Effects of Pulse Transit Time and Pulse Arrival Time on Cuff-less Blood Pressure Estimation: A Comparison Study with Multiple Experimental Interventions.

Pulse transit time (PTT) has shown a correlation with blood pressure (BP), and it is considered as a potential marker for cuff-less BP estimation. However, pulse arrival time (PAT) including pre-ejection period (PEP) has been utilized more widely because of its convenience to acquisition and calculation. In spite of this, whether PAT can surrogate PTT has been a controversial topic for many years. In this study, we designed an experiment on 55 subjects with multiple interventions, those may cause the changes in BP and PEP. We analyzed the linear and nonlinear correlations between BP and PTT/PAT, and also assessed the performances of PTT-based and PAT-based models on tracking the BP variation. Five typical BP estimation models were used for comparison. We found that PEP could change rapidly in response to the interventions related with physical stress. Although PTT had a better linear correlation with BP, most of the PAT-based models showed more accuracy than PTT-based models in all of the interventions, especially for the calibrated models. It is suggested that PAT has the potential to predict BP, and the inclusion of PEP in the measurement of PAT is necessary.

Impact of Paxlovid on in-hospital outcomes and post-COVID-19 condition in adult patients infected with SARS-CoV-2 Omicron variant: A non-randomized controlled clinical trial.

BACKGROUND: Nirmatrelvir plus ritonavir (Paxlovid) have been used in the treatment of adult patients with mild-to-moderate coronavirus disease 2019 (COVID-19). This study aimed to evaluate the impact of Paxlovid on in-hospital outcomes and post-COVID-19 condition in Chinese adult patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant. METHODS: This non-randomized clinical controlled trial recruited patients infected with SARS-CoV-2 Omicron variant from the designated hospital for treating COVID-19 between November 5 and November 28, 2022, in Shijiazhuang, China. Participants were administered Paxlovid (300 mg of nirmatrelvir and 100 mg of ritonavir orally) or standard treatment. The primary outcome was the nucleic acid shedding time and post-COVID-19 condition. RESULTS: A total of 320 patients infected with SARS-CoV-2 Omicron variant were included, with mean age of 29.10 ±â€…7.34 years old. Two hundred patients received Paxlovid. Compared to patients in the standard treatment group, those in Paxlovid group had a significantly shorter nucleic acid shedding time (3.26 ±â€…1.80 vs 7.75 ±â€…3.68 days, P < .001), shorter days until negative swab test (1.74 ±â€…1.15 vs 5.33 ±â€…2.91, P < .001), shorter days of first symptoms resolution (4.86 ±â€…1.62 vs 7.45 ±â€…2.63, P < .001), higher in nucleic acid test negative rate within 3 days [138 (70.77%) vs 14 (11.67%), P < .001], higher negative rate within 5 days [174 (89.23%) vs 26 (21.67%), P < .001], negative rate within 7 days [185 (94.87%) vs 78 (65.00%), P < .001], and were less likely to have post-COVID-19 condition [32 (18.60%) vs 30 (31.57%), P = .016]. There was no significant difference in duration of post-COVID-19 condition (43.00 ±â€…26.00 vs 49.00 ±â€…26.34 days, P = .354) between the 2 groups. CONCLUSION: Compared to standard treatment, Paxlovid significantly reduced nucleic acid shedding time, days until negative swab test, and days of first symptoms resolution, as well as improved nucleic acid test negative rate and post-COVID-19 condition.

Metabolic alterations in patients with Helicobacter pylori-related gastritis: The H. pylori-gut microbiota-metabolism axis in progression of the chronic inflammation in the gastric mucosa.

PURPOSE: To characterize the serum metabolism in patients with Helicobacter pylori-positive and H. pylori-negative gastritis. METHODS: Clinical data and serum gastric function parameters, PGI (pepsinogen I), PGII, PGR (PGI/II), and G-17 (gastrin-17) of 117 patients with chronic gastritis were collected, including 57 H. pylori positive and 60 H. pylori negative subjects. Twenty cases in each group were randomly selected to collect intestinal mucosa specimens and serum samples. The gut microbiota profiles were generated by 16S rRNA gene sequencing, and the serum metabolites were analyzed by a targeted metabolomics approach based on liquid chromatography-mass spectrometry (LC-MS) technology. RESULTS: Altered expression of 20 metabolites, including isovaleric acid, was detected in patients with HPAG. Some taxa of Bacteroides, Fusobacterium, and Prevotella in the gut microbiota showed significant correlations with differentially expressed metabolites between H. pylori positive and H. pylori negative individuals. As a result, an H. pylori-gut microbiota-metabolism (HGM) axis was proposed. CONCLUSION: Helicobacter pylori infection may influence the progression of mucosal diseases and the emergence of other complications in the host by altering the gut microbiota, and thus affecting the host serum metabolism.

Exosomes Derived by SIRT1-Overexpressing Bone Marrow Mesenchymal Stem Cells Improve Pubococcygeus Muscle Injury in Rats.

BACKGROUND AND OBJECTIVES: To evaluate the effect of exosomes (Exos) derived from silent mating type information regulation 2 homolog 1 (SIRT1)-overexpressing human bone marrow mesenchymal stem cells (BMSCs) on the recovery of pubococcygeus muscle Injury. METHODS AND RESULTS: Exos isolated from SIRT1-overexpressing BMSCs (SIRT1/exos) were injected into a vaginal dilation-induced rat model of Stress urinary incontinence (SUI). The efficacy of Exos treatment on SUI was evaluated by determining the values of urodynamic parameters. The proliferation and differentiation of satellite cells (SCs) were examined by CCK-8 assay, Western blotting, and immunofluorescence staining. The mRNA and protein expression of molecules related to SC differentiation were detected by RT-qPCR and Western blotting, respectively. Treatment with SIRT1/exos significantly improved the values of abdominal leak point pressure (ALPP), maximum bladder volume (MBV), and estimated marginal mean in rats of SUI. Exposure of SIRT1/exos enhanced the proliferation, differentiation, and activation of SCs. Moreover, SIRT1/exos exhibited their positive effect on BMSCs by activating the ERK signaling. CONCLUSIONS: Our findings demonstrated that SIRT1/exos meliorated pubococcygeus muscle injury in rats by promoting ERK pathway, which may provide a novel cell-free therapeutic strategy for SUI.

Electrochemical modeling and evaluation for textile electrodes to skin.

BACKGROUND: With the development of wearable health-monitoring technologies, a variety of textile electrodes have been produced and applied by researchers. However, there are no universal and effective methods even testing platforms for evaluating the skin-electrode electrochemical interface for textile electrodes because different human bodies have different skin characteristics. METHODS: An electrochemical modeling and evaluation for textile electrodes to skin was proposed, and two electrochemical evaluation platforms (EEP) were set up based on two simulated skin models (SSM). First, skin-electrode electrochemical interface (SEEI) models for traditional wet electrodes and textile electrodes were analyzed. Based on the SEEI models and YY/T 0196-2005 (Chinese YY/T pharmaceutical industry standard for disposable ECG electrode), three skin-electrode electrochemical characteristics (SEEC), including skin-electrode static impedance (SESI), skin-electrode alternating current impedance (SEAI), and skin-electrode polarization voltage (SEPV), were proposed. Then, three electrochemical evaluation methods for textile electrodes to skin were proposed and analyzed, which were the correlation between SEEC and skin-electrode contact pressure (SECP), skin-electrode relative movement (SERM), and conduction loss of active signals (CLAS). Finally, an electrochemical evaluation platform was set up based on an active simulated skin model (ASSM) and passive simulated skin model (PSSM). RESULTS: 9 feature parameters based on the passive electrochemical evaluation platform (PEEP) and 11 feature parameters based on the active electrochemical evaluation platform (AEEP) were obtained for evaluating textile electrodes. And four kinds of textile electrode characteristics including SEEC, SECP, SERM, and CLAS were quantitatively measured based on the electrochemical evaluation platform, and the testing accuracy and range for these characteristics were measured separately. Finally, correlation between SEEC and SECP for 10 kinds of textile electrode samples was studied, and 14 electrochemical characteristics and four skin-electrode contact pressure characteristics were extracted. Experimental results showed that significant correlations were found between six SEEC characteristics and SECP characteristics, and the correlation coefficient between ACI_3 and USECP was the highest. And the polarization voltages of most dry electrode samples showed a downward trend with the increase of contact pressure. CONCLUSIONS: The electrochemical evaluation platform yielded effective experimental data and could provide strong support for the evaluation and application of textile electrodes, which was also effective in evaluating other bioelectric electrodes such as 3M electrode, stainless steel electrode, dry electrode and microneedle electrode.

Lying position classification based on ECG waveform and random forest during sleep in healthy people.

BACKGROUND: Several different lying positions, such as lying on the left side, supine, lying on the right side and prone position, existed when healthy people fell asleep. This article explored the influence of lying positions on the shape of ECG (electrocardiograph) waveform during sleep, and then lying position classification based on ECG waveform features and random forest was achieved. METHODS: By means of de-noising the overnight sleep ECG data from ISRUC website dataset, as well as extracting the waveform features, we calculated a total of 30 ECG waveform features, including 2 newly proposed features, S/R and ∠QSR. The means and significant difference level of these features within different lying positions were calculated, respectively. Then 12 features were selected for three kinds of classification schemes. RESULTS: The lying positions had comparatively less effect on time-limit features. QT interval and RR interval were significantly lower than that in supine ([Formula: see text]). Significant differences appeared in most of the amplitude and double-direction features. When lying on the left side, the height of P wave and T wave, QRS area and T area, the QR potential difference and ∠QSR were significantly lower than those in supine ([Formula: see text]). However, S/R was significantly greater on left than those in supine ([Formula: see text]) and on right ([Formula: see text]). The height of T wave and area under T wave were significantly higher in supine than those on right ([Formula: see text]). For the subject specific classifier, a mean accuracy of 97.17% with Cohen's kappa statistic κ of 0.91, and AUC > 0.97 were achieved. While the accuracy and κ dropped to 63.87% and 0.32, AUC > 0.66, respectively when the subject independent classifier was considered. CONCLUSIONS: When subjects were lying on the left side during sleep, due to the effect of gravity on heart, the position of heart changed, for example, turned and rotated, causing changes in the vectorcardiogram of frontal plane and horizontal plane, which lead to a change in ECG. When lying on the right side, the heart was upheld by the mediastinum, so that the degree of freedom was poor, and the ECG waveform was almost unchanged. The proposed method could be used as a technique for convenient lying position classification.

Highly Stable and Flexible Pressure Sensors with Modified Multi-Walled Carbon Nanotube/Polymer Composites for Human Monitoring.

A facile method for preparing an easy processing, repeatable and flexible pressure sensor was presented via the synthesis of modified multi-walled carbon nanotubes (m-MWNTs) and polyurethane (PU) films. The surface modification of multi-walled carbon nanotubes (MWNTs) simultaneously used a silane coupling agent (KH550) and sodium dodecyl benzene sulfonate (SDBS) to improve the dispersibility and compatibility of the MWNTs in a polymer matrix. The electrical property and piezoresistive behavior of the m-MWNT/PU composites were compared with raw multi-walled carbon nanotube (raw MWNT)/PU composites. Under linear uniaxial pressure, the m-MWNT/PU composite exhibited 4.282%kPa−1 sensitivity within the pressure of 1 kPa. The nonlinear error, hysteresis error and repeatability error of the piezoresistivity of m-MWNT/PU decreased 9%, 16.72% and 54.95% relative to raw MWNT/PU respectively. Therefore, the piezoresistive response of m-MWNT/PU had better stability than that of raw MWNT/PU composites. The m-MWNT/PU sensors could be utilized in wearable devices for body movement detection, monitoring of respiration and pressure detection in garments.

A principal component analysis based data fusion method for ECG-derived respiration from single-lead ECG.

An ECG-derived respiration (EDR) algorithm based on principal component analysis (PCA) is presented and applied to derive the respiratory signals from single-lead ECG. The respiratory-induced variabilities of ECG features, P-peak amplitude, Q-peak amplitude, R-peak amplitude, S-peak amplitude, T-peak amplitude and RR-interval, are fused by PCA to yield a better surrogate respiratory signal than other methods. The method is evaluated on data from the MIT-BIH polysomnographic database and validated against a "gold standard" respiratory obtained from simultaneously recorded respiration data. The performance of fusion algorithm is assessed by comparing the EDR signals to a reference respiratory signal, using the quantitative evaluation indexes that include true positive (TP), false positive (FP), false negative (FN), sensitivity (SE) and positive predictivity (PP). The statistically difference is significant among the PCA data fusion method and the EDR methods based on the RR intervals and the RS amplitudes, showing that PCA data fusion algorithm outperforms the others in the extraction of respiratory signals from single-lead ECGs.

Characters available in photoplethysmogram for blood pressure estimation: beyond the pulse transit time.

The continuous and noninvasive blood pressure (BP) measurement based on pulse transit time (PTT) doesn't need cuff and could monitor BP in real time for a long period. However, PTT is just a time index derived from electrocardiogram (ECG) and photoplethysmogram (PPG), while BP-related information within the PPG waveform has seldom been taken into consideration. We hypothesized that PPG waveform feature might be useful for BP estimation. Nine healthy subjects took part in an exercise stress test, including baseline resting, exercise on bicycle ergometry and recovering resting. ECG of lead V5 and PPG from left finger were collected simultaneously, and systolic blood pressure (SBP) and diastolic blood pressure (DBP) were recorded from a cuff sphygmometer on the right wrist. The correlation coefficients were obtained between BP (SBP, DBP and pulse pressure (PP)) and PPG morphological indices (total 15 indices in terms of waveform amplitude, time span and area ratio). Five PPG indices were correlated with both SBP and PP (absolute value of correlation coefficient |r| > 0.6) and were further tested for the capability to BP estimation, which were: (1) PTTA, time delay between the R peak of ECG and the foot point of PPG; (2) RSD, time ratio of systole to diastole; (3) RtArea, area ratio of systole to diastole; (4) TmBB, time span of PPG cycle; (5) TmCA, diastolic duration. Comparisons were made between the measured BP and the estimated BP by regression lines and quadratic curve fitting, respectively. As a result, the mean errors of SBP liner fitting with RSD, RtArea, TmBB and TmCA respectively were 5.5, 5.4, 5.2, 5.1 mmHg, which were smaller than that with PTTA of 5.8 mmHg. And the mean errors of SBP quadratic curve fitting with RSD, RtArea, TmBB and TmCA were all 5.1 mmHg, which were smaller than that with PTTA of 5.7 mmHg. The mean errors of multiple regression for SBP, PP and DBP was 4.7, 4.7, 3.5 mmHg respectively, which were more accurate than the regression with single PTTA of 5.8, 5.3, 5.2 mmHg respectively. However, PPG-based SBP and DBP could under estimate cuff pressure by 8 mmHg and over estimate by 10 mmHg respectively, which is a clinically significant error. In conclusion, the combination of time span (PTT, time ratio of systole to diastole, time span of PPG cycle and diastolic duration) and waveform morphology (area ratio of systole to diastole) could improve the performance of PPG-based BP estimation.

A new approach of QRS complex detection based on matched filtering and triangle character analysis.

QRS complex detection usually provides the fundamentals to automated electrocardiogram (ECG) analysis. In this paper, a new approach of QRS complex detection without the stage of noise suppression was developed and evaluated, which was based on the combination of two techniques: matched filtering and triangle character analysis. Firstly, a template of QRS complex was selected automatically by the triangle character in ECG, and then it was time-reversed after removing its direct current component. Secondly, matched filtering was implemented at low computational cost by finite impulse response, which further enhanced QRS complex and attenuated non-QRS regions containing P-wave, T-wave and various noise components. Subsequently, triangle structure-based threshold decision was processed to detect QRS complexes. And RR intervals and triangle structures were further analyzed for the reduction of false-positive and false-negative detections. Finally, the performance of the proposed algorithm was tested on all 48 records of the MIT-BIH Arrhythmia Database. The results demonstrated that the detection rate reached 99.62 %, the sensitivity got 99.78 %, and the positive prediction was 99.85 %. In addition, the proposed method was able to identify QRS complexes reliably even under the condition of poor signal quality.

[Application of fuzzy reasoning to myocardial ischemia judgment based on electrocardiogram ST-T complex].

Electrocardiogram (ECG) is a convenient, economic, and non-invasive detecting tool in myocardial ischemia (MI). Its clinical appearance is mainly exhibited by ST-T complex change. MI events are usually instantaneous and asymptomatic in some cases, which cannot be forecasted to have a precautionary measure in time by doctors. The automatic detection of MI by computer and a cued warning of danger in real time play an important role in diagnosing heart disease. With the help of the medical staff, some quantitative approbatory indicators, such as ST-segment deviation, the amplitude of T-wave peak and the rate of ST and heart rate (HR), were combined to judge MI using fuzzy reasoning. After MIT-BIH database and the long-term ST database (LTST) verification, sensitivity and positive predictive values reached 75% and 78% respectively, and specificity and negative predictive values were 85% and 87% respectively. In addition, the proposed method was close to human way of thinking and understanding, and easy to apply in clinical detection and engineering fields.

[A squeeze approach for electrocardiogram ST-segment detection based on R-wave and T-wave].

ST-segment is the main clinical appearance in myocardial ischemia detection based on electrocardiogram (ECG) signals. However, it is highly sensitive to interferences (baseline wandering, postural changes, electrode interference, etc.), which cause the feature points of ECG ST-segment to be difficult to detect accurately. Currently, the common detection methods of ST-segment are: R+x and J+x, but they are affected badly by T-wave morphological variability and J point location. For these reasons, firstly we proposed a convenient and accurate approach for T-wave onset in this paper. It did not need to locate T-wave peak and was robust to baseline wandering and T-wave morphology. Secondly, we proposed a squeeze approach for ST-segment detection based on R-wave peak and T-wave onset. After the Long-Term ST database (LTST) verification, the proposed method has shown a good timeliness and robustness, and the accuracy of ST-segment detection has reached above 92%.

Myocardial ischemia analysis based on electrocardiogram QRS complex.

Electrocardiogram (ECG) is an economic, convenient, and non-invasive detecting tool in myocardial ischemia (MI), and its clinical appearance is mainly exhibited by the changes in ST-T complex. Recently, QRS complex characters were proposed to analyze MI by more and more researchers. In this paper, various QRS complex characters were extracted in ECG signals, and their relationship was analyzed systematically. As a result, these characters were divided into two groups, and there existed good relationship among them for each group, while the poor relationship between the groups. Then these QRS complex characters were applied for statistical analysis on MI, and five characters had significant differences after ECG recording verification, which were: QRS upward and downward slopes, transient heart rate, angle R and angle Q. On the other hand, these QRS complex characters were analyzed in frequency domain. Experimental results showed that the frequency features of RR interval series (Heart Rate Variability, HRV), and QRS barycenter sequence had significant differences between MI states and normal states. Moreover, QRS barycenter sequence performed better.

Research on electrocardiogram baseline wandering correction based on wavelet transform, QRS barycenter fitting, and regional method.

Baseline wandering in electrocardiogram (ECG) is one of the biggest interferences in visualization and computerized detection of waveforms (especially ST-segment) based on threshold decision. A new method based on wavelet transform, QRS barycenter fitting and regional method was proposed in this paper. Firstly, wavelet transform as a coarse correction was used to remove the baseline wandering, whose frequency bands were non-overlapping with that of ST-segment. Secondly, QRS barycenter fitting was applied as a detailed correction. The third, the regional method was used to transfer baseline to zero. Finally, the method in this paper was proved to perform better than filtering and function fitting methods in baseline wandering correction after the long-term ST database (LTST) verification. In addition, the proposed method is simple and easy to carry out, and in current use.