Gender differences in concussion-related knowledge, attitudes and reporting behaviors of varsity athletes.

BACKGROUND: Concussion is a pathophysiological process that occurs due to a traumatic biomechanical force. Concussions are an "invisible" and common traumatic brain injury with symptoms that may be underestimated. This necessitates fundamental improvements in public knowledge specifically addressing young university athletes and different genders. This cross-sectional study aimed to explore the possibility of gender differences with respect to university student athletes' concussion knowledge, attitude and reporting behaviors. We hypothesized that there should be no significant difference in concussion knowledge among male and female student athletes; however, females would show a more positive attitude and more reporting behaviors than male student athletes. METHODS: Overall, 115 university athlete students completed a survey questionnaire; we eliminated some participants based on required inclusion criteria of Rosenbaum Concussion Knowledge and Attitude Survey-student version (RoCKAS-ST). Our final analysis consisted of 96 participants: 20 males (mean age 21.15 years) and 75 females (mean age 22.36 years). This study included questions about the athletes' given reasons for reporting or not reporting a concussion. Additionally, 33 RoCKAS-ST questions on Concussion Knowledge Index (CKI) with fair test-retest reliability (r=0.67) and 15 items on Concussion Attitude Index (CAI) with satisfactory test-retest reliability (r=0.79) were provided. RESULTS: Males reported more sources for learning about concussions and more sport-related reasons for reporting a concussion than females (P<0.05). Both genders provided equal numbers of reasons for neglecting a concussion report or not disclosing a concussion for the sake of others (i.e., family, teammates or the coach). Out of 16 given reasons for not reporting a concussion, males significantly chose sport-related reasons over female athletes (P<0.05). Additionally, by looking at the two components of RoCKAS-ST, the independent t-test results showed no significant gender-based differences in concussion knowledge and attitude indices (P>0.05). Nevertheless, females were less optimistic about evaluating other athletes' attitude over concussion reporting (P<0.05). CONCLUSIONS: Our study indicated that concussion knowledge is not gender biased among Canadian university athletes; however, more investigation is required to learn how safe environments for concussion disclosure could encourage reporting the symptoms in varsity athletes, especially in males who are more susceptible to not reporting a concussion to not miss their sport-related goals.

Epidemiological Factors Associated with Gross Diagnosis of Pulmonary Pathology in Feedyard Mortalities.

Respiratory disease continues to be the major cause of mortality in feedyard cattle, with bronchopneumonia (BP) and acute interstitial pneumonia (AIP) as the two most common syndromes. Recent studies described a combination of these pathological lesions with the presence of AIP in the caudodorsal lungs and BP in the cranioventral lungs of necropsied cattle. This pulmonary pathology has been described as bronchopneumonia with an interstitial pneumonia (BIP). The epidemiological characteristics of BIP in U.S. feedyard cattle are yet to be described. This study's objectives were to describe the agreement between feedyard clinical and necropsy gross diagnosis and to characterize epidemiological factors associated with four gross pulmonary diagnoses (AIP, BIP, BP, and Normal pulmonary tissue) observed during feedyard cattle necropsies. Systemic necropsies were performed at six feedyards in U.S. high plains region, and gross pulmonary diagnoses were established. Historical data were added to the dataset, including sex, days on feed at death (DOFDEATH), arrival weight, treatment count, and feedyard diagnosis. Generalized linear models were used to evaluate epidemiological factors associated with the probability of each pulmonary pathology. Comparing feedyard clinical diagnosis with gross pathological diagnosis revealed relatively low agreement and the frequency of agreement varied by diagnosis. The likelihood of AIP at necropsy was higher for heifers than steers and in the 100-150 DOFDEATH category compared with the 0-50 DOFDEATH (p = 0.05). The likelihood of BIP increased after the first treatment, whereas the DOFDEATH 0-50 category had a lower likelihood compared with the 150-200 category (p = 0.05). These findings highlight the importance of necropsy for final diagnosis and can aid the development of future diagnosis and therapeutic protocols for pulmonary diseases.

Determining Frequency of Common Pulmonary Gross and Histopathological Findings in Feedyard Fatalities.

Pulmonary disease is often associated with feedlot cattle mortality, and the most common syndromes include bronchopneumonia, acute interstitial pneumonia, and bronchopneumonia with an interstitial pneumonia. The study objective was to utilize gross necropsy and histopathology to determine the frequency of pulmonary lesions from three major syndromes and agreement between gross and histopathological diagnosis. A cross sectional, observational study was performed at six U.S. feedyards using a full systematic necropsy to assess mortalities during summer 2022. A subset of mortalities had four lung samples submitted for histopathological diagnosis. Gross necropsy was performed on 417 mortalities, 402 received a gross diagnosis and 189 had a histopathological diagnosis. Descriptive statistics were used to evaluate pulmonary diagnosis frequency based on method (gross/histopathology), and generalized linear mixed models were used to evaluate agreement between histopathological and gross diagnoses. Using gross diagnosis, bronchopneumonia represented 36.6% of cases with acute interstitial pneumonia and bronchopneumonia with an interstitial pneumonia representing 10.0% and 35.8%, respectively. Results identified bronchopneumonia with an interstitial pneumonia as a frequent syndrome which has only been recently reported. Histopathological diagnosis had similar findings; bronchopneumonia represented 32.3% of cases, with acute interstitial pneumonia and bronchopneumonia with an interstitial pneumonia representing 12.2% and 36.0%, respectively. Histopathological diagnosis tended (p-VALUE = 0.06) to be associated with gross diagnosis. Pulmonary disease was common and both diagnostic modalities illustrated three primary syndromes: bronchopneumonia, acute interstitial pneumonia, and bronchopneumonia with an interstitial pneumonia with similar frequencies. Improved understanding of pulmonary pathology can be valuable for evaluating and adjusting therapeutic interventions.

Image Classification and Automated Machine Learning to Classify Lung Pathologies in Deceased Feedlot Cattle.

Bovine respiratory disease (BRD) and acute interstitial pneumonia (AIP) are the main reported respiratory syndromes (RSs) causing significant morbidity and mortality in feedlot cattle. Recently, bronchopneumonia with an interstitial pattern (BIP) was described as a concerning emerging feedlot lung disease. Necropsies are imperative to assist lung disease diagnosis and pinpoint feedlot management sectors that require improvement. However, necropsies can be logistically challenging due to location and veterinarians' time constraints. Technology advances allow image collection for veterinarians' asynchronous evaluation, thereby reducing challenges. This study's goal was to develop image classification models using machine learning to determine RS diagnostic accuracy in right lateral necropsied feedlot cattle lungs. Unaltered and cropped lung images were labeled using gross and histopathology diagnoses generating four datasets: unaltered lung images labeled with gross diagnoses, unaltered lung images labeled with histopathological diagnoses, cropped images labeled with gross diagnoses, and cropped images labeled with histopathological diagnoses. Datasets were exported to create image classification models, and a best trial was selected for each model based on accuracy. Gross diagnoses accuracies ranged from 39 to 41% for unaltered and cropped images. Labeling images with histopathology diagnoses did not improve average accuracies; 34-38% for unaltered and cropped images. Moderately high sensitivities were attained for BIP (60-100%) and BRD (20-69%) compared to AIP (0-23%). The models developed still require fine-tuning; however, they are the first step towards assisting veterinarians' lung diseases diagnostics in field necropsies.