Pedersen Monica Due, Klesiewicz Anja Bach, Marqvorsen Henriette Medom, Pedersen Hanne Gervi, Secher Jan Bojsen-Møller
University of Copenhagen, Department of Veterinary Clinical Sciences, Section for Reproduction and Obstetrics, Højbakkegårds Allé 5A, 2830 Taastrup, Denmark.
Nysted Dyreklinik, Aarestrupvej 8, 4880 Nysted, Denmark; Repro Ultrasound, Hydebysvej 11, 4990 Sakskøbing, Denmark.
Theriogenology. 2022 May;184:124-131. doi: 10.1016/j.theriogenology.2022.03.001. Epub 2022 Mar 13.
The aim of this retrospective study was to compare simple linear regression and mixed linear regression on data grouped by breed or maternal weight group. The comparison was done to find the most accurate model for predicting day of parturition in pregnant bitches in clinical practice. The retrospective data consisted of fetal biparietal diameter determined by ultrasonography and day of parturition for all included bitches. The study population was divided into five maternal weight groups (miniature (≤5 kg), small (>5 to 10 kg), medium (>10 to 25 kg), large (>25 to 40 kg), and giant (>40 kg)) with three breeds in each group with 26 miniature-breed bitches, 13 small-breed bitches, 19 medium-breed bitches, 22 large-breed bitches, and 20 giant-breed bitches. The data was used to develop models to determine the number of days before parturition based on fetal biparietal diameter. A statistically significant effect was seen for grouping by maternal weight group (p<0.0001) and by breed (p=0.0057). Breed-specific models were derived and compared to each other within the same maternal weight group. Statistically significant differences between some miniature-breed and small-breed bitches were found using mixed linear regression analysis. The accuracies of all models were given as number of births within ±1 and ±2 days of estimated day of parturition and compared to an acceptable limit of 80% at ±2 days. All breeds and maternal weight groups except Dogue de Bordeaux and giant-breed bitches met the limit. Poor accuracies were seen when applying data from each breed to the maternal weight grouped model. Simple linear regression analyses were compared to mixed linear regression analyses. The simple linear regression analyses obtained the best accuracies for most of the breeds which is most likely to be caused by overestimation. Comparison of Chihuahua and German Shepherd to other studies showed similar accuracies between the highest reported and the two linear models. We recommend the use of breed-specific models based on mixed linear regression analysis in clinical practice. Further research is needed to analyze the differences between the two linear models and to confirm the tendency of more accurate predictions of day of parturition for medium-breed, large-breed, and giant-breed bitches when using breed-specific models.
这项回顾性研究的目的是比较简单线性回归和混合线性回归在按品种或母犬体重分组的数据上的表现。进行此次比较是为了在临床实践中找到预测怀孕母犬分娩日期的最准确模型。回顾性数据包括通过超声检查确定的胎儿双顶径以及所有纳入母犬的分娩日期。研究人群被分为五个母犬体重组(微型(≤5千克)、小型(>5至10千克)、中型(>10至25千克)、大型(>25至40千克)和巨型(>40千克)),每组有三个品种,其中有26只微型品种母犬、13只小型品种母犬、19只中型品种母犬、22只大型品种母犬和20只巨型品种母犬。这些数据被用于建立基于胎儿双顶径来确定分娩前天数的模型。按母犬体重组分组(p<0.0001)和按品种分组(p = 0.0057)均显示出统计学上的显著影响。推导了特定品种的模型,并在同一母犬体重组内相互比较。使用混合线性回归分析发现一些微型品种和小型品种母犬之间存在统计学上的显著差异。所有模型的准确性以在估计分娩日期的±1天和±2天内的出生数量给出,并与±2天内80%的可接受限度进行比较。除了波尔多犬和巨型品种母犬外,所有品种和母犬体重组均达到了该限度。将每个品种的数据应用于按母犬体重分组的模型时,准确性较差。对简单线性回归分析和混合线性回归分析进行了比较。简单线性回归分析在大多数品种中获得了最佳准确性,这很可能是由高估导致的。将吉娃娃犬和德国牧羊犬与其他研究进行比较,结果显示最高报告的准确性与这两种线性模型之间相似。我们建议在临床实践中使用基于混合线性回归分析的特定品种模型。需要进一步研究来分析这两种线性模型之间的差异,并确认在使用特定品种模型时,中型、大型和巨型品种母犬在预测分娩日期方面更准确的趋势。