Effects of interval training on haemodynamic variables after coronary artery bypass graft: A meta-analysis.

Objective: To assess the combined impact of interval training programme on haemodynamic variables, specifically blood pressure and heart rate, in patients having undergone coronary artery bypass graft surgery. METHODS: The meta-analysis was conducted from October to December 2022, and comprised search on PubMed, MEDLINE, Web of Science, PeDro, EMBASE, Science Direct, Cochrane Central Register of Controlled Clinical Trials, Google Scholar and Scopus electronic databases by two researchers independently for literature published between 2009 and 2020 related to the effects of interval training on coronary artery bypass graft patients. Meta-analysis was then performed to analyse the effects of an interval training on systolic blood pressure, diastolic blood pressure, and heart rate. The meta-analysis was performed in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. RESULTS: Of the 122 studies initially located, 7 were related to the effects of different forms of interval trainings and their impact on systolic and diastolic blood pressure of the patients, and 5 studies analysing the effects of interval trainings on heart rate. Interval training showed mild improvement in decreasing SBP compared to control groups. Standardized mean difference suggested an effect size of -0.226 in random effect model (I2=52.01; p=0.064). Similarly, a small effect size of 0.136 (I2=39.19%, p=0.14) was observed for diastolic blood pressure. Also, there was a small effect size of 0.155 (I2= 28.08, p=0.23) observed for heart rate. Conclusion: Interval training programmes, including high-intensity interval training, low-volume interval training, and aerobic interval training, had a small effect on systolic blood pressure, whereas continuous training protocols had a similarly small effect size on diastolic blood pressure and heart rate.

Stress responses in surgical trainees during simulation-based training courses in laparoscopy.

BACKGROUND: Simulation-based training courses in laparoscopy have become a fundamental part of surgical training programs. Surgical skills in laparoscopy are challenging to master, and training in these skills induces stress responses in trainees. There is limited data on trainees' stress levels, the stress responses related to training on different laparoscopic simulators, and how previous experiences influence trainees' stress response during a course. This study investigates physiologic, endocrine and self-reported stress responses during simulation-based surgical skills training in a course setting. METHODS: We conducted a prospective observational study of trainees attending basic laparoscopic skills training courses at a national training centre. During the three-day course, participants trained on different laparoscopic simulators: Two box-trainers (the D-box and P.O.P. trainer) and a virtual reality simulator (LAPMentor™). Participants' stress responses were examined through heart rate variability (HRV), saliva cortisol, and the State Trait Anxiety Inventory-6 (STAI-6). The correlation between previous laparoscopic experiences and stress response measurements was explored. RESULTS: Twenty-four surgical trainees were included in the study. Compared to resting conditions, stress measures were significantly higher during simulation-training activity (the D-box (SDNN = 58.5 ± 23.4; LF/HF-ratio = 4.58 ± 2.71; STAI-6 = 12.3 ± 3.9, P < 0.05), the P.O.P trainer (SDNN = 55.7 ± 7.4; RMSSD = 32.4 ± 17.1; STAI-6 = 12.1 ± 3.9, P < 0.05), and the LAPMentor™ (SDNN = 59.1 ± 18.5; RMSSD = 34.3 ± 19.7; LF/HF-ratio = 4.71 ± 2.64; STAI-6 = 9.9 ± 3.0, P < 0.05)). A significant difference in endocrine stress response was seen for the simulation-training activity on the D-box (saliva cortisol: 3.48 ± 1.92, P < 0.05), however, no significant differences were observed between the three simulators. A moderate correlation between surgical experience, and physiologic and endocrine stress response was observed (RMSSD: r=-0.31; SDNN: r=-0.42; SD2/SD1 ratio: r = 0.29; Saliva cortisol: r = 0.46; P < 0.05), and a negative moderate correlation to self-reported stress (r=-0.42, P < 0.05). CONCLUSION: Trainees have a significant higher stress response during simulation-training compared to resting conditions, with no difference in stress response between the simulators. Significantly higher cortisol levels were observed on the D-box, indicating that simulation tasks with time pressure stress participants the most. Trainees with more surgical experience are associated with higher physiologic stress measures, but lower self-reported stress scores, demonstrating that surgical experience influences trainees' stress response during simulation-based skills training courses.

From physiological complexity to data interactions-A case study of recordings from exercise monitoring.

The popularity of nonlinear analysis has been growing simultaneously with the technology of effort monitoring. Therefore, considering the simple methods of physiological data collection and the approaches from the information domain, we proposed integrating univariate and bivariate analysis for the rest and effort comparison. Two sessions separated by an intensive training program were studied. Nine subjects participated in the first session (S1) and seven in the second session (S2). The protocol included baseline (BAS), exercise, and recovery phase. During all phases, electrocardiogram (ECG) was recorded. For the analysis, we selected corresponding data lengths of BAS and exercise usually lasting less than 5 min. We found the utility of the differences between original data and their surrogates for sample entropy Sdiff and Kullback-Leibler divergence KLDdiff. Sdiff of heart rate variability was negative in BAS and exercise but its sensitivity for phases discrimination was not satisfactory. We studied the bivariate analysis of RR intervals and corresponding QT peaks by Interlayer Mutual Information (IMI) and average edge overlap (AVO) markers. While the IMI parameter decreases in exercise conditions, AVO increased in effort compared to BAS. These findings conclude that researchers should consider a bivariate analysis of extracted RR intervals and corresponding QT datasets, when only ECG is recorded during tests.

Multimodal ECG heartbeat classification method based on a convolutional neural network embedded with FCA.

Arrhythmias are irregular heartbeat rhythms caused by various conditions. Automated ECG signal classification aids in diagnosing and predicting arrhythmias. Current studies mostly focus on 1D ECG signals, overlooking the fusion of multiple ECG modalities for enhanced analysis. We converted ECG signals into modal images using RP, GAF, and MTF, inputting them into our classification model. To optimize detail retention, we introduced a CNN-based model with FCA for multimodal ECG tasks. Achieving 99.6% accuracy on the MIT-BIH arrhythmia database for five arrhythmias, our method outperforms prior models. Experimental results confirm its reliability for ECG classification tasks.

[Design of Pulse and Respiratory Signals Detection System].

A pulse and respiration synchronous detection system is designed to explore the changes of physiological signals in different situations. The system obtains the corresponding signal through STM32 control pulse and respiratory acquisition circuit, calculates and displays real-time parameters such as heart rate and respiratory rate, and transmits the data to the upper computer for storage in the database. The experimental test results show that the system can monitor pulse and respiratory waveform in different situations, and the waveform is in good condition. Compared with medical pulse oximeter, the error of measured heart rate and blood oxygen concentration is less than 3%, and the error of respiratory rate is less than 5% compared with the actual value, which verifies the accuracy of system signal acquisition. The system is small in size, low in cost, and comfortable to wear, and can be applied in experimental research related to pulse and respiratory signals.

Nimble vs. torpid responders to hydration pulse duration among soil microbes.

Environmental parameters vary in time, and variability is inherent in soils, where microbial activity follows precipitation pulses. The expanded pulse-reserve paradigm (EPRP) contends that arid soil microorganisms have adaptively diversified in response to pulse regimes differing in frequency and duration. To test this, we incubate Chihuahuan Desert soil microbiomes under separate treatments in which 60 h of hydration was reached with pulses of different pulse duration (PD), punctuated by intervening periods of desiccation. Using 16S rRNA gene amplicon data, we measure treatment effects on microbiome net growth, growth efficiency, diversity, and species composition, tracking the fate of 370 phylotypes (23% of those detected). Consistent with predictions, microbial diversity is a direct, saturating function of PD. Increasingly larger shifts in community composition are detected with decreasing PD, as specialist phylotypes become more prominent. One in five phylotypes whose fate was tracked responds consistently to PD, some preferring short pulses (nimble responders; NIRs) and some longer pulses (torpid responders; TORs). For pulses shorter than a day, microbiome growth efficiency is an inverse function of PD, as predicted. We conclude that PD in pulsed soil environments constitutes a major driver of microbial community assembly and function, largely consistent with the EPRP predictions.

Heart Rate Variability Monitoring Based on Doppler Radar Using Deep Learning.

The potential of microwave Doppler radar in non-contact vital sign detection is significant; however, prevailing radar-based heart rate (HR) and heart rate variability (HRV) monitoring technologies often necessitate data lengths surpassing 10 s, leading to increased detection latency and inaccurate HRV estimates. To address this problem, this paper introduces a novel network integrating a frequency representation module and a residual in residual module for the precise estimation and tracking of HR from concise time series, followed by HRV monitoring. The network adeptly transforms radar signals from the time domain to the frequency domain, yielding high-resolution spectrum representation within specified frequency intervals. This significantly reduces latency and improves HRV estimation accuracy by using data that are only 4 s in length. This study uses simulation data, Frequency-Modulated Continuous-Wave radar-measured data, and Continuous-Wave radar data to validate the model. Experimental results show that despite the shortened data length, the average heart rate measurement accuracy of the algorithm remains above 95% with no loss of estimation accuracy. This study contributes an efficient heart rate variability estimation algorithm to the domain of non-contact vital sign detection, offering significant practical application value.

Heart Rate Variability and Pulse Rate Variability: Do Anatomical Location and Sampling Rate Matter?

Wearable technology and neuroimaging equipment using photoplethysmography (PPG) have become increasingly popularized in recent years. Several investigations deriving pulse rate variability (PRV) from PPG have demonstrated that a slight bias exists compared to concurrent heart rate variability (HRV) estimates. PPG devices commonly sample at ~20-100 Hz, where the minimum sampling frequency to derive valid PRV metrics is unknown. Further, due to different autonomic innervation, it is unknown if PRV metrics are harmonious between the cerebral and peripheral vasculature. Cardiac activity via electrocardiography (ECG) and PPG were obtained concurrently in 54 participants (29 females) in an upright orthostatic position. PPG data were collected at three anatomical locations: left third phalanx, middle cerebral artery, and posterior cerebral artery using a Finapres NOVA device and transcranial Doppler ultrasound. Data were sampled for five minutes at 1000 Hz and downsampled to frequencies ranging from 20 to 500 Hz. HRV (via ECG) and PRV (via PPG) were quantified and compared at 1000 Hz using Bland-Altman plots and coefficient of variation (CoV). A sampling frequency of ~100-200 Hz was required to produce PRV metrics with a bias of less than 2%, while a sampling rate of ~40-50 Hz elicited a bias smaller than 20%. At 1000 Hz, time- and frequency-domain PRV measures were slightly elevated compared to those derived from HRV (mean bias: ~1-8%). In conjunction with previous reports, PRV and HRV were not surrogate biomarkers due to the different nature of the collected waveforms. Nevertheless, PRV estimates displayed greater validity at a lower sampling rate compared to HRV estimates.

Visualizing a Cold Stress-Specific Pulse Wave in Traditional Pulse Diagnosis ('Tight Pulse') Correlated with Vascular Changes in the Radial Artery Induced by a Cold Pressor Trial.

Radial pulse diagnosis is the most common method to examine the human health state in Traditional East Asian Medicine (TEAM). A cold stress-related suboptimal health state (subhealth) is often undetectable during routine medical examinations, however, it can be detected through the palpation of specific pulse waves, particularly a 'tight pulse', in TEAM. Therefore, this study examined a correlation between 'tight pulse' and vascular changes in the radial artery (RA) induced by a cold pressor trial (CPT). Twenty healthy subjects underwent sequentially control trial and CPT with room-temperature and ice-cold water, respectively, on the right forearm. The radial pulse and vascular changes were then examined on the left arm. The radial pulse scores for frequencies of 'tight pulse' with strong arterial tension increased after the CPT compared with the control trial. The pulse scores were reversely correlated with the RA thickness and volumes in ultrasonography, but not with changes in the systolic/diastolic blood pressure. The RA thickness-based vascular surface and three-dimensional images visualized a 'tight pulse' showing the vasoconstriction and bumpy-/rope-shaped vascular changes in the radial pulse diagnostic region after the CPT. These findings provide valuable insights into the potential integration of clinical radial pulse diagnosis with ultrasonography for cold-related subhealth.

Neurophysiological and Autonomic Correlates of Metacognitive Control of and Resistance to Distractors in Ecological Setting: A Pilot Study.

In organisational contexts, professionals are required to decide dynamically and prioritise unexpected external inputs deriving from multiple sources. In the present study, we applied a multimethodological neuroscientific approach to investigate the ability to resist and control ecological distractors during decision-making and to explore whether a specific behavioural, neurophysiological (i.e., delta, theta, alpha and beta EEG band), or autonomic (i.e., heart rate-HR, and skin conductance response-SCR) pattern is correlated with specific personality profiles, collected with the 10-item Big Five Inventory. Twenty-four participants performed a novel Resistance to Ecological Distractors (RED) task aimed at exploring the ability to resist and control distractors and the level of coherence and awareness of behaviour (metacognition ability), while neurophysiological and autonomic measures were collected. The behavioural results highlighted that effectiveness in performance did not require self-control and metacognition behaviour and that being proficient in metacognition can have an impact on performance. Moreover, it was shown that the ability to resist ecological distractors is related to a specific autonomic profile (HR and SCR decrease) and that the neurophysiological and autonomic activations during task execution correlate with specific personality profiles. The agreeableness profile was negatively correlated with the EEG theta band and positively with the EEG beta band, the conscientiousness profile was negatively correlated with the EEG alpha band, and the extroversion profile was positively correlated with the EEG beta band. Taken together, these findings describe and disentangle the hidden relationship that lies beneath individuals' decision to inhibit or activate intentionally a specific behaviour, such as responding, or not, to an external stimulus, in ecological conditions.

Heart Rate Measurement Using the Built-In Triaxial Accelerometer from a Commercial Digital Writing Device.

Currently, wearable technology is an emerging trend that offers remarkable access to our data through smart devices like smartphones, watches, fitness trackers and textiles. As such, wearable devices can enable health monitoring without disrupting our daily routines. In clinical settings, electrocardiograms (ECGs) and photoplethysmographies (PPGs) are used to monitor heart and respiratory behaviors. In more practical settings, accelerometers can be used to estimate the heart rate when they are attached to the chest. They can also help filter out some noise in ECG signals from movement. In this work, we compare the heart rate data extracted from the built-in accelerometer of a commercial smart pen equipped with sensors (STABILO's DigiPen) to standard ECG monitor readouts. We demonstrate that it is possible to accurately predict the heart rate from the smart pencil. The data collection is carried out with eight volunteers writing the alphabet continuously for five minutes. The signal is processed with a Butterworth filter to cut off noise. We achieve a mean-squared error (MSE) better than 6.685 × 10-3 comparing the DigiPen's computed Δt (time between pulses) with the reference ECG data. The peaks' timestamps for both signals all maintain a correlation higher than 0.99. All computed heart rates (HR =60Δt) from the pen accurately correlate with the reference ECG signals.

Analysis of Heart Rate Variability in Individuals Affected by Amyotrophic Lateral Sclerosis.

INTRODUCTION: Amyotrophic lateral sclerosis (ALS) produces alterations in the autonomic nervous system (ANS), which explains the cardiac manifestations observed in patients. The assessment of heart rate variability (HRV) is what best reflects the activity of the ANS on heart rate. The Polar H7 Bluetooth® device proves to be a non-invasive and much faster technology than existing alternatives for this purpose. OBJECTIVE: The goal of this study is to determine HRV using Polar H7 Bluetooth technology in ALS patients, comparing the obtained measurements with values from healthy individuals. METHOD: The sample consisted of 124 participants: 68 diagnosed with ALS and 56 healthy individuals. Using Polar H7 Bluetooth technology and the ELITE HRV application, various HRV measurements were determined for all participants, specifically the HRV index, RMSSD, RMSSD LN, SDNN index, PNN50, LF, HF, LF/HF ratio, HR average, and HF peak frequency. RESULTS: Statistically significant differences were observed between ALS patients and healthy individuals in the HRV index, RMSSD, RMSSD LN, SDNN index, PNN50, HF, and LF, where healthy individuals exhibited higher scores. For the HR average, the ALS group showed a higher value. Values were similar when comparing men and women with ALS, with only a higher HF peak frequency observed in women. CONCLUSION: The Polar H7 Bluetooth® device is effective in determining heart rate variability alterations in ALS, being a promising prognostic tool for the disease.

Respiratory modulation of the heart rate: A potential biomarker of cardiorespiratory function in human.

In recent decade, wearable digital devices have shown potentials for the discovery of novel biomarkers of humans' physiology and behavior. Heart rate (HR) and respiration rate (RR) are most crucial bio-signals in humans' digital phenotyping research. HR is a continuous and non-invasive proxy to autonomic nervous system and ample evidence pinpoints the critical role of respiratory modulation of cardiac function. In the present study, we recorded longitudinal (7 days, 4.63 ± 1.52) HR and RR of 89 freely behaving human subjects (Female: 39, age 57.28 ± 5.67, Male: 50, age 58.48 ± 6.32) and analyzed their dynamics using linear models and information theoretic measures. While HR's linear and nonlinear characteristics were expressed within the plane of the HR-RR directed flow of information (HR→RR - RR→HR), their dynamics were determined by its RR→HR axis. More importantly, RR→HR quantified the effect of alcohol consumption on individuals' cardiorespiratory function independent of their consumed amount of alcohol, thereby signifying the presence of this habit in their daily life activities. The present findings provided evidence for the critical role of the respiratory modulation of HR, which was previously only studied in non-human animals. These results can contribute to humans' phenotyping research by presenting RR→HR as a digital diagnosis/prognosis marker of humans' cardiorespiratory pathology.

When Studying Affective Responses to Exercise, the Definition of "Intensity" Must Reference Homeostatic Perturbations: A Retort to Vollaard et al.

In articles on the methodology of studies investigating affective and enjoyment responses to high-intensity interval training, we noted that, occasionally, exercise conditions described as involving "high" intensity exhibited heart rates that were only as high as, or even lower than, heart rates recorded during comparator conditions described as being of "moderate" intensity. Drs. Vollaard, Metcalfe, Kinghorn, Jung, and Little suggest instead that exercise intensity in high-intensity interval-training studies can be defined in terms of percentages of peak workload. Although we maintain that defining exercise intensity in terms of percentages of maximal heart rate is a suboptimal way to quantify the degree of homeostatic perturbations in response to exercise, we are unconvinced that definitions of intensity relying solely on workload are appropriate for studies investigating affective and enjoyment responses to exercise. The reason is that affect is theorized to have evolved to relay information about homeostatic perturbations to consciousness.

Electrocardiogram prediction of atrial fibrillation risk after stroke: A protocol for systematic review and meta-analysis.

BACKGROUND: Atrial fibrillation (AF) is one of the most common clinical arrhythmias. This study aims to predict the risk of post-stroke AF through electrocardiographic changes in sinus rhythm. METHODS: We searched the MEDLINE (PubMed) and EMBASE databases to identify relevant research articles published until August 2023. Prioritized items from systematic reviews and meta-analyses were screened, and data related to AF detection rate were extracted. A meta-analysis using a random-effects model was conducted for data synthesis and analysis. RESULTS: A total of 32 studies involving electrocardiograms (ECG) were included, with a total analysis population of 330,284 individuals. Among them, 16,662 individuals (ECG abnormal group) developed AF, while 313,622 individuals (ECG normal group) did not. ECG patterns included terminal P-wave terminal force V1, interatrial block (IAB), advanced interatrial block, abnormal P-wave axis, pulse rate prolongation, and atrial premature complexes. Overall, 15,762 patients experienced AF during the study period (4.77%). In the ECG abnormal group, the proportion was 14.21% (2367/16,662), while in the control group (ECG normal group), the proportion was 4.27% (13,395/313,622). The pooled risk ratio for developing AF was 2.45 (95% confidence interval [CI]: 2.02-2.98, P < .001), with heterogeneity (I2) of 95%. The risk ratio values of alAB, P-wave terminal force V1, interatrial block, abnormal P-wave axis, pulse rate prolongation and atrial premature complexes were 4.12 (95% CI, 2.99-5.66), 1.47 (95% CI, 1.19-1.82), 2.54 (95% CI, 1.83-3.52), 1.70 (95% CI, 0.98-2.97), 2.65 (95% CI, 1.88-3.72), 3.79 (95% CI, 2.12-6.76), respectively. CONCLUSION: There is a significant correlation between ECG patterns and the occurrence of AF. The alAB exhibited the highest level of predictability for the occurrence of AF. These indicators support their use as screening tools to identify high-risk individuals who may benefit from further examinations or empirical anticoagulation therapy following stroke.

Defining Ultra-Massive Transfusion through a Systematic Review.

Background: Despite the widespread use of ultra-massive transfusion (UMT) as an intervention for trauma patients in hemorrhagic shock, no standard definition exists. We performed a systematic review to determine a consensus definition for UMT. Methods: A search was performed from 1979-2022. The authors screened studies defining UMT and associated outcomes as defined by our prespecified PICO questions. The PRISMA guidelines were used. Results: 1662 articles met criteria for eligibility assessment, 17 for full-text review and eight for data extraction. Only two studies demonstrated a consensus definition of UMT, which used ≥20 units of red blood cell product within 24hrs. Parameters associated with increased mortality included lower blood pressure, lower pulse and lower Glasgow Coma Score at the time of presentation and a higher injury severity score and undergoing a resuscitative thoracotomy. Conclusions: The absence of a consensus definition for UMT raises challenges from clinical, research and ethical perspectives. Based on our findings, the authors advocate for the feasibility of standardizing the definition of UMT as ≥20 units of red blood cell product within 24hrs.

Sleep-stage dependence and co-existence of cardio-respiratory coordination and phase synchronization.

Interactions between the cardiac and respiratory systems play a pivotal role in physiological functioning. Nonetheless, the intricacies of cardio-respiratory couplings, such as cardio-respiratory phase synchronization (CRPS) and cardio-respiratory coordination (CRC), remain elusive, and an automated algorithm for CRC detection is lacking. This paper introduces an automated CRC detection algorithm, which allowed us to conduct a comprehensive comparison of CRPS and CRC during sleep for the first time using an extensive database. We found that CRPS is more sensitive to sleep-stage transitions, and intriguingly, there is a negative correlation between the degree of CRPS and CRC when fluctuations in breathing frequency are high. This comparative analysis holds promise in assisting researchers in gaining deeper insights into the mechanics of and distinctions between these two physiological phenomena. Additionally, the automated algorithms we devised have the potential to offer valuable insights into the clinical applications of CRC and CRPS.

Evaluation of cardiac autonomic dysfunctions in children with type 1 diabetes mellitus.

BACKGROUND: Cardiovascular autonomic neuropathy (CAN) is a serious complication of diabetes, impacting the autonomic nerves that regulate the heart and blood vessels. Timely recognition and treatment of CAN are crucial in averting the onset of cardiovascular complications. Both clinically apparent autonomic neuropathy and subclinical autonomic neuropathy, particularly CAN pose a significant risk of morbidity and mortality in children with type 1 diabetes mellitus (T1DM). Notably, CAN can progress silently before manifesting clinically. In our study, we assessed patients with poor metabolic control, without symptoms, following the ISPAD 2022 guideline. The objective is is to determine which parameters we can use to diagnose CAN in the subclinical period. METHODS: Our study is a cross-sectional case-control study that includes 30 children diagnosed with T1DM exhibiting poor metabolic control (average HbA1c > 8.5% for at least 1 year) according to the ISPAD 2022 Consensus Guide. These patients, who are under the care of the pediatric diabetes clinic, underwent evaluation through four noninvasive autonomic tests: echocardiography, 24-h Holter ECG for heart rate variability (HRV), cardiopulmonary exercise test, and tilt table test. RESULTS: The average age of the patients was 13.73 ± 1.96 years, the average diabetes duration was 8 ± 3.66 years, and the 1-year average HbA1c value was 11.34 ± 21%. In our asymptomatic and poorly metabolically controlled patient group, we found a decrease in HRV values, the presence of postural hypotension with the tilt table test, and a decrease in ventricular diastolic functions that are consistent with the presence of CAN. Despite CAN, the systolic functions of the ventricles were preserved, and the dimensions of the cardiac chambers and cardiopulmonary exercise test were normal. CONCLUSIONS: CAN is a common complication of T1DM, often associated with the patient's age and poor glycemic control. HRV, active orthostatic tests, and the evaluation of diastolic dysfunctions play significant roles in the comprehensive assessment of CAN. These diagnostic measures are valuable tools in identifying autonomic dysfunction at an early stage, allowing for timely intervention and management to mitigate the impact of cardiovascular complications associated with T1DM.

Independent and interactive associations of heart rate and obesity with type 2 diabetes mellites: A population-based study.

BACKGROUND: Although obesity and heart rate (HR) were closely related to the prevalence and development of type 2 diabetes mllitus (T2DM), few studies have shown a co-association effect of them on T2DM. We aimed at assessing the interactive effects of HR and obesity with prevalence of T2DM in Chinese population, providing the exact cutpoint of the risk threshold for blood glucose with high HR. MATERIALS AND METHODS: In the Risk Evaluation of cAncers in Chinese diabeTic Individuals: a lONgitudinal study (REACTION) cohorts (N = 8398), the relationship between HR and T2DM was explored by linear regression, logistic regression, and restricted cubic spline, and odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Interaction terms between HR and body mass index (BMI) and HR and waist circumference (WC) were introduced into the logistic regression model. RESULTS: In those with HR > 88.0 beats/min, fasting plasma glucose and oral glucose tolerance tests were significantly correlated with HR, and the prevalence of T2DM was highly correlated with HR (all p < .05). There were interactive associations of HR and obesity in patients with T2DM with HR < 74 beats/min. CONCLUSION: High HR was in interaction with obesity, associating with prevalence of T2DM. The newly subdivided risk threshold for HR with T2DM might be HR > 88 beats/minute.