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Internal MedicineCohort / Prospective2 min read · distilled by Vetree AI

Association of hypoalbuminemia with disease and survival in 1664 cats presenting to a tertiary teaching hospital: a retrospective case-control study.

Hayes CC, Zhu X, Pazzi P, Schmid SM · Journal of Veterinary Internal Medicine · 1 July 2026

Clinical bottom line

Severe hypoalbuminemia in cats strongly predicts poor survival and warrants prioritized investigation for infectious disease.

Summary

This retrospective case-control study evaluated 1664 cats (832 hypoalbuminemic [HA] and 832 controls without hypoalbuminemia [wHA]) presenting to a tertiary teaching hospital between 2017 and 2023 to characterize disease associations and outcomes across HA severity groups. Hypoalbuminemia was defined as mild (2.5–2.9 g/dL), moderate (2.0–2.4 g/dL), or severe (<2.0 g/dL), with a prevalence of 32% in the studied population. Cats with HA were significantly more likely to have infectious (25%) or neoplastic (24%) pathoetiologies, and diseases affecting the hematopoietic or multisystemic organ systems compared to wHA cats. Severe HA was disproportionately associated with infectious disease compared to all other severity groups. Cats with HA experienced longer hospitalizations and significantly shorter survival times than wHA cats. Restricted mean survival analysis to 6 months demonstrated markedly reduced survival in severe HA cats (71 days) compared to wHA cats (144 days), mild HA cats (119 days), and moderate HA cats (108 days). These findings support hypoalbuminemia as a clinically meaningful prognostic indicator in cats, with severity correlating with worsening outcomes. The authors recommend prioritizing investigation for infectious etiologies in cats presenting with severe hypoalbuminemia, as this association was statistically robust. Clinicians should consider albumin concentration both as a diagnostic clue and a prognostic marker when evaluating hospitalized cats.

Internal MedicineSmall AnimalEmergencyPathology

This summary was distilled by AI and may occasionally misinterpret data. Confirm critical details with the primary literature before clinical application.