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DOI 10.1007/s10877-025-01317-8

Медицинская библиотека · Journal of clinical monitoring and computing · 2025

Effectiveness of diaphragmatic ultrasound as a predictor of successful weaning from mechanical ventilation.

Elfeky Hanady Mohammed, Omaran Janna, Shaban Noha S, Elmohamady Ahmed, Doha Nagwa, Afify Noha

СтатьяНаблюдательное исследованиеПеревод пока не подготовлен

Аннотация

Purpose: Weaning from mechanical ventilation (MV) is the transition from ventilator dependence to independent breathing. Optimal timing reduces complications. Traditional predictors like the Rapid Shallow Breathing Index (RSBI), diaphragmatic excursion (DE), and diaphragm thickening fraction (DTF) have limitations. This study evaluates the clinical utility of diaphragmatic excursion RSBI (DE-RSBI) and diaphragm thickening fraction RSBI (DTF-RSBI) alongside conventional RSBI in predicting weaning success.

Methods

An observational study was conducted in the ICU of Menoufia University Hospitals on 50 adult patients mechanically ventilated for over 48 hours who underwent spontaneous breathing trials (SBT). Diaphragmatic ultrasound measured DE and DTF, from which DE-RSBI and DTF-RSBI were calculated and compared with RSBI. Weaning success was defined as maintaining spontaneous breathing for more than 48 hours post-extubation.

Results

DE-RSBI (≥1.685) showed the highest predictive accuracy (AUC=0.851, sensitivity=80%, specificity=85%). Both DE-RSBI and DTF-RSBI correlated with ICU mortality (p<0.001) and MV duration (p≤0.001). Weaning failure odds were significantly higher for DE-RSBI >1.56 (OR=12, p=0.004) and DTF-RSBI >62.33 (OR=8.04, p=0.008) compared to RSBI alone (OR=4.84, p=0.04).

Conclusions

DE-RSBI and DTF-RSBI are reliable predictors of MV weaning, outperforming RSBI alone. Their use can enhance weaning decisions, reducing failure rates and improving patient outcomes.

Для цитирования: Elfeky Hanady Mohammed, Omaran Janna, Shaban Noha S, Elmohamady Ahmed, Doha Nagwa, Afify Noha. Effectiveness of diaphragmatic ultrasound as a predictor of successful weaning from mechanical ventilation.. Journal of clinical monitoring and computing. 2025. DOI: 10.1007/s10877-025-01317-8.

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