Clinicopathological features and comorbidities of cats with mild, moderate or severe hyperthyroidism: a radioiodine referral population
Bibliographic record
Abstract
OBJECTIVES: This study sought to explore the clinicopathological features and comorbidities of cats with mild, moderate and severe hyperthyroidism in a radioiodine referral population. METHODS: Medical records were reviewed, along with results of serum biochemistry, urinalysis, systolic blood pressure and diagnostic imaging performed at the time of radioiodine referral. Cats were grouped by total thyroxine (TT4) levels as mildly (TT4 60.1-124.9 nmol/l), moderately (TT4 125-250 nmol/l) or severely (TT4 >250 nmol/l) hyperthyroid at the time of diagnosis and referral. RESULTS: Thirty percent (42/140) of the cats were <10 years old at diagnosis. In 24.3% (34/140), hyperthyroidism was diagnosed incidentally. The time between diagnosis and referral for radioiodine was significantly longer in cats with severe hyperthyroidism at the time of referral ( P = 0.004). An increase in severity group between the time of diagnosis and referral occurred in 38.6% (54/140) of cats. At referral, 54.3% (25/46) of cats with mild, 66.7% (42/63) with moderate and 80.6% (25/31) with severe hyperthyroidism were unstable despite ongoing medical or dietary management. The prevalence of cardiac abnormalities was significantly increased in cats with severe hyperthyroidism ( P = 0.014) compared with those with mild or moderate hyperthyroidism. There was no significant difference in the likelihood of renal disease ( P = 0.708) or hypertension ( P = 0.328) between the groups. CONCLUSIONS AND RELEVANCE: Incidental diagnosis of hyperthyroidism occurs commonly, potentially owing to increased disease screening. Cats with severe hyperthyroidism at referral were more likely to be chronically hyperthyroid with a history of poor stabilisation. This subset of patients was significantly more likely to have cardiac abnormalities. Thyrotoxic cardiomyopathy may ultimately affect patient suitability for curative treatments (radioiodine or thyroidectomy) owing to higher anaesthetic risks and potential for decompensation into congestive heart failure with the stress of travel and hospitalisation. Curative therapy should be considered before the development of severe hyperthyroidism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".