高级检索
当前位置: 首页 > 详情页

Artificial intelligence (AI) versus expert: A comparison of left ventricular outflow tract velocity time integral (LVOT-VTI) assessment between ICU doctors and an AI tool

文献详情

资源类型:
WOS体系:
Pubmed体系:

收录情况: ◇ SCIE

单位: [1]China Japan Friendship Hosp, Dept Surg Intens Care Unit, Beijing, Peoples R China [2]China Japan Friendship Hosp, Dept Emergency Med, Beijing, Peoples R China [3]China Japan Friendship Hosp, Dept Ultrasound Med, Beijing, Peoples R China [4]Capital Med Univ, Beijing Childrens Hosp, Natl Ctr Childrens Hlth, Dept Emergency Med, Beijing, Peoples R China [5]Henan Univ Tradit Chinese Med, Clin Med Coll 6, Dept Intens Care Unit, Zhumadian 463000, Henan, Peoples R China
出处:
ISSN:

关键词: artificial intelligence critical care left ventricular outflow tract velocity time integral point of care ultrasound training

摘要:
Purpose The application of point of care ultrasound (PoCUS) in medical education is a relatively new course. There are still great differences in the existence, quantity, provision, and depth of bedside ultrasound education. The left ventricular outflow tract velocity time integral (LVOT-VTI) has been successfully used in several studies as a parameter for hemodynamic management of critically ill patients, especially in the evaluation of fluid responsiveness. While LVOT-VTI has been broadly used, valuable applications using artificial intelligence (AI) in PoCUS is still limited. We aimed to identify the degree of correlation between auto LVOT-VTI and the manual LVOT-VTI acquired by PoCUS trained ICU doctors. Methods Among the 58 ICU doctors who attended PoCUS training from 1 September 2019 to 30 November 2020, 46 ICU doctors who trained for more than 3 months were enrolled. At the end of PoCUS training, each of the enrolled ICU doctors acquired echocardiography parameters of a new ICU patient in 2 h after new patient was admitted. One of the two bedside expert sonographers would take standard echocardiogram of new ICU patients within 24 h. For ICU doctors, manual LVOT-VTI was obtained for reference and auto LVOT-VTI was calculated instantly by using an AI software tool. Based on the image quality of the auto LVOT-VTI, ICU patients was separated into ideal group (n = 31) and average group (n = 15). Results Left ventricular end-diastolic dimension (LVEDd, p = 0.1028), left ventricular ejection fraction (LVEF, p = 0.3251), left atrial dimension (LA-d, p = 0.0962), left ventricular E/A ratio (p = 0.160), left ventricular wall motion (p = 0.317) and pericardial effusion (p = 1) had no significant difference between trained ICU doctors and expert sonographer. ICU patients in average group had greater sequential organ failure assessment (SOFA) score (7.33 +/- 1.58 vs. 4.09 +/- 0.57, p = 0.022) and lactic acid (3.67 +/- 0.86 mmol/L vs. 1.46 +/- 0.12 mmol/L, p = 0.0009) with greater value of LVEDd (51.93 +/- 1.07 vs. 47.57 +/- 0.89, p = 0.0053), LA-d (39.06 +/- 1.47 vs. 35.22 +/- 0.98, p = 0.0334) and percentage of decreased wall motion (p = 0.0166) than ideal group. There were no significant differences of delta LVOT-VTI (|manual LVOT-VTI - auto LVOT-VTI|/manual VTI*100%) between the two groups (8.8% +/- 1.3% vs. 10% +/- 2%, p = 0.6517). Statistically, significant correlations between manual LVOT-VTI and auto LVOT-VTI were present in the ideal group (R-2 = 0.815, p = 0.00) and average group (R-2 = 0.741, p = 0.00). Conclusions ICU doctors could achieve the satisfied level of expertise as expert sonographers after 3 months of PoCUS training. Nearly two thirds of the enrolled ICU doctors could obtain the ideal view and one third of them could acquire the average view. ICU patients with higher SOFA scores and lactic acid were less likely to acquire the ideal view. Manual and auto LVOT-VTI had statistically significant agreement in both ideal and average groups. Auto LVOT-VTI in ideal view was more relevant with the manual LVOT-VTI than the average view. AI might provide real-time guidance among novice operators who lack expertise to acquire the ideal standard view.

基金:
语种:
WOS:
PubmedID:
中科院(CAS)分区:
出版当年[2021]版:
大类 | 4 区 医学
小类 | 4 区 核医学
最新[2025]版:
大类 | 4 区 医学
小类 | 4 区 核医学
JCR分区:
出版当年[2020]版:
Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
最新[2023]版:
Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

影响因子: 最新[2023版] 最新五年平均[2021-2025] 出版当年[2020版] 出版当年五年平均[2016-2020] 出版前一年[2019版] 出版后一年[2021版]

第一作者:
第一作者单位: [1]China Japan Friendship Hosp, Dept Surg Intens Care Unit, Beijing, Peoples R China
共同第一作者:
通讯作者:
通讯机构: [1]China Japan Friendship Hosp, Dept Surg Intens Care Unit, Beijing, Peoples R China [*1]2 Yinghuadongjie Rd, Beijing 100029, Peoples R China
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:1320 今日访问量:0 总访问量:816 更新日期:2025-04-01 建议使用谷歌、火狐浏览器 常见问题

版权所有:重庆聚合科技有限公司 渝ICP备12007440号-3 地址:重庆市两江新区泰山大道西段8号坤恩国际商务中心16层(401121)