Ko Dennis T, Ahmed Tareq, Austin Peter C, Cantor Warren J, Dorian Paul, Goldfarb Michael, Gong Yanyan, Graham Michelle M, Gu Jing, Hawkins Nathaniel M, Huynh Thao, Humphries Karin H, Koh Maria, Lamarche Yoan, Lambert Laurie J, Lawler Patrick R, Légaré Jean-Francois, Ly Hung Q, Qiu Feng, Quraishi Ata Ur Rehman, So Derek Y, Welsh Robert C, Wijeysundera Harindra C, Wong Graham, Yan Andrew T, Gurevich Yana
Schulich Heart Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.
ICES, Toronto, Ontario, Canada.
CJC Open. 2021 May 1;3(8):1051-1059. doi: 10.1016/j.cjco.2021.04.012. eCollection 2021 Aug.
Given changes in the care and outcomes of acute myocardial infarction (AMI) patients over the past several decades, we sought to develop prediction models that could be used to generate accurate risk-adjusted mortality and readmission outcomes for hospitals in current practice across Canada.
A Canadian national expert panel was convened to define appropriate AMI patients for reporting and develop prediction models. Preliminary candidate variable evaluation was conducted using Ontario patients hospitalized with a most responsible diagnosis of AMI from April 1, 2015 to March 31, 2018. National data from the Canadian Institute for Health Information was used to develop AMI prediction models. The main outcomes were 30-day all-cause in-hospital mortality and 30-day urgent all-cause readmission. Discrimination of these models (measured by c-statistics) was compared with that of existing Canadian Institute for Health Information models in the same study cohort.
The AMI mortality model was assessed in 54,240 Ontario AMI patients and 153,523 AMI patients across Canada. We observed a 30-day in-hospital mortality rate of 6.3%, and a 30-day all-cause urgent readmission rate of 10.7% in Canada. The final Canadian AMI mortality model included 12 variables and had a c-statistic of 0.834. For readmission, the model had 13 variables and a c-statistic of 0.679. Discrimination of the new AMI models had higher c-statistics compared with existing models (c-statistic 0.814 for mortality; 0.673 for readmission).
In this national collaboration, we developed mortality and readmission models that are suitable for profiling performance of hospitals treating AMI patients in Canada.
鉴于过去几十年急性心肌梗死（AMI）患者的护理和治疗结果发生了变化，我们试图开发预测模型，以用于为加拿大当前实际运营中的医院生成准确的风险调整死亡率和再入院结果。
召集了一个加拿大国家专家小组，以确定适合报告的AMI患者并开发预测模型。使用2015年4月1日至2018年3月31日因最主要诊断为AMI而住院的安大略省患者进行初步候选变量评估。利用加拿大卫生信息研究所的全国数据开发AMI预测模型。主要结局为30天全因院内死亡率和30天紧急全因再入院率。在同一研究队列中，将这些模型的区分度（用c统计量衡量）与加拿大卫生信息研究所现有模型的区分度进行比较。
在安大略省的54240例AMI患者和加拿大全国的153523例AMI患者中对AMI死亡率模型进行了评估。我们观察到加拿大的30天院内死亡率为6.3%，30天全因紧急再入院率为10.7%。最终的加拿大AMI死亡率模型包含12个变量，c统计量为0.834。对于再入院，该模型有13个变量，c统计量为0.679。与现有模型相比，新的AMI模型的区分度具有更高的c统计量（死亡率的c统计量为0.814；再入院的c统计量为0.673）。
在这项全国性合作中，我们开发了死亡率和再入院模型，适用于剖析加拿大治疗AMI患者的医院的表现。
