Evidence map›Paper›PMID 35816461›Full record

ArticleJournal of applied clinical medical physics2022

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.

Shanshan Zhai, Hui Wang, Lichao Sun, Bo Zhang, Feng Huo, Shuang Qiu, Xiaoqing Wu, Junyu Ma, Yina Wu, Jun Duan

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Trial
  2. Observational
  3. Review
  4. AI-Enhanced POCUS in Emergency Care.Diagnostics (Basel, Switzerland) · 2026
    Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Shanshan ZhaiDepartment of Surgery Intensive Care Unit, China-Japan Friendship Hospital, Beijing, China.
Hui WangDepartment of Surgery Intensive Care Unit, China-Japan Friendship Hospital, Beijing, China.
Lichao SunDepartment of Emergency Medicine, China-Japan Friendship Hospital, Beijing, China.
Bo ZhangDepartment of Ultrasound Medicine, China-Japan Friendship Hospital, Beijing, China.
Feng HuoDepartment of Emergency Medicine, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, Beijing, China.
Shuang QiuDepartment of Intensive Care Unit, The Sixth Clinical Medical, College of Henan University of Traditional Chinese Medicine, Zhumadian, Henan Province, 463000, China.
Xiaoqing WuDepartment of Surgery Intensive Care Unit, China-Japan Friendship Hospital, Beijing, China.
Junyu MaDepartment of Surgery Intensive Care Unit, China-Japan Friendship Hospital, Beijing, China.
Yina WuDepartment of Surgery Intensive Care Unit, China-Japan Friendship Hospital, Beijing, China.
Jun DuanDepartment of Surgery Intensive Care Unit, China-Japan Friendship Hospital, Beijing, China.

Funding

China-Japan Friendship Hospital Youth Science and Technology Project 2019-1-QN-40Peking Union Medical College Teaching Reform Project 10023201902301
6 · The paper itself

Abstract

purposeThe 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.

methodsAmong 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).

resultsLeft 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 δLVOT-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

conclusionsICU 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.

Indexed as

Artificial IntelligenceVentricular Function, LeftHumansIntensive Care UnitsLactic AcidStroke VolumeLactic Acidartificial intelligencecritical careleft ventricular outflow tract velocity time integralpoint of care ultrasound training

Identifiers

PMID35816461
PMCPMC9359021

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