Artificial Intelligence in Lung Ultrasound for Preeclampsia

Study Overview
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Brief Summary
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A total of eight quadrants of standard lung US examination was performed to all pregnant women with preeclampsia within the scope of the study by the same anesthesiologist, dividing each hemithorax into four regions through the parasternal, anterior axillary, posterior axillary vertical lines, and the horizontal line assumed to pass under the nipple. The resulting images were stored in digital media. A Lung US examination was performed once for an average of 5-10 minutes. The presence of B lines was investigated in the examination. The case was defined as interstitial edema when the B lines, which are defined as vertical linear hyperechoic reverberation artifacts representing the edematous interlobular septa/alveoli, extend posteriorly from below the pleural line and moving in sync with lung movements, are found in two or more lung areas. B-lines were determined for each case and reported in standard form in terms of number and morphology. The diagnostic accuracy of B lines was determined with the artificial intelligence supported SmartAlpha Rievi 1300 software program. B-lines validated by artificial intelligence assisted algorithm in all stored digital images were reported blindly by another anesthesiologist experienced in lung US. The clinical features, laboratory parameters, and intraoperative hemodynamic data of the cases were recorded to be evaluated in terms of relationship with lung US data. We predict that the application of lung US with artificial intelligence software will provide an opportunity to quickly evaluate the clinic of preeclamptic pregnant women who are frequently operated on in emergency conditions.

Detailed Description
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After ethics committee approval, standard lung ultrasound (US) examination in eight quadrants was performed to search presence of B lines in 35 ASA III-IV parturients with preeclampsia by the same anesthesiologist. Interstitial edema was defined by recognition of the B lines in two or more lung regions. The digital images of B-lines verified with artificial intelligence (AI) were evaluated blindly by another anesthesiologist experienced in lung US. After assigning preeclamptic patients as mild or severe; demographic, hemodynamic and labarotary results were compared. Then, lung US findings (A pattern, 3 B lines and 1 or 2 B lines) were documented. Additionally, amount of protein / 24 hr, amount of fluid infusion (crystalloid or colloid) and hemodynamic parameters acording to lung US findings were compared.

Official Title
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Evaluation of Artificial Intelligence in Defining Lung Ultrasound Findings in Anesthesia Management of Preeclampsia

Conditions
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Preeclampsia, Lung Edema

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Pregnant women who underwent cesarean section with a diagnosis of preeclampsia Exclusion Criteria: Preeclamptic parturients who have another lung disease Preeclamptic parturients whose optimal lung US image could not be obtained

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 45 Years

Sexes Eligible for Study
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Female

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| For comparison, artificial intelligence assisted ultrasound and standard ultrasound in the follow-up of 35 preeclamptic parturients will be performed. | If present, pulmonary edema will be diagnosed by visualising 3 B lines at least 2 or more regions | Lung ultrasound application once in the preoperative period | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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preeclampsia, lung ultrasound, artificial intelligence