Heart Rate Variability of Interventional Cardiology Fellows and Attendings and Changes Over Time
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J INVASIVE CARDIOL 2025. doi:10.25270/jic/25.00011. Epub April 1, 2025.
Abstract
Objectives. The levels of stress experienced by interventional cardiologists (IC) while performing procedures are not well known. The study examined the IC fellow and attending stress levels using both objective (heart rate variability [HRV]) and subjective (State Trait Anxiety Inventory [STAI]) metrics across the IC fellowship.
Methods. Six ICs participated in a study conducted over 2 periods, each lasting 10 to 14 days. Participants recorded their HRV using a Polar H10 chest strap (Polar Electro, Inc.) and a WHOOP 4.0 wrist band (WHOOP). The low frequency/high frequency (LF/HF) ratio, biomarker of sympathetic system activation, and related metrics were calculated using Kubios HRV Scientific software (Kubios Oy).
Results. A total of 217 procedures were analyzed. The median LF/HF ratio during procedures was significantly higher than at baseline (6.2 vs 4.1, P < .001). Complex procedures had higher LF/HF ratio difference (procedural minus baseline LH/HF ratio) compared with non-complex procedures (2.55 vs 1.73, P < .001), as did procedures with complications compared with uncomplicated procedures (3.01 vs 1.82, P < .001) and emergent compared with non-emergent (3.51 vs 1.84, P < .001) procedures. Procedures performed during period 2 (end of IC fellowship) had a lower LF/HF ratio difference (2.96 vs 1.10, P < .001) but higher daily resting HRV (52 vs 46, P < .001) compared with period 1 (beginning of IC fellowship). No correlation was detected between the pre- and post-procedural LF/HF ratio difference and the STAI score difference.
Conclusions. Interventional cardiologists experience significant stress, as measured by the LF/HF ratio, during complex, emergency, and complicated procedures; however, stress levels decrease later in the IC fellowship.
Introduction
Stress can occur in association with procedures performed by interventional cardiology (IC) fellows and attendings. Surveys indicate that IC training is considered stressful by most interventional fellows.1 Almost one-third of IC fellows considered leaving their job during the prior year and felt overwhelmed at least 3 times a week.2 Likewise, burnout affects most ICs.3 It remains unknown, however, whether ICs deal with increased stress before, during, and after a procedure, if their stress decreases with experience, and how they recover after a procedure.
Heart rate variability (HRV) has been used as a biomarker of stress in various studies, reflecting the activity of the autonomic nervous system (ANS).4-10 A systematic review including 10 studies assessing the association between occupational stress and HRV found that increased occupational stress was associated with lower HRV and reduced parasympathetic activation.5 The intraprocedural changes of HRV has not been studied in the field of IC, while studies in the field of surgery have indicated increased intraoperative stress.6,7,11 The current study examined the stress levels of IC fellows and attendings using HRV and related metrics.
Methods
In this prospective single-center cohort study, we studied the stress levels of IC fellows and attendings usings various subjective and objective metrics (Central Illustration). The primary endpoint of the study was HRV, as assessed by the wearable devices. Subjective stress, as the primary psychological outcome, was assessed by the 6-item State Trait Anxiety Inventory (STAI) questionnaire12 (eg, “I am tense”), including 6 items each rated on a 4-point anchored Likert scale and rated 5 minutes before and 5 minutes after each procedure. Each component of the STAI-6 can score between 1 and 4, with a minimum total score of 6 and maximum score of 24. Procedure-related questions were assessed by the post-procedural questionnaire 5 minutes after each procedure. Burnout at baseline was assessed once at the beginning of the study by the Mini-Z survey,13 which is validated against the Maslach Burnout Inventory.14
The study was divided into 2 periods: period 1 was at the beginning/middle of the IC fellowship (October 2023 - January 2024), and period 2 was at the end of the fellowship (April 2024 - June 2024). Each period lasted 10 to 14 days. Six participants (3 IC attendings and 3 IC fellows) were enrolled in the study. The demographic information of the participants is presented in Table 1. Due to the sample size and single-center nature of the study, detailed demographic information is not reported to maintain participant anonymity and confidentiality. One of the attendings discontinued enrollment at the second period, so data were captured only for the first period. None of the participants were smokers (current or past). Three participants were casual drinkers, while the other three reported never drinking. No participant had a diagnosed anxiety disorder or depression.
Written informed consent was obtained from all volunteers before their participation. Exclusion criteria were any health conditions that in the opinion of the investigators would preclude the individual’s participation in the study, such as conditions that would preclude them from wearing the study wearables and participating to provide wearable data. Study data were collected and managed using REDCap (Research Electronic Data Capture) electronic data capture tools hosted at the Minneapolis Heart Institute Foundation.15,16 The study was approved by the institutional review board.
A case was classified as complicated if the operator reported any significant periprocedural adverse event. Procedural complexity was classified based on the operator’s real-time assessment at the time of the procedure, without predefined criteria. This approach reflects the dynamic nature of IC wherein complexity is influenced by multiple factors, including lesion characteristics, hemodynamic stability, career stage, and overall procedural difficulty. While subjective variability may exist, this classification aligns with the way complexity is assessed in daily clinical practice.
The term 'on-call' refers to procedures performed during an operator’s designated on-call shift, regardless of urgency. Emergency procedures were defined as unscheduled, time-sensitive interventions such as ST-elevation myocardial infarction (STEMI) percutaneous coronary intervention (PCI) or urgent hemodynamic support cases.
All procedures in this study were either performed jointly by a fellow and an attending or by an attending alone. The included procedures were those reported during the study period of each participant, regardless of whether they were performed by an attending alone or by a fellow-attending team. We did not track whether procedures were performed by which fellow-attending pair, and we did not link specific fellows to specific attendings across multiple procedures. However, we did note whether the primary operator is a fellow or an attending, which enables us to report any differences based on who is primarily performing the procedure each time.
HRV recordings
Data regarding HRV were collected through 2 wearables: (1) the Polar H10 heart rate sensor (chest strap; Polar Electro, Inc.) and (2) the WHOOP 4.0 (wrist/bicep band; WHOOP).
The Polar H10 has been validated against the electrocardiogram (ECG) gold standard.17 Measurements with the Polar H10 heart rate sensor were conducted beat-to-beat, recording all the interval data (RR or pulse-to-pulse intervals). The Polar H10 collected heart rate data wirelessly and transmitted data via Bluetooth to the Kubios HRV mobile application, enabling custom measurements that were then analyzed with the Kubios HRV Scientific software 4.0.3 (Kubios Oy), allowing for time and frequency domain analysis. The participants were asked to record a morning baseline HRV measurement (duration around 5 minutes), while being in a resting state for 5 to 10 minutes before the measurement. For each procedure during the day, participants were asked to create a continuous custom HRV measurement for the duration of the procedure, saving the recording to the sensor each time.
For the RR analysis, automatic beat correction was used to correct artifacts from a corrupted RR interval series. The automatic correction is an accurate algorithm for detecting artifacts (missed, extra, and misaligned beat detections) as well as ectopic beats.
The HRV parameters reported were time and frequency domain, and were derived according to the guidelines.18 The HRV were parameters divided into those primarily reflecting parasympathetic nervous system (PNS) tone and those reflecting sympathetic nervous system (SNS) tone, as presented at Table 2.19 For the time domain results, we evaluated the following: mean RR (ms), standard deviation of normal to normal intervals (SDNN; ms), mean heart rate (HR; bpm), min HR (bpm), max HR (bpm), square root of the mean normal to normal interval (RMSSD; ms), percentage of adjacent pairs of normal to normal intervals differing by more than 50 milliseconds in the recording (pNN50; %), NN50 (beats), and Stress Index (the square root of the Baevsky’s stress index; ms20). For the frequency domain results, we evaluated the following: the power of high frequency (HF; ms2), very low frequency (VLF; ms2), low frequency (LF) and the LF/HF ratio.
WHOOP measures heart rate using advanced optical sensors with photoplethysmography (PPG) technology. WHOOP bands have been validated against the gold standard assessment via ECG.21 The WHOOP 4.0 wearable was linked to the Whoop app for data collection and storage. Participants were asked to wear the wearable throughout the day, including sleep, for each study period to capture resting HRV.22 The WHOOP 4.0 tracks physiologic and sleep cycles, including the following metrics: resting HR (bpm) calculated from sleep, HRV (ms) calculated from sleep using RMSSD, the root mean square of successive differences between heartbeats, maximum HR (bpm) during physiological cycle, average HR (bpm) during physiological cycle, sleep performance (%) calculated from hours of sleep divided by sleep need, and recovery score (%) from the physiological cycle, which reflects how well prepared the body is to take on strain.2,3,24
Statistical analysis
Categorical variables were expressed as n (percentages) and were compared using the Pearson’s chi-square test. Continuous variables are presented as mean ± SD or as median (IQR) and were compared using the paired t-test for normally distributed variables and the Wilcoxon signed-rank test for non-parametric variables, as appropriate. The Shapiro-Wilk test was used to assess the normality of selected variables, guiding the selection of appropriate parametric or non-parametric tests. Spearman's rank correlation was employed to assess the strength and direction of monotonic relationships between key variables. All statistical analyses were performed using R Statistical Software, version 4.2.2 (R Foundation for Statistical Computing). A P-value of less than 0.05 was considered statistically significant.
Results
Procedural characteristics
A total of 217 procedures were analyzed. Detailed information regarding these procedures can be found in Supplemental Table 1. The mean procedural time was 76.78 ± 73.72 minutes, and 36.6% (79) of the procedures were characterized as complex by the operators. In 63.4% (138) of the cases, the participant was the primary operator; 28.2% (61) of the procedures were performed while the operator was on-call, and 11.1% (24) of the procedures were emergency procedures. Most of the procedures (38.7% - 84) were diagnostic angiograms, 29.5% (64) were PCIs, 18.0% (39) were chronic total occlusion (CTO) PCIs, 10.1% (22) were right heart catheterizations, and 13.4% (29) were structural heart interventions. The technical success of the procedures was 95.8% (205), while 6.9% (15) of the procedures had a complication.
Intraprocedural HRV metrics
Procedural metrics related to the HRV and captured by the Polar H10 chest strap are presented in Table 2. The median LF/HF ratio during the procedures was higher than at baseline (6.2 [IQR 4.5-9.5] vs 4.1 [IQR 3.0-5.8], P < .001), while the median RMSSD during the procedure was lower than at baseline (21 [IQR 17-28] vs 24 [IQR 17-32], P < .001).
The differences in LF/HF ratio (procedural LH/HF ratio minus baseline LH/HF ratio) across various procedural contexts were assessed using Wilcoxon signed-rank tests with continuity correction (Figure 1, Figure 2). A statistically significant difference was observed between complex (median 2.55, IQR 0.36-5.18) and non-complex procedures (median 1.73, IQR 0.02-3.80, P < .001), as well as between procedures with complications (median 3.01, IQR 1.30-4.71) and procedures without any complications (median 1.82, IQR 0.02-4.22, P < .001). Procedures performed as the primary operator had a significantly higher LF/HF ratio (median 2.06, IQR 0.21-5.02) compared with when assisting/teaching (median 1.56, IQR -0.15-3.43, P < .001). Emergency procedures showed a higher LF/HF ratio (median 3.51, IQR 0.53-4.95) compared with non-emergency procedures (median 1.84, IQR 0.15-4.10, P < .001).
A significant reduction in LF/HF ratio was found between period 1 (median 2.96, IQR 0.95-5.84) and period 2 (median 1.10, IQR -0.31-2.60, P < .001), suggesting a decrease in stress and sympathetic activation over time. The changes in the LF/HF ratio were consistent in a subgroup analysis for both fellows and attendings (P < .001). There was a significant reduction in RMSSD between period 1 and period 2 (median difference -1.45 [IQR -7.38-3.82] vs -2.10 [IQR -10.8-2.65], P = .035).
Procedures lasting 90 minutes or longer had a slightly higher LF/HF ratio (median 1.94, IQR 0.36-4.13) compared with those lasting less than 90 minutes (median 1.85, IQR 0.02-4.50, P < .001). No statistically significant difference was observed between on-call (median 1.94, IQR -0.85-3.80) and not on-call (median 1.82, IQR 0.52-4.54, P = .225) cases.
Fellows performed 111 procedures and attendings performed 106. The slight discrepancy in the number of procedures between fellows and attendings may reflect missing cases because of incomplete data entry, device recording errors, or other data collection limitations for these cases. The mean procedural LF/HF ratio was higher for attendings than for fellows (9.31 [IQR 5.87-11.41] vs 5.06 [IQR 3.82-6.41], P < .001), similarly as was the mean baseline LH/HF ratio (4.54 [IQR 3.21-5.85] vs 3.89 [IQR 2.57-5.55], P = .027) and the LH/HF ratio difference (3.60 [IQR 0.84-7.05] vs 1.44 [IQR -0.34-2.71], P < .001). However, the attendings reported more complex cases (46.7% vs 27.0%, P = .004).
Resting HRV and sleep metrics
Supplementary Table 2 presents heart rate and sleep data captured by the WHOOP 4.0 device. HRV measured during sleep was statistically significantly higher in the second study period (at the end of the IC fellowship) compared with the first. The median HRV was 52 ms (IQR 46-60) in the second period vs 46 ms (IQR 39-55, P < .001) in the first period.
Recovery score, provided by the WHOOP app as a daily percentage (0%-100%) indicating how prepared the body is to perform, was higher in the second study period compared with the first (60 ± 21% vs 56 ± 22%, P < .001). This score is based on resting HR, HRV, blood oxygen, skin temperature, respiratory rate, and sleep performance.
Day strain, a metric provided by the WHOOP strap that summarizes the total stress on the body, including both muscular and cardiovascular strain, was statistically significantly higher during the first study period. Day strain is scored on a scale from 0 to 21, with higher scores indicating greater stress. Similarly, max HR, resting HR, and average HR were all significantly higher during the first study period compared with the second.
Despite higher strain during the first period, participants reported higher recovery scores and improved HRV during the second period, suggesting better physiological adaptation and resilience over time. Higher recovery scores indicate greater readiness to perform, while higher HRV is associated with improved autonomic balance and reduced stress levels. These findings suggest that while the initial phase of training was associated with higher strain, participants demonstrated enhanced recovery and stress management later in the fellowship.
For sleep metrics, the second study period was marked by significantly lower sleep performance, sleep duration, in bed duration, deep sleep duration, rapid eye movement duration, and sleep efficiency, while sleep debt was higher. However, sleep consistency improved during the second period, indicating more regular sleep patterns despite reductions in overall sleep quality.
Subjective and objective stress: correlation
The Spearman correlation between the difference in RMSSD and post-procedural STAI score was weak and negative (R = -0.13, P = .069), indicating a slight but statistically non-significant inverse relationship between RMSSD changes and anxiety levels. No statistically significant correlation was observed between the LF/HF ratio difference (procedural minus baseline LF/HF ratio) and the STAI score difference (post-procedural STAI score minus pre-procedural STAI score) (R = -0.015, P = .830) or the post-procedural STAI score (R = 0.01, P = .890). A statistically significant positive correlation was observed between the STAI score that was reported before the procedure and the STAI score reported after the end of the procedure (R = 0.76, P < .001) (Supplemental Figure).
Discussion
Our study provides insights into the stress experienced by IC fellows and attendings. The major findings of our study are that the intraprocedural HRV was significantly lower, indicating higher sympathetic activity (a) during a procedure compared with the baseline; (b) during complex compared with simple procedures, as defined by the operators; (c) during procedures that had a complication compared with uncomplicated procedures; (d) during emergency procedures compared with scheduled procedures; (e) when working as first operator compared with second operator; and (f) during the first months compared with the end of training; the resting HRV was significantly higher at the end of the training compared with the first months of training.
Compared with baseline, the significant increase in the LF/HF ratio during procedures suggests more sympathetic and less parasympathetic activation, indicating that IC procedures are acutely stressful for operators. This is consistent with findings from studies in other fields, such as surgery, where intraprocedural stress has also been shown to increase significantly during operations.25,26 A study of cardiac surgical residents found a higher LF/HF ratio (on average 6.7) while operating compared with non-surgical times (on average 3.8), which is consistent with other sympathetic activity markers.26 A recent observational study among 5 CTO operators found that CTO PCI was associated with significantly higher HR and blood pressure compared with regular work and non-CTO interventions.27
In our study, the LF/HF ratio was higher in complex procedures and those with complications, highlighting the increased autonomic demand placed on operators in more challenging clinical scenarios. The higher stress experienced during complex procedures is consistent with the cognitive and physical demands (eg, prolonged standing) of these cases. Several studies have shown that with increase of the cognitive load the HRV decreases.28,29 A study in laparoscopic surgery revealed that event rates like bleeding from needle puncturing vessel or burns from inadvertent touching of other structures were more common in higher stress quantiles (reflected by SDNN).30
Our results also revealed that stress levels were higher when participants were the primary operators compared with when they were assisting or teaching. The increased LF/HF ratio in these instances may reflect the greater responsibility and direct involvement in decision making during the procedure. This finding is consistent with prior studies in the field of surgery that suggested that stress is more pronounced for actual operators than for first assistants.31-33
Intraprocedural stress significantly decreased over the course of the fellowship, suggesting that operators become better in managing procedural stress as they gain experience and familiarity with their role. A cross-sectional study recruiting physicians performing lumbar puncture found that the pre- and post-performance stress reflected by the STAI scores was significantly higher in less experienced physicians compared with intermediate and expert physicians.34 Another study on the intraoperative stress of surgeons and assistants demonstrated that less experienced surgeons and assistants exhibit more stress during microsurgery.35 Similarly, attendings in our study also showed a reduction in stress as they worked with more experienced fellows. Given the small sample size of this pilot study, future studies with larger sample sizes are needed to further investigate the dynamics of stress reduction with experience.
An important secondary finding of our study is the significant improvement in resting HRV, as measured by the WHOOP wrist band, during the second study period. This increase in HRV, along with better recovery scores, suggests that participants recover from stress more quickly as their training progresses. Improved recovery metrics may reflect better autonomic balance and overall well-being. This aligns with the findings of Park et al,36 which showed that individuals with higher tonic HRV demonstrate better regulatory function and task performance under stress.
Despite improvements in HRV, sleep quality and duration were lower during the second study period. However, the improvement in sleep consistency suggests that even if the total sleep time was reduced, participants may have developed more regular sleep patterns. The decline in sleep quality may reflect increased workload and night shifts as fellows assumed greater responsibility. Additionally, circadian rhythm disruption due to long procedural days and call responsibilities may have contributed to this trend. Further research is needed to better understand the interplay between workload, stress adaptation, and sleep patterns in interventional cardiologists, as well as potential strategies to mitigate sleep disturbances and optimize recovery.
There are several potential explanations for the differences between fellows and attendings. Age-related changes37 could have affected the LF/HF ratio (mean age of fellows, SD: 34 ± 2 vs mean age of attendings, SD: 47 ± 8). However, because of the presence of several confounding factors and the limited sample size, direct comparisons between the 2 groups should be interpreted with caution.
The STAI questionnaire, a widely used tool for measuring state anxiety, represents subjective stress but does not capture physiological changes related to stress. The significant correlation between pre- and post-procedural STAI scores suggests that individuals who reported feeling anxious before the procedure often continued to experience high anxiety levels afterward. Despite the physiological changes observed in HRV, the lack of a strong correlation between the difference in HRV metrics and the STAI score indicates that subjective stress perception and objective physiological stress are not always aligned. Studies have shown conflicting results regarding the correlation between HRV and mental stress scores.4,6,38-40 In real-world settings, the association between HRV and perceived stress has been shown to be significant but small.41
Subjective or perceived stress is influenced by multiple factors, including individual resilience.42,43 Therefore, while HRV is a marker of autonomic activity, the STAI questionnaire captures the psychological experience during procedures.44 The complexity of the stress responses underscores the importance of addressing both perceived and physiological stress when designing and implementing interventions.
Limitations
Our study has limitations. The sample size was small, all the participants were male, and it was a single-center study, which may limit the generalizability of the findings and lead to selection bias. Some of the participants’ demographics were not disclosed to maintain confidentiality, which limits our ability to assess how other factors may have influenced the results. Moreover, while HRV is a well-established measure of autonomic function, it is influenced by factors that could not be controlled in this study. The range of procedural complexity, from diagnostic right heart catheterization to high-risk STEMI PCI, also represents a limitation of the current study.
Conclusions
Our findings highlight the significant physiological stress experienced by IC fellows and attendings during procedures, identifying key procedural characteristics that may be associated with increased stress. While stress levels decrease with experience, the high demands placed on ICs can contribute to long-term health risks. Interventions aimed at building resilience and promoting recovery should be explored further to improve the well-being and performance of IC professionals.
Affiliations and Disclosures
Michaella Alexandrou, MD1; Pedro E. P. Carvalho, MD1; Dimitrios Strepkos, MD1; Deniz Mutlu, MD1; Athanasios Rempakos, MD1; Olga Mastrodemos, BA1; Bavana V. Rangan, BDS, MPH1; Sandeep Jalli, DO1; Mario Goessl, MD, PhD1; Ahmed Al Ogaili, MD1; Konstantinos Voudris, MD1; Özgür Selim Ser, MD1; Muhammad Hamza Saad Shaukat, MD1; Gauravpal Singh Gill, MD1; Joe Jensen, MD1; Jaskanwal Deep Singh Sara, MD1; Maksymilian P. Opolski, MD2; Yader Sandoval, MD1; M. Nicholas Burke, MD1; Mark Linzer, MD3,4; Emmanouil S. Brilakis, MD, PhD1
From the 1Minneapolis Heart Institute and Minneapolis Heart Institute Foundation, Abbott Northwestern Hospital, Minneapolis, Minnesota; 2Department of Interventional Cardiology and Angiology, National Institute of Cardiology Warsaw, Warsaw, Poland; 3Department of Medicine, University of Minnesota, Minneapolis, Minnesota, USA; 4Institute for Professional Worklife, Hennepin Healthcare, Minneapolis, Minnesota.
Acknowledgments: The authors are grateful for the philanthropic support of our generous anonymous donors (2), and the philanthropic support of Drs. Mary Ann and Donald A Sens; Mrs. Diane and Dr. Cline Hickok; Mrs. Wilma and Mr. Dale Johnson; Mrs. Charlotte and Mr. Jerry Golinvaux Family Fund; the Roehl Family Foundation; the Joseph Durda Foundation; Ms. Marilyn and Mr. William Ryerse; Mr. Greg and Mrs. Rhoda Olsen. The generous gifts of these donors to the Minneapolis Heart Institute Foundation’s Science Center for Coronary Artery Disease (CCAD) helped support this research project.
Disclosures: Dr Opolski reports consulting/speaker honoraria from B.Braun, Boston Scientific, Siemens Healthineers, and Terumo; research support from B. Braun; and other (proctoring) from Asahi Intecc, Biotronik, Medtronic, Terumo, and Volcano. Dr Sandoval receives consulting/speaker honoraria from Abbott Diagnostics, Roche Diagnostics, Zoll, and Phillips; is an associate editor for JACC Advances; and holds patent 20210401347. Dr Burke receives consulting and speaker honoraria from Abbott Vascular and Boston Scientific. Dr Linzer reports grants from the American Medical Association, the National Institutes of Health, and the Agency for Healthcare Research and Quality; other support through his employer from the American College of Physicians, the Optum Office for Provider Advancement, the Institute for Healthcare Improvement, the American Board of Internal Medicine, Essentia Health, Gillette Children’s Specialty Healthcare, and the California Area Health Education Center outside the submitted work; and is a consultant for Harvard University on a grant assessing work conditions and diagnostic accuracy. Dr. Brilakis reports consulting/speaker honoraria from Abbott Vascular, American Heart Association (associate editor Circulation), Biotronik, Boston Scientific, Cardiovascular Innovations Foundation (Board of Directors), Cordis, CSI, Elsevier, GE Healthcare, Haemonetics, IMDS, Medtronic, SIS Medical, Teleflex, and Orbus Neich; research support: Boston Scientific, GE Healthcare; owner, Hippocrates LLC; shareholder: LifeLens Technologies, Inc, MHI Ventures, Cleerly Health, Stallion Medical, TrueVue Inc. The remaining authors report no financial relationships or conflicts of interest regarding the content herein.
Address for correspondence: Emmanouil S. Brilakis, MD, PhD, Minneapolis Heart Institute, 920 E 28th Street #300, Minneapolis, MN 55407, USA. Email: esbrilakis@gmail.com; X: @CCAD_MHIF, @esbrilakis, @m1chaella_alex
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