Sleep apnea causes cardiac arrest, sleep rhythm disorders, nocturnal hypoxia and abnormal blood pressure fluctuations in patients, which eventually lead to nocturnal target organ damage in hypertensive patients. The incidence of obstructive sleep apnea hypopnea syndrome (OSAHS) is extremely high, which seriously affects the physical and mental health of patients. This study attempts to extract features associated with OSAHS from 24-hour ambulatory blood pressure data and identify OSAHS by machine learning models for the differential diagnosis of this disease. The study data were obtained from ambulatory blood pressure examination data of 339 patients collected in outpatient clinics of the Chinese PLA General Hospital from December 2018 to December 2019, including 115 patients with OSAHS diagnosed by polysomnography (PSG) and 224 patients with non-OSAHS. Based on the characteristics of clinical changes of blood pressure in OSAHS patients, feature extraction rules were defined and algorithms were developed to extract features, while logistic regression and lightGBM models were then used to classify and predict the disease. The results showed that the identification accuracy of the lightGBM model trained in this study was 80.0%, precision was 82.9%, recall was 72.5%, and the area under the working characteristic curve (AUC) of the subjects was 0.906. The defined ambulatory blood pressure features could be effectively used for identifying OSAHS. This study provides a new idea and method for OSAHS screening.
The prevalence of cardiovascular disease in our country is increasing, and it has been a big problem affecting the social and economic development. It has been demonstrated that early intervention of cardiovascular risk factors can effectively reduce cardiovascular disease-caused mortality. Therefore, extensive implementation of cardiovascular testing and risk factor screening in the general population is the key to the prevention and treatment of cardiovascular disease. However, the categories of devices available for quick cardiovascular testing are limited, and in particular, many existing devices suffer from various technical problems, such as complex operation, unclear working principle, or large inter-individual variability in measurement accuracy, which lead to an overall low popularity and reliability of cardiovascular testing. In this study, we introduce the non-invasive measurement mechanisms and relevant technical progresses for several typical cardiovascular indices (e.g., peripheral/central arterial blood pressure, and arterial stiffness), with emphasis on describing the applications of biomechanical modeling and simulation in mechanism verification, analysis of influential factors, and technical improvement/innovation.
Objective To recognize the different phases of Korotkoff sounds through deep learning technology, so as to improve the accuracy of blood pressure measurement in different populations. Methods A classification model of the Korotkoff sounds phases was designed, which fused attention mechanism (Attention), residual network (ResNet) and bidirectional long short-term memory (BiLSTM). First, a single Korotkoff sound signal was extracted from the whole Korotkoff sounds signals beat by beat, and each Korotkoff sound signal was converted into a Mel spectrogram. Then, the local feature extraction of Mel spectrogram was processed by using the Attention mechanism and ResNet network, and BiLSTM network was used to deal with the temporal relations between features, and full-connection layer network was applied in reducing the dimension of features. Finally, the classification was completed by SoftMax function. The dataset used in this study was collected from 44 volunteers (24 females, 20 males with an average age of 36 years), and the model performance was verified using 10-fold cross-validation. Results The classification accuracy of the established model for the 5 types of Korotkoff sounds phases was 93.4%, which was higher than that of other models. Conclusion This study proves that the deep learning method can accurately classify Korotkoff sounds phases, which lays a strong technical foundation for the subsequent design of automatic blood pressure measurement methods based on the classification of the Korotkoff sounds phases.
Objective To explore the impact of early blood pressure reduction on the prognosis of acute ischemic stroke. Methods We searched PubMed, Embase, Cochrane Library, Wanfang, China National Knowledge Infrastructure, and Chongqing VIP, with the search period from databases establishment to December 31, 2024. Randomized controlled studies on early blood pressure reduction within 7 days after the onset of acute ischemic stroke were included, and meta-analysis was conducted using RevMan 5.4 software. Results Finally, 15 randomized controlled studies were included. The meta-analysis results showed that there was no statistically significant difference in the primary outcome (90 days disability or death) and the secondary outcomes (90 days all-cause death) between the early blood pressure reduction group and the control group (P>0.05). Compared with the control group, the early blood pressure reduction group had a higher National Institute of Health Stroke Scale score at 2 weeks [standardized mean difference=0.25, 95% confidence interval (0.07, 0.44), P=0.008]. Conclusion Early blood pressure reduction cannot reduce the risk of 90 days disability or death and 90 days all-cause death in patients with acute ischemic stroke, and may be detrimental to 2 weeks neurological function recovery.
摘要:目的:研究老年患者动脉弹性功能与围术期血压变化的关系。方法:随机选择68例ASA分级Ⅰ－Ⅱ级行全麻手术的老年患者,根据检查所得动脉弹性的结果分为四组,分别是A组(C1、C2均正常),B组(C1异常,C2正常),C组(C1正常,C2异常),D组(C1、C2均异常)。测量其术前血压及全麻诱导8分钟后的血压水平。结果:〓动脉弹性功能不良的患者其术前MAP较高,且全麻诱导以后血压波动的比例较大。结论:高血压病的老年患者动脉弹性功能普遍降低;动脉弹性下降的老年病人全麻诱导后血压波动较大。Abstract: Objective:To investigate the relationship between the function of arterial elasticity and BP changes during perioperation in senile patients.Methods: 68 senile patients ASA class Ⅰor Ⅱ undergoing elective surgery under general anesthestia, were divided into four groups by evaluation of arterial elasticity (C1 was for large arterial elastic index and C2 for small. C1 and C2 were normal in group A, only C2 normal in group B, only C1 normal in group C, neither was normal in group D). Arterial blood pressure (BP) before operation and 8 min after induction were monitored and recorded. Results: Patients with dysfunction of arterial elasticity presented higher MAP during preoperation and significant BP changes after induction. Conclusion: Hypertension plays a key role in arterial elasticity.Arterial Blood Pressure of the senile patients with decreased arterial elasticity changes significantly after general anesthesia induction.
ObjectiveTo investigate the value of morning blood pressure surge in the evaluation of atherosclerosis by the observation of the relationship between morning blood pressure surge and ambulatory arterial stiffness index. MethodsFrom May 2011 to March 2013, we followed up 300 hypertensive patients who received ambulatory blood pressure monitoring, and they were divide into elevated morning blood pressure surge group and non-elevated morning blood pressure surge group. The AASI value was recorded and compared between the two groups according to the grade of hypertension. ResultsMorning blood pressure surge was more common in patients with hypertension. Compared with patients in the non-elevated morning blood pressure surge group, ambulatory arterial stiffness index was significantly higher in patients in the elevated morning blood pressure surge group. ConclusionThere is a certain correlation between morning blood pressure surge and arterial stiffness, which is an important factor leading to a variety of target organ damage.
摘要:目的: 观察腰硬联合麻醉在前列腺电切术患者中的临床应用效果。 方法 : 76例经尿道前列腺电切术患者(78±7岁)随机均分为腰硬联合麻醉组(C组)及硬膜外组(E组)。C组以腰硬联合穿刺针于L34穿刺至蛛网膜下腔后,注入05%布比卡因2 mL,通过硬膜外穿刺针置入硬膜外导管;E组行L34间隙硬膜外穿刺置管。记录麻醉起效时间、麻醉效果、麻醉前及麻醉后5、15、30分钟时血压、心率。 结果 : 所有患者均穿刺顺利,麻醉起效时间C组为36±13 min, E组68±15 min;C组麻醉效果完善率为100%,E组为95%;麻醉后两组血压均下降(〖WTBX〗P lt;005),但降幅均未超过基础值的20%;两组麻醉前及麻醉后血压、心率均无显著性差异。 结论 :腰硬联合麻醉用于前列腺电切术具有起效快、麻醉效果佳的优点。Abstract: Objective: To investigate and compare the clinical efficacy and safety of combined spinalepidural(CSEA) and epidural(EA) anesthesia on elderly patients undergoing transurethral resection of the prostate(TURP). Methods : 76 patients(78±7 years) suffering TURP were divided into two group: group CSEA(38cases) and groupEA(38 cases). The dose of bupivacaine in spinal anesthesia is 10 mg. Blood pressure(BP), heart rate(HR) and anesthesia efficacy were observed before anesthesia, 5, 15 and 30min after anesthesia. Results : BP decreased after anesthesia in two groups than before anesthesia(〖WTBX〗P lt;005). The decreases of BP were less than 20% of basises. There were no significant differents of BP and HR between two groups before and after anesthesia. Conclusion :CSEA with bupivacaine 10 mg is safe and efficient in elderly undergoing TURP.
The European Society of Cardiology (ESC) released the "2024 ESC guidelines for the management of elevated blood pressure and hypertension" on August 30, 2024. This guideline updates the 2018 "Guidelines for the management of arterial hypertension." One notable update is the introduction of the concept of "elevated blood pressure" (120-139/70-89 mm Hg). Additionally, a new systolic blood pressure target range of 120-129 mm Hg has been proposed for most patients receiving antihypertensive treatment. The guideline also includes numerous additions or revisions in areas such as non-pharmacological interventions and device-based treatments for hypertension. This article interprets the guideline's recommendations on definition and classification of elevated blood pressure and hypertension, and cardiovascular disease risk assessment, diagnosing hypertension and investigating underlying causes, preventing and treating elevated blood pressure and hypertension. We provide a comparison interpretation with the 2018 "Guidelines for the management of arterial hypertension" and the "2017 ACC/AHA guideline on the prevention, detection, evaluation, and management of high blood pressure in adults."
ObjectiveTo systematically review the relationship between frailty and risk of orthostatic hypotension.MethodsPubMed, EMbase, Web of Science, CNKI, CBM, VIP and WanFang Data databases were electronically searched to collect studies on the association between frailty and orthostatic hypotension from inception to July 7th, 2020. Two reviewers independently screened literature, extracted data and assessed risk of bias of included studies. Meta-analysis was then performed by RevMan 5.3 software.ResultsFive cross-sectional studies involving 8 671 patients were included. The results of meta-analysis showed that prefrailty (OR=1.04, 95%CI 0.99 to 1.09, P=0.11) and frailty (OR=1.02, 95%CI=0.92 to 1.13, P=0.70) were not associated with orthostatic hypotension. The results of subgroup analysis showed that differences of sample size (<500 or ≥500), using different frailty assessment tools (Fried scale, clinical frailty scale, and frailty index), different regions (Europe, Asia, and America) and different sources of studied subjects (hospitals and communities), the risk of orthostatic hypotension were not increased with frailty.ConclusionsCurrent evidence shows that frailty does not increase the risk of orthostatic hypotension. Due to limited quality and quantity of included studies, the above conclusions are needed to be validated by more high-quality studies.
The continuous left ventricle blood pressure prediction based on selected heart sound features was realized in this study. The experiments were carried out on three beagle dogs and the variations of cardiac hemodynamics were induced by various dose of epinephrine. The phonocardiogram, electrocardiogram and blood pressures in left ventricle were synchronously acquired. We obtained 28 valid recordings in this study. An artificial neural network was trained with the selected feature to predict left ventricular blood pressure and this trained network made a good performance. The results showed that the absolute average error was 7.3 mm Hg even though the blood pressures had a large range of fluctuation. The average correlation coefficient between the predicted and the measured blood pressure was 0.92. These results showed that the method in this paper was helpful to monitor left ventricular hemodynamics non-invasively and continuously.