Artificial Intelligence Versus Anesthesiologist Visual Assessment of Ejection Fraction by Transesophageal Echocardiography During Cardiac Surgery
Reliability of Artificial Intelligent General Application in Assessing Ejection Fraction in Comparison to Anesthesiologist Eye Ball by Trans Oesophageal Echo During Cardiac Surgery
This prospective observational study evaluated the reliability of a general-purpose artificial intelligence application in estimating left ventricular ejection fraction from intraoperative transesophageal echocardiography images during cardiac surgery. The artificial intelligence estimates were compared with visual assessment by two independent blinded professor anesthesiologists and with preoperative transthoracic echocardiography findings. Ejection fraction measured using M-mode and the time required for each assessment were also evaluated. The study included 93 adults undergoing elective coronary artery bypass grafting or valve surgery. The artificial intelligence assessments were performed using pseudonymized images and were not used to guide clinical decisions or patient management.
調査の概要
詳細な説明
This was a prospective, single-cohort observational study conducted at the Cardiothoracic Surgery Academy, Ain Shams University. Adults aged 21 years or older undergoing elective coronary artery bypass grafting or valve repair or replacement surgery were enrolled consecutively after providing written informed consent.
After induction of anesthesia and hemodynamic stabilization, transesophageal echocardiography images were obtained using a transgastric short-axis view at the mid-papillary level and an angle of 0 degrees. End-diastolic and end-systolic frames and an M-mode recording were collected for assessment of left ventricular ejection fraction.
Pseudonymized echocardiographic images were assessed using a general-purpose artificial intelligence application. The same images were independently assessed by two blinded professor anesthesiologists who had no access to the artificial intelligence output or the other assessments. Visual estimation of ejection fraction, M-mode-derived ejection fraction, and interpretation time were recorded. These findings were also compared with the preoperative transthoracic echocardiography assessment.
The artificial intelligence output was used exclusively for research and was not used to make or modify any clinical decision. A total of 93 eligible participants were included in the final analysis.
研究の種類
入学 (実際)
連絡先と場所
研究場所
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Cairo Governorate
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Cairo、Cairo Governorate、エジプト
- Cardiothoracic Surgery Academy, Ain Shams University Hospitals
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参加基準
適格基準
就学可能な年齢
健康ボランティアの受け入れ
受講資格のある性別
サンプリング方法
調査対象母集団
Adult patients aged 21 years or older who were scheduled for elective coronary artery bypass grafting, valve repair, or valve replacement surgery at the Cardiothoracic Surgery Academy, Ain Shams University and had an available preoperative transthoracic echocardiographic assessment.
説明
Inclusion Criteria:
- Age 21 years or older.
- Scheduled for elective cardiac surgery involving coronary artery bypass grafting, valve repair, or valve replacement.
- Availability of a preoperative transthoracic echocardiographic assessment.
- Either sex.
- American Society of Anesthesiologists physical status III or IV.
Exclusion Criteria:
- Coagulopathy, defined as an international normalized ratio greater than 2 or a platelet count below 50,000/mm3.
- Previous cardiac surgery (redo procedure).
- Esophageal or upper gastrointestinal pathology preventing safe transesophageal echocardiography probe placement, including esophageal stricture, tumor, or large varices.
- Poor-quality transesophageal echocardiography images despite standard optimization, preventing reliable interpretation.
- Severe arrhythmia or hemodynamic instability before surgery, during induction, or during surgery that could compromise the accuracy of the transesophageal echocardiography assessment.
- Refusal to participate or a condition limiting valid consent or participation, including cognitive impairment or a language barrier.
研究計画
研究はどのように設計されていますか？
デザインの詳細
- 観測モデル：COHORT
- 時間の展望：PROSPECTIVE
コホートと介入
グループ/コホート |
介入・治療 |
|---|---|
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Elective Cardiac Surgery Patients
A single cohort of 93 adult patients undergoing elective coronary artery bypass grafting or valve repair or replacement surgery. Intraoperative transesophageal echocardiography images were evaluated for left ventricular ejection fraction using artificial intelligence, anesthesiologist visual assessment, and M-mode echocardiography. |
Pseudonymized end-diastolic and end-systolic frames and an M-mode recording obtained from the transgastric short-axis mid-papillary view at 0 degrees were analyzed by a general-purpose artificial intelligence application to estimate left ventricular ejection fraction. The artificial intelligence results were compared with assessments by two independent blinded professor anesthesiologists and with preoperative transthoracic echocardiography. The artificial intelligence output was used only for research and did not guide clinical management. |
この研究は何を測定していますか？
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Difference Between AI and Anesthesiologist Visual Assessment of LVEF
時間枠：During cardiac surgery, at the time of the intraoperative TEE assessment
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Left ventricular ejection fraction was assessed from the same intraoperative transesophageal echocardiography transgastric short-axis mid-papillary view at 0 degrees by a general-purpose artificial intelligence application and by two independent blinded professor anesthesiologists using visual (eyeball) assessment. The paired assessments were compared to evaluate the difference and agreement between the artificial intelligence and anesthesiologist assessments. |
During cardiac surgery, at the time of the intraoperative TEE assessment
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二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Difference Between AI and Anesthesiologist M-Mode Assessment of LVEF
時間枠：During cardiac surgery, at the time of the intraoperative TEE assessment
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Left ventricular ejection fraction was assessed using M-mode in the intraoperative transesophageal echocardiography transgastric short-axis mid-papillary view at 0 degrees by a general-purpose artificial intelligence application and by two independent blinded professor anesthesiologists. The paired M-mode ejection fraction assessments were compared to evaluate the difference and agreement between methods. |
During cardiac surgery, at the time of the intraoperative TEE assessment
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Time Required for AI and Anesthesiologist LVEF Assessment
時間枠：During intraoperative TEE image review, from the start of each visual (eyeball) or M-mode LVEF assessment until the corresponding estimate is completed, assessed up to 3 minutes per assessment per participant.
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The time required for the general-purpose artificial intelligence application and the anesthesiologist assessors to complete the visual (eyeball) and M-mode left ventricular ejection fraction assessments was recorded separately using a timer and reported in seconds. Assessment times were compared between the artificial intelligence and anesthesiologist methods. |
During intraoperative TEE image review, from the start of each visual (eyeball) or M-mode LVEF assessment until the corresponding estimate is completed, assessed up to 3 minutes per assessment per participant.
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Difference Between Intraoperative TEE and Preoperative TTE LVEF Assessments
時間枠：From the available preoperative TTE assessment to the intraoperative TEE assessment during cardiac surgery
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Left ventricular ejection fraction estimates obtained from intraoperative transesophageal echocardiography by the general-purpose artificial intelligence application and the blinded anesthesiologist assessors were compared with the available preoperative transthoracic echocardiography ejection fraction for the same participant. The difference between each intraoperative assessment and the preoperative transthoracic echocardiography value was evaluated. |
From the available preoperative TTE assessment to the intraoperative TEE assessment during cardiac surgery
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協力者と研究者
スポンサー
研究記録日
主要日程の研究
研究開始 (実際)
一次修了 (実際)
研究の完了 (実際)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
本研究に関する用語
その他の研究ID番号
- FMASU MS 82/2026
個々の参加者データ (IPD) の計画
個々の参加者データ (IPD) を共有する予定はありますか?
IPD プランの説明
Individual participant data will not be shared because external sharing of participant-level data was not included in the approved study protocol, ethics approval, or informed consent. Only aggregate study results will be reported.
医薬品およびデバイス情報、研究文書
米国FDA規制医薬品の研究
米国FDA規制機器製品の研究
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