Background: Oxidative stress significantly impacts feline health, but routine biomarker testing is limited by cost, required sample volume and animal discomfort. Identifying relationships among physiological, hematological and biochemical parameters and developing predictive formulas can improve clinical screening and reduce the need for repeated blood sampling, supporting better health monitoring in companion animal practice. This study aims to investigate the relationship between physiological parameters and oxidative stress and to develop a predictive model for malondialdehyde (MDA), nitric oxide (NO) and reduced glutathione (GSH) levels in clinically healthy domestic cats. Methods: Twenty healthy domestic short-haired cats were evaluated for physiological variables, hematological profiles and oxidative stress biomarkers, including MDA, NO, GSH, ferric reducing ability of plasma (FRAP) and catalase. Pearson’s correlation and multiple linear regression analyses were used to identify significant associations and create predictive formulas. Model accuracy was validated by comparing calculated biomarker levels with laboratory measurements using paired t-tests. Result: Significant positive correlations were observed between NO and monocytes, GSH and body temperature, MDA and GSH and FRAP and heart rate (P less than 0.05). Negative correlations occurred between FRAP and eosinophils and between catalase activity and body condition score (P less than 0.05). Predictive formulas for estimating MDA, NO and GSH showed high reliability, with no significant differences from laboratory-measured values (P greater than 0.05). These formulas provide clinically applicable tools for estimating oxidative stress biomarkers from simple physiological and hematological parameters, supporting routine health monitoring in companion animal practice while reducing invasive sampling and improving feline welfare.
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Chaiyasak et al. (2026) studied this question.
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