摘要
目的对心血管手术患者术中获得性压力性损伤风险预测工具进行范围综述,为临床实践和未来预测工具的优化和开发提供参考。方法检索PubMed、Embase、Cochrane Library、Web of Science核心合集、中国知网、万方数据服务平台、维普中文科技期刊数据库、中国生物医学文献数据库中有关心血管手术患者术中获得性压力性损伤风险预测工具的研究,检索时限为建库至2023年12月1日。由2名研究者独立筛选文献和提取数据。采用预测模型偏倚风险评价工具及诊断准确性研究质量评价工具2对纳入文献进行偏倚风险及适用性评价。结果共纳入16篇文献,涉及11个预测模型和7种筛查量表。模型构建方法多样,预测性能总体较好,手术时间、体外循环时间、年龄、术中体温、糖尿病史是模型中出现频次最高的预测因子。筛查量表预测性能较预测模型差,区分度均在0.7以下。结论目前心血管手术患者术中获得性压力性损伤风险预测工具的预测效能中等,风险预测模型的预测效能优于筛查量表,但纳入文献偏倚风险较高。临床护理人员应关注心血管手术患者术中获得性压力性损伤的高危因素,完善、更新现有工具,或在多中心大样本、前瞻性设计基础上,借助人工智能,构建预测性能佳、可操作性强的低偏倚高适用的预测工具。
ObjectiveA scoping review was performed to examine the risk prediction instruments of intraoperative acquired pressure injury(IAPI)in cardiovascular surgery patients,in order to provides references for the clinical practice and further research.MethodsThe PubMed,Embase,Cochrane Library,Web of Science,CNKI,WanFang Database,VIP Database and China Biology Medicine were searched from inception to December 1,2023.Two researchers independently screened the literature and extracted the information from the researches on instruments for predicting the risk of IAPI in cardiovascular surgery patients,to assess the risk of bias and applicability of the prediction model by using of bias assessment tool and quality assessment of diagnostic accuracy studies-2.ResultsA total of 16 studies were involved in the final review,including 11 prediction models and 7 screening instruments.There are various methods for prediction model construction with overall good prediction performance.Operation time,cardiopulmonary bypass time,age,intraoperative body temperature and history of diabetes mellitus were the most frequent predictors.The predictive performance of the screening instruments was worse than the prediction models with the area under the curve(AUC)value of below 0.7.ConclusionThe risk prediction instruments of IAPI in cardiovascular surgery patients had moderate predictive performance,and risk prediction models are better than that of screening instruments,but with higher risk of bias in risk prediction models.Clinical nursing staff should pay attention to the risk factors of IAPI in cardiovascular surgery patients,to improve and update the existing instruments,or on the basis of multicenter large sample,prospective design,prediction models with high predictive performance and operability can be developed with artificial intelligence.
作者
郭聪慧
王翔宇
臧美娜
吴荣
赵琳
李怡锦
李雪樱
侯佳艳
马艳
Guo Conghui;Wang Xiangyu;Zang Meina;Wu Rong;Zhao Lin;Li Yijin;Li Xueying;Hou Jiayan;Ma Yan(Adult Postoperative Recovery Center,Fuwai Hospital of Chinese Academy of Medical Sciences&Peking Union Medical College,Beijing 100037,China;Operation Room,Fuwai Hospital of Chinese Academy of Medical Sciences&Peking Union Medical College,Beijing 100037,China;Operation Room,Fuwai Yunnan Hospital,Chinese Academy of Medical Sciences,Kunming 650102,China)
出处
《中华心力衰竭和心肌病杂志（中英文）》
2024年第2期107-117,共11页
Chinese Journal of Heart Failure and Cardiomyopathy
基金
中国医学科学院阜外医院人工智能与信息化应用基金项目(2022-AI08)
中央高水平医院临床科研业务费资助(零余额2022-GSP-QZ-9)。
