Effects of acupuncture on the relationship between cerebral hemodynamics and arterial blood pressure in patients with hypertension

The present study aimed to investigate the effect of an auricular acupuncture intervention on the relationship between changes in oxyhemoglobin concentration(Δ[O2Hb])and arterial blood pressure(ABP).The cerebral oxygenation signals in the bilateral prefrontal cortex(PFC),sensorimotor cortex(SMC),and temporal lobe cortex(TLC)of 15 patients with hypertension were measured by a 24-channel functional near-infrared spectroscopy(fNIRS)device before(State_R)and after(State_AT)the auricular acupuncture intervention.Coupling strength was used to quantitatively evaluate the strength of the couplings between ABP andΔ[O2Hb]in low-frequency oscillations(LF,0.07–0.2 Hz)and very-low-frequency oscillations(VLF,0.02–0.07 Hz).Results showed that the changes in wavelet amplitudes in the LF and VLF intervals did not exhibit significant differences after auricular acupuncture.The coupling strength from ABP toΔ[O2Hb]was significantly lower in the LF range after auricular acupuncture in the bilateral PFC,SMC,and TLC(p<0.0083).Additionally,the coupling strength from ABP toΔ[O2Hb]in the VLF range was significantly lower in the bilateral PFC in State_AT than in State_R(p<0.0083).These results indicated that fNIRS together with ABP can effectively evaluate cerebral hemodynamic responses to interventions and is therefore capable of guiding more individualized acupuncture strategies.The auricular acupuncture intervention improved hemodynamic responses in patients suffering from hypertension.

Future of neurocritical care:Integrating neurophysics,multimodal monitoring,and machine learning

Multimodal monitoring(MMM)in the intensive care unit(ICU)has become increasingly sophisticated with the integration of neurophysical principles.However,the challenge remains to select and interpret the most appropriate combination of neuromonitoring modalities to optimize patient outcomes.This manuscript reviewed current neuromonitoring tools,focusing on intracranial pressure,cerebral electrical activity,metabolism,and invasive and noninvasive autoregulation moni-toring.In addition,the integration of advanced machine learning and data science tools within the ICU were discussed.Invasive monitoring includes analysis of intracranial pressure waveforms,jugular venous oximetry,monitoring of brain tissue oxygenation,thermal diffusion flowmetry,electrocorticography,depth electroencephalography,and cerebral microdialysis.Noninvasive measures include transcranial Doppler,tympanic membrane displacement,near-infrared spectroscopy,optic nerve sheath diameter,positron emission tomography,and systemic hemodynamic monitoring including heart rate variability analysis.The neurophysical basis and clinical relevance of each method within the ICU setting were examined.Machine learning algorithms have shown promise by helping to analyze and interpret data in real time from continuous MMM tools,helping clinicians make more accurate and timely decisions.These algorithms can integrate diverse data streams to generate predictive models for patient outcomes and optimize treatment strategies.MMM,grounded in neurophysics,offers a more nuanced understanding of cerebral physiology and disease in the ICU.Although each modality has its strengths and limitations,its integrated use,especially in combination with machine learning algorithms,can offer invaluable information for individualized patient care.

Cognitive Functional Impairment and Hemodynamic Changes in Patients with Symptomatic Leukoaraiosis

Objective: The pathogenesis of leukoaraiosis is still unclear. Many studies have determined that changes in the hemodynamics associated with leukoaraiosis, impaired cerebrovascular reserve, and intracranial hypoperfusion can lead to various clinical manifestations such as motor or cognitive impairment. The purpose of this study was to investigate the relationship between cognitive functional changes and imaging characteristics in patients with symptomatic leukoaraiosis, and to observe the corresponding changes in hemodynamics. Methods: A total of 203 Han patients (aged 43 - 93 years) with symptomatic leukoaraiosis were included in this study. Head magnetic resonance imaging was semi-quantified according to the Fazekas grading standard. Then, each patient was evaluated in terms of cognitive (Montreal scale) and executive function (trail-making test A [TMTA] and TMTB). Specifically, the TMTA asks patients to connect points on a piece of paper numbered from 1 to 25 in order and the TMTB asks patients to arrange numbers and letters in alternating order. In the current work, revised versions of these tests used are to include numbers in square and circular shapes where the shapes needed to be arranged in alternating order. The time required to complete the TMTA and TMTB was recorded. The changes in the blood flow velocity of the middle cerebral artery were also observed using routine Transcranial Doppler ultrasound and the breath-holding test. The dynamic curves of blood flow velocity during the breath-holding test were examined. Results: The cognitive and executive functions of patients with leukoaraiosis are related to the classification of image-based disease characteristics. In this sense, the more serious the leukoaraiosis is, the larger the impairment of cognitive and executive function is. According to the breath-holding test, the peak pattern of the blood flow velocity in the middle cerebral artery was significantly different between the various grades of leukoaraiosis. The peak type of Fazekas grade 0 and I was in the same direction, while the peak type of Fazekas grade II and III was significantly opposed (both p Conclusions: The impairment of cognitive and executive functions in patients with leukoaraiosis correlates with the severity of image-based disease manifestations, which are generally depicted as intracranial hypoperfusion.

Near-infrared spectroscopy(NIRS)as a useful tool to evaluate the treatment efficacy of positive airways pressure therapy in patients with obstructive sleep apnea syndrome(OSAS):A pilot study

In obstructive sleep apnea syndrome(OSA)the periodic reduction or cessation of breathing dueto narrowing or occlusion of the upper airway during slep leads to an impaired cerebral vascularautoregulation that is associated with an increased cardiovascular risk,including stroke.Con-tinuous positive airways pressure(CPAP)therapy at night is the most effective treatment forOSA and has been shown to reduce the cardiovascular risk in OSA patients.However,there is nosuitable bedside monitoring method evaluating the recovery of cerebral hemodynamics duringCPAP therapy.Near-infrared spectroscopy(NiRS)is idelly suited for non-invasive monitoringthe cerebral hemodynamics during sleep due to its properties of local measurement,totally sa feapplication and good tolerance to motion.In this pilot study,we monitored cerebral hemody-namics during standard CPAP therapy at night in thre patients with severe OSA using NIRS.We found periodic oscllations in HbO2,HHb,tisue oxygenation index(TO1)and blood volume(BV)associa ted with periodic apnea events without CPAP in all OSA patients.These osillationswere eliminated under the optimal CPAP pressures in all patients.These results sugg ested thatthe recovery of cerebral hemodynamics impaired by apnea events can be evaluated by bedsideNIRS measurements in real time during ll night CPAP therapy.NIRS is a usefi bedsidemonitoring tool to evaluate the treatment elicacy of CPAP therapy in patients with OSA.

A review on functional near-infrared spectroscopy and application in stroke rehabilitation

Functional near-infrared spectroscopy(fNIRS)has gained great interest as a noninvasive modality to study the changes in cerebral hemodynamics related to brain activity.The unique and beneficial characteristics of fNIRS allow ecologically effective investigations of all ages and conditions in more realistic and clinical environments.In this review,we provide a comprehensive description of fNIRS basics,analytical method developments and applications in stroke rehabilitation.We first review various new methods for the time-series processing and functional analysis of fNIRS data.Then,we review the fNIRS-based application in clinical research for stroke rehabilitation and highlight the exciting developments based on fNIRS.Finally,we discuss the possible technical limitations of the implementation of fNIRS and provide suggestions from different aspects for practical application.