Predictive Value of Neutrophil–Lymphocyte Ratio and Other Inflammation Indices in Febrile Seizures in Children
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Population
2.2. Measures
2.3. Statistical Analysis
3. Results
4. Discussion
Limitations and Strengths
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Han, M.J.; Heo, J.H.; Hwang, J.S.; Jang, Y.-T.; Lee, M.; Kim, S.J. Incidence of Febrile Seizures in Children with COVID-19. J. Clin. Med. 2023, 12, 1076. [Google Scholar] [CrossRef]
- Xixis, K.L.; Samanta, D.; Smith, T.; Keenaghan, M. Febrile Seizure. Available online: https://www.ncbi.nlm.nih.gov/books/NBK448123/ (accessed on 3 September 2024).
- Eilbert, W.; Chan, C. Febrile seizures: A review. J. Am. Coll. Emerg. Physicians Open 2022, 3, e12769. [Google Scholar] [CrossRef]
- Kwon, A.; Kwak, B.O.; Kim, K.; Ha, J.; Kim, S.J.; Bae, S.H.; Son, J.S.; Kim, S.N.; Lee, R. Cytokine levels in febrile seizure patients: A systematic review and meta-analysis. Seizure 2018, 59, 5–10. [Google Scholar] [CrossRef]
- Moldovan, F. Sterile Inflammatory Response and Surgery-Related Trauma in Elderly Patients with Subtrochanteric Fractures. Biomedicines 2024, 12, 354. [Google Scholar] [CrossRef]
- Kuzyk, P.R.; Bhandari, M.; McKee, M.D.; Russell, T.A.; Schemitsch, E.H. Intramedullary versus extramedullary fixation for subtrochanteric femur fractures. J. Orthop. Trauma 2009, 23, 465–470. [Google Scholar] [CrossRef] [PubMed]
- Jackson, C.; Tanios, M.; Ebraheim, N. Management of Subtrochanteric Proximal Femur Fractures: A Review of Recent Literature. Adv. Orthop. 2018, 2018, 1326701. [Google Scholar] [CrossRef] [PubMed]
- Hosseini, S.; Gharedaghi, H.; Hassannezhad, S.; Sadeghvand, S.; Maghari, A.; Dastgiri, S.; Talebi, M.; Khanzadeh, S. The Impact of Neutrophil-Lymphocyte Ratio in Febrile Seizures: A Systematic Review and Meta-Analysis. BioMed Res. Int. 2022, 2022, 8472795. [Google Scholar] [CrossRef]
- Hamad, D.A.; Aly, M.M.; Abdelhameid, M.A.; Ahmed, S.A.; Shaltout, A.S.; Abdel-Moniem, A.E.; Ragheb, A.M.R.; Attia, M.N.; Meshref, T.S. Combined Blood Indexes of Systemic Inflammation as a Mirror to Admission to Intensive Care Unit in COVID-19 Patients: A Multicentric Study. J. Epidemiol. Glob. Health 2022, 12, 64–73. [Google Scholar] [CrossRef]
- Moldovan, F.; Gligor, A.; Moldovan, L.; Bataga, T. The Impact of the COVID-19 Pandemic on the Orthopedic Residents: A Pan-Romanian Survey. Int. J. Environ. Res. Public Health 2022, 19, 9176. [Google Scholar] [CrossRef] [PubMed]
- Feng, W.; Hou, J.; Xiang, C.; Die, X.; Sun, J.; Guo, Z.; Liu, W.; Wang, Y. Correlation of systemic immune-inflammation Index with surgical necrotizing enterocolitis. Front. Pediatr. 2022, 10, 1044449. [Google Scholar] [CrossRef]
- Yaradilmiş, R.M.; Güneylioğlu, M.M.; Öztürk, B.; Göktuğ, A.; Aydın, O.; Güngör, A.; Bodur, İ.; Kaya, Ö.; Örün, U.A.; Karacan, C.D.; et al. A Novel Marker for Predicting Fulminant Myocarditis: Systemic Immune-Inflammation Index. Pediatr. Cardiol. 2023, 44, 647–655. [Google Scholar] [CrossRef] [PubMed]
- Ouyang, H.; Wang, Z. Predictive value of the systemic immune-inflammation index for cancer-specific survival of osteosarcoma in children. Front. Public Health 2022, 10, 879523. [Google Scholar] [CrossRef]
- Güngör, A.; Göktuğ, A.; Yaradılmış, R.M.; Güneylioğlu, M.M.; Öztürk, B.; Bodur, İ.; Karacan, C.D.; Tuygun, N. Utility of the systemic immune-inflammation index to predict serious bacterial infections in infants with fever without a source. Postgrad. Med. 2022, 134, 698–702. [Google Scholar] [CrossRef]
- Aydogan, S.; Dilli, D.; Soysal, C.; Akduman, H.; Örün, U.A.; Taşar, M.; Taşoglu, I.; Zenciroglu, A. Role of systemic immune-inflammatory index in early diagnosis of sepsis in newborns with CHD. Cardiol. Young 2022, 32, 1826–1832. [Google Scholar] [CrossRef] [PubMed]
- Wei, L.; Xie, H.; Yan, P. Prognostic value of the systemic inflammation response index in human malignancy: A meta-analysis. Medicine 2020, 99, e23486. [Google Scholar] [CrossRef] [PubMed]
- Wang, P.; Guo, X.; Zhou, Y.; Li, Z.; Yu, S.; Sun, Y.; Hua, Y. Monocyte-to-high-density lipoprotein ratio and systemic inflammation response index are associated with the risk of metabolic disorders and cardiovascular diseases in general rural population. Front. Endocrinol. 2022, 13, 944991. [Google Scholar] [CrossRef] [PubMed]
- Xu, Y.; He, H.; Zang, Y.; Yu, Z.; Hu, H.; Cui, J.; Wang, W.; Gao, Y.; Wei, H.; Wang, Z. Systemic inflammation response index (SIRI) as a novel biomarker in patients with rheumatoid arthritis: A multi-center retrospective study. Clin. Rheumatol. 2022, 41, 1989–2000. [Google Scholar] [CrossRef]
- Biyik, M.; Biyik, Z.; Asil, M.; Keskin, M. Systemic Inflammation Response Index and Systemic Immune Inflammation Index Are Associated with Clinical Outcomes in Patients with Acute Pancreatitis? J. Investig. Surg. 2022, 35, 1613–1620. [Google Scholar] [CrossRef]
- Guven, D.C.; Sahin, T.K.; Erul, E.; Kilickap, S.; Gambichler, T.; Aksoy, S. The Association between the Pan-Immune-Inflammation Value and Cancer Prognosis: A Systematic Review and Meta-Analysis. Cancers 2022, 14, 2675. [Google Scholar] [CrossRef]
- Lee, L.E.; Ahn, S.S.; Pyo, J.Y.; Song, J.J.; Park, Y.B.; Lee, S.W. Pan-immune-inflammation value at diagnosis independently predicts all-cause mortality in patients with antineutrophil cytoplasmic antibody-associated vasculitis. Clin. Exp. Rheumatol. 2011, 39 (Suppl. S129), 88–93. [Google Scholar] [CrossRef]
- Demiröz Taşolar, S.; Çiftçi, N. Role of pan immune inflammatory value in the evaluation of hepatosteatosis in children and adolescents with obesity. J. Pediatr. Endocrinol. Metab. 2022, 35, 1481–1486. [Google Scholar] [CrossRef] [PubMed]
- Shi, Y.; Yang, C.; Chen, L.; Cheng, M.; Xie, W. Predictive value of neutrophil-to-lymphocyte and platelet ratio in in-hospital mortality in septic patients. Heliyon 2022, 8, e11498. [Google Scholar] [CrossRef]
- Ghobadi, H.; Mohammadshahi, J.; Javaheri, N.; Fouladi, N.; Mirzazadeh, Y.; Aslani, M.R. Role of leukocytes and systemic inflammation indexes (NLR, PLR, MLP, dNLR, NLPR, AISI, SIR-I, and SII) on admission predicts in-hospital mortality in non-elderly and elderly COVID-19 patients. Front. Med. 2022, 9, 916453. [Google Scholar] [CrossRef] [PubMed]
- International League Against Epilepsy. Febrile Seizures. Available online: https://www.ilae.org/patient-care/febrile-seizures (accessed on 3 September 2024).
- Goksugur, S.B.; Kabakus, N.; Bekdas, M.; Demircioglu, F. Neutrophil-to-lymphocyte ratio and red blood cell distribution width is a practical predictor for differentiation of febrile seizure types. Eur. Rev. Med. Pharmacol. Sci. 2014, 18, 3380–3385. [Google Scholar] [PubMed]
- Liu, Z.; Li, X.; Zhang, M.; Huang, X.; Bai, J.; Pan, Z.; Lin, X.; Yu, D.; Zeng, H.; Wan, R.; et al. The role of Mean Platelet Volume/platelet count Ratio and Neutrophil to Lymphocyte Ratio on the risk of Febrile Seizure. Sci. Rep. 2018, 8, 15123. [Google Scholar] [CrossRef]
- Yigit, Y.; Yilmaz, S.; Akdogan, A.; Halhalli, H.C.; Ozbek, A.E.; Gencer, E.G. The role of neutrophil-lymphocyte ratio and red blood cell distribution width in the classification of febrile seizures. Eur. Rev. Med. Pharmacol. Sci. 2017, 21, 554–559. [Google Scholar]
- Cokyaman, T.; Kasap, T. Contribution of neutrophil/lymphocyte ratio, RDW, RPR, MPV and MPR indexes to febrile seizure diagnosis. Güncel Pediatri 2020, 18, 346–357. [Google Scholar] [CrossRef]
- Kubota, J.; Hirano, D.; Suzuki, T.; Kakegawa, D.; Ito, A. The role of inflammatory markers and calculated osmotic pressure in the classification of febrile seizures. Eur. Rev. Med. Pharmacol. Sci. 2020, 24, 11187–11191. [Google Scholar] [CrossRef]
- Tan, T.H.; Perucca, P.; O’Brien, T.J.; Kwan, P.; Monif, M. Inflammation, ictogenesis, and epileptogenesis: An exploration through human disease. Epilepsia 2021, 62, 303–324. [Google Scholar] [CrossRef]
- Pooja, A.; Aroor, A.R.; Soans, S.T. The usefulness of neutrophil to lymphocyte ratio in febrile seizure. Int. J. Contemp. Pediatr. 2020, 7, 985–987. [Google Scholar] [CrossRef]
- Tang, L.; Chen, J.R. The Predictive Value of Hemocytometry Based on Peripheral Platelet-Related Parameters in Identifying the Causes of Febrile Seizures. J. Inflamm. Res. 2021, 14, 5381–5392. [Google Scholar] [CrossRef] [PubMed]
Febrile Seizure (FS) Group | Fever Control (FC) Group | Healthy Control (HC) | p Value | ||
---|---|---|---|---|---|
FS Group vs. FC Group | FS Group vs. HC Group | ||||
Age (months), mean ± SD | 27.9 ± 8.5 | 26.5 ± 10 | 29.9 ± 9.5 | 0.440 | 0.373 |
Gender (male, %) | 65 | 62 | 50 | 0.657 | 0.022 |
Fever etiology, n (%) | 0.052 | ||||
Upper rsp.tract inf. | 89 | 75 | |||
Gastroenteritis | 5 | 5 | |||
Pneumonia | 4 | 17 | |||
Urinary tract inf. | 1 | 2 | |||
Otitis | 1 | 1 | |||
WBC, ×109/L, median (min–max) | 13.1 (3.6–35.5) | 13.5 (2.3–27.5) | 8.7 (5.5–10.5) | 0.722 | <0.001 |
Neutrophil, ×109/L, median (min–max) | 8.8 (1.7–26.5) | 7.1 (0.6–17.8) | 3.5 (1–7.8) | 0.001 | <0.001 |
Lymphocyte, ×109/L, median (min–max) | 2.5 (0.4–16.6) | 4.2 (0.7–17.3) | 4.3 (1.8–8.8) | <0.001 | <0.001 |
CRP (mg/L), median (min-max) | 10.7 (0.2–104) | 19.3 (0.9–280) | <0.001 | ||
Monocytes, ×109/L, median (min–max) | 1.02 (0.4–2.5) | 1 (0.2–2.7) | 0.58 (0.2–2) | 0.708 | <0.001 |
Hemoglobin (g/dL), median (min-max) | 11.2 (6.6–13.2) | 11.2 (7.4–15.5) | 11.8 (9.8–14.7) | 0.309 | <0.001 |
MCV (fL), mean ± SD | 76.2 ± 6.8 | 76.3 ± 6.4 | 77.9 ± 5 | 0.939 | 0.043 |
RDW (fL), median (min–max) | 14 (11.7–18.5) | 14.3 (12.9–21.7) | 13.7 (12.1–20.2) | 0.199 | 0.132 |
Platelet, ×109/L, median (min–max) | 284 (137–560) | 321 (57–966) | 336 (141–509) | 0.032 | 0.001 |
MPV (fL), median (min–max) | 8 (6.7–11.8) | 8.2 (6.6–12.6) | 8.4 (6.7–10.7) | 0.058 | 0.008 |
PCT (%), median (min-max) | 0.24 (0.1–0.5) | 0.26 (0.07–0.8) | 0.3 (0.13–0.61) | 0.007 | <0.001 |
NLR, median (min–max) | 3.6 (0.5–21.3) | 1.5 (0.1–5.8) | 0.8 (0.1–2.9) | <0.001 | <0.001 |
SII median (min–max) | 1003.5 (114–4880) | 482.2 (17.3–1870) | 272.1 (54.6–943.2) | <0.001 | <0.001 |
SIRI median (min–max) | 3.24 (0.4–21.6) | 1.6 (0.03–13.1) | 0.5 (0.06–4.7) | <0.001 | <0.001 |
PIV median (min–max) | 910.3 (103.8–7866.4) | 565.1 (4.1–2431.5) | 151.0 (20.9–1778.5) | <0.001 | <0.001 |
NLPR median (min–max) | 1.1 (0.1–9.4) | 0.4 (0.03–4.7) | 0.2 (0.03–1) | <0.001 | <0.001 |
ROC Curve Analysis | Statistical Diagnostic Measures | ||||||
---|---|---|---|---|---|---|---|
AUC (95% CI) | p-Value | Optimal Cut-Off | Sensitivity | Specificity | PPV | NPV | |
FS vs. HC | |||||||
NLPR | 0.811 (0.762–0.854) | <0.001 | >0.38 | 73.23 (66.5–79.3) | 79.80 (70.5–87.2) | 87.9 (82.9–91.5) | 59.8 (53.7–65.7) |
NLR | 0.825 (0.777–0.867) | <0.001 | >1.14 | 78.28 (71.9–83.8) | 75.76 (66.1–83.8) | 86.6 (81.9–90.2) | 63.6 (56.7–69.9) |
SII | 0.804 (0.755–0.848) | <0.001 | >451.64 | 69.70 (62.8–76.0) | 80.81 (71.7–88) | 87.9 (82.8–91.7) | 57.1 (51.4–62.7) |
SIRI | 0.868 (0.824–0.905) | <0.001 | >1.02 | 77.27 (70.8–82.9) | 87.88 (79.8–93.6) | 92.7 (88.2–95.6) | 65.9 (59.7–71.6) |
PIV | 0.850 (0.804–0.888) | <0.001 | >396.21 | 72.22 (65.4–78.3) | 90.91 (83.4–95.8) | 94.1 (89.4–96.8) | 62.1 (56.4–67.4) |
FS vs. FC | |||||||
NLPR | 0.774 (0.709–0.830) | <0.001 | >0.96 | 57.58 (47.2–67.5) | 87.88 (79.8–93.6) | 82.6 (73.1–89.2) | 67.4 (61.9–72.5) |
NLR | 0.782 (0.718–0.838) | <0.001 | >3.59 | 52.53 (42.2–62.7) | 95.96 (90–98.9) | 92.9 (83–97.2) | 66.9 (62.1–71.4) |
SII | 0.755 (0.689–0.813) | <0.001 | >870.47 | 59.60 (49.3–69.3) | 81.82 (72.8–88.9) | 76.6 (67.7–83.7) | 66.9 (61–72.4) |
SIRI | 0.737 (0.670–0.797) | <0.001 | >1.96 | 75.76 (66.1–83.8) | 59.60 (49.3–69.3) | 65.2 (59–70.9) | 71.1 (62.6–78.3) |
PIV | 0.692 (0.623–0.756) | <0.001 | >532.75 | 80.81 (71.7–88) | 48.48 (38.3–58.7) | 61.1 (55.9–66) | 71.6 (61.6–79.9) |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Söğütlü, Y.; Altaş, U. Predictive Value of Neutrophil–Lymphocyte Ratio and Other Inflammation Indices in Febrile Seizures in Children. J. Clin. Med. 2024, 13, 5330. https://doi.org/10.3390/jcm13175330
Söğütlü Y, Altaş U. Predictive Value of Neutrophil–Lymphocyte Ratio and Other Inflammation Indices in Febrile Seizures in Children. Journal of Clinical Medicine. 2024; 13(17):5330. https://doi.org/10.3390/jcm13175330
Chicago/Turabian StyleSöğütlü, Yakup, and Uğur Altaş. 2024. "Predictive Value of Neutrophil–Lymphocyte Ratio and Other Inflammation Indices in Febrile Seizures in Children" Journal of Clinical Medicine 13, no. 17: 5330. https://doi.org/10.3390/jcm13175330
APA StyleSöğütlü, Y., & Altaş, U. (2024). Predictive Value of Neutrophil–Lymphocyte Ratio and Other Inflammation Indices in Febrile Seizures in Children. Journal of Clinical Medicine, 13(17), 5330. https://doi.org/10.3390/jcm13175330