Development of a clinical prediction score for detection of suspected cases of equine grass sickness (dysautonomia) in France

Clinical predictive models in equine medicine: A systematic review

Clinical predictive models use a patient's baseline demographic and clinical data to make predictions about patient outcomes and have the potential to aid clinical decision making. The extent of equine clinical predictive models is unknown in the literature. Using PubMed and Google Scholar, we systematically reviewed the predictive models currently described for use in equine patients. Models were eligible for inclusion if they were published in a peer-reviewed article as a multivariable model used to predict a clinical/laboratory/imaging outcome in an individual horse or herd. The agreement of at least two authors was required for model inclusion. We summarised the patient populations, model development methods, performance metric reporting, validation efforts, and, using the Predictive model Risk of Bias Assessment Tool (PROBAST), assessed the risk of bias and applicability concerns for these models. In addition, we summarised the index conditions for which models were developed and provided detailed information on included models. A total of 90 predictive models and 9 external validation studies were included in the final systematic review. A plurality of models (41%) was developed to predict outcomes associated with colic, for example, need for surgery or survival to discharge. All included models were at high risk of bias, defined as failing one or more PROBAST signalling questions, primarily for analysis-related reasons. Importantly, a high risk of bias does not necessarily mean that models are unusable, but that they require more careful consideration prior to clinical use. Concerns about applicability were low for the majority of models. Systematic reviews such as this can serve to increase veterinarians' awareness of predictive models, including evaluation of their performance and their use in different patient populations.

Equine grass sickness in italy: a case series study

BACKGROUND

Equine grass sickness (EGS) has been reported in several European and extra-European countries. Despite this, no scientific paper about clinical cases of EGS in Italy has been published. EGS is a disease affecting almost exclusively horses kept on pasture, characterized by clinical signs related to lesions in autonomic nervous system (ANS), particularly in the enteric nervous system (ENS). According to clinical presentation, acute, subacute and chornic syndromes can be observed, with various sympthoms including dullness, anorexia, dysphagia, drooling of saliva, tachycardia, ptosis, patchy sweating and muscle fasciculations. In horses affected by acute forms, mild to moderate abdominal pain and large volumes of nasogastric reflux can be observed. The etiology is still speculative and many hypothesis have been proposed to explain the pathogenesis.

CASE PRESENTATION

The present study describes four cases of EGS (one subacute and three chronic forms) occurred in Central Italy during early spring. In all the cases included in the study, the prognosis was poor and the horses were euthanized. The diagnosis was confirmed by histological examination of ANS or ENS. In two cases, in vivo diagnosis was obtained by histological examination of enteric bioptic samples collected during laparoscopy.

CONCLUSIONS

EGS in Italy could be underdiagnosed and incidence understimated. Greater awareness should be applied in Italy for the inclusion of EGS in differential diagnosis for horses presenting clinical signs of abdominal pain associated or not with gastric reflux and muscular fasciculation. All the cases in this study concerned horses kept in the same pasture, confirming a possible premise-linked and management-linked factors on the ethiopathogenesis of EGS. The age of horses ranged from 2 to 6 years, that is consistent with the risk factor age for EGS (from 2 to 7 years of age). Previous suspected EGS diagnosis in the same livestock and recent cool dry weather were considered additional potential risk factors.