PAH-specific therapy for pulmonary hypertension and interstitial lung disease: A systemic review and meta-analysis.

Objective: Pulmonary hypertension (PH) in context with interstitial lung disease (ILD) portends serious clinical consequences and a high rate of mortality. Recently published randomized controlled trials (RCTs) which assessed the pulmonary arterial hypertension (PAH)-specific drugs for pulmonary hypertension and interstitial lung disease (PH-ILD) revealed inconsistent clinical outcomes with previous studies. We conducted a systemic review and meta-analysis to further investigate the effect of PAH-specific therapies for PH-ILD. Methods: Clinical trials were searched from the EMBASE, PUBMED, and CENTRAL databases. The duration from the establishment of the database to June 2022 for RCTs evaluates the effect of PAH-specific therapy in patients with PH-ILD. RevMan 5.4 was used for the meta-analysis. Results: A total of six articles (with a total of 791 patients) were included, including 412 patients in the treated group and 379 patients in the control group. As compared to placebo, the change of 6MWD was a significant improvement with PAH-specific therapy in the six RCTs (23.09; 95% CI, 12.07-34.12 P < 0.0001); but when the study with inhaled treprostinil was excluded, the significant improvement in the change of 6MWD from baseline was not present anymore (MD 11.01, 95%CI-6.43-28.46 P = 0.22). There was no significant improvement in the change in lung function, hemodynamic parameters, clinical worsening, all-cause death, and serious adverse effects in the treated group compared to placebo. Conclusion: PAH-specific therapy significantly improved exercise capacity in the patients with PH-ILD, but this is due to the greater contribution of the study with inhaled treprostinil. Therefore, our findings still did not support the routine use of the whole PAH-specific drugs for PH-ILD.

Sparse ECG Denoising with Generalized Minimax Concave Penalty.

The electrocardiogram (ECG) is an important diagnostic tool for cardiovascular diseases. However, ECG signals are susceptible to noise, which may degenerate waveform and cause misdiagnosis. In this paper, the ECG noise reduction techniques based on sparse recovery are investigated. A novel sparse ECG denoising framework combining low-pass filtering and sparsity recovery is proposed. Two sparsity recovery algorithms are developed based on the traditional ℓ 1 -norm penalty and the novel generalized minimax concave (GMC) penalty, respectively. Compared with the ℓ 1 -norm penalty, the non-differentiable non-convex GMC penalty has the potential to strongly promote sparsity while maintaining the convexity of the cost function. Moreover, the GMC punishes large values less severely than ℓ 1 -norm, which is utilized to overcome the drawback of underestimating the high-amplitude components for the ℓ 1 -norm penalty. The proposed methods are evaluated on ECG signals from the MIT-BIH Arrhythmia database. The results show that underestimating problem is overcome by the proposed GMC-based method. The GMC-based method shows significant improvement with respect to the average of output signal-to-noise ratio improvement ( S N R i m p ), the average of root mean square error (RMSE) and the percent root mean square difference (PRD) over almost any given SNR compared with the classical methods, thus providing promising approaches for ECG denoising.