Investigation of the pathophysiological mechanism for altered calcium homeostasis in hyperthyroid cats
Bibliographic record
Abstract
OBJECTIVE: To investigate possible pathophysiological mechanisms (reduced plasma calcitriol concentrations and/or presence of concurrent or masked chronic kidney disease) for hypocalcaemiain hyperthyroid cats. METHODS: Prospective cohort study. Routine plasma biochemical parameters, plasma parathyroid hormone and calcitriol concentrations, ionized calcium concentrations, and venous pH, were measured at diagnosis and following treatment of hyperthyroidism. Linear regression analysis was used to determine predictors of ionized calcium concentration. RESULTS: Hyperthyroid cats (n=45) had lower ionized calcium concentrations than healthy geriatric cats (n=52), however, ionized calcium concentrations were higher in hyperthyroid cats with concurrent or masked chronic kidney disease than non-azotaemic hyperthyroid cats. Plasma calcitriol concentrations were higher in hyperthyroid cats than control cats. Plasma total thyroxine concentration and venous pH were independent predictors of ionized calcium concentration. Plasma total thyroxine concentration was also a predictor of ionized calcium concentration after adjustment for plasma parathyroid hormone and calcitriol concentrations. CLINICAL SIGNIFICANCE: Hypocalcaemia in hyperthyroid cats is not associated with the presence of concurrent or masked chronic kidney disease or reduced plasma calcitriol concentrations. Increased thyroid hormone concentrations might influence ionized calcium concentrations through a mechanism, yet to be determined, that is independent of control by parathyroid hormone and calcitriol.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".