Non-invasive foetal electrocardiography (NI-FECG) has become an important prenatal monitoring method in the hospital. However, due to its susceptibility to non-stationary noise sources and lack of robust extraction methods, the capture of high-quality NI-FECG remains a challenge. Recording waveforms of sufficient quality for clinical use typically requires human visual inspection of each recording. A Signal Quality Index (SQI) can help to automate this task but, contrary to adult ECG, work on SQIs for NI-FECG is sparse. In this paper, a multi-channel signal quality classifier for NI-FECG waveforms is presented. The model can be used during the capture of NI-FECG to assist technicians to record high-quality waveforms, which is currently a labour-intensive task. A Convolutional Neural Network (CNN) is trained to distinguish between NI-FECG segments of high and low quality. NI-FECG recordings with one maternal channel and three abdominal channels were collected from 100 subjects during a routine hospital screening ($102.6$ $\min$ of data). The model achieves an average 10-fold cross-validated AUC of $0.95 \pm 0.02$. The results show that the model can reliably assess the FECG signal quality on our dataset. The proposed model can improve the automated capture and analysis of NI-FECG as well as reduce technician labour time.

Background: In patients with advanced cancer receiving immune checkpoint inhibitors (ICIs) therapy, there are conflict perspectives about the influence of concomitant use of proton pump inhibitors (PPIs). We are aimed at exploring the influence of concomitant PPIs exposure on clinical outcome among cancer patients receiving ICIs treatment. Methods: We searched relevant literatures in PubMed, EMBASE, and the Cochrane Library without language restrictions. We extracted the data from selected studies and calculated the pooled hazard ratios (HRs) with 95% CIs through professional software for overall survival and progression-free survival among cancer patients undergoing ICIs therapy exposed to PPIs. Results: Fourteen studies including 6716 advanced cancer patients receiving ICIs treatment were appropriate for analysis judging by pre-set inclusion and exclusion criteria. The result indicated that concomitant PPIs exposure was significantly related to shorter overall survival (HR=1.388; 95% CI: 1.278-1.498, P<0.001) and progression-free survival (HR=1.285; 95% CI: 1.193-1.384, P<0.001) among multiple cancer patients receiving ICIs therapy. Conclusions: Our meta-analysis showed that concomitant PPIs exposure had an adverse impact on clinical outcome among patients receiving ICIs therapy. Clinical oncologists must be cautious of PPIs delivery during ICIs treatment.