Meningoencephalitis of unknown origin in dogs under veterinary referral care in England (2017-2021): a multicenter...

A considerable body of published research on meningoencephalitis of unknown origin (MUO) exists; however, certain fundamental aspects relating to the epidemiology remain poorly characterized. These include the frequency of MUO diagnosis at referral level, reliable demographic risk factors, and the extent to which proposed diagnostic criteria are applied in referral clinical settings.

Based on 1,121 MUO cases (from 01 January 2017 to 31 December 2021) treated at 13 referral centers in England and 750,000 control dogs from the VetCompass Programme, this study investigated a range of demographic risk factors using multivariable logistic regression analysis. Additionally, we report on clinical methods used for diagnosis.

Meningoencephalitis of unknown origin represented 2.21% (95% CI: 2.08-2.34) of new neurological referrals (1,121/50721). Clinical diagnosis included both magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) analysis in 1026 (91.5%) cases. Of these, 961 (89.3%) showed results indicative of MUO in both MRI and CSF. Abnormal MRI but normal CSF were found in 55 cases (5.4%), while normal MRI and abnormal CSF were found in 36 cases (3.5%). Both normal MRI and normal CSF were reported in 19 cases (1.5%). Screening for infectious disease was carried out in 1037 (92.5%) of cases. The diagnosis of MUO peaked at 4 years (median 4.33, IQR 2.50-6.92, range 0.30-15.00) and declined after age 10. Welsh Springer Spaniel (OR 23.76, 95% CI 10.37-54.43), Maltese (OR 20.53, 95% CI 14.53-29.01), Papillon (OR 17.48, 95% CI 7.66-39.91), Boston Terrier (OR 17.31, 95% CI 11.17-26.82), and French Bulldog (OR 9.14, 95% CI 7.14-11.71) had the highest MUO odds compared to crossbreed dogs. Brachycephalic breeds had 2.56 times higher odds (95% CI 2.23-2.95) than mesocephalic breeds. Dogs ≥15 kg had lower odds than those <10 kg.

This study provides the largest referral-based analysis of MUO cases to date, offering updated insights into breed predispositions and clinical diagnosis. This more precise characterization of the demographic factors adds valuable context for future research design, particularly in breed-focused investigations and risk stratification. By documenting current diagnostic practices used by referral specialists, this work lays the foundation for greater consistency in case recognition and offers practical guidance for structuring future MUO clinical trials.