19 (5,26), and our study extends this evidence to pediatric patients. AKI, a well-documented complication in adults, was also confirmed as a critical risk factor in children. However, pediatric patients exhibit distinct susceptibilities, disease progression, and immune responses compared to adults (27). For example, children are more prone to metabolic disturbances and have lower nutritional reserves, which may explain the strong association between low ALB levels and mortality in our study. Unlike adult-focused research, our study introduces a combined biomarker risk stratification model, enhancing reliability and clinical applicability.

By integrating IL-6, ALB, and AKI, we provided a comprehensive assessment of COVID-19 severity in children. The risk stratification model offers an intuitive approach for tiered management and resource allocation in clinical settings. While this study advances the understanding of pediatric COVID-19, it has limitations. The small sample size may limit the generalizability of findings across different regions and populations. Although our study incorporated data from Qingdao University Affiliated Hospital and its alliance hospitals, all participating hospitals were located within Shandong Province, China. This, coupled with the exclusive focus on the Omicron variant, may limit the generalizability of our findings to other geographic regions, populations of different ethnic backgrounds, healthcare settings, or infections caused by other severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Future external validation in independent, international cohorts is essential before our model can be considered for broad clinical application. Additionally, as a retrospective study, data completeness and quality constraints may have introduced potential biases. The exclusion of 15 patients (10.6% of screened cases) due to missing biomarker data is a potential source of selection bias. Although the analyzed cohort demonstrated a wide spectrum of disease severity and the findings are biologically highly plausible, we cannot entirely rule out the possibility that the excluded patients differed in unmeasured ways. The generalizability of our model should therefore be confirmed in future prospective studies. The lack of a long-term follow-up also prevents analysis of post-discharge outcomes, such as organ function recovery and late complications. Furthermore, serum creatinine alone may not fully capture AKI incidence, as its levels can be influenced by nonrenal factors such as hypoalbuminemia and fluid overload. The absence of baseline creatinine levels may have led to an underestimation of AKI and its impact on mortality.

While the traditional regression approaches employed in this study successfully identified a combinatory biomarker panel with significant prognostic value, further validation in larger cohorts remains necessary to confirm the robustness of our model. Furthermore, although the proportional hazards assumption was tested and upheld for our Cox regression model, future studies should continue to verify this assumption when applying similar predictive frameworks. Beyond conventional regression techniques, future investigations may benefit from incorporating advanced machine learning methods. For instance, ensemble learning frameworks, such as those demonstrated in cardiovascular risk prediction (28), or feature representation approaches inspired by self-supervised learning (SSL), could provide more sophisticated ways to integrate multiple predictors beyond simple risk scoring, thereby improving predictive accuracy for outcomes in pediatric severe infections.

Conclusions

The combined evaluation of IL-6 levels, ALB serum levels, and AKI provides a novel approach for predicting inpatient mortality in pediatric COVID-19 patients. Risk stratification effectively distinguishes high-risk children, enabling personalized treatment and optimized medical resource allocation. Future studies should validate this model across larger, more diverse populations and incorporate additional renal biomarkers such as neutrophil gelatinase-associated lipocalin to enhance diagnostic accuracy. Longitudinal studies exploring dynamic changes in IL-6, ALB, and creatinine levels could further refine real-time risk prediction tools, improving early detection and clinical management.

Acknowledgments

We thank the following individuals for their assistance in data collection: Lingyan Li, Wenxiao Wang, Xiumin Chen, Xiaofeng Hou, Weimei Wang, Tuo Min, Jinmei Liu, Lecui Liu, Chengjun Liu, Zhong Jiang, Yangping Wang, Dayun Chang.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-480/rc

Data Sharing Statement: Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-480/dss

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-480/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-480/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. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Medical Ethics Committee of The Affiliated Hospital of Qingdao University (No. QYFY WZLL 29938) and the requirement for written informed consent was waived due to the retrospective design of the study.

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/.

References

1. World Health Organization: Coronavirus disease 2019 (covid-19) situation report. 2020. Available online: https://www.who.int
2. Viner RM, Mytton OT, Bonell C, et al. Susceptibility to SARS-CoV-2 Infection Among Children and Adolescents Compared With Adults: A Systematic Review and Meta-analysis. JAMA Pediatr 2021;175:143-56. [Crossref] [PubMed]
3. Luo C, Chen W, Cai J, et al. The mechanisms of milder clinical symptoms of COVID-19 in children compared to adults. Ital J Pediatr 2024;50:28. [Crossref] [PubMed]
4. Qamar MA, Sajid MI, Dhillon RA, et al. Who is at a Higher Risk? A brief review of Recent Evidence on comorbidities in children infected with COVID-19. J Ayub Med Coll Abbottabad 2020;32:S695-700.
5. AbdelAziz RA, Abd-Allah ST, Moness HM, et al. Role of interleukin 6 polymorphism and inflammatory markers in outcome of pediatric Covid- 19 patients. BMC Pediatr 2024;24:625. [Crossref] [PubMed]
6. Del Valle DM, Kim-Schulze S, Huang HH, et al. An inflammatory cytokine signature predicts COVID-19 severity and survival. Nat Med 2020;26:1636-43. [Crossref] [PubMed]
7. Viana-Llamas MC, Arroyo-Espliguero R, Silva-Obregón JA, et al. Hypoalbuminemia on admission in COVID-19 infection: An early predictor of mortality and adverse events. A retrospective observational study. Med Clin (Barc) 2021;156:428-36. [Crossref] [PubMed]
8. Hilton J, Boyer N, Nadim MK, et al. COVID-19 and Acute Kidney Injury. Crit Care Clin 2022;38:473-89. [Crossref] [PubMed]
9. Kari JA, Shalaby MA, Albanna AS, et al. Acute kidney injury in children with COVID-19: a retrospective study. BMC Nephrol 2021;22:202. [Crossref] [PubMed]
10. Oh J, Lee M, Park J, et al. Prenatal and postnatal exposure to antibiotics and risk of food allergy in the offspring: A nationwide birth cohort study in South Korea. Pediatr Allergy Immunol 2024;35:e14114. [Crossref] [PubMed]
11. Oh J, Woo HG, Kim HJ, et al. Prenatal and infant exposure to antibiotics and subsequent risk of neuropsychiatric disorders in children: A nationwide birth cohort study in South Korea. Psychiatry Res 2024;340:116117. [Crossref] [PubMed]
12. Montazersaheb S, Hosseiniyan Khatibi SM, Hejazi MS, et al. COVID-19 infection: an overview on cytokine storm and related interventions. Virol J 2022;19:92. [Crossref] [PubMed]
13. Zhang J, Gao XL, Yang LH. Research progress in coagulation dysfunction and its relationship with cytokine storm syndrome in patients with severe/critical COVID-19. Zhonghua Xue Ye Xue Za Zhi 2021;42:700-4. [Crossref] [PubMed]
14. Wang X, Tang G, Liu Y, et al. The role of IL-6 in coronavirus, especially in COVID-19. Front Pharmacol 2022;13:1033674. [Crossref] [PubMed]
15. Liu F, Li L, Xu M, et al. Prognostic value of interleukin-6, C-reactive protein, and procalcitonin in patients with COVID-19. J Clin Virol 2020;127:104370. [Crossref] [PubMed]
16. Potere N, Batticciotto A, Vecchié A, et al. The role of IL-6 and IL-6 blockade in COVID-19. Expert Rev Clin Immunol 2021;17:601-18. [Crossref] [PubMed]
17. Soetedjo NNM, Iryaningrum MR, Damara FA, et al. Prognostic properties of hypoalbuminemia in COVID-19 patients: A systematic review and diagnostic meta-analysis. Clin Nutr ESPEN 2021;45:120-6. [Crossref] [PubMed]
18. Paliogiannis P, Mangoni AA, Cangemi M, et al. Serum albumin concentrations are associated with disease severity and outcomes in coronavirus 19 disease (COVID-19): a systematic review and meta-analysis. Clin Exp Med 2021;21:343-54. [Crossref] [PubMed]
19. Pereira M, Rodrigues N, Godinho I, et al. Acute kidney injury in patients with severe sepsis or septic shock: a comparison between the 'Risk, Injury, Failure, Loss of kidney function, End-stage kidney disease' (RIFLE), Acute Kidney Injury Network (AKIN) and Kidney Disease: Improving Global Outcomes (KDIGO) classifications. Clin Kidney J 2017;10:332-40. [Crossref] [PubMed]
20. Yazılıtaş F, Çakıcı EK, Güngör T, et al. Retrospective evaluation of acute kidney injury in paediatric COVID-19 patients: a tertiary referral hospital experience. J Nephrol 2024;37:2541-50. [Crossref] [PubMed]
21. Chopra S, Saha A, Kumar V, et al. Acute Kidney Injury in Hospitalized Children with COVID19. J Trop Pediatr 2021;67:fmab037. [Crossref] [PubMed]
22. Leghrouz B, Kaddourah A. Impact of Acute Kidney Injury on Critically Ill Children and Neonates. Front Pediatr 2021;9:635631. [Crossref] [PubMed]
23. Nadim MK, Forni LG, Mehta RL, et al. COVID-19-associated acute kidney injury: consensus report of the 25th Acute Disease Quality Initiative (ADQI) Workgroup. Nat Rev Nephrol 2020;16:747-64. [Crossref] [PubMed]
24. Mirzaee M, Jamee M, Mohkam M, et al. Acute Kidney Injury in Pediatric Patients with COVID-19; Clinical Features and Outcome. Iran J Kidney Dis 2023;17:20-7.
25. Bjornstad EC, Krallman KA, Askenazi D, et al. Preliminary Assessment of Acute Kidney Injury in Critically Ill Children Associated with SARS-CoV-2 Infection: A Multicenter Cross-Sectional Analysis. Clin J Am Soc Nephrol 2021;16:446-8. [Crossref] [PubMed]
26. Laguna-Goya R, Utrero-Rico A, Talayero P, et al. IL-6-based mortality risk model for hospitalized patients with COVID-19. J Allergy Clin Immunol 2020;146:799-807.e9. [Crossref] [PubMed]
27. Zimmermann P, Curtis N. Why is COVID-19 less severe in children? A review of the proposed mechanisms underlying the age-related difference in severity of SARS-CoV-2 infections. Arch Dis Child 2021;106:429-39. [Crossref] [PubMed]
28. Zaidi SAJ, Ghafoor A, Kim J, et al. HeartEnsembleNet: An Innovative Hybrid Ensemble Learning Approach for Cardiovascular Risk Prediction. Healthcare (Basel) 2025;13:507. [Crossref] [PubMed]