Duration of constant rate infusion with diazepam or propofol for canine cluster seizures and status epilepticus.

Introduction: Constant rate infusion (CRI) of benzodiazepines or propofol (PPF) is a therapeutic option for cluster seizures (CS) and status epilepticus (SE) in canine patients non-responding to first-line benzodiazepines or non-anesthetics. However, specific indications for optimal duration of CRI are lacking. The aim of this study was to determine the effect of duration of anesthetic CRI on outcome and length of hospital stay in dogs with refractory seizure activity of different etiology. Study design: Open-label non-randomized clinical trial. Materials and methods: Seventy-three client-owned dogs were enrolled. Two groups [experimental (EXP) vs. control (CTRL)] were compared. The EXP group received diazepam (DZP) or PPF CRI for 12 h (±1 h) and the CTRL group received DZP or PPF CRI for 24 h (±1 h) in addition to a standardized emergency treatment protocol identical for both study groups. The historical control group was made up of a population of dogs already reported in a previously published paper by the same authors. Favorable outcome was defined as seizure cessation after CRI, no seizure recurrence, and clinical recovery. Poor outcome was defined as seizure recurrence, death in hospital or no return to acceptable clinical baseline. Univariate statistical analysis was performed. Results: The study sample was 73 dogs: 45 (62%) received DZP CRI and 28 (38%) received PPF CRI. The EXP group was 39 dogs (25 DZP CRI and 14 PPF CRI) and the CTRL group 34 dogs (20 DZP CRI and 14 PPF CRI). We found no statistically significant difference in outcomes between the groups. The median length of stay was 56 h (IQR, 40-78) for the ALL EXP group and 58.5 h (IQR, 48-74.5) for the ALL CTRL group (p = 0.8). Conclusion: Even though a shorter DZP or PPF CRI duration was not associated with a worse outcome, the study failed to identify a clear superiority of shorter CRI duration on outcome or length of hospital stay in dogs with refractory seizure activity of different etiology.

A novel machine learning-based web application for field identification of infectious and inflammatory disorders of the central nervous system in cattle.

BACKGROUND: Central nervous system (CNS) infections in cattle are a major cause of economic loss and mortality. Machine learning (ML) techniques are gaining widespread application in solving predictive tasks in both human and veterinary medicine. OBJECTIVES: Our primary aim was to develop and compare ML models that could predict the likelihood of a CNS disorder of infectious or inflammatory origin in neurologically-impaired cattle. Our secondary aim was to create a user-friendly web application based on the ML model for the diagnosis of infection and inflammation of the CNS. ANIMALS: Ninety-eight cattle with CNS infection and 86 with CNS disorders of other origin. METHODS: Retrospective observational study. Six different ML methods (logistic regression [LR]; support vector machine [SVM]; random forest [RF]; multilayer perceptron [MLP]; K-nearest neighbors [KNN]; gradient boosting [GB]) were compared for their ability to predict whether an infectious or inflammatory disease was present based on demographics, neurological examination findings, and cerebrospinal fluid (CSF) analysis. RESULTS: All 6 methods had high prediction accuracy (≥80%). The accuracy of the LR model was significantly higher (0.843 ± 0.005; receiver operating characteristic [ROC] curve 0.907 ± 0.005 ) than the other models and was selected for implementation in a web application. CONCLUSION AND CLINICAL IMPORTANCE: Our findings support the use of ML algorithms as promising tools for veterinarians to improve diagnosis. The open-access web application may aid clinicians in achieving correct diagnosis of infectious and inflammatory neurological disorders in livestock, with the added benefit of promoting appropriate use of antimicrobials.

Feasibility of 16S rRNA sequencing for cerebrospinal fluid microbiome analysis in cattle with neurological disorders: a pilot study.

Bacterial infection of the central nervous system (CNS) in cattle requires prompt and adequate antimicrobial treatment. The current gold standard for antemortem etiological diagnosis is cerebrospinal fluid (CSF) culture, which often yields false negative results. CSF has long been considered a sterile district in healthy patients, but this notion has been recently challenged. For this pilot study, we used 16S rRNA gene sequencing to investigate the microbial composition of CSF of cattle presenting with CNS disorders and to compare it between subjects with CNS infections and with CNS disorders of other nature. The study sample was 10 animals: 4 presenting with CNS infectious-inflammatory diseases and 6 with other CNS disorders, based on definitive diagnosis. Since the initial round of a standard 16S rRNA PCR did not yield sufficient genetic material for sequencing in any of the samples, the protocol was modified to increase its sensitivity. Bacterial genetic material was identified in 6 animals and 2 groups were formed: an infectious inflammatory (n = 3) and a noninfectious inflammatory group (n = 3). The most frequently expressed bacterial families were Pseudomonadaceae (44.61%), Moraxellaceae (19.54%), Mycobacteriaceae (11.80%); the genera were Pseudomonas (45.42%), Acinetobacter (19.91%), Mycobacterium (12.01%). There were no detectable differences in the CSF microbial composition of the samples from the two groups. Sequencing of bacterial DNA present in the CSF was possible only after increasing PCR sensitivity. The results of 16S rRNA sequencing showed the presence of a microbial community in the CSF in cattle with neurological disorders. Further studies, in which CSF samples from healthy animals and samples from the environment are included as controls, are needed.

Analysis of Early Assessable Risk Factors for Poor Outcome in Dogs With Cluster Seizures and Status Epilepticus.

Status epileptics (SE) and cluster seizures (CS) are serious neurological emergencies associated with poor outcome in epileptic patients. Data on risk factors associated with outcome in epileptic patients affected by CS and SE have not been studied extensively to date. In the present retrospective study potential risk factors predictive of negative outcome in a population of dogs affected by CS and SE were analyzed. Ninety-three dogs were included in the study: 21/93 patients (23%) presented with SE and 72/93 (77%) with CS. Based on multivariate statistical analysis, factors statistically associated with a poor outcome were the occurrence of the first epileptic seizure outside the defined idiopathic interval (6 months-6 years), a condition of hyperthermia at presentation and the absence of previous antiepileptic drugs (AEDs) in case of previous history of seizures. The results of the present study implement data on risk factors associated with poor outcome in dogs affected by CS or SE and can aid in the creation of an ad hoc scoring system, similar to systems currently applied in human medicine upon hospital admission to benchmark performances and establish protocols for triage and therapeutic management.