Clinical trial NCT05487014: Artificial Intelligence in Lung Ultrasound for Preeclampsia
Official title: Evaluation of Artificial Intelligence in Defining Lung Ultrasound Findings in Anesthesia Management of Preeclampsia
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Preeclampsia
Lung Edema
Keywords: preeclampsia
lung ultrasound
artificial intelligence
Lead sponsor: Gazi University
Sponsor class: OTHER
First posted: 2022-08-04
Enrollment: 35
Sex: FEMALE
Minimum age (years): 18
Maximum age (years): 45
Standard ages: ADULT
Accepts healthy volunteers: no
Observational model: CASE_CONTROL
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: 35 parturients who diagnosed with preeclampsia

Brief summary: 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: 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.

Eligibility criteria: 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

Primary outcomes:
measure: For comparison, artificial intelligence assisted ultrasound and standard ultrasound in the follow-up of 35 preeclamptic parturients will be performed.
timeFrame: Lung ultrasound application once in the preoperative period
Secondary outcomes:
Other outcomes:
Locations:
city: Çankaya
country: Turkey
facility: Selin Bağcaz
state: Ankara
Study officials:
affiliation: Gazi University
name: D.Berrin Gunaydin, Prof.
role: PRINCIPAL_INVESTIGATOR
References: