Non-invasive prognostic biomarker of lung cancer patients with brain metastases: Recurrence quantification analysis of heart rate variability

Li, Guangqiao; Wu, Shuang; Zhao, Huan; Guan, Weizheng; Zhou, Yu‐Fu; Shi, Bo

doi:10.3389/fphys.2022.987835

Cited by 3 publications

(4 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“… Mohebbi and Ghassemian (2011) showed that compared with the ECG signals that are distant from paroxysmal atrial fibrillation, RQA indexes, such as Lmean, Lmax, REC, and ShanEn with the ECG signals that are before paroxysmal atrial fibrillation were significantly higher. Li et al (2022) showed that higher Lmax is significantly associated with shorter overall survival in LC patients with brain metastasis. Similar to the above studies, our results showed that the RQA indexes REC and DET are independent prognostic factors for the overall survival of advanced NSCLC patients ( p < 0.05), indicating that the increase in REC and DET, that is, the decrease in heartbeat complexity, is an independent risk factor for poor prognosis in patients with advanced NSCLC.…”

Section: Discussionmentioning

confidence: 98%

“…Because the RQA can be applied to short, nonstationary and high-noise signal sequences of the R-R interval, where there is not a strict requirement for the length of data, it has been used in many studies on heart rate dynamics ( Mohebbi and Ghassemian, 2011 ; Acharya et al, 2014 ; Li et al, 2022 ). For example, Acharya et al (2014) showed that Lmean, Lmax, REC, and DET in patients with coronary artery disease are significantly higher than those in healthy populations.…”

Section: Discussionmentioning

confidence: 99%

“…For example, Shi et al (2019) found that decreased heartbeat complexity was associated with higher carcinoembryonic antigen levels in gastric cancer patients. Li et al (2022) showed that lower heartbeat complexity was predictive of shorter survival of LC patients with brain metastasis. However, few studies have explored the role of heartbeat complexity in the prognosis of patients with advanced NSCLC.…”

Section: Introductionmentioning

confidence: 98%

“…Previous studies have also shown that compared with healthy people, the heartbeat complexity of patients with atrial fibrillation ( Mohebbi and Ghassemian, 2011 ), coronary artery disease ( Acharya et al, 2014 ), or acute myocardial ischemia ( Peng and Sun, 2011 ) is significantly lower. Recently, some studies have been conducted to preliminarily examine the prognostic value of nonlinear HRV parameters in cancer ( Shi et al, 2019 ; Escutia-Reyes et al, 2021 ; Li et al, 2022 ). For example, Shi et al (2019) found that decreased heartbeat complexity was associated with higher carcinoembryonic antigen levels in gastric cancer patients.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Association of heartbeat complexity with survival in advanced non-small cell lung cancer patients

Chen³

et al. 2023

Front. Neurosci.

Self Cite

View full text Add to dashboard Cite

BackgroundPrevious studies have shown that the predictive value of traditional linear (time domain and frequency domain) heart rate variability (HRV) for the survival of patients with advanced non-small cell lung cancer (NSCLC) is controversial. Nonlinear methods, based on the concept of complexity, have been used to evaluate HRV, providing a new means to reveal the physiological and pathological changes in HRV. This study aimed to assess the association between heartbeat complexity and overall survival in patients with advanced NSCLC.MethodsThis study included 78 patients with advanced NSCLC (mean age: 62.0 ± 9.3 years). A 5-min resting electrocardiogram of advanced NSCLC patients was collected to analyze the following HRV parameters: time domain indicators, i.e., standard deviation of the normal-normal intervals (SDNN) and root mean square of successive interval differences (RMSSD); frequency domain indicators, i.e., total power (TP), low frequency power (LF), high frequency power (HF), and the ratio of LF to HF (LF/HF); nonlinear HRV indicators characterizing heartbeat complexity, i.e., approximate entropy (ApEn), sample entropy (SampEn), and recurrence quantification analysis (RQA) indexes: mean diagonal line length (Lmean), maximal diagonal line length (Lmax), recurrence rate (REC), determinism (DET), and shannon entropy (ShanEn).ResultsUnivariate analysis revealed that the linear frequency domain parameter HF and nonlinear RQA parameters Lmax, REC, and DET were significantly correlated with the survival of advanced NSCLC patients (all p < 0.05). After adjusting for confounders in the multivariate analysis, HF, REC, and DET were found to be independent prognostic factors for the survival of patients with advanced NSCLC (all p < 0.05).ConclusionThere was an independent association between heartbeat complexity and survival in advanced NSCLC patients. The nonlinear analysis method based on RQA may provide valuable additional information for the prognostic stratification of patients with advanced NSCLC and may supplement the traditional time domain and frequency domain analysis methods.

show abstract

Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Association of heartbeat complexity with survival in advanced non-small cell lung cancer patients

Chen³

et al. 2023

Front. Neurosci.

Self Cite

View full text Add to dashboard Cite

show abstract

Effect of “needle sensation” and the real-time changes in autonomic nervous system activity during acupuncture analgesia

Liu,

Huang,

Yan

et al. 2024

Front. Neurosci.

View full text Add to dashboard Cite

IntroductionAcupuncture analgesia (AA) is widely used in clinical practice. The autonomic nervous system (ANS) may be an important pathway for acupuncture signal transduction. However, real-time changes in autonomic function during AA and the effect of “needle sensation” remain unclear.MethodsWe established a human pain model in healthy adults and randomly assigned 128 participants to the model, sham acupuncture, and acupuncture groups in a 1:1:2 ratio. Heart rate variability (HRV), including total power (TP), low-frequency power (LF), high-frequency power (HF), ratio of LF to HF (LF/HF), standard deviation of the normal-normal intervals (SDNN), and root mean square of successive interval differences (RMSSD), were used to assess autonomic function. The visual analog scale (VAS) and efficiency were used to assess the analgesic effect of acupuncture. The Massachusetts General Hospital acupuncture sensation scale (MASS) was used to indicate the intensity of the needle sensation. Anxiety levels were also measured. Finally, the correlation of MASS with HRV, VAS, and anxiety levels was analyzed.ResultsVAS decreased after 10 min of needling and 5 min after needle withdrawal in the acupuncture group compared with those in the model group (p = 0.038, p = 0.020). The efficacy rates were 82.0, 50.0, and 61.3% in the acupuncture, model, and sham groups, respectively. These represent significant differences between the acupuncture group and the model and sham acupuncture groups (p < 0.001 in each case). No differences were observed between the model and sham acupuncture groups. HF, TP, SDNN, and RMSSD were all increased in the acupuncture group compared with those in the model group (p = 0.045, p = 0.041, p = 0.002, p = 0.006, respectively). No differences were observed in the sham acupuncture group compared to the model group (p = 0.632, p = 0.542, p = 0.093, p = 0.222, respectively). The LF and LF/HF did not differ among all three groups. A positive correlation was observed between MASS and RMSSD2, LF2, RMSSD4, TP4, VAS5, and anxiety levels.ConclusionAA was associated with enhanced vagal activity. The intensity of needle sensation was positively correlated with vagal and sympathetic nerve activities. Acupuncture is an effective means of regulating autonomic function, and needle sensation may be an important modulator.

show abstract

Exploring Biosignals for Quantitative Pain Assessment in Cancer Patients: A Proof of Concept

Cascella,

Vitale,

D’Antò

et al. 2023

Electronics

View full text Add to dashboard Cite

Perception and expression of pain in cancer patients are influenced by distress levels, tumor type and progression, and the underlying pathophysiology of pain. Relying on traditional pain assessment tools can present limitations due to the highly subjective and multifaceted nature of the symptoms. In this scenario, objective pain assessment is an open research challenge. This work introduces a framework for automatic pain assessment. The proposed method is based on a wearable biosignal platform to extract quantitative indicators of the patient pain experience, evaluated through a self-assessment report. Two preliminary case studies focused on the simultaneous acquisition of electrocardiography (ECG), electrodermal activity (EDA), and accelerometer signals are illustrated and discussed. The results demonstrate the feasibility of the approach, highlighting the potential of EDA in capturing skin conductance responses (SCR) related to pain events in chronic cancer pain. A weak correlation (R = 0.2) is found between SCR parameters and the standard deviation of the interbeat interval series (SDRR), selected as the Heart Rate Variability index. A statistically significant (p < 0.001) increase in both EDA signal and SDRR is detected in movement with respect to rest conditions (assessed by means of the accelerometer signals) in the case of motion-associated cancer pain, thus reflecting the relationship between motor dynamics, which trigger painful responses, and the subsequent activation of the autonomous nervous system. With the objective of integrating parameters obtained from biosignals to establish pain signatures within different clinical scenarios, the proposed framework proves to be a promising research approach to define pain signatures in different clinical contexts.

show abstract

Non-invasive prognostic biomarker of lung cancer patients with brain metastases: Recurrence quantification analysis of heart rate variability

Cited by 3 publications

References 53 publications

Association of heartbeat complexity with survival in advanced non-small cell lung cancer patients

Association of heartbeat complexity with survival in advanced non-small cell lung cancer patients

Effect of “needle sensation” and the real-time changes in autonomic nervous system activity during acupuncture analgesia

Exploring Biosignals for Quantitative Pain Assessment in Cancer Patients: A Proof of Concept

Contact Info

Product

Resources

About