Conference Abstract | Volume 8, Abstract ELIC2025172 (Oral 077) | Published: 18 Aug 2025
Nneka Marian Chika-Igwenyi1,&, Uche Sonny Unigwe2, Godsent Chichebem Isiguzo1, Kingsley Nnanna Ukwaja1, Nnennaya Anthony Ajayi1, Michael Onyebuchi Iroezindu2
1Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria, 2University of Nigeria Teaching Hospital, Ituku-Ozalla, Enugu, Nigeria
&Corresponding author: Nneka Marian Chika-Igwenyi, Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria, Email: nnekaigwenyi@gmail.com
Received: 31 May 2025, Accepted: 09 Ju 2025, Published: 18 Aug 2025
Domain: Infectious Disease Epidemiology
Keywords: Lassa fever, Predictive score, Diagnosis, Nigeria
©Nneka Marian Chika-Igwenyi et al. Journal of Interventional Epidemiology and Public Health (ISSN: 2664-2824). This is an Open Access article distributed under the terms of the Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Cite this article: Nneka Marian Chika-Igwenyi et al., Predictive parameters for Lassa fever diagnosis in Nigeria: An empirical model. Journal of Interventional Epidemiology and Public Health. 2025;8(ConfrProc5):00077. https://doi.org/10.37432/JIEPH-CONFPRO5-00077
This hospital based, cross sectional study at Alex Ekwueme Federal University Teaching Hospital, Abakaliki (2023 2024) recruited febrile adults (≥18 years) suspected of LF. Data collection via interviewer administered questionnaires, physical exams, laboratory tests, and real time polymerase chain reaction (RT-PCR) were performed. Parameters were compared between RT-PCR positive/negative participants. Predictive variables were assessed using multivariate logistic regression. A predictive scoring system for LF diagnosis (PLF score) was developed, and sensitivity/specificity calculated (p< 0.05).
A total of 150 participants (males 76 [50.6%], females 74 [49.3%], mean age 36.6±15.3 years) were recruited. Self reported rodent exposure was the commonest epidemiologic factor (64.6%). RT PCR confirmed LF case positivity was 58.6% (88/150). LF positivity was significantly associated with rodent exposure (70.1% vs 29.8%, p=< 0.001), bush meat consumption (76.3% vs 23.7%, p=0.009), and Ebonyi State residence (53.1% vs 46.9%, p=< 0.001). LF positive participants were significantly more likely to present with fatigue, muscle pain, red eyes, haematuria, and proteinuria (All p values < 0.05). LF positivity was independently associated with rodent exposure, adjusted odd ratio (AOR)= 9.14, 95% C.I: 1.51 55.48), tinnitus (AOR=34.60, 95% C.I: 1.25 954.31), muscle pain (AOR=6.98, 95% C.I: 1.36 35.92), elevated AST (AOR=76.923, 95% C.I: 6.29 1000.00), and elevated creatinine (AOR=10.989, 95% C.I: 17.27 – 71.43). The PLF score had 95.5% sensitivity and 87.3% specificity at ≥5.5, area under the curve (AUC) 0.95, p< 0.001).
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