Seroprevalence of heartworm infection, risk factors for seropositivity, and frequency of prescribing heartworm preventives for cats in the United States and Canada
Bibliographic record
Abstract
OBJECTIVE To determine the seroprevalence of heartworm infection, risk factors for seropositivity, and frequency of prescribing heartworm preventives for cats. DESIGN Prospective cross-sectional study. ANIMALS 34,975 cats from 1,353 veterinary clinics (n = 26,707) and 125 animal shelters (8,268) in the United States and Canada. PROCEDURES Blood samples were collected from all cats and tested with a point-of-care ELISA for Dirofilaria immitis antigen, FeLV antigen, and FIV antibody. Results were compared among geographic regions and various cat groupings. RESULTS Seropositivity for heartworm antigen in cats was identified in 35 states but not in Canada; overall seroprevalence in the United States was 0.4%. Seroprevalence of heartworm infection was highest in the southern United States. A 3-fold increase in the proportion of seropositive cats was identified for those with (vs without) outdoor access, and a 2.5-fold increase was identified for cats that were unhealthy (vs healthy) when tested. Seroprevalence was 0.3% in healthy cats, 0.7% in cats with oral disease, 0.9% in cats with abscesses or bite wounds, and 1.0% in cats with respiratory disease. Coinfection with a retrovirus increased the risk of heartworm infection. Heartworm preventives were prescribed for only 12.6% of cats at testing, and prescribing was more common in regions with a higher seroprevalence. CONCLUSIONS AND CLINICAL RELEVANCE At an estimated prevalence of 0.4%, hundreds of thousands of cats in the United States are likely infected with heartworms. Given the difficulty in diagnosing infection at all clinically relevant parasite stages and lack of curative treatment options, efforts should be increased to ensure all cats receive heartworm preventives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".