Big data analysis of influenza vaccination and liver cancer risk in hypertensive patients: insights from a nationwide population-based cohort study.

Background: previous studies have indicated that influenza vaccination may be associated with reduced risks of certain types of cancer. However, the protective effect of influenza vaccination against primary liver cancer in individuals with hypertension remains unclear.

Methods: In this cohort study, 37,022 patients over 55 years of age who received a diagnosis of hypertension at any time between January 1, 2001, and December 31, 2012, were enrolled from the National Health Insurance Research Database.

Deep learning for the classification of atrial fibrillation using wavelet transform-based visual images.

Background: As the incidence and prevalence of Atrial Fibrillation (AF) proliferate worldwide, the condition has become the epicenter of a plethora of ECG diagnostic research. In recent diagnostic methodologies, Morse Continuous Wavelet Transform (MsCWT) is a feature extraction technique utilized to draw out distinctive attributes of ECG signals. In our study, we explore the employment of MsCWT in the classification of AF with ECG signals in a continuum.

Assessing the severity of AstraZeneca COVID-19 vaccine-related side effects through pulse spectrum analysis.

AstraZeneca (AZ) vaccine is one of the most common vaccines against COVID-19 used globally. However, adverse reactions post-vaccination have been reported, including severe symptoms and cases of sudden death within several hours. Therefore, this study aimed to establish a database of spectral characteristics of blood pressure waveforms (BPWs) for the AZ vaccine and analyze reactions after vaccine administration using objective physiological signal and symptom analyses for identifying potential differences between heavy and slight groups defined in the study.

The Effects of Different Types of Sleep Disorder on Colorectal Cancer: A Nationwide Population-Based Cohort Study.

The impact of sleep disorders (SDs), particularly sleep apnea (SA), on the development of colorectal cancer (CRC) has been the subject of significant research. However, the potential contribution of other SDs to the incidence of CRC remains unexplored. The objective of this study was to examine the effects of SDs on the risk of developing CRC.

Effects of anthracycline chemotherapy and Kuan-Sin-Yin on the spectral indices of arterial pulse waveforms in breast cancer patients.

The vascular structure and function are potentially useful biomarkers for tumor detection. Treatment with chemotherapeutic agents may impair vascular function and increase the risk of cardiovascular disease. This study aimed to use noninvasive pulse waveform measurements to identify differences in the frequency-domain indices of the pulse waveform in breast-cancer patients following anthracycline chemotherapy between with (Group KSY) and without (Group NKSY) receiving Kuan-Sin-Yin (KSY) treatment.

Using Arterial Pulse and Laser Doppler Analyses to Discriminate between the Cardiovascular Effects of Different Running Levels.

Background And Aims: Running can induce advantageous cardiovascular effects such as improved arterial stiffness and blood-supply perfusion. However, the differences between the vascular and blood-flow perfusion conditions under different levels of endurance-running performance remains unclear. The present study aimed to assess the vascular and blood-flow perfusion conditions among 3 groups (44 male volunteers) according to the time taken to run 3 km: Level 1, Level 2, and Level 3.

Discrimination between possible sarcopenia and metabolic syndrome using the arterial pulse spectrum and machine-learning analysis.

Sarcopenia is defined as decreased skeletal muscle mass and function, and is an important cause of frailty in the elderly, also being associated with vascular lesions and poor microcirculation. The present study aimed to combine noninvasive pulse measurements, frequency-domain analysis, and machine learning (ML) analysis (1) to determine the effects on the pulse waveform induced by sarcopenia and (2) to develop discriminating models for patients with possible sarcopenia. Radial blood pressure waveform (BPW) signals were measured noninvasively for 1 min in 133 subjects who visited Tri-Service General Hospital for geriatric health checkups.

Machine-Learning Classification of Pulse Waveform Quality.

Pulse measurements made using wearable devices can aid the monitoring of human physiological condition. Accurate estimation of waveforms is often difficult for nonexperts; motion artifacts may occur during tonometry measurements when the skin-sensor contact pressure is insufficient. An alternative approach is to extract only high-quality pulses for use in index calculations.

Machine Learning Analyses Revealed Distinct Arterial Pulse Variability According to Side Effects of Pfizer-BioNTech COVID-19 Vaccine (BNT162b2).

Various adverse events and complications have been attributed to COVID-19 (coronavirus disease 2019) vaccinations, which can affect the cardiovascular system, with conditions such as myocarditis, thrombosis, and ischemia. The aim of this study was to combine noninvasive pulse measurements and frequency domain analysis to determine if the Pfizer-BioNTech COVID-19 vaccine (BNT162b2) vaccination and its accompanying cardiovascular side effects will induce changes in arterial pulse transmission and waveform. Radial blood pressure waveform and photoplethysmography signals were measured noninvasively for 1 min in 112 subjects who visited Shuang-Ho Hospital for a BNT162b2 vaccination.

Characteristics of sarcopenia subjects in arterial pulse spectrum analysis.

Aims: Sarcopenia is significantly associated with the number of cardiovascular and metabolic diseases, however, the underlying pathophysiological processes are largely unknown. This study performed harmonic index of finger photoplethysmography (PPG) waveforms with the aims of distinguishing different arterial pulse waveform signals between sarcopenia, presarcopenia, dynapenia, and healthy subjects.

Methods: Sixty-eight subjects were enrolled and obtained 1-min PPG signals, then were assigned to four age-matched groups: control, dynapenia, presarcopenia, and sarcopenia which definition according to Asian Working Group for Sarcopenia (AWGS): 2019 Consensus Update on Sarcopenia Diagnosis and Treatment.

Discrimination of the Cognitive Function of Community Subjects Using the Arterial Pulse Spectrum and Machine-Learning Analysis.

Early identification of cognitive impairment would allow affected patients to receive care at earlier stage. Changes in the arterial stiffness have been identified as a prominent pathological feature of dementia. This study aimed to verify if applying machine-learning analysis to spectral indices of the arterial pulse waveform can be used to discriminate different cognitive conditions of community subjects.

Discrimination of vascular aging using the arterial pulse spectrum and machine-learning analysis.

Aging contributes to the progression of vascular dysfunction and is a major nonreversible risk factor for cardiovascular disease. The aim of this study was to determine the effectiveness of using arterial pulse-wave measurements, frequency-domain pulse analysis, and machine-learning analysis in distinguishing vascular aging. Radial pulse signals were measured noninvasively for 3 min in 280 subjects aged 40-80 years.

Beat-to-beat and spectral analyses of the noninvasive radial pulse and laser-Doppler signals in patients with hypertension.

This study performed beat-to-beat and spectral analyses of 20-minute skin-surface laser-Doppler-flowmetry (LDF) and radial blood-pressure-waveform (BPW) signals in order to compare the blood-flow perfusion condition and regulatory mechanisms between essential-hypertension (EHT) patients and aged-matched control subjects. Beat-to-beat LDF analyses yielded the pulse width (PW), AC-to-DC ratio (AD), and their corresponding variability indices (coefficients of variation [CVs]). The relative energy contributions (RECs) of five characteristic frequency peaks (defined as FR1-FR5) were also calculated.

Classification of patients with Alzheimer's disease using the arterial pulse spectrum and a multilayer-perceptron analysis.

Cerebrovascular atherosclerosis has been identified as a prominent pathological feature of Alzheimer's disease (AD); the link between vessel pathology and AD risk may also extend to extracranial arteries. This study aimed to determine the effectiveness of using arterial pulse-wave measurements and multilayer perceptron (MLP) analysis in distinguishing between AD and control subjects. Radial blood pressure waveform (BPW) and finger photoplethysmography signals were measured noninvasively for 3 min in 87 AD patients and 74 control subjects.

Comparison of complexity and spectral indices of skin-surface laser-doppler signals in patients with breast cancer receiving chemotherapy and Kuan-Sin-Yin.

This study tested the hypothesis that measuring and analyzing skin-surface blood flow dynamics can be used to noninvasively discriminate the different microcirculatory and physiological function states of breast-cancer patients with chemotherapy between receiving and not receiving Kuan-Sin-Yin (KSY) treatment. The 17 included patients were assigned randomly to 2 comparison groups: Group K (n = 10) received KSY treatment, while Group NK (n = 7) did not receive KSY treatment. Beat-to-beat, spectral, and approximate-entropy (ApEn) analyses were applied to the 20-minute laser-Doppler sequences.

Differences in time-domain and spectral indexes of skin-surface laser-Doppler signals between controls and breast-cancer subjects.

Background: There is an urgent need to improve the early diagnosis of breast cancer.

Objective: The present study applied spectral and beat-to-beat analyses to laser-Doppler (LDF) data sequences measured on the skin surface on the back of the right hands, with the aim of comparing the different peripheral microcirculatory-blood-flow (MBF) perfusion condition between breast-cancer and control subjects.

Methods: ECG and LDF signals were obtained simultaneously and noninvasively from 23 breast-cancer patients and 23 age-matched control subjects.

Differences in laser-Doppler indices between skin-surface measurement sites in subjects with diabetes.

This study performed laser-Doppler flowmetry (LDF) measurements with the aim of identifying differences in diabetes-induced microcirculatory-blood-flow (MBF) responses between the following skin surface measurement sites: an acupoint around the wrist, an acupoint around the ankle, and a nearby nonacupoint around the ankle. The 67 study subjects were assigned to diabetic, prediabetic, and healthy groups according to the results of oral glucose tolerance tests. Beat-to-beat and spectral analyses were applied to the LDF waveform to obtain the foot delay time (FDT), the flow rise time (FRT), and the relative energy contributions (RECs) in five frequency bands.

Changes in the spectral index of skin-surface laser Doppler signals of nude mice following the injection of CT26 tumor cells.

This study investigated microcirculatory-blood-flow responses in nude mice following the injection of CT26 tumor cells by analyzing the frequency content of skin blood-flow signals recorded on the skin surface. CT26 cells were injected subcutaneously (10^4/100 μl) into the right back flank of each 7-week-old mouse. Three-minute laser Doppler flowmetry (LDF) signals were measured in 60 nude mice.

Characteristics of beat-to-beat photoplethysmography waveform indexes in subjects with metabolic syndrome.

Unlabelled: Metabolic syndrome (MetS) increases the risk of the subsequent development of cardiovascular disease. This study aimed to determine if the harmonic indexes of finger photoplethysmography (PPG) waveforms can be used to discriminate different arterial pulse transmission conditions between MetS and healthy subjects. Three-minute PPG signals were obtained in 65 subjects, who were assigned to 3 age-matched groups (MS, with no less than three MetS factors; pre-MS, with one or two MetS factors;

Control: with no MetS factor).

Complexity Analysis of Beat-to-Beat Skin-Surface Laser-Doppler Flowmetry Signals in Stroke Patients.

Objectives: This study performed skin-surface LDF measurements and SampEn analysis with the aims of (i) capturing the temporal complexity of cerebral hemodynamics in stroke patients and (ii) discriminating stroke patients from healthy control subjects. We also investigated the response induced by AS in beat-to-beat SampEn indexes of LDF signals.

Methods: LDF signals were obtained at bilateral TaiYang acupoints in 52 stroke patients.

Characteristics of harmonic indexes of the arterial blood pressure waveform in polycystic ovary syndrome.

Motivations: Patients with polycystic ovary syndrome (PCOS; which is often associated with increased cardiovascular risk factors) may present hemodynamic changes in the cardiovascular system. The aim of the present study was to verify whether harmonic indexes of the arterial blood pressure waveform (BPWs) can be used to discriminate between PCOS patients and healthy individuals.

Methods: Twenty-minute bilateral radial BPW signals were obtained in 20 PCOS patients and 20 healthy individuals.

Complexity analysis of beat-to-beat skin-surface laser-Doppler signals in diabetic subjects.

Motivations: This study performed skin-surface laser-Doppler flowmetry (LDF) measurements with the aim of verifying if complexity analysis applied to the beat-to-beat LDF waveform index can be used to discriminate diabetic, prediabetic, and normoglycemic subjects.

Methods: Sixty-six subjects were assigned to three age-matched groups according to the results of oral glucose tolerance tests. Beat-to-beat analysis was performed on the pulsatile LDF waveform to obtain the pulse-to-mean ratio (AD) and pulse width (PW), and then approximate-entropy (ApEn) values for their 20-minute index sequences were calculated to evaluate the signal complexity.

Characteristics in the beat-to-beat laser-Doppler waveform indices in subjects with diabetes.

Motivations: The present study performed laser-Doppler flowmetry (LDF) measurements on the skin surface around the ankle with the aim of verifying if beat-to-beat analysis of the LDF waveform can help to discriminate the microcirculatory-blood-flow (MBF) characteristics between diabetic, prediabetic, and healthy subjects.

Methods: 84 subjects were assigned to three groups (diabetic, prediabetic, and normal) according to the results of oral glucose tolerance tests. Beat-to-beat analysis was performed on the pulsatile LDF waveform to obtain foot delay time (FDT), flow rise time (FRT), and the corresponding MBF-variability parameters (FDTCV and FRTCV).