283 Identification of new or existing risk factors associated with the development of sow pelvic organ prolapse
Notice bibliographique
Résumé
Abstract A survey was conducted between March and December of 2022 to examine the variation between farms that had high and low pelvic organ prolapse (POP) rate. The objective was to identify new or existing risk factors associated with the development of POP, which could open new avenues for further investigation. Sow farms (n = 53) across 26 production systems located in the US, Canada, and Mexico were used. Sampling of farms was not random. High and low POP systems were selected within each region as well as high and low POP farms within each system. Over 800 variables related to general farm information and management, performance traits, reproductive management, replacement gilt management, gestation and farrowing practices, labor and health management, and nutrition were collected during farm visits. To be included in the analysis, at least 70% of observations were needed for continuous variables with at least 10% of observation for each category for categorical variables. Univariable models were fitted to identify variables associated with annualized POP rate for 2021. Variables with P ≤ 0.10 were selected for further analysis, with 94 predictor variables selected for principal components analysis (PCA). A factor analysis of mixed data was conducted, and results were then fitted into a hierarchical clustering on PCA, which segregated the data into three clusters: 2 with low POP (2.5%) and 1 with high POP (6.1%) prevalence (low vs high P < 0.05). The resulting clusters explained 33.7% of the variability in annualized 2021 POP rate. Differences between clusters were evaluated by Kruskall-Wallis test for numerical variables and chi-square test for categorical variables. High POP cluster farms had greater total piglets born over the years, greater number of sows per worker, greater annual gestation feed usage, and a lower mean body condition score at 16 wk of gestation compared with low POP cluster farms. High POP cluster farms had a decreased proportion of farms using conventional artificial insemination, a greater proportion of farms utilizing cup waterers in gestation for sows in group housing and in farrowing, and greater proportion of farms with a routine sleeving practice. High POP cluster farms compared with low POP cluster farms had greater gestation distillers dried grains with solubles (DDGS) inclusion level (14.6% vs 4.0%, SE 3.02), greater levels of standardized total tract digestibility (STTD) P% (0.49% vs 0.39%, SE 0.014), narrower analyzed Ca to STTD P ratio (1.7 vs 2.2, SE 0.06), and lower phytase inclusion and release (0.16% vs 0.09%, SE 0.014). These variables were also the predictors with the greatest R2 values in the univariable models. These observations suggest further research is needed to evaluate the connection between dietary Ca and P and pelvic organ prolapse.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».