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Objectives: To develop a predictive model for patent ductus arteriosus (PDA) in preterm infants at seven days postpartum. The model employs ultrasound measurements of the ductus arteriosus (DA) intimal thickness (IT) obtained within 24â h after birth. Methods: One hundred and five preterm infants with gestational ages ranging from 27.0 to 36.7 weeks admitted within 24â h following birth were prospectively enrolled. Echocardiographic assessments were performed to measure DA IT within 24â h after birth, and DA status was evaluated through echocardiography on the seventh day postpartum. Potential predictors were considered, including traditional clinical risk factors, M-mode ultrasound parameters, lumen diameter of the DA (LD), and DA flow metrics. A final prediction model was formulated through bidirectional stepwise regression analysis and subsequently subjected to internal validation. The model's discriminative ability, calibration, and clinical applicability were also assessed. Results: The final predictive model included birth weight, application of mechanical ventilation, left ventricular end-diastolic diameter (LVEDd), LD, and the logarithm of IT (logIT). The receiver operating characteristic (ROC) curve for the model, predicated on logIT, exhibited excellent discriminative power with an area under the curve (AUC) of 0.985 (95% CI: 0.966-1.000), sensitivity of 1.000, and specificity of 0.909. Moreover, the model demonstrated robust calibration and goodness-of-fit (χ2 value = 0.560, p > 0.05), as well as strong reproducibility (accuracy: 0.935, Kappa: 0.773), as evidenced by 10-fold cross-validation. A decision curve analysis confirmed the model's broad clinical utility. Conclusions: Our study successfully establishes a predictive model for PDA in preterm infants at seven days postpartum, leveraging the measurement of DA IT. This model enables identifying, within the first 24â h of life, infants who are likely to benefit from timely DA closure, thereby informing treatment decisions.
RESUMO
BACKGROUND: Early identification of abnormal left ventricular function in children with obstructive sleep apnea (OSA) is difficult using conventional echocardiographic indices and commonly used clinical markers of myocardial damage. We sought to investigate the value of automatic function imaging and myocardial work parameters in predicting early cardiac impairment in children having OSA with preserved left heart function and thereby identifying an optimal index for assessment. PATIENTS AND METHODS: Fifty-two children who presented with symptoms of nocturnal sleep snoring and open-mouth breathing and 34 healthy controls were enrolled in this study. Clinical characteristics and conventional echocardiographic data were collected, and image analysis was performed using two-dimensional speckle-tracking echocardiography to obtain left ventricular global longitudinal strain (GLS), post-systolic index, peak strain dispersion, global work index (GWI), global constructive work (GCW), global wasted work, and global work efficiency. RESULTS: Children with OSA had significantly lower GLS, GWI, and GCW than those without (P < 0.05). Additionally, GWI (ß = -32.87, 95% CI: -53.47 to -12.27), and GCW (ß = -35.09, 95% CI: -55.35 to -14.84) were found to correlate with the disease severity in the multiple linear regression mode, with worsening values observed as the severity of the disease increased. ROC curve analysis revealed that GCW was the best predictor of myocardial dysfunction, with an AUC of 0.809 (P < 0.001), and the best cutoff point for diagnosing myocardial damage in children with OSA was 1965.5 mmHg%, with a sensitivity of 92.5% and a specificity of 58.7%. CONCLUSIONS: GLS, GWI, and GCW were identified as predictors of myocardial dysfunction in children with OSA, with GCW being the best predictor.