The use of systemic immune inflammatory index as a predictor for nematodes infections in horses.
Abstract: Nematode infections are a significant health concern in horses, causing a range of clinical signs and economic losses. Early detection and diagnosis are crucial for effective treatment and management. Unassigned: Examining the application of the systemic immune Inflammatory index (SII) as a predictor for nematode infections in horses, using platelets count, leucocytes count, and neutrophils count. Unassigned: A cross-sectional study was conducted on 164 horses, consisting of 66 horses with nematode infections and 98 horses without infections. The SII was computed using the platelets count, leucocytes count, and neutrophils count. Receiver operating characteristic (ROC) curve analysis was used to evaluate the SII's diagnostic accuracy. Unassigned: Nematode infections were severe in horses with mixed infections, with an average of 1805.90 ± 292.68 eggs per gram (epg). Notably, among specific species, spp., exhibited a significantly different average of 2264.29 ± 132.61epg compared to other nematodes. There is a significant negative correlations between the systemic immune-inflammatory index (SII) and the Eggs per gram count for nematodes infections at ( = -0.6023; < .0001). The SII values were significantly lower (0.06) in horses with nematode infections compared to those without infections (0.19) at < .001. With an area under the ROC curve (AUC) of 0.990, the SII demonstrated exceptional diagnostic precision. For the SII, the ideal cut-off value is ≤0.108, with a sensitivity of 98.5 % and a specificity of 100 %. The ROC curve was validated using the Youden index (J) with a higher value of 0.9848 indicating better performance. Unassigned: The study demonstrated that the SII is a reliable predictor for nematode infections in horses, using platelets count, leucocytes count, and neutrophils count. The SII is a non-invasive, reasonably priced method for identifying and diagnosing nematode infections in horses.
© 2025 The Authors. Published by Elsevier Ltd on behalf of World Federation of Parasitologists.
Publication Date: 2025-07-31 PubMed ID: 40837204PubMed Central: PMC12361788DOI: 10.1016/j.parepi.2025.e00453Google Scholar: Lookup
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Summary
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Overview
- This study investigates the use of the systemic immune-inflammatory index (SII) as a diagnostic tool to predict nematode infections in horses by analyzing blood cell counts.
- It demonstrates that SII is a highly accurate, non-invasive, and cost-effective biomarker for detecting these infections early.
Background and Importance
- Nematode infections are common and problematic in horses, leading to various health issues and economic burdens.
- Effective management of these infections depends on early and accurate diagnosis to allow prompt treatment.
- Traditional diagnosis relies on fecal egg counts, which can be variable and sometimes not sensitive enough for early detection.
- The systemic immune-inflammatory index (SII), calculated from routine blood parameters (platelets, leucocytes, and neutrophils), could offer a reliable alternative.
Study Design and Methods
- A cross-sectional study was conducted involving 164 horses, divided into two groups: 66 horses confirmed with nematode infections and 98 apparently healthy horses without infections.
- Blood samples were collected to measure platelets count, leucocytes count, and neutrophils count, from which the SII was calculated.
- The SII calculation integrates these three counts to reflect the systemic immune and inflammatory status of the horse.
- Fecal samples were analyzed to quantify the intensity of nematode infections through eggs per gram (epg) counts.
- Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic accuracy of the SII index in distinguishing infected from non-infected horses.
Key Findings
- Horses with mixed nematode infections had severe parasite loads, averaging approximately 1805.90 eggs per gram of feces.
- Some nematode species exhibited significantly higher egg counts, such as one genus with an average of about 2264.29 epg, highlighting variability in infection intensity.
- A significant negative correlation was found between SII values and nematode egg counts (correlation coefficient = -0.6023, p < 0.0001), indicating that lower SII values correspond to higher parasite loads.
- Horses infected with nematodes showed significantly lower SII values (mean of 0.06) compared to non-infected horses (mean of 0.19), with a p-value < 0.001 indicating strong statistical significance.
- The ROC curve analysis yielded an area under the curve (AUC) of 0.990, demonstrating excellent diagnostic accuracy of the SII index.
- An optimal SII cut-off value of ≤0.108 was identified for predicting infection status.
- At this cut-off, the SII achieved a sensitivity of 98.5% (correctly identifying infected horses) and a specificity of 100% (correctly identifying non-infected horses), illustrating near-perfect diagnostic performance.
- The Youden Index (J), a metric combining sensitivity and specificity, was 0.9848, confirming the robust predictive power of SII.
Implications and Conclusion
- The study validates the systemic immune-inflammatory index as a reliable biomarker for early detection of nematode infections in horses.
- SII offers a practical diagnostic tool because it is based on routine blood tests that are easy to perform and cost-effective.
- Because it is minimally invasive compared to some other methods, SII can be conveniently used for regular screening to prevent the progression of nematode infections.
- Early identification using SII supports timely treatment, which can improve horse health and reduce economic losses related to parasitic infections.
- The study encourages the incorporation of SII into veterinary diagnostic protocols for better management of equine nematode infections.
Cite This Article
APA
Kyari F, Pogu CJ, Mairiga IA, Adamu L.
(2025).
The use of systemic immune inflammatory index as a predictor for nematodes infections in horses.
Parasite Epidemiol Control, 30, e00453.
https://doi.org/10.1016/j.parepi.2025.e00453 Publication
Researcher Affiliations
- Faculty of Veterinary Medicine, Department of Veterinary Parasitology, University of Maiduguri, Maiduguri P.M.B. 1069, Borno State, Nigeria.
- Faculty of Veterinary Medicine, Department of Veterinary Medicine, University of Maiduguri, Maiduguri P.M.B. 1069, Borno State, Nigeria.
- Faculty of Veterinary Medicine, Department of Veterinary Medicine, University of Maiduguri, Maiduguri P.M.B. 1069, Borno State, Nigeria.
- Faculty of Veterinary Medicine, Department of Veterinary Medicine, University of Maiduguri, Maiduguri P.M.B. 1069, Borno State, Nigeria.
Conflict of Interest Statement
No conflicting interest to declare.
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