A colic scoring system to predict the survival outcome in horses has been developed by researchers in the United States.
Acute abdominal pain in horses is a common emergency seen at equine practices. The wide variety of causes can make assessing the chances of survival a challenge.
Alanna Farrell and her fellow researchers said colic can be successfully treated medically or surgically. However, treatment can be costly and take an emotional toll on owners.
The prediction of whether a horse is likely to survive colic is often based on the veterinarian’s clinical impression. This typically depends on the horse’s comfort level at initial evaluation, clinical history, physical exam parameters, rectal examination, peritoneal fluid evaluation, abdominal ultrasound findings, and clinical pathology.
The study team, writing in the journal Frontiers in Veterinary Science, noted that a significant portion of the clinical exam for a horse with signs of colic is based on human interpretation — the comfort level, transrectal palpation, and ultrasound findings.
However, it is important to base prognoses and therapies on both empirical evidence and the clinical picture to avoid cognitive biases, they said.
“Cognitive biases have been shown to contribute to physician diagnostic errors and it is reasonable to presume that veterinarians are not immune to the same biases,” they said.
Therefore, the creation of a scoring system would aid in making colic assessment more objective and could ensure that more unbiased clinical findings are also considered.
In the first part of the study, the medical records of 658 horses presenting to the Lloyd Veterinary Medical Hospital at Iowa State University with signs of colic between 2014 and 2019 were evaluated. Horses euthanized because of financial constraints were excluded, as were those with colitis and those aged under 6 months.
In all, the number was reduced to 67, as the researchers wanted to include only horses in which a key range of diagnostic parameters was covered. In all, 28 variables were assessed for each patient.
Of these, six variables were ultimately included in the colic assessment score: Heart rate, respiratory rate, total calcium, blood lactate, an abnormal ultrasound, and an abnormal rectal exam.
The scoring ranges from 0 to 12, with the highest score representing the lowest probability of survival. The way in which is scoring works is shown in the table below.
The optimal cutoff value to predict survival was seven, resulting in an 86% sensitivity and 64% specificity, with a positive predictive value of 88% and a negative predictive value of 57%.
The scoring system was then tested on 95 horses presenting for abdominal pain to two equine hospitals. Horses that received a score above seven were classified as predicted to die, and those with a score of seven or less were predicted to survive.
The classification was then compared to the actual outcome, showing a sensitivity of 84%, specificity of 62%, a positive predictive value of 88%, and a negative predictive value of 52%.
The researchers said their scoring system is applicable for clinicians in a hospital setting with a clinical caseload of horses with colic signs using data available in most equine practices. “The Colic Assessment Score should be considered in light of the entirety of the clinical picture,” the authors said.
Further evaluation and validation of the scoring system in a larger population of horses from multiple hospitals, with the inclusion of mobile practices, would strengthen its use in clinical practice, they said.
The study team comprised Farrell and Kevin Kersh, with the Department of Veterinary Clinical Sciences at Iowa State University; Rachel Liepman, with the Chaparral Veterinary Medical Center in Cave Creek, Arizona; and Katarzyna Dembek, with the Department of Veterinary Clinical Sciences at North Carolina State University.
Farrell A, Kersh K, Liepman R and Dembek KA (2021) Development of a Colic Scoring System to Predict Outcome in Horses. Front. Vet. Sci. 8:697589. doi: 10.3389/fvets.2021.697589
The study, published under a Creative Commons License, can be read here.