ObjectiveTo investigate the effects of continuous positive airway pressure (CPAP) ventilation on blood pressure and related inflammatory factors in patients with obstructive sleep apnea hypopnea syndrome (OSAHS) and refractory hypertension, and explore the correlation between respiratory function and related inflammatory factors.MethodsPatients with OSAHS and refractory hypertension who visited Shenzhen Nanshan People’s Hospital between January 2014 and September 2018 were randomly divided into a CPAP group and a control group. The control group received routine treatment. The CPAP group received CPAP on the basis of conventional treatment. Each intervention lasted for 7 days. The changes of systolic and diastolic blood pressure were measured before and after 1, 3, 5, and 7 days, respectively. The respiratory function and related inflammatory factors were measured after 7 days of intervention.ResultsAfter 7 days of treatment in the CPAP group, the levels of apnea hyperpnoea index (AHI), lowest oxygen saturation and oxygen desaturation index were significantly better than those before intervention, with the improvement of respiratory function significantly higher than that of the control group after 7 days. Meanwhile the systolic and diastolic blood pressure levels were significantly lower in the CPAP group than those of the control group at 1, 3, 5, and 7 days, and lower than the pre-intervention after 7 days of intervention. After 7 days of intervention, the inflammatory factors in both groups were significantly improved (all P<0.05). However, the serum levels of high sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α) and endothelin-1 (ET-1) in the CPAP group were significantly lower than those of the control group after 7 days of treatment (P<0.05). There was a significant positive correlation between AHI level and hs-CRP, IL-6, TNF-α and ET-1 in the CPAP group after intervention (P<0.001).ConclusionsCPAP can significantly improve the blood pressure of patients with OSAHS and refractory hypertension. CPAP may improve the related inflammatory factors by improving the respiratory function of patients, thus reduce the patient’s blood pressure.
In computer-aided medical diagnosis, obtaining labeled medical image data is expensive, while there is a high demand for model interpretability. However, most deep learning models currently require a large amount of data and lack interpretability. To address these challenges, this paper proposes a novel data augmentation method for medical image segmentation. The uniqueness and advantages of this method lie in the utilization of gradient-weighted class activation mapping to extract data efficient features, which are then fused with the original image. Subsequently, a new channel weight feature extractor is constructed to learn the weights between different channels. This approach achieves non-destructive data augmentation effects, enhancing the model's performance, data efficiency, and interpretability. Applying the method of this paper to the Hyper-Kvasir dataset, the intersection over union (IoU) and Dice of the U-net were improved, respectively; and on the ISIC-Archive dataset, the IoU and Dice of the DeepLabV3+ were also improved respectively. Furthermore, even when the training data is reduced to 70 %, the proposed method can still achieve performance that is 95 % of that achieved with the entire dataset, indicating its good data efficiency. Moreover, the data-efficient features used in the method have interpretable information built-in, which enhances the interpretability of the model. The method has excellent universality, is plug-and-play, applicable to various segmentation methods, and does not require modification of the network structure, thus it is easy to integrate into existing medical image segmentation method, enhancing the convenience of future research and applications.