Transthoracic ultrasound in neonatal respiratory distress syndrome (NRDS): Complementary diagnostic tool

Diagnostic value of bedside lung ultrasound and 12-zone score in the 65 cases of neonatal respiratory distress syndrome and its severity

OBJECTIVE

To explore the predictive value of bedside lung ultrasound score in the severity of neonatal respiratory distress syndrome (NRDS) and mechanical ventilation and extubation.

METHODS

The clinical data of 65 neonates with NRDS and invasive mechanical ventilation diagnosed in the neonatal intensive care unit of our hospital from July 2021 to July 2022 were retrospectively analyzed. 65 neonates were included in the NRDS group, and 40 neonates with other common lung diseases were selected as the other lung disease groups. All neonates underwent lung ultrasound and X-ray examination. The correlation between lung ultrasound scores and arterial blood gas indexes was analyzed by Pearson. The efficacy of successful evacuation of mechanical ventilation was evaluated by lung ultrasound analysis by ROC curve analysis.

RESULTS

The positive rates of lung consolidation and white lung in NRDS group were higher than the other lung disease groups (P < 0.05). The positive rates of bronchial inflation sign and double lung points were lower than these in the other lung disease groups (P < 0.05). The ultrasound scores of both lungs, left lung, right lung, bilateral lung and double basal lung in the NRDS group were significantly higher than those in the other lung disease groups (P < 0.05). There was a significant positive correlation between lung ultrasound score and X-ray grade (r = 0.841, P < 0.001). The area under the curve (AUC) of lung ultrasound score for the differential diagnosis of NRDS and common lung diseases was 0.907. The AUC of lung ultrasound score in the differential diagnosis of mild and moderate, and moderate and severe NRDS were 0.914 and 0.933, respectively, which had high clinical value. The lung ultrasound score was positively correlated with the level of PaCO2 (r = 0.254, P = 0.041), and negatively correlated with the levels of SpO2 and PaO2 (r = - 0.459, - 0.362, P = 0.001, 0.003). The AUC of successful mechanical ventilation withdrawal predicted by the pulmonary ultrasound score before extubation was 0.954 (95% CI 0.907-1.000). The predictive value of successful extubation was 10 points of the pulmonary ultrasound score, with a sensitivity of 93.33% and a specificity of 88.00%.

CONCLUSION

The bedside lung ultrasound score can intuitively reflect the respiratory status of neonates, which provides clinicians with an important basis for disease evaluation.

Lung Ultrasound in the Evaluation of Neonatal Respiratory Distress Syndrome

OBJECTIVE

The purpose of this study is to examine the impact of bedside lung ultrasound (LUS) and LUS scores in the evaluating and grading of neonatal respiratory distress syndrome (NRDS).

METHODS

We performed a prospective study on 80 children with suspected NRDS. Infants with a PaO2 -to-FiO2 ratio of <200, 200-300, and >300 mmHg were categorized as the "severe-NRDS group," "mild-NRDS group," and "non-NRDS group," respectively. Left and right lungs were divided into six areas, respectively. For each lung area, a 0- to 3-point score was given.

RESULTS

The most common ultrasonic signs of NRDS include bilateral coalescent B-lines, thickened pleural line, and white lung without spared areas. Moreover, different LUS scores among non-NRDS, mild-NRDS, and severe-NRDS groups were identified (6.00 ± 4.033, 25.82 ± 3.778 and 27.90 ± 4.071, respectively; P < .05). When the cutoff value of LUS score was selected as 13 for the differentiation of non-NRDS from NRDS, the sensitivity and specificity were 96.9% and 93.3%, respectively, and the area under the curve (AUC) of receiver operating characteristics (ROC) was 0.938 (95% confidence interval [CI], 0.84-1.00). With a cutoff value of 26.5 for the differentiation between mild- and severe-ARDS, the AUC of ROC curve of the LUS score was 0.707 (95% CI, 0.58-0.83). Similar results were revealed as those with chest X-ray.

CONCLUSION

This study showed that LUS and LUS scores complement each other, and are highly reliable and efficient in bedside radiological diagnostic investigations in newborns with NRDS.

Ultrasound Lung Image under Artificial Intelligence Algorithm in Diagnosis of Neonatal Respiratory Distress Syndrome

In order to analyze the application of ultrasonic lung imaging diagnosis model based on artificial intelligence algorithm in neonatal respiratory distress syndrome (NRDS), an ultrasonic lung imaging diagnosis model based on a deep residual network (DRN) was proposed. In this study, 90 premature infants in the hospital were selected as the research object and divided into the experimental group (45 cases) and control group (45 cases) according to whether or not they have NRDS. DRN was compared with the deep residual network (DRWSR) based on wavelet domain, deep residual network detection with normalization framework (Fisher-DRN), and distorted image edge detection preprocessor (DIEDP). Then, it was applied to the diagnosis of NRDS. The clinical data and ultrasound imaging results of infants with NRDS and ordinary premature infants were compared. The results showed that the gestational age, birth weight, and Apgar scores of the NRDS group were remarkably lower than those of ordinary children (P < 0.05). In addition, the segmentation accuracy, image feature extraction accuracy, algorithm convergence, and time loss of the DRN algorithm were better than the other three algorithms, and the differences were considerable (P < 0.05). In children with NRDS, the positive rate of abnormal pleural line, disappearance of A line, appearance of B line, and alveolar interstitial syndrome (AIS) test in the results of lung ultrasound examination in children with NRDS were all 100%. The lung consolidation became 70.8%, and the white lung-like change was 50.1%, both of which were higher than those of ordinary preterm infants, and the differences were considerable (P < 0.05). The diagnostic model of this study predicted that the AUC area of grade 1-2, grade 2-3, and grade 3-4 NRDS were 0.962, 0.881, and 0.902, respectively. To sum up, the ultrasound lung imaging diagnosis model based on the DRN algorithm had good diagnostic performance in children with NRDS and can provide useful information for clinical NRDS diagnosis and treatment.

The safety and effectiveness of heated humidified high-flow nasal cannula as an initial ventilation method in the treatment of neonatal respiratory distress syndrome: A protocol for systematic review and meta-analysis

BACKGROUND

This study uses a method of systematic evaluation to evaluate the safety and effectiveness of heated humidified high-flow nasal cannula (HHHFNC) as an initial ventilation method in the treatment of neonatal respiratory distress syndrome (NRDS) scientifically. In the field of evidence-based medicine, this study provides a theoretical reference and basis for choosing appropriate initial non-invasive ventilation methods in the treatment of NRDS, thereby providing assistance for clinical treatment.

METHODS

The main electronic network databases were searched by computer, including 4 Chinese databases: CNKI, WangFang Data, CQVIP, SinoMed and 3 English databases: PubMed, The Cochrane Library and EMBASE, the time range of retrieval from the beginning of each database to September 1, 2020. The content involves all the published randomized controlled trials on the effectiveness of HHHFNC compared with NCPAP as an initial ventilation method in the treatment of NRDS. Using a search method that combines medical subject words and free words. Based on the Cochrane risk bias assessment tool, 2 researchers independently screen the literature, and then extract the data we needed in the literature, and cross-check. If it is difficult to decide whether to include literature, then turning to a third researcher for help and making a final decision after discussion, and using RevMan 5.3 and STATA 13.0 to analyze the relative data.

RESULTS

Based on the method of meta-analysis, this study analyzes the pre-determined outcome indicators through scientific statistical analysis, and compares the effectiveness and safety of HHHFNC compared with NCPAP as an initial ventilation method in the treatment of NRDS. All results will be published in peer-reviewed high-quality professional academic journals.

CONCLUSION

Based on evidence-based medicine, this study will obtain the establishing evidence of comparison that the clinical effectiveness and safety of HHHFNC compared with NCPAP as an initial ventilation method in the treatment of NRDS through the existing data and data, which provides the evidence support of evidence-based medicine in the treatment of NRDS.

OSF REGISTRATION NUMBER

September 17, 2020. osf.io/f6at4 (https://osf.io/f6at4).