Transcatheter aortic valve implantation amid the COVID-19 pandemic: a nationwide analysis of the first COVID-19 wave in the Netherlands.

INTRODUCTION: The coronavirus disease 2019 (COVID-19) pandemic has put tremendous pressure on healthcare systems. Most transcatheter aortic valve implantation (TAVI) centres have adopted different triage systems and procedural strategies to serve highest-risk patients first and to minimise the burden on hospital logistics and personnel. We therefore assessed the impact of the COVID-19 pandemic on patient selection, type of anaesthesia and outcomes after TAVI. METHODS: We used data from the Netherlands Heart Registration to examine all patients who underwent TAVI between March 2020 and July 2020 (COVID cohort), and between March 2019 and July 2019 (pre-COVID cohort). We compared patient characteristics, procedural characteristics and clinical outcomes. RESULTS: We examined 2131 patients who underwent TAVI (1020 patients in COVID cohort, 1111 patients in pre-COVID cohort). EuroSCORE II was comparable between cohorts (COVID 4.5 ± 4.0 vs pre-COVID 4.6 ± 4.2, p = 0.356). The number of TAVI procedures under general anaesthesia was lower in the COVID cohort (35.2% vs 46.5%, p < 0.001). Incidences of stroke (COVID 2.7% vs pre-COVID 1.7%, p = 0.134), major vascular complications (2.3% vs 3.4%, p = 0.170) and permanent pacemaker implantation (10.0% vs 9.4%, p = 0.634) did not differ between cohorts. Thirty-day and 150-day mortality were comparable (2.8% vs 2.2%, p = 0.359 and 5.2% vs 5.2%, p = 0.993, respectively). CONCLUSIONS: During the COVID-19 pandemic, patient characteristics and outcomes after TAVI were not different than before the pandemic. This highlights the fact that TAVI procedures can be safely performed during the COVID-19 pandemic, without an increased risk of complications or mortality.

Critical analysis of electrohysterographic methods for continuous monitoring of intrauterine pressure.

Monitoring the progression of uterine activity provides important prognostic information during pregnancy and delivery. Currently, uterine activity monitoring relies on direct or indirect mechanical measurements of intrauterine pressure (IUP), which are unsuitable for continuous long-term observation. The electrohysterogram (EHG) provides a non-invasive alternative to the existing methods and is suitable for long-term ambulatory use. Several published state-of-the-art methods for EHG-based IUP estimation are here discussed, analyzed, optimized, and compared. By means of parameter space exploration, key parameters of the methods are evaluated for their relevance and optimal values. We have optimized all methods towards higher IUP estimation accuracy and lower computational complexity. Their accuracy was compared with the gold standard accuracy of internally measured IUP. Their computational complexity was compared based on the required number of multiplications per second (MPS). Significant reductions in computational complexity have been obtained for all published algorithms, while improving IUP estimation accuracy. A correlation coefficient of 0.72 can be obtained using fewer than 120 MPS. We conclude that long-term ambulatory monitoring of uterine activity is possible using EHG-based methods. Furthermore, the choice of a base method for IUP estimation is less important than the correct selection of electrode positions, filter parameters, and postprocessing methods. The presented review of state-of-the-art methods and applied optimizations show that long-term ambulatory IUP monitoring is feasible using EHG measurements.

Feasibility Study of a New Method for Low-Complexity Fetal Movement Detection From Abdominal ECG Recordings.

Fetal movement counting can provide valuable information on the fetal health, as a strong decrease in the number of movements can be seen as a precursor to fetal death. Typically, assessment of fetal health by fetal movement counting relies on the maternal perception of fetal activity. The percentage of detected movements is strongly subject dependent and with undivided attention of the mother varies between 37% and 88%. Various methods to assist in fetal movement detection exist based on a wide spectrum of measurement techniques. However, these are unsuitable for ambulatory or long-term observation. In this paper, a novel low-complexity method for fetal movement detection is presented based on amplitude and shape changes in the abdominally recorded fetal ECG. This method was compared to a state-of-the-art method from the literature. Using ultrasound-based movement annotations as ground truth, the presented method outperforms the state-of-the-art abdominal-ECG based method, with a sensitivity, specificity, and accuracy of 56%, 68%, and 63%, respectively. Additionally, a significant reduction in algorithm complexity is achieved, possibly enabling continuous ambulatory fetal movement detection and early detection of reduced fetal motility.

Influence of electrode placement on signal quality for ambulatory pregnancy monitoring.

Noninvasive fetal health monitoring during pregnancy has become increasingly important in order to prevent complications, such as fetal hypoxia and preterm labor. With recent advances in signal processing technology using abdominal electrocardiogram (ECG) recordings, ambulatory fetal monitoring throughout pregnancy is now an important step closer to becoming feasible. The large number of electrodes required in current noise-robust solutions, however, leads to high power consumption and reduced patient comfort. In this paper, requirements for reliable fetal monitoring using a minimal number of electrodes are determined based on simulations and measurement results. To this end, a dipole-based model is proposed to simulate different electrode positions based on standard recordings. Results show a significant influence of bipolar lead orientation on maternal and fetal ECG measurement quality, as well as a significant influence of interelectrode distance for all signals of interest.

Fetal movement detection based on QRS amplitude variations in abdominal ECG recordings.

Evaluation of fetal motility can give insight in fetal health, as a strong decrease can be seen as a precursor to fetal death. Typically, the assessment of fetal health by fetal movement detection relies on the maternal perception of fetal activity. The percentage of detected movements is strongly subject dependent and with undivided attention of the mother varies between 37% to 88%. Various methods to assist in fetal movement detection exist based on a wide spectrum of measurement techniques. However, these are typically unsuitable for ambulatory or long-term observation. In this paper, a novel method for fetal motion detection is presented based on amplitude and shape changes in the abdominally recorded fetal ECG. The proposed method has a sensitivity and specificity of 0.67 and 0.90, respectively, outperforming alternative fetal ECG-based methods from the literature.

Low-complexity intrauterine pressure monitoring by Teager energy estimation.

Monitoring the progression of maternal uterine activity provides important prognostic information during pregnancy and parturition. Currently used methods, however, are unsuitable for long-term observation of uterine activity. The abdominally measured electrohysterogram (EHG) provides a non-invasive alternative to the existing methods for long-term ambulatory uterine contraction monitoring. A new EHG signal analysis method for intrauterine pressure (IUP) estimation based on the Teager energy estimate is proposed. The new method is compared to existing methods from the literature in terms of estimation accuracy and computational complexity. An accurate IUP estimate, with a complexity up to 40 times lower than that of algorithms from the literature is obtained. Therefore, the proposed method offers a valuable new option for long-term uterine monitoring.

A continuous wavelet transform-based method for time-frequency analysis of artefact-corrected heart rate variability data.

Time-frequency analysis of heart rate variability (HRV) provides relevant clinical information. However, time-frequency analysis is very sensitive to artefacts. Artefacts that are present in heart rate recordings may be corrected, but this reduces the variability in the signal and therefore adversely affects the accuracy of calculated spectral estimates. To overcome this limitation of traditional techniques for time-frequency analysis, a new continuous wavelet transform (CWT)-based method was developed in which parts of the scalogram that have been affected by artefact correction are excluded from power calculations. The method was evaluated by simulating artefact correction on HRV data that were originally free of artefacts. Commonly used spectral HRV parameters were calculated by the developed method and by the short-time Fourier transform (STFT), which was used as a reference. Except for the powers in the very low-frequency and low-frequency (LF) bands, powers calculated by the STFT proved to be extremely sensitive to artefact correction. The CWT-based calculations in the high-frequency and very high-frequency bands corresponded well with their theoretical values. The standard deviations of these powers, however, increase with the number of corrected artefacts which is the result of the non-stationarity of the R-R interval series that were analysed. The powers calculated in the LF band turned out to be slightly sensitive to artefact correction, but the results were acceptable up to 20% artefact correction. Therefore, the CWT-based method provides a valuable alternative for the analysis of HRV data that cannot be guaranteed to be free of artefacts.

Latency variable source separation for heart rate detection in low-quality ECG signals.

Monitoring of the heart rate can provide vital clinical information, but can, in specific situations, be complicated due to the low signal to noise ratio (SNR) of the available physiological signals. Several methods to enhance the SNR are known from literature, e.g. wavelet-based enhancement methods, but most of these methods require a priori information on the recorded signals and are only applicable in specific situations. In this paper a generic method is presented that uses latency variable source separation (LVSS) to derive a matched filter for enhancement of electrocardiogram (ECG) signals. Besides its use on ECG signals, the LVSS method has the potential capability to enhance any kind of (quasi-) periodical signal. The LVSS method is evaluated by comparing its performance in SNR enhancement to the performance of a wavelet-based enhancement method. This performance demonstrates that for low-SNR ECG signals, the LVSS method outperforms the wavelet-based method.