Furusato Shimon, Kurogochi Kentaro, Mizuno Masashi, Shinoda Satoru, Tanoshima Reo, Uechi Masami
JASMINE Veterinary Cardiovascular Medical Center, Yokohama, Japan.
Department of Health Data Science, Graduate School of Data Science, Yokohama City University, Yokohama, Japan.
J Vet Intern Med. 2025 Jul-Aug;39(4):e70152. doi: 10.1111/jvim.70152.
Mitral valve repair (MVR) has emerged as a novel surgical intervention for dogs with myxomatous mitral valve disease (MMVD). However, no objective risk assessment method has been established for these cases.
The primary aim of this study was to develop and evaluate preoperative prediction models for 30-day postoperative mortality in dogs undergoing MVR. The secondary aim was to assess the association between short-term predictive risk and long-term mortality following MVR.
A total of 2089 client-owned dogs with MMVD that underwent MVR between 2016 and 2023 were included.
This was a single-center retrospective cohort study. Preoperative variables including demographic data, routine blood test results, diagnostic imaging examination data, and medication history were selected as predictor candidates. Prediction models for 30-day all-cause mortality were developed using these variables and shrinkage estimation methods, and the model performances were evaluated. The association between the predicted probabilities and 2-year cumulative all-cause mortality was assessed using Cox proportional hazards analysis.
The 30-day all-cause mortality rate after MVR was 4.9% (102/2089). The best preoperative prediction model for 30-day all-cause death demonstrated low-to-moderate discrimination abilities (c-statistics, 0.654) and good calibration performance (slope = 1.003; intercept = 0.007; E = 0.002) in internal validation. The quartile grouping of the predicted 30-day all-cause mortality risk was associated with 2-year mortality.
The preoperative prediction model for short-term mortality in dogs undergoing MVR demonstrated acceptable predictive performance. The prediction model may provide an objective preoperative risk assessment in dogs undergoing MVR at this center.
二尖瓣修复术(MVR)已成为治疗患有黏液瘤性二尖瓣疾病(MMVD)犬的一种新型手术干预方法。然而,尚未针对这些病例建立客观的风险评估方法。
本研究的主要目的是开发并评估接受MVR的犬术后30天死亡率的术前预测模型。次要目的是评估MVR后短期预测风险与长期死亡率之间的关联。
纳入了2016年至2023年间接受MVR的总共2089只客户拥有的患有MMVD的犬。
这是一项单中心回顾性队列研究。选择术前变量,包括人口统计学数据、常规血液检测结果、诊断性影像学检查数据和用药史作为预测指标候选变量。使用这些变量和收缩估计方法开发30天全因死亡率的预测模型,并评估模型性能。使用Cox比例风险分析评估预测概率与2年累积全因死亡率之间的关联。
MVR后30天全因死亡率为4.9%(102/2089)。用于30天全因死亡的最佳术前预测模型在内部验证中显示出低至中等的区分能力(c统计量,0.654)和良好的校准性能(斜率 = 1.003;截距 = 0.007;E = 0.002)。预测的30天全因死亡风险的四分位数分组与2年死亡率相关。
接受MVR的犬短期死亡率的术前预测模型显示出可接受的预测性能。该预测模型可为该中心接受MVR的犬提供客观的术前风险评估。