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Record W4413785389 · doi:10.61838/kman.jpsad.3.4.9

Emerging Histomoniasis in Poultry Farms: A Narrative Review

2025· review· en· W4413785389 on OpenAlexaff
Sanaz Majidi, Mohammad Barari, Ali Tolooe

Bibliographic record

VenueJournal of Poultry Sciences and Avian Diseases · 2025
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicCoccidia and coccidiosis research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsNarrativeNarrative reviewPoultry farmingVeterinary medicineGeographyMedicineArt

Abstract

fetched live from OpenAlex

This review explores histomoniasis in poultry, focusing on its epidemiology, pathogenesis, clinical manifestations, risk factors, diagnostic methods, and control strategies. We analyzed recent literature on histomoniasis published between 2014 and 2024 using a narrative review approach. Articles were selected based on their relevance to the disease's epidemiology, clinical signs, diagnosis, and control measures. Histomoniasis, caused by Histomonas meleagridis, primarily affects turkeys and chickens, showing significant geographic variations in prevalence. The disease is transmitted through contaminated earthworms, with environmental factors such as moisture and soil type playing a crucial role in its transmission dynamics. Clinical signs include lethargy, diarrhea, and liver lesions, which can lead to high mortality rates, especially among young birds. Pathological findings typically reveal necrosis in the cecum and liver, and if left untreated, the infection can cause severe tissue damage. Various risk factors, including farming practices and co-infections, contribute to the spread and severity of histomoniasis. Diagnosis often relies on clinical signs, histopathology, and molecular methods, such as PCR, although early detection can be challenging. Control measures include antimicrobial treatments, biosecurity practices, and ongoing research into vaccines. However, existing solutions face limitations in terms of resistance and efficacy. Histomoniasis remains a significant threat to poultry health, influenced by farming practices, environmental conditions, and the presence of intermediate hosts. While antimicrobial treatments and management practices provide some level of control, further research into diagnostic tools, alternative treatments, and vaccines is essential for effective long-term disease management. Comprehensive control strategies, including enhanced biosecurity and preventive measures, are vital for reducing the impact of histomoniasis on poultry farms.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.006
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.032
GPT teacher head0.359
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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