Prognostic implications of ultra-short heart rate variability indices in hospitalized patients with infective endocarditis

Shay Perek; Udi Nussinovitch; Neta Sagi; Yori Gidron; Ayelet Raz-Pasteur

doi:10.1371/journal.pone.0287607

. 2023 Jun 23;18(6):e0287607. doi: 10.1371/journal.pone.0287607

Prognostic implications of ultra-short heart rate variability indices in hospitalized patients with infective endocarditis

Shay Perek ^1,^2,³, Udi Nussinovitch ^4,⁵, Neta Sagi ⁶, Yori Gidron ⁷, Ayelet Raz-Pasteur ^1,^3,^*

Editor: Atnafu Mekonnen Tekleab⁸

PMCID: PMC10289432 PMID: 37352199

Abstract

Background

Infective endocarditis (IE) is a disease that poses a serious health risk. It is important to identify high-risk patients early in the course of their treatment. In the current study, we evaluated the prognostic value of ultra-short heart-rate variability (HRV), an index of vagal nerve activity, in IE.

Methods

Retrospective analysis was performed on adult patients admitted to a tertiary hospital due to IE. A logistic regression (LR) was used to determine whether clinical, laboratory, and HRV parameters were predictive of specific clinical features (valve type, staphylococcal infection) or severe short-term complications (cardiac, metastatic infection, and death). The accuracy of the model was evaluated through the measurement of the area under the curve (AUC) of the receiver operating characteristic curve (ROC). An analysis of survival was conducted using Cox regression. A number of HRV indices were calculated, including the standard deviation of normal heart-beat intervals (SDNN) and the root mean square of successive differences (RMSSD).

Results

75 patients, aged 60.3(±18.6) years old, were examined. When compared with published age- and gender-adjusted HRV norms, SDNN and RMSSD were found to be relatively low in our cohort (75%-76% lower than the median; 33%-41% lower than the 2^nd percentile). 26(34.6%) patients developed a metastatic infection, with RMSSD<7.03ms (adjusted odds ratio (aOR) 9.340, p = 0.002), incorporated in a multivariate LR model (AUC 0.833). Furthermore, 27(36.0%) patients were diagnosed with Staphylococcus IE, with SDNN<4.92ms (aOR 5.235, p = 0.004), a major component of the multivariate LR model (AUC 0.741). Multivariate Cox regression survival model, included RMSSD (HR 1.008, p = 0.012).

Conclusion

SDNN, and particularly RMSSD, derived from ultra-short ECG recordings, may provide prognostic information about patients presenting with IE.

Introduction

Infective endocarditis (IE) is associated with high mortality rates and severe complications, including embolic events, valvular destruction and arrhythmias [1]. Therefore, it is crucial to stratify patients’ risks at an early stage of their treatment. IE’s prognosis depends on clinical factors, lab testing, imaging findings, or a combination of them [2]. Several hematological, chemical, and inflammatory markers have been suggested for the evaluation of prognosis in patients with IE, including white blood cell count levels, C-reactive protein (CRP) levels, procalcitonin levels, neutrophil-lymphocyte ratios [3–5], in addition to complete blood count indices and N-terminal pro-B-type natriuretic peptide levels [6–8]. More complex assessments of cytokines and cell-derived macrovesicles may also have potential value in diagnosis and prognostication of IE patients [9–11]. Several studies have demonstrated that echocardiographic findings are effective predictors of mortality and embolic events [12]. Additionally, echo-guided decision-making for early surgery in IE patients has been shown to be a cost-effective management strategy [13]. Cardiac computed tomography may be an adjunctive test to echocardiography in patients with IE who are undergoing surgery [14].

While the majority of these methods are unavailable at the time of patient arrival, an electrocardiogram (ECG) is a routinely performed, non-invasive test, which is usually performed during the course of an emergency department (ED) visit. Electrocardiographic changes are prevalent in IE and are indicative of invasive disease, thereby have the ability to predict high morbidity and mortality [15]. Conduction abnormalities can also suggest that the disease is extending into the peri-valvular region [16] or signal the presence of complicated aortic valve disease [17, 18].

However, neuro-cardiac regulatory processes could also play a role in IE. The dynamic modulation of heart rate (HR) is considered a surrogate of the interaction between the sympathetic and parasympathetic nervous systems [19], and is quantified by the fluctuation or variability in the time intervals between normal heartbeats (i.e.; heart rate variability [HRV]). HRV decreases under stress, either emotional or physical, increases in rest and is considered an important noninvasive marker. It could be used to assess the function of the autonomic nervous system (ANS) as well as to determine if a cardiac response to autonomic modulation of heart rate is appropriate [20]. An inverse relation between HRV and inflammatory surrogates such as CRP has been established with 24 hour HRV. Moreover, HRV and CRP were found to have a synergistic effect in the prediction of death and myocardial infarction in ambulatory subjects with no apparent heart disease [21]. An increased mortality rate was associated with a lower HRV indices, calculated from short-term recordings, in patients with sepsis [22]. Similar findings were demonstrated in inflammatory bowel disease patients [23]. Interactions between autonomic innervation and immune responses are complex and intriguing. The vagus reflexively inhibits inflammation by activating the hypothalamic-pituitary-adrenal axis resulting with cortisol secretion [24]. Additionally, the vagus inhibits inflammation by a vagal-to-sympathetic innervation of the spleen, where unique T-cells signal macrophages to stop synthesizing pro-inflammatory cytokines [25]. In contrast to its anti-inflammatory role, vagus nerve stimulation could also increase cytotoxic T-cells, as well as natural killer cells [26].

Ultra short HRV analysis, focuses on computation of HRV indices from recordings lasting less than 5 minutes [27]. Several studies have demonstrated strong correlations between certain ultra-short HRV indices and parameters derived from longer HRV recordings, especially for time-domain indices [28–34]. Additionally, several ultra-short HRV parameters have been shown to be prognostic in patients admitted with various cardiac conditions. For instance, in patients with ST segment elevation myocardial infarction, reduced 10-second HRV has been found to be an independent predictor of all-cause mortality [35]. Ultra short HRV indices were also found to poses prognostic potential in COVID-19 [36], as well as in myocarditis patients [37]. Yet, there is little information available about the HRV response in IE patients. Low 24-hour HRV has been proposed as a method for IE complication marker [38]. Reports on ultra-short electrocardiographic markers for ANS dysfunction in IE are lacking. Our study thus aimed to evaluate the prognostic implications of ultra-short HRV indices derived from admission ECGs in patients with IE.

Materials and methods

Study design and population

This retrospective analysis is based on Rambam health care campus (RHCC; Haifa, Israel) patient medical records. This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Rambam Health Care Campus on 7 February 2017, number 0603-16-RMB. Since all the data was retrospectively collected, the IRB waived the need for individual informed consent. The following ICD-9-CM diagnosis codes were screened for: 421.0 (Acute and subacute bacterial endocarditis), 421.1 (Acute and subacute infective endocarditis in diseases classified elsewhere), 421.9 (Acute endocarditis, unspecified), 424.90 (Endocarditis, valve unspecified, unspecified cause), 424.91 (Endocarditis in diseases classified elsewhere), 424.99 (Other endocarditis, valve unspecified), 036.42 (Meningococcal endocarditis), 098.84 (Gonococcal endocarditis), 112.81 (Candidal endocarditis), 115.04 (Infection by Histoplasma capsulatum, endocarditis), 115.14) Infection by Histoplasma duboisii, endocarditis), and 115.94 (Histoplasmosis, unspecified, endocarditis).

All patients 18 years and older, who were diagnosed with IE based on the modified Duke criteria [39], between January 2010 and June 2015, were considered. Exclusion criteria included: missing ECG or HRV record from their ED visit, ECGs with irregular heartbeats (any non-sinus rhythm including atrial fibrillation or flutter, premature beats) or low resolution.

Data collection

All ED visits and hospital discharge letters from the study period, were screened for a diagnosis of IE, utilizing the MDClone (Beer-Sheva, Israel) computer software. This study included only patients who had undergone a 10-second resting ECG in the ED. In addition, all medical records were reviewed to identify and exclude potentially ineligible patients. Patients’ medical history (including IE risk factors), presenting symptoms (including clinical components of the modified Duke criteria), ED vital signs as well as laboratory results (i.e. complete blood count, chemistry panel and blood cultures), were collected. All echocardiography reports were studied, and disease specific findings, including valve dysfunction or rupture, peri-valvular abscess, as well as cardiac dysfunction were documented. Furthermore, date of death and IE disease specific complications were noted.

ECG analysis and computation of ultra-short HRV indices

Participating patients underwent a 10-second resting ECG (LAN Green model, Norav Medical, Yokneam, Israel), while lying motionless in a supine position for at least 30 seconds. The ECG electrodes were placed in anatomical positions according to standard procedure. An ECG viewing program was used to visualize the resting ECG files (Resting ECG version 5.62, Norav Medical), PR interval duration and QRS interval duration were automatically measured, and QT interval duration was calculated based on the Bazzett equation. Later, ECG files were analyzed with a custom version of the HRV analysis software able to import and analyze 10-second long recordings (HRV version 5.62, Norav Medical). These programs allowed for the automatic computation of HRV parameters. In addition, ECGs were manually checked and recordings with disturbances (e.g.; excessive noise, sudden baseline instability or low resolution), were excluded. ECGs which contained excessive premature ventricular or supraventricular activity (e.g.; atrial fibrillation, atrial flutter, atrial tachycardia) as well as advanced atrioventricular conduction abnormalities (e.g.; second degree atrioventricular blocks, complete heart block or other high degree AV conduction abnormalities) were also excluded. HRV linear time-domain variables (e.g.; standard deviation of RR intervals [SDNN] and root mean square successive differences [RMSSD]) were the focus of our study in light of their highest association with long-term recordings [33].

Endpoints and evaluated clinical features

The collected clinical features included age, gender, predispositions such as the presence of a prostatic valve, systolic and diastolic blood pressure (BP), resting heart rate, O2 saturation, core body temperature, white blood cells (WBC) count, circulatory levels of Neutrophils, Lymphocytes, Platelets, Hemoglobin and serum creatinine levels. The resting short-term resting heart rate has been shown to provide a crude estimate of the HRV parameters over a 5-minute period, although the effectiveness varies depending on the parameter measured [31].

Study outcomes included IE complications—cardiac complications (e.g.; new heart failure with reduced ejection fraction [HFrEF; based on echocardiographic findings], arrhythmia, abscess); metastatic infection (e.g.; emboli, abscess and mycotic aneurysm); and the need for valvular surgical intervention. As staphylococcus infection is considered a more severe condition [40], the eventual isolation of this pathogen was also examined as a study endpoint. In addition, survival analysis during the follow-up period was carried out.

Statistical analysis

The study database was analyzed with R software (version 4.0.3, The R Foundation for Statistical Computing, Vienna, Austria).

Descriptive statistics—continuous variables are presented as means with Standard Deviation (SD) or medians with interquartile range (IQR) and categorical variables are presented as percentages. Comparisons between groups were performed with Wilcoxon Rank Sum for continuous variables and Fisher’s exact test for categorical variables.

Ultra-short HRV indices for each patient in the study cohort were compared with published normal value ranges, corrected for age and gender [41].

Correlations between variables and Boolean outcomes were examined with logistic regressions (LR) and presented as odds ratio (OR) with 95% confidence intervals (95%CI) and p-values. LR was carried out after verification of compliance with relevant assumptions (e.g.; sufficiently large sample size, linearity of independent variables and log-odds, lack of strongly influential outliers and absence of multicollinearity). Variables found to have statistical significance (p-value<0.050) or trend (p-value<0.090) in univariate analyses, were introduced into a multivariate LR model, in a backward stepwise fashion. Multivariate model accuracy is presented with receiver operating characteristic (ROC) curves, including the area under the curve (AUC), with 95%CIs based on the bootstrapping method, as well as by the Hosmer and Lemeshow goodness-of-fit (HLGOF) and overall model p-value. HRV parameters were assessed as both continuous and Boolean variables (e.g. smaller than values corresponding to quartile 1 [Q1; 25^th percentile]). Survival analysis was carried out with univariate and multivariate Cox regression and presented as hazard ratios (HR) with 95%Cis and p-values.

Results

Study population

In the initial evaluation, 229 patients were included based on ICD codes that corresponded to IE diagnoses. Upon additional review of patients’ medical records, 45 patients were excluded as they did not fulfill the modified Duke criteria for IE diagnosis. An additional 75 patients did not have an ED ECG on the day of their admission to the hospital. 34 other patients had either a technically flawed ECG or an irregular rhythm. Thus, the final study sample included 75 patients, aged 60.3 (±18.6) years old. The majority (51, 68.0%) were men and 38 (50.7%) of the patients suffered from native valve IE.

Patient clinical, laboratory and electrocardiographic characteristics in patients with infected native and prosthetic valve, are presented in Table 1. Patients with prosthetic valve IE were significantly older, had lower heart rate, lower hemoglobin levels, longer PR interval and QTc. Notably, time domain HRV indices did not differ between native and prosthetic valve IE patients.

Table 1. Patient clinical, laboratory and electrocardiographic characteristics (native valve IE vs. prosthetic valve IE).

	Native valve IE (n = 38)	Prosthetic valve IE (n = 37)	p-value
Age (years)	53.5 (37.0–64.5)	73.0 (63.0–81.0)	<0.001^*
Male gender (%)	27 (71.0)	24 (64.8)	0.626
Emergency department vital signs
Systolic BP (mmHg)	129.0 (117.2–138.7)	126.0 (111.0–140.0)	0.622
Diastolic BP (mmHg)	72.5 (62.0–81.7)	67.0 (63.0–76.0)	0.138
Heart rate (bpm)	100.0 (90.0–116.7)	83.0 (77.0–96.0)	<0.001^*
Saturation (%)	96.0 (92.2–97.7)	96.0 (94.0–97.0)	0.864
Body temperature (°C)	37.0 (36.7–37.4)	36.9 (36.6–37.4)	0.413
Emergency department labs
WBC (×10⁹/L)	11.0 (8.6–15.2)	11.2 (9.3–14.3)	0.987
Hemoglobin (g/dL)	11.9 (10.5–13.1)	10.8 (10.0–11.7)	0.036^*
Platelets (×10⁹/L)	184.0 (122.5–265.0)	175 (144.0–228.7)	0.833
Creatinine (mg/dL)	1.1 (0.9–1.4)	1.3 (0.9–1.5)	0.337
ECG
PR interval (ms)	156.0 (143.0–181.0)	214.0 (168.0–250.0)	<0.001^*
QRS duration (ms)	90.0 (82.0–99.5)	94.0 (82.0–106.0)	0.487
QTc interval (ms)	421.0 (397.7–451.5)	453.0 (424.0–496.0)	0.004^*
HRV
SDNN (ms)	7.7 (4.6–21.6)	7.7 (5.4–19.6)	0.685
RMSSD (ms)	9.8 (6.9–24.6)	11.9 (7.4–33.7)	0.517

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median (IQR) or number (percentage of group)

BP–blood pressure; bpm–beats per minute; ECG–electrocardiography; SDNN—standard deviation of NN intervals; RMSSD—root mean square of successive RR interval differences; WBC–white blood cells; QTc–heart rate corrected QT interval

* P-value<0.05

HRV indices compared to published norms

HRV parameters were relatively low in the study cohort. Compared with published normal 10-second HRV values, corrected for age and gender [41], SDNN (median 7.72[ms], IQR 4.92[ms] -21.42[ms]) was found to be lower than median values in 57 (76.0%) patients, with 31 (41.3%) patients having SDNN values lower than the 2^nd percentile of their age and gender corrected range. As for RMSSD (median 11.8[ms], IQR 7.03[ms]– 28.18[ms]), 56 (74.6%) patients and 25 (33.3%) patients had values lower than age and gender corrected median and 2^nd percentile, respectively.

HRV indices and study outcomes

SDNN and RMSSD were found to be statistically significant lower in patients who developed HFrEF or metastatic infections. SDNN was also reduced (statistical trend) in patients ultimately diagnosed with Staphylococcus IE (Table 2). While analysis of HRV indices with regard to the development of a new arrhythmia yielded statistically insignificant results, stratification based on the type of arrhythmia (tachyarrhythmia vs. bradyarrhythmia) was also carried out. RMSSD in the tachyarrhythmia sub-group (median 65.0[ms], IQR 16.9[ms]-120.3[ms]) was high compared to RMSSD in the bradyarrhythmia sub-group (median 12.0[ms], IQR 5.6[ms]-16.7[ms]). Due to this heterogeneity, additional correlations were not conducted for this outcome.

Table 2. HRV indices with relation to study outcomes.

	Outcome		p-value
	HRrEF (n = 16)	No HRrEF (n = 59)
SDNN (ms)	5.0 (4.1–7.7)	8.8 (6.0–28.2)	0.017^*
RMSSD (ms)	7.6 (5.0–12.2)	12.1 (7.6–35.3)	0.023^*
	Peri-valvular Abscess (n = 8)	No Peri-valvular Abscess (n = 67)
SDNN (ms)	5.9 (3.8–9.0)	7.8 (5.2–23.3)	0.205
RMSSD (ms)	8.1 (3.9–11.8)	12.0 (7.4–32.0)	0.130
	Arrhythmia (n = 13)	No Arrhythmia (n = 62)
SDNN (ms)	7.7 (4.2–67.2)	7.7 (5.0–15.8)	0.623
RMSSD (ms)	12.5 (7.1–83.6)	11.4 (7.0–20.2)	0.450
	Metastatic Infection (n = 26)	No Metastatic Infection (n = 49)
SDNN (ms)	5.7 (4.0–13.1)	8.4 (6.4–23.4)	0.025^*
RMSSD (ms)	7.6 (4.6–20.2)	12.5 (8.2–33.7)	0.018^*
	Valvular Surgery (n = 21)	No Valvular Surgery (n = 54)
SDNN (ms)	6.9 (4.6–9.5)	8.2 (5.5–28.3)	0.304
RMSSD (ms)	8.3 (5.7–13.0)	11.9 (7.4–36.1)	0.293
	Staphylococcus Infection (n = 27)	No Staphylococcus Infection (n = 48)
SDNN (ms)	5.4 (4.0–11.7)	8.6 (6.3–23.2)	0.065^†
RMSSD (ms)	7.8 (5.2–17.4)	12.0 (8.0–31.2)	0.147

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median (IQR)

HFrEF–heart failure with reduced ejection fraction; SDNN—standard deviation of NN intervals; RMSSD—root mean square of successive RR interval differences

* P-value<0.05

† P-value<0.09

Heart failure with reduced ejection fraction

Six-teen patients (21.3%) were diagnosed with HFrEF, Univariate LR correlations are presented in Table 3. Patients who had developed HFrEF, were found to have higher heart rates on ED arrival as well as HRV in the lower quartile (SDNN<4.92ms, OR 4.36, p-value 0.014; RMSSD<7.03ms, OR 3.04, p-value 0.062). However, for predicting HFrEF, the multivariate LR model did not include any HRV parameter and was comprised of only initial heart rate on ED arrival (OR 1.05 [95%CI 1.01–1.08], p-value 0.002; ROC AUC 0.736).

Table 3. Development of new HFrEF–univariate logistic regression.

	Odds ratio	95% Confidence interval		p-value
	Odds ratio	Low	High	p-value
Age (years)	0.97	0.94	1.00	0.085^†
Male gender	2.39	0.61	9.36	0.209
Native valve	1.33	0.43	4.04	0.615
Systolic BP (mmHg)	0.99	0.97	1.02	0.863
Diastolic BP (mmHg)	0.98	0.93	1.03	0.589
Heart rate (bpm)	1.05	1.01	1.08	0.002^*
O2 saturation (%)	0.99	0.95	1.03	0.762
Body temperature (C°)	0.93	0.44	1.98	0.865
WBC (×10⁹/L)	1.06	0.96	1.17	0.195
Neutrophils (×10⁹/L)	1.06	0.96	1.18	0.207
Lymphocytes (×10⁹/L)	1.25	0.53	2.94	0.608
Hemoglobin (g/dL)	0.96	0.72	1.28	0.802
Platelets (×10⁹/L)	0.99	0.99	1.00	0.537
Creatinine (mg/dL)	1.88	0.80	4.38	0.141
SDNN (ms)	0.97	0.93	1.01	0.157
RMSSD (ms)	0.97	0.93	1.00	0.142
SDNN<4.92ms	4.36	1.34	14.18	0.014^*
RMSSD<7.03ms	3.04	0.94	9.85	0.062^†

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BP–blood pressure; bpm–beats per minute; SDNN—standard deviation of NN intervals; RMSSD—root mean square of successive RR interval differences; WBC–white blood cells

* P-value<0.05

† P-value<0.09

Metastatic infection

Twenty-six (34.6%) patients developed a metastatic infection during their index admission (23 metastatic emboli, 2 metastatic abscess and 1 –mycotic aneurysm). Patients who had been diagnosed with a metastatic infection, were found to be younger, with native valve IE, higher heart rate and body temperature on ED arrival and lower initial platelet levels. In addition, these patients had HRV in the lower quartile (SDNN<4.92ms, OR 3.75, p-value 0.016; RMSSD<7.03ms, OR 5.14, p-value 0.003), as described in Table 4. Multivariate LR model included 3 parameters: native valve IE (aOR 8.21 [95%CI 2.41–35.77], p-value 0.001), ED body temperature upon arrival (aOR 2.56 [95%CI 1.17–6.46], p-value 0.026) and RMSSD<7.03ms (aOR 9.34 [95% CI 2.46–44.67], p-value 0.002). Multivariate LR model ROC curve is presented in Fig 1. AUC was 0.83 (95%CI 0.74–0.92), with HLGOF p-value of 0.487 and overall model p-value <0.0001. Notably, RMSSD in the lower quartile had the strongest aOR in this multivariate classification model.

Table 4. Metastatic infection–univariate logistic regression.

	Odds ratio	95% Confidence interval		p-value
	Odds ratio	Low	High	p-value
Age (years)	0.97	0.94	0.99	0.033^*
Male gender	1.44	0.50	4.10	0.493
Native valve	5.74	1.94	16.93	0.001^*
Systolic BP (mmHg)	1.01	0.99	1.03	0.118
Diastolic BP (mmHg)	1.02	0.98	1.07	0.188
Heart rate (bpm)	1.02	1.00	1.05	0.031^*
O2 saturation (%)	0.99	0.96	1.03	0.959
Body temperature (C°)	2.10	1.06	4.17	0.032^*
WBC (×10⁹/L)	1.01	0.93	1.10	0.738
Neutrophils (×10⁹/L)	1.01	0.91	1.11	0.826
Lymphocytes (×10⁹/L)	0.79	0.36	1.74	0.571
Hemoglobin (g/dL)	1.09	0.86	1.40	0.448
Platelets (×10⁹/L)	0.99	0.98	0.99	0.049^*
Creatinine (mg/dL)	0.88	0.39	1.98	0.772
SDNN (ms)	0.98	0.96	1.00	0.177
RMSSD (ms)	0.99	0.97	1.00	0.210
SDNN<4.92ms	3.75	1.26	11.13	0.016^*
RMSSD<7.03ms	5.14	1.69	15.62	0.003^*

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BP–blood pressure; bpm–beats per minute; SDNN—standard deviation of NN intervals; RMSSD—root mean square of successive RR interval differences; WBC–white blood cells

* P-value<0.05

Valve surgery

Twenty-one (28.0%) IE patients required valvular surgery. HRV indices were not found to be correlated with the need for valve surgery, with only patient age found to have a statistically significant correlation (OR 0.96 (95%CI 0.93–0.99); p-value 0.017).

Staphylococcus IE

Twenty-seven (36.0%) patients were diagnosed with Staphylococcus IE. SDNN<4.92ms was found to have statistically significant univariate correlation with Staphylococcus IE (OR 4.68; p-value 0.006), as presented in Table 5. Multivariate LR model included 2 parameters: ED creatinine (aOR 2.47 [95%CI 1.08–6.29], p-value 0.039) and SDNN<4.92ms (aOR 5.23 [95%CI 1.70–17.49], p-value 0.004). Multivariate LR model ROC curve is presented in Fig 2. AUC was 0.741 (95%CI 0.622–0.860), with HLGOF p-value of 0.585 and overall model p-value 0.001. Noticeably, SDNN in the lower quartile had the strongest aOR in the multivariate classification model.

Table 5. Staphylococcus IE–univariate logistic regression.

	Odds ratio	95% Confidence interval		p-value
	Odds ratio	Low	High	p-value
Age (years)	0.99	0.96	1.01	0.473
Male gender	2.10	0.71	6.17	0.177
Native valve	1.35	0.52	3.50	0.525
Systolic BP (mmHg)	0.98	0.96	1.00	0.203
Diastolic BP (mmHg)	0.97	0.93	1.01	0.283
Heart rate (bpm)	1.01	0.99	1.04	0.164
O2 saturation (%)	0.98	0.94	1.02	0.349
Body temperature (C°)	1.53	0.81	2.87	0.183
WBC (×10⁹/L)	1.08	0.99	1.18	0.080^†
Neutrophils (×10⁹/L)	1.09	0.98	1.20	0.081^†
Lymphocytes (×10⁹/L)	0.53	0.22	1.22	0.140
Hemoglobin (g/dL)	0.89	0.69	1.15	0.391
Platelets (×10⁹/L)	0.99	0.99	1.00	0.694
Creatinine (mg/dL)	2.24	0.99	5.09	0.051^†
SDNN (ms)	1.00	0.98	1.01	0.943
RMSSD (ms)	1.00	0.99	1.01	0.754
SDNN<4.92ms	4.68	1.55	14.13	0.006^*
RMSSD<7.03ms	2.54	0.87	7.39	0.085^†

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BP–blood pressure; bpm–beats per minute; SDNN—standard deviation of NN intervals; RMSSD—root mean square of successive RR interval differences; WBC–white blood cells

* P-value<0.05

† P-value<0.09

Survival analysis

Forty-four patients (58.6%) died within the study follow-up period (median follow-up 5.06 years, IQR 0.20–8.84 years). SDNN (HR 1.01 [95%CI 1.00–1.02], p-value 0.010) and RMSSD (HR 1.00 [1.00–1.01], p-value 0.012) were both found to have univariate statistically significant Cox regression relations (Table 6).

Table 6. Survival analysis–univariate cox regression.

	Hazard ratio (95%CI)	p-value
Age (years)	1.02 (1.00–1.04)	0.014^*
Male gender	0.70 (0.37–1.32)	0.281
Native valve	0.78 (0.43–1.43)	0.435
Systolic BP (mmHg)	1.01 (0.99–1.02)	0.066^†
Diastolic BP (mmHg)	0.99 (0.96–1.02)	0.758
Heart rate (bpm)	1.00 (0.98–1.01)	0.646
Saturation (%)	0.98 (0.97–1.00)	0.071^†
Body temperature (°C)	1.02 (0.65–1.58)	0.929
WBC (×10⁹/L)	1.01 (0.96–1.06)	0.560
Neutrophils (×10⁹/L)	1.01 (0.96–1.07)	0.539
Lymphocytes (×10⁹/L)	0.37 (0.19–0.69)	0.001^*
Hemoglobin (g/dL)	0.80 (0.67–0.96)	0.018^*
Platelets (×10⁹/L)	0.99 (0.99–0.99)	0.030^*
Creatinine (mg/dL)	2.18 (1.46–3.25)	0.0001^*
SDNN (ms)	1.01 (1.00–1.02)	0.010^*
RMSSD (ms)	1.00 (1.00–1.01)	0.012^*

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BP–blood pressure; bpm–beats per minute; SDNN—standard deviation of NN intervals; RMSSD—root mean square of successive RR interval differences; WBC–white blood cells

* P-value<0.05

† P-value<0.09

Multivariate Cox regression survival model, included 3 parameters: ED hemoglobin (HR 0.79 [95%CI 0.66–0.95], p-value 0.014), ED creatinine (HR 2.13 [95%CI 1.38–3.28], p-value 0.0005), RMSSD (HR 1.00 [95%CI 1.00–1.01], p-value 0.012). An increase in HRV indices was found to be associated with reduced survival over time, in both univariate and multivariate analyses.

Discussion

In this retrospective study, we have demonstrated, for the first time, that the use of ultra-short time domain HRV indices, collected upon arrival to the ED, can predict morbidity and mortality in IE patients. HRV indices were found to be lower in our cohort, when compared with published age and gender adjusted norms. 75%-76% of patients had HRV values lower than median norms and 33%-41% were found to have HRV levels lower than the normal 2^nd percentile. The SDNN and the RMSSD are the primary time-domain measure used to estimate the vagally mediated changes reflected in HRV [42]. In our study, we have demonstrated independent associations between RMSSD, SDNN and IE complications as well as with survival. Of note, HRV indices did not differ significantly between patients with native versus prosthetic valve IE.

IE patients who had developed systemic emboli, were found to have lower RMSSD values upon their ED presentation. Low RMSSD has been established as a negative prognostic index in several patient populations. In a group of adult bone marrow transplant patients, the investigators observed a significant reduction in RMSSD prior to the clinical diagnosis and treatment of sepsis [43]. Similar findings regarding the prognostic role of RMSSD, have been demonstrated in oncologic [44, 45] and post myocardial infarction patients [46].

On the other hand, our study findings have demonstrated that an increase in RMSSD, as a continuous variable, is correlated with mortality over time. However, the magnitude of this association was weak. Several studies have shown correlations between high RMSSD and patient negative outcome, in other infectious diseases. An increased RMSDD, was documented in patients who developed septic shock within a few hours of presentation at the ED [47]. RMSDD was also found to be significantly increased among COVID-19 patients compared to healthy controls matched for age, gender and comorbidities [48]. Finally, in patients suffering from bacterial pneumonia, increased RMSSD obtained form 10-second ECGs has been associated with decreased survival [49].

In an analysis of HRV in patients undergoing peritoneal dialysis, higher RMSSD was associated with increased mortality [50]. Furthermore, in a large cohort of patients with chronic kidney disease, both very low and very high RMSDD were associated with increased risk for all-cause mortality [51]. These findings are in line with our observation that high RMSSD may predict a higher risk of death in patients with IE. The common factor in all these studies, may be that patients with high vagal activity at arrival to the hospital, could already have an infectious or inflammatory condition, to which the cholinergic anti-inflammatory vagus may respond. It is possible that, in the context of an infectious disease, sub-clinically elevated inflammation could cause an increase in vagal activity, indexed by high HRV, to activate the cholinergic anti-inflammatory reflex, and such a compensatory increase in HRV in such contexts, may then predict poor prognosis in infectious diseases such as IE. However, given our relatively small sample size and the small effect size of this HRV-survival relation, this requires replication in larger studies, together with testing this proposed compensation mechanism.

Low SDNN values were correlated with Staphylococcal IE, in both univariate and multivariate LR classification. Staphylococcal infection has been identified as a risk factor for embolic events in IE [52]. In our study, we have demonstrated the association between low HRV indices and both embolic events and Staphylococcal IE, indicating these known reciprocal relations may be identified by HRV parameters.

Similar to our findings, low SDNN has also been correlated with infectious disease complications. In children diagnosed with viral myocarditis, lower SDNN predicted the development of ventricular arrhythmia [53].

Echocardiography has a significant role in the risk stratification of endocarditis patients, by providing information correlated with negative outcomes, such as a large vegetation, para-valvular infection, signs of increased left-cavities filling pressures, pulmonary hypertension and low left ventricular ejection fraction [54]. At admission, early assessment of prognosis is critical and has the ability to identify high risk patients, who may need closer monitoring, require more aggressive treatment (e.g. early surgery) and who may benefit from more frequent follow-up assessments. Serial echocardiographic examinations allow close follow up of endocarditis patients during antibiotic therapy and after disease resolution. Echocardiogram frequency and type depend on the clinical presentation, the involved pathogen and initial echocardiographic findings on admission [55].

In addition to echocardiography, PET-CT is another tool which has recently been established for the diagnosis and follow up of IE, and can assist the early detection of its complications such as systemic embolism [56]. Following our research, we suggest considering more frequent echocardiography studies, as well as early PET-CT for endocarditis patients, with HRV indices associated with high risk of uncontrolled infection, systemic embolism, heart failure and increased mortality, regardless of their clinical condition.

The results of our study indicate a simple and readily available prognostic factor, namely HRV, which can be simply derived from brief 10-seconds ECGs or even from fingertip photo-plethysmography sensors. Nonetheless, this study has limitations, which are related to its retrospective cohort design and also to its possible selection bias. Several patients were excluded from our analysis due to incorrect IE diagnosis and missing or inadequate ECGs. By only including patients with IE diagnosis based on the fulfilment of the Duke criteria with a high-quality ECG tracing of regular cardiac rhythm, we created a smaller yet more accurate IE patient cohort with valid ultra-short HRV indices. By focusing on patients enrolled in a tertiary referral medical center for 5.5 years and applying various statistical tests, which included adjustment for confounders, we have attempted to limit the consequences of a potential selection bias. In spite of this, we cannot predict if a larger study and a longer follow-up period would provide different results, and as such, future research should be conducted to address this question.

In addition, we included ultra-short ECGs for measuring HRV. These could not enable us to derive reliably the frequency-domain parameters of HRV, such as high frequency and low frequency HRV, which could potentially have additional prognostic value in IE. Furthermore, the exact length of time the patients laid down in a supine position prior to undergoing ECG is unknown. Nonetheless, even short stabilization periods prior to HRV assessment may be acceptable, especially in younger, healthier patients [57] and in static conditions [58] (similar to the setting in our study). Finally, due to the relatively small sample, a stratification to native and prosthetic valve IE did not yield significant results. Future prospective studies should address these issues, in order to validate our findings. Following our research, we suggest to consider more frequent radiographic studies (e.g.; PET-CT, echocardiogram) for endocarditis patients, with HRV indices associated with high risk of uncontrolled infection, systemic embolism and increased mortality, regardless of their clinical condition.

Conclusions

Time domain ultra-short HRV indices based on ECG, carried out upon ED arrival, have the potential to allow for early risk stratification, in IE patients. Our findings should be validated, prior to implementation in patient management strategies.

Data Availability

The dataset generated and analyzed during the current study are available in the figshare repository, https://doi.org/10.6084/m9.figshare.21679742.v1.

Funding Statement

The authors received no specific funding for this work.

References

1.Habib G, Lancellotti P, Antunes MJ, Bongiorni MG, Casalta J-P, Del Zotti F, et al. 2015 ESC Guidelines for the management of infective endocarditis: The Task Force for the Management of Infective Endocarditis of the European Society of Cardiology (ESC). Endorsed by: European Association for Cardio-Thoracic Surgery (EACTS), the European. European heart journal. 2015;36(44):3075–3128. doi: 10.1093/eurheartj/ehv319 [DOI] [PubMed] [Google Scholar]
2.Wei X-B, Su Z-D, Liu Y-H, Wang Y, Huang J-L, Yu D-Q, et al. Age, creatinine and ejection fraction (ACEF) score: a simple risk-stratified method for infective endocarditis. QJM: monthly journal of the Association of Physicians. 2019;112(12):900–906. doi: 10.1093/qjmed/hcz191 [DOI] [PubMed] [Google Scholar]
3.Tascini C, Aimo A, Arzilli C, Sbrana F, Ripoli A, Ghiadoni L, et al. Procalcitonin, white blood cell count and C-reactive protein as predictors of S. aureus infection and mortality in infective endocarditis. International journal of cardiology. 2020;301:190–194. doi: 10.1016/j.ijcard.2019.08.013 [DOI] [PubMed] [Google Scholar]
4.Mohanan S, Gopalan Nair R, Vellani H, C G S, George B, M N K. Baseline C-reactive protein levels and prognosis in patients with infective endocarditis: A prospective cohort study. Indian heart journal. 2018;70 Suppl 3(Suppl 3):S43–S49. doi: 10.1016/j.ihj.2018.05.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Chen Y, Ye L-J, Wu Y, Shen B-Z, Zhang F, Qu Q, et al. Neutrophil-Lymphocyte Ratio in Predicting Infective Endocarditis: A Case-Control Retrospective Study. Mediators of inflammation. 2020;2020:8586418. doi: 10.1155/2020/8586418 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Ferrera C, Vilacosta I, Fernández C, López J, Sarriá C, Olmos C, et al. Usefulness of thrombocytopenia at admission as a prognostic marker in native valve left-sided infective endocarditis. The American journal of cardiology. 2015;115(7):950–955. doi: 10.1016/j.amjcard.2015.01.021 [DOI] [PubMed] [Google Scholar]
7.Tok D, Canpolat U, Tok D, Turak O, İşleyen A, Öksüz F, et al. Association of mean platelet volume level with in-hospital major adverse events in infective endocarditis. Wiener klinische Wochenschrift. 2015;127(5–6):197–202. doi: 10.1007/s00508-015-0746-2 [DOI] [PubMed] [Google Scholar]
8.Kahveci G, Bayrak F, Mutlu B, Bitigen A, Karaahmet T, Sonmez K, et al. Prognostic value of N-terminal pro-B-type natriuretic peptide in patients with active infective endocarditis. The American journal of cardiology. 2007;99(10):1429–1433. doi: 10.1016/j.amjcard.2006.12.071 [DOI] [PubMed] [Google Scholar]
9.Araújo IR, Ferrari TCA, Teixeira-Carvalho A, Campi-Azevedo AC, Rodrigues LV, Guimarães Júnior MH, et al. Cytokine Signature in Infective Endocarditis. PloS one. 2015;10(7):e0133631. doi: 10.1371/journal.pone.0133631 [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Ris T, Teixeira-Carvalho A, Coelho RMP, Brandao-de-Resende C, Gomes MS, Amaral LR, et al. Inflammatory biomarkers in infective endocarditis: machine learning to predict mortality. Clinical and experimental immunology. 2019;196(3):374–382. doi: 10.1111/cei.13266 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Guimarães Júnior MH, Ferrari TCA, Teixeira-Carvalho A, Moreira M de L, de Souza Santos LJ, Costa-Silva MF, et al. Cell-derived microvesicles in infective endocarditis: Role in diagnosis and potential for risk stratification at hospital admission. The Journal of infection. 2019;79(2):101–107. doi: 10.1016/j.jinf.2019.06.005 [DOI] [PubMed] [Google Scholar]
12.Thuny F, Di Salvo G, Belliard O, Avierinos J-F, Pergola V, Rosenberg V, et al. Risk of embolism and death in infective endocarditis: prognostic value of echocardiography: a prospective multicenter study. Circulation. 2005;112(1):69–75. doi: 10.1161/CIRCULATIONAHA.104.493155 [DOI] [PubMed] [Google Scholar]
13.Liao L, Kong DF, Samad Z, Pappas PA, Jollis JG, Lin SS, et al. Echocardiographic risk stratification for early surgery with endocarditis: a cost-effectiveness analysis. Heart (British Cardiac Society). 2008;94(5):e18. doi: 10.1136/hrt.2006.106716 [DOI] [PubMed] [Google Scholar]
14.Wang TKM, Bin Saeedan M, Chan N, Obuchowski NA, Shrestha N, Xu B, et al. Complementary Diagnostic and Prognostic Contributions of Cardiac Computed Tomography for Infective Endocarditis Surgery. Circulation. Cardiovascular imaging. 2020;13(9):e011126. doi: 10.1161/CIRCIMAGING.120.011126 [DOI] [PubMed] [Google Scholar]
15.Meine TJ, Nettles RE, Anderson DJ, Cabell CH, Corey GR, Sexton DJ, et al. Cardiac conduction abnormalities in endocarditis defined by the Duke criteria. American heart journal. 2001;142(2):280–285. doi: 10.1067/mhj.2001.116964 [DOI] [PubMed] [Google Scholar]
16.Miyamoto MI, Hutter AMJ, Blum JH, Torchiana DF. Cardiac conduction abnormalities preceding transoesophageal echocardiographic evidence of perivalvar extension of infection in a case of Salmonella prosthetic valve endocarditis. Heart (British Cardiac Society). 1997;78(4):416–418. doi: 10.1136/hrt.78.4.416 [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Berk WA. Electrocardiographic findings in infective endocarditis. The Journal of emergency medicine. 1988;6(2):129–132. doi: 10.1016/0736-4679(88)90153-9 [DOI] [PubMed] [Google Scholar]
18.Kohli U, Obuobi S, Addetia K, Ota T, Nayak HM. PR interval prolongation is significantly associated with aortic root abscess: An age- and gender-matched study. Annals of noninvasive electrocardiology: the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc. 2021;26(4):e12849. doi: 10.1111/anec.12849 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Pecchia L, Castaldo R, Montesinos L, Melillo P. Are ultra-short heart rate variability features good surrogates of short-term ones? State-of-the-art review and recommendations. Healthcare technology letters. 2018;5(3):94–100. doi: 10.1049/htl.2017.0090 [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Dekker JM, Crow RS, Folsom AR, Hannan PJ, Liao D, Swenne CA, et al. Low heart rate variability in a 2-minute rhythm strip predicts risk of coronary heart disease and mortality from several causes: the ARIC Study. Atherosclerosis Risk In Communities. Circulation. 2000;102(11):1239–1244. doi: 10.1161/01.cir.102.11.1239 [DOI] [PubMed] [Google Scholar]
21.Sajadieh A, Nielsen OW, Rasmussen V, Hein HO, Hansen JF. C-reactive protein, heart rate variability and prognosis in community subjects with no apparent heart disease. Journal of internal medicine. 2006;260(4):377–387. doi: 10.1111/j.1365-2796.2006.01701.x [DOI] [PubMed] [Google Scholar]
22.de Castilho FM, Ribeiro ALP, Nobre V, Barros G, de Sousa MR. Heart rate variability as predictor of mortality in sepsis: A systematic review. PloS one. 2018;13(9):e0203487. doi: 10.1371/journal.pone.0203487 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Kim K-N, Yao Y, Ju S-Y. Heart rate variability and inflammatory bowel disease in humans: A systematic review and meta-analysis. Medicine. 2020;99(48):e23430. doi: 10.1097/MD.0000000000023430 [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Tracey KJ. Reflex control of immunity. Nature reviews. Immunology. 2009;9(6):418–428. doi: 10.1038/nri2566 [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Rosas-Ballina M, Olofsson PS, Ochani M, Valdés-Ferrer SI, Levine YA, Reardon C, et al. Acetylcholine-synthesizing T cells relay neural signals in a vagus nerve circuit. Science (New York, N.Y.). 2011;334(6052):98–101. doi: 10.1126/science.1209985 [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Mihaylova S, Schweighöfer H, Hackstein H, Rosengarten B. Effects of anti-inflammatory vagus nerve stimulation in endotoxemic rats on blood and spleen lymphocyte subsets. Inflammation research: official journal of the European Histamine Research Society… [et al.]. 2014;63(8):683–690. doi: 10.1007/s00011-014-0741-5 [DOI] [PubMed] [Google Scholar]
27.Malik M, Camm AJ, Bigger JT, Breithardt G, Cerutti S, Cohen RJ, et al. Heart rate variability. Standards of measurement, physiological interpretation, and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. European Heart Journal. 1996:354–81. doi: 10.1093/oxfordjournals.eurheartj.a014868 [DOI] [PubMed] [Google Scholar]
28.Shaffer F, Ginsberg JP. An Overview of Heart Rate Variability Metrics and Norms. Frontiers in public health. 2017;5:258. doi: 10.3389/fpubh.2017.00258 [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Baek HJ, Cho CH, Cho J, Woo JM. Reliability of ultra-short-term analysis as a surrogate of standard 5-min analysis of heart rate variability. Telemedicine and e-Health. 2015;21(5):404–414. doi: 10.1089/tmj.2014.0104 [DOI] [PubMed] [Google Scholar]
30.Munoz ML, Van Roon A, Riese H, Thio C, Oostenbroek E, Westrik I, et al. Validity of (Ultra-)Short recordings for heart rate variability measurements. PLoS ONE. 2015;10(9). doi: 10.1371/journal.pone.0138921 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Nussinovitch U, Elishkevitz KP, Kaminer K, Nussinovitch M, Segev S, Volovitz B, et al. The efficiency of 10-second resting heart rate for the evaluation of short-term heart rate variability indices. PACE—Pacing and Clinical Electrophysiology. 2011;34(11):1498–1502. doi: 10.1111/j.1540-8159.2011.03178.x [DOI] [PubMed] [Google Scholar]
32.Politi K, Kaminer K, Nussinovitch U. Reliability of ultrashort electrocardiographic indices in hypertension: The quest for a clinically applicable prognostic marker. Journal of Investigative Medicine. 2020. doi: 10.1136/jim-2019-001106 [DOI] [PubMed] [Google Scholar]
33.Nussinovitch U. Reliability of ultra-short indices for autonomic dysfunction in dyslipidemia. Clinical physiology and functional imaging. 2020;40(6):423–433. doi: 10.1111/cpf.12661 [DOI] [PubMed] [Google Scholar]
34.Nussinovitch U, Cohen O, Kaminer K, Ilani J, Nussinovitch N. Evaluating reliability of ultra-short ECG indices of heart rate variability in diabetes mellitus patients. Journal of Diabetes and its Complications. 2012;26(5):450–453. doi: 10.1016/j.jdiacomp.2012.05.001 [DOI] [PubMed] [Google Scholar]
35.Karp E, Shiyovich A, Zahger D, Gilutz H, Grosbard A, Katz A. Ultra-short-term heart rate variability for early risk stratification following acute st-elevation myocardial infarction. Cardiology. 2009;114(4):275–283. doi: 10.1159/000235568 [DOI] [PubMed] [Google Scholar]
36.Mol MBA, Strous MTA, van Osch FHM, Vogelaar FJ, Barten DG, Farchi M, et al. Heart-rate-variability (HRV), predicts outcomes in COVID-19. PloS one. 2021;16(10):e0258841. doi: 10.1371/journal.pone.0258841 [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Perek S, Nussinovitch U, Cohen R, Gidron Y, Raz-Pasteur A. Ultra Short Heart Rate Variability Predicts Clinical Outcomes in Patients with a Clinical Presentation Consistent with Myocarditis: A Derivation Cohort Analysis. Journal of clinical medicine. 2022;12(1). doi: 10.3390/jcm12010089 [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Feaktsistava N, Sujayeva V, Sudzhaeva S. The significance of cardiac rhythm variability value assessment in partients with infective endocarditis. E Journal of Cardiovascular Medicine. 2013;1(2):32–35. doi: 10.15511/ejcm.13.00232 [DOI] [Google Scholar]
39.Li JS, Sexton DJ, Mick N, Nettles R, Fowler VG, Ryan T, et al. Proposed Modifications to the Duke Criteria for the Diagnosis of Infective Endocarditis. Clin Infect Dis. 2000;April(30(4)):633–638. doi: 10.1086/313753 [DOI] [PubMed] [Google Scholar]
40.Liesenborghs L, Meyers S, Lox M, Criel M, Claes J, Peetermans M, et al. Staphylococcus aureus endocarditis: distinct mechanisms of bacterial adhesion to damaged and inflamed heart valves. European heart journal. 2019;40(39):3248–3259. doi: 10.1093/eurheartj/ehz175 [DOI] [PMC free article] [PubMed] [Google Scholar]
41.van den Berg ME, Rijnbeek PR, Niemeijer MN, Hofman A, Herpen G van Bots ML, et al. Normal values of corrected heart-rate variability in 10-second electrocardiograms for all ages. Frontiers in Physiology. 2018;9(4):424. doi: 10.3389/fphys.2018.00424 [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Shaffer F, McCraty R, Zerr CL. A healthy heart is not a metronome: an integrative review of the heart’s anatomy and heart rate variability. Frontiers in Psychology. 2014;5(September):1–19. doi: 10.3389/fpsyg.2014.01040 [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Ahmad S, Tejuja A, Newman KD, Zarychanski R, Seely AJ. Clinical review: a review and analysis of heart rate variability and the diagnosis and prognosis of infection. Critical care (London, England). 2009;13(6):232. doi: 10.1186/cc8132 [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Hu S, Lou J, Zhang Y, Chen P. Low heart rate variability relates to the progression of gastric cancer. World Journal of Surgical Oncology. 2018;16(1):1–5. doi: 10.1186/s12957-018-1348-z [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Gidron Y, De Couck M, Schallier D, De Greve J, Van Laethem JL, Maréchal R. The relationship between a new biomarker of vagal neuroimmunomodulation and survival in two fatal cancers. Journal of Immunology Research. 2018;2018. doi: 10.1155/2018/4874193 [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Hayano J, Ueda N, Kisohara M, Yuda E, Carney RM, Blumenthal JA. Survival Predictors of Heart Rate Variability After Myocardial Infarction With and Without Low Left Ventricular Ejection Fraction. Frontiers in neuroscience. 2021;15:610955. doi: 10.3389/fnins.2021.610955 [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Wee BYH, Lee JH, Mok YH, Chong S-L. A narrative review of heart rate and variability in sepsis. Annals of translational medicine. 2020;8(12):768. doi: 10.21037/atm-20-148 [DOI] [PMC free article] [PubMed] [Google Scholar]
48.Kaliyaperumal D, Rk K, Alagesan M, Ramalingam S. Characterization of cardiac autonomic function in COVID-19 using heart rate variability: a hospital based preliminary observational study. Journal of basic and clinical physiology and pharmacology. 2021;32(3):247–253. doi: 10.1515/jbcpp-2020-0378 [DOI] [PubMed] [Google Scholar]
49.Izhaki N, Perek S, Agbaria M, Raz-Pasteur A. Ultrashort Heart Rate Variability for Early Risk Stratification in Pneumonia Patients: Preliminary Analysis. The Israel Medical Association journal: IMAJ. 2022;24(11):741–746. [PubMed] [Google Scholar]
50.Pei J, Tang W, Li L-X, Su C-Y, Wang T. Heart rate variability predicts mortality in peritoneal dialysis patients. Renal failure. 2015;37(7):1132–1137. doi: 10.3109/0886022X.2015.1061729 [DOI] [PubMed] [Google Scholar]
51.Drawz PE, Babineau DC, Brecklin C, He J, Kallem RR, Soliman EZ, et al. Heart rate variability is a predictor of mortality in chronic kidney disease: a report from the CRIC Study. American journal of nephrology. 2013;38(6):517–528. doi: 10.1159/000357200 [DOI] [PMC free article] [PubMed] [Google Scholar]
52.Habib G. Management of infective endocarditis. Heart (British Cardiac Society). 2006;92(1):124–130. doi: 10.1136/hrt.2005.063719 [DOI] [PMC free article] [PubMed] [Google Scholar]
53.Ling N, Li CL, Wang ZZ, Zhang HN, Xu H, An XJ. Heart rate variability in children with myocarditis presenting with ventricular arrhythmias. European Review for Medical and Pharmacological Sciences. 2018;22(4):1102–1105. doi: 10.26355/eurrev_201802_14397 [DOI] [PubMed] [Google Scholar]
54.Thuny F, Grisoli D, Collart F, Habib G, Raoult D. Management of infective endocarditis: challenges and perspectives. Lancet (London, England). 2012;379(9819):965–975. doi: 10.1016/S0140-6736(11)60755-1 [DOI] [PubMed] [Google Scholar]
55.Habib G, Badano L, Tribouilloy C, Vilacosta I, Zamorano JL, Galderisi M, et al. Recommendations for the practice of echocardiography in infective endocarditis. European journal of echocardiography: the journal of the Working Group on Echocardiography of the European Society of Cardiology. 2010;11(2):202–219. doi: 10.1093/ejechocard/jeq004 [DOI] [PubMed] [Google Scholar]
56.Pelletier-Galarneau M, Abikhzer G, Harel F, Dilsizian V. Detection of Native and Prosthetic Valve Endocarditis: Incremental Attributes of Functional FDG PET/CT over Morphologic Imaging. Current cardiology reports. 2020;22(9):93. doi: 10.1007/s11886-020-01334-w [DOI] [PubMed] [Google Scholar]
57.Krejčí J, Botek M MA. Stabilization period before capturing an ultra- short vagal index can be shortened to 60 s in endurance athletes and to 90 s in university students. PloS one. 2018;Oct 8(13(10)):e0205115. doi: 10.1371/journal.pone.0205115 [DOI] [PMC free article] [PubMed] [Google Scholar]
58.Kim JW, Seok HS, Shin H. Is Ultra-Short-Term Heart Rate Variability Valid in Non-static Conditions? Frontiers in physiology. 2021;12(3):596060. doi: 10.3389/fphys.2021.596060 [DOI] [PMC free article] [PubMed] [Google Scholar]

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Reviewer #2: Partly

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Reviewer #2: Yes

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Reviewer #1: Dear Authors,

I compliment on your innovative work. Namely, as yourself declare, this is the first paper that addresses the topic of HRV as a prognosticator in patients with infective endocarditis.

A MEDLINE search yielded no results specifically on this topic, although there are published studies of HRV in other infectious and inflammatory conditions.

The other point of discussion is that you are using an ultra short HRV of 10 seconds, which is also a less frequently analyzed method when talking about HRV, where the most commonly published results for time domain analyzes are 5 minute SDNN analyses.

Given the structure of the written manuscript, after the clear introduction and nicely described pathophysiological mechanism of the role of the vagus in HRV mechanisms, as well as the clearly described methodology, the results section is a bit difficult to follow. There is no decisive statement for which of the monitored outcomes multivariate analysis is performed and for which not (due to the insufficient number of detected univariate predictors). It is necessary to read the text two or three times to understand it. The etiology (Staphylococcus) is not a subsequent outcome, but a feature that you have taken as a predictor that should be clearly emphasized.

Regarding the statistical power of the analyzed data, the insufficiency of the identified univariate predictors is a consequence of the small number of subjects (for such a strong analysis), and the small number of outcomes, especially perivalvular abscess-8 patients.

It is also debatable to create multivariate models consisting of only two variables (staphylococcal infection), or 3 variables (metastatic infection).

This observation of mine is best seen in the fatal outcome section where you have a powerful analysis, and where the debatable points about the statistical power of the analysis that I mentioned in the previous section are overcome. This is the strongest part of your manuscript.

Suggestion!

Please consider regrouping the outcomes (perivalvular abscess and metastatic infection basically have the same underlying mechanism - disseminated inflammation/infection!!!)

Finally, go through the text again for small typos, and pay attention to the brackets, they are not clearly placed. Use two types of brackets.

Reviewer #2: The research does try to add a new and easy way of assessing prognosis in IE patients in the way of HRV indices. However, I doubt its clinical application in the near future. Sample size is small as the authors state, and this will definitely affects the observed findings. I recommend major revision or explanation in the following areas:

1. More than half of IE patients were excluded. There is heavy selection bias, and I am concerned on the reliability & applicability of the findings presented.

2. The data analysis needs to be looked at again. Unlike what was described in the methods of data analysis, HRV parameters are instead presented using median values (not means), suggesting a skewed data. Sample size is small and data appears skewed, hence parametric tests such as Logistic regression may not be appropriate.

3. There appears some contradictory findings that are not fully explained. On one hand, lower HRV indices show predictive value in metastatic infections and Staph infection, and on the other increase in HRV predicts arrhythmic complications and mortality. Please explain.

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Reviewer #1: Yes: Marija Vavlukis

Reviewer #2: No

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PLoS One. 2023 Jun 23;18(6):e0287607. doi: 10.1371/journal.pone.0287607.r002

Author response to Decision Letter 0

3 Jun 2023

Prof. Emily Chenette

Editor-in-chief, PLOS One

Re: PONE-D-23-02781

Thank you for your email of April 14, 2023, informing us that you are willing to reconsider acceptance of our paper for publication subject to revisions recommended by the reviewers.

Enclosed please find our revised manuscript entitled “Prognostic implications of ultra-short heart rate variability indices in hospitalized patients with infective endocarditis” by Shay Perek et al., marked with the changes made (as well as a clean version of the manuscript), and our detailed reply to the reviewers’ comments.

We hope the paper will now be considered suitable for publication. Our point-by-point response to the reviewer's remarks is outlined below.

Sincerely yours,

A. Raz-Pasteur, MD

Clinical Assistant Professor

Director, Internal Medicine 'A' Department

Rambam Health Care Campus

POB 9602 Haifa, Israel

Tel: 972-4-7773106

Fax: 972-4-7772721

E-mail: a_raz@rambam.health.gov.il

Editor:

Remark: As stated by both reviewers, please make sure that the statistical method is suitable for the nature of the data at hand and also please revise the result and discussion sections accordingly.

Response: Clarifications and corrections have been made to the methods, results and discussion sections.

Remark: Also, please highlight the implications of your findings.

Response: Following the mentioned corrections, our study provides insight into the use of ultra-short HRV indices as prognostic markers in infective endocarditis.

Remark: Please ensure that your manuscript meets PLOS ONE's style requirements

Response: The manuscript has been reviewed and the layout has been verified to be in accordance with the style requirements.

Remark: We noticed you have some minor occurrence of overlapping text with the following previous publication(s), which needs to be addressed: https://www.mdpi.com/2077-0383/12/1/89/html

Response: Considerable revisions have been made to the few paragraphs that shared similarities with our previous paper, published in the Journal of Clin. Med.

Remark: Your ethics statement should only appear in the Methods section of your manuscript. If your ethics statement is written in any section besides the Methods, please move it to the Methods section and delete it from any other section.

Response: Ethics statements have been removed from the 'Statements and Declarations' section and are now included in the Method section only.

Reviewer 1

Remark: …after the clear introduction and nicely described pathophysiological mechanism of the role of the vagus in HRV mechanisms, as well as the clearly described methodology, the results section is a bit difficult to follow. There is no decisive statement for which of the monitored outcomes multivariate analysis is performed and for which not (due to the insufficient number of detected univariate predictors). It is necessary to read the text two or three times to understand it.

Response: The results section has been changed with an emphasis on logistic regression analysis for three outcomes (e.g.; heart failure with reduced ejection fraction, metastatic infection, Staphylococcal infection) as well as survival analysis.

Remark: The etiology (Staphylococcus) is not a subsequent outcome, but a feature that you have taken as a predictor that should be clearly emphasized.

Response: A change has been made to the results section to clarify that the likelihood of developing Staphylococcal infection was estimated not as an outcome, but rather as a clinical feature generally associated with a more severe illness.

Remark: Regarding the statistical power of the analyzed data, the insufficiency of the identified univariate predictors is a consequence of the small number of subjects (for such a strong analysis), and the small number of outcomes, especially perivalvular abscess-8 patients.

It is also debatable to create multivariate models consisting of only two variables (staphylococcal infection), or 3 variables (metastatic infection). This observation of mine is best seen in the fatal outcome section where you have a powerful analysis, and where the debatable points about the statistical power of the analysis that I mentioned in the previous section are overcome. This is the strongest part of your manuscript.

Please consider regrouping the outcomes (perivalvular abscess and metastatic infection basically have the same underlying mechanism - disseminated inflammation/infection!!!)

Response: The corrected results section includes logistic regression analysis only for outcomes with sufficient amount of observations. In case of a small number of subjects (e.g.; perivalvular abscess), only descriptive statistics is provided.

Remark: Finally, go through the text again for small typos, and pay attention to the brackets, they are not clearly placed. Use two types of brackets.

Response: We appreciate the reviewer's comments. Numerous sentences were revised, and the manuscript was screened for typos.

Reviewer 2:

Remark: Sample size is small as the authors state, and this will definitely affect the observed findings. More than half of IE patients were excluded. There is heavy selection bias, and I am concerned on the reliability & applicability of the findings presented.

Response: In response to the reviewer's concern and to discuss the possible implications, we have expanded the limitations section of this study. It is true that ECGs are not routinely performed in emergency departments when patients are suspected of having infectious diseases such as IE. This study may be important because it highlights the valuable prognostic information that can be obtained from ECGs of patients with IE. ECGs should therefore be performed more frequently in patients with a predisposition to IE, any sign that suggests a seemingly new cardiac murmur, or any number of symptoms that might suggest IE.

Remark: The data analysis needs to be looked at again. Unlike what was described in the methods of data analysis, HRV parameters are instead presented using median values (not means), suggesting a skewed data. Sample size is small and data appears skewed, hence parametric tests such as Logistic regression may not be appropriate.

Response: The results section has been corrected and includes both non-parametric group comparisons (of HRV indices with relation to study outcomes), as well as logistic regression, only if the regression assumptions have been met (e.g.; linearity assumption). The methods section has been amended to include the description of these assumptions.

Remark: There appears some contradictory findings that are not fully explained. On one hand, lower HRV indices show predictive value in metastatic infections and Staph infection, and on the other increase in HRV predicts arrhythmic complications and mortality. Please explain.

Response: The results section has been revised with an emphasis on the arrhythmic complication. This outcome included both tachyarrhythmia and bradyarrhtyhmias. A sub-analysis of these two groups revealed major differences between HRV indices (as mentioned in the results section). Therefore, we decided not to carry out the logistic regression analysis for the arrhythmia outcome and provide only descriptive statistics and non-parametric comparisons. As to survival analysis, the discussion section has been expanded with proposed mechanistic explanations.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(20.4KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0287607.r003

Decision Letter 1

Atnafu Mekonnen Tekleab

8 Jun 2023

Prognostic implications of ultra-short heart rate variability indices in hospitalized patients with infective endocarditis

PONE-D-23-02781R1

Dear Dr. Ayelet Raz-Pasteur,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Atnafu Mekonnen Tekleab, M.D

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0287607.r004

Acceptance letter

Atnafu Mekonnen Tekleab

14 Jun 2023

PONE-D-23-02781R1

Prognostic implications of ultra-short heart rate variability indices in hospitalized patients with infective endocarditis

Dear Dr. Raz-Pasteur:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Atnafu Mekonnen Tekleab

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

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Data Availability Statement

The dataset generated and analyzed during the current study are available in the figshare repository, https://doi.org/10.6084/m9.figshare.21679742.v1.

[pone.0287607.ref001] 1.Habib G, Lancellotti P, Antunes MJ, Bongiorni MG, Casalta J-P, Del Zotti F, et al. 2015 ESC Guidelines for the management of infective endocarditis: The Task Force for the Management of Infective Endocarditis of the European Society of Cardiology (ESC). Endorsed by: European Association for Cardio-Thoracic Surgery (EACTS), the European. European heart journal. 2015;36(44):3075–3128. doi: 10.1093/eurheartj/ehv319 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref002] 2.Wei X-B, Su Z-D, Liu Y-H, Wang Y, Huang J-L, Yu D-Q, et al. Age, creatinine and ejection fraction (ACEF) score: a simple risk-stratified method for infective endocarditis. QJM: monthly journal of the Association of Physicians. 2019;112(12):900–906. doi: 10.1093/qjmed/hcz191 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref003] 3.Tascini C, Aimo A, Arzilli C, Sbrana F, Ripoli A, Ghiadoni L, et al. Procalcitonin, white blood cell count and C-reactive protein as predictors of S. aureus infection and mortality in infective endocarditis. International journal of cardiology. 2020;301:190–194. doi: 10.1016/j.ijcard.2019.08.013 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref004] 4.Mohanan S, Gopalan Nair R, Vellani H, C G S, George B, M N K. Baseline C-reactive protein levels and prognosis in patients with infective endocarditis: A prospective cohort study. Indian heart journal. 2018;70 Suppl 3(Suppl 3):S43–S49. doi: 10.1016/j.ihj.2018.05.001 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref005] 5.Chen Y, Ye L-J, Wu Y, Shen B-Z, Zhang F, Qu Q, et al. Neutrophil-Lymphocyte Ratio in Predicting Infective Endocarditis: A Case-Control Retrospective Study. Mediators of inflammation. 2020;2020:8586418. doi: 10.1155/2020/8586418 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref006] 6.Ferrera C, Vilacosta I, Fernández C, López J, Sarriá C, Olmos C, et al. Usefulness of thrombocytopenia at admission as a prognostic marker in native valve left-sided infective endocarditis. The American journal of cardiology. 2015;115(7):950–955. doi: 10.1016/j.amjcard.2015.01.021 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref007] 7.Tok D, Canpolat U, Tok D, Turak O, İşleyen A, Öksüz F, et al. Association of mean platelet volume level with in-hospital major adverse events in infective endocarditis. Wiener klinische Wochenschrift. 2015;127(5–6):197–202. doi: 10.1007/s00508-015-0746-2 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref008] 8.Kahveci G, Bayrak F, Mutlu B, Bitigen A, Karaahmet T, Sonmez K, et al. Prognostic value of N-terminal pro-B-type natriuretic peptide in patients with active infective endocarditis. The American journal of cardiology. 2007;99(10):1429–1433. doi: 10.1016/j.amjcard.2006.12.071 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref009] 9.Araújo IR, Ferrari TCA, Teixeira-Carvalho A, Campi-Azevedo AC, Rodrigues LV, Guimarães Júnior MH, et al. Cytokine Signature in Infective Endocarditis. PloS one. 2015;10(7):e0133631. doi: 10.1371/journal.pone.0133631 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref010] 10.Ris T, Teixeira-Carvalho A, Coelho RMP, Brandao-de-Resende C, Gomes MS, Amaral LR, et al. Inflammatory biomarkers in infective endocarditis: machine learning to predict mortality. Clinical and experimental immunology. 2019;196(3):374–382. doi: 10.1111/cei.13266 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref011] 11.Guimarães Júnior MH, Ferrari TCA, Teixeira-Carvalho A, Moreira M de L, de Souza Santos LJ, Costa-Silva MF, et al. Cell-derived microvesicles in infective endocarditis: Role in diagnosis and potential for risk stratification at hospital admission. The Journal of infection. 2019;79(2):101–107. doi: 10.1016/j.jinf.2019.06.005 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref012] 12.Thuny F, Di Salvo G, Belliard O, Avierinos J-F, Pergola V, Rosenberg V, et al. Risk of embolism and death in infective endocarditis: prognostic value of echocardiography: a prospective multicenter study. Circulation. 2005;112(1):69–75. doi: 10.1161/CIRCULATIONAHA.104.493155 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref013] 13.Liao L, Kong DF, Samad Z, Pappas PA, Jollis JG, Lin SS, et al. Echocardiographic risk stratification for early surgery with endocarditis: a cost-effectiveness analysis. Heart (British Cardiac Society). 2008;94(5):e18. doi: 10.1136/hrt.2006.106716 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref014] 14.Wang TKM, Bin Saeedan M, Chan N, Obuchowski NA, Shrestha N, Xu B, et al. Complementary Diagnostic and Prognostic Contributions of Cardiac Computed Tomography for Infective Endocarditis Surgery. Circulation. Cardiovascular imaging. 2020;13(9):e011126. doi: 10.1161/CIRCIMAGING.120.011126 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref015] 15.Meine TJ, Nettles RE, Anderson DJ, Cabell CH, Corey GR, Sexton DJ, et al. Cardiac conduction abnormalities in endocarditis defined by the Duke criteria. American heart journal. 2001;142(2):280–285. doi: 10.1067/mhj.2001.116964 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref016] 16.Miyamoto MI, Hutter AMJ, Blum JH, Torchiana DF. Cardiac conduction abnormalities preceding transoesophageal echocardiographic evidence of perivalvar extension of infection in a case of Salmonella prosthetic valve endocarditis. Heart (British Cardiac Society). 1997;78(4):416–418. doi: 10.1136/hrt.78.4.416 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref017] 17.Berk WA. Electrocardiographic findings in infective endocarditis. The Journal of emergency medicine. 1988;6(2):129–132. doi: 10.1016/0736-4679(88)90153-9 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref018] 18.Kohli U, Obuobi S, Addetia K, Ota T, Nayak HM. PR interval prolongation is significantly associated with aortic root abscess: An age- and gender-matched study. Annals of noninvasive electrocardiology: the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc. 2021;26(4):e12849. doi: 10.1111/anec.12849 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref019] 19.Pecchia L, Castaldo R, Montesinos L, Melillo P. Are ultra-short heart rate variability features good surrogates of short-term ones? State-of-the-art review and recommendations. Healthcare technology letters. 2018;5(3):94–100. doi: 10.1049/htl.2017.0090 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref020] 20.Dekker JM, Crow RS, Folsom AR, Hannan PJ, Liao D, Swenne CA, et al. Low heart rate variability in a 2-minute rhythm strip predicts risk of coronary heart disease and mortality from several causes: the ARIC Study. Atherosclerosis Risk In Communities. Circulation. 2000;102(11):1239–1244. doi: 10.1161/01.cir.102.11.1239 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref021] 21.Sajadieh A, Nielsen OW, Rasmussen V, Hein HO, Hansen JF. C-reactive protein, heart rate variability and prognosis in community subjects with no apparent heart disease. Journal of internal medicine. 2006;260(4):377–387. doi: 10.1111/j.1365-2796.2006.01701.x [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref022] 22.de Castilho FM, Ribeiro ALP, Nobre V, Barros G, de Sousa MR. Heart rate variability as predictor of mortality in sepsis: A systematic review. PloS one. 2018;13(9):e0203487. doi: 10.1371/journal.pone.0203487 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref023] 23.Kim K-N, Yao Y, Ju S-Y. Heart rate variability and inflammatory bowel disease in humans: A systematic review and meta-analysis. Medicine. 2020;99(48):e23430. doi: 10.1097/MD.0000000000023430 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref024] 24.Tracey KJ. Reflex control of immunity. Nature reviews. Immunology. 2009;9(6):418–428. doi: 10.1038/nri2566 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref025] 25.Rosas-Ballina M, Olofsson PS, Ochani M, Valdés-Ferrer SI, Levine YA, Reardon C, et al. Acetylcholine-synthesizing T cells relay neural signals in a vagus nerve circuit. Science (New York, N.Y.). 2011;334(6052):98–101. doi: 10.1126/science.1209985 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref026] 26.Mihaylova S, Schweighöfer H, Hackstein H, Rosengarten B. Effects of anti-inflammatory vagus nerve stimulation in endotoxemic rats on blood and spleen lymphocyte subsets. Inflammation research: official journal of the European Histamine Research Society… [et al.]. 2014;63(8):683–690. doi: 10.1007/s00011-014-0741-5 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref027] 27.Malik M, Camm AJ, Bigger JT, Breithardt G, Cerutti S, Cohen RJ, et al. Heart rate variability. Standards of measurement, physiological interpretation, and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. European Heart Journal. 1996:354–81. doi: 10.1093/oxfordjournals.eurheartj.a014868 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref028] 28.Shaffer F, Ginsberg JP. An Overview of Heart Rate Variability Metrics and Norms. Frontiers in public health. 2017;5:258. doi: 10.3389/fpubh.2017.00258 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref029] 29.Baek HJ, Cho CH, Cho J, Woo JM. Reliability of ultra-short-term analysis as a surrogate of standard 5-min analysis of heart rate variability. Telemedicine and e-Health. 2015;21(5):404–414. doi: 10.1089/tmj.2014.0104 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref030] 30.Munoz ML, Van Roon A, Riese H, Thio C, Oostenbroek E, Westrik I, et al. Validity of (Ultra-)Short recordings for heart rate variability measurements. PLoS ONE. 2015;10(9). doi: 10.1371/journal.pone.0138921 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref031] 31.Nussinovitch U, Elishkevitz KP, Kaminer K, Nussinovitch M, Segev S, Volovitz B, et al. The efficiency of 10-second resting heart rate for the evaluation of short-term heart rate variability indices. PACE—Pacing and Clinical Electrophysiology. 2011;34(11):1498–1502. doi: 10.1111/j.1540-8159.2011.03178.x [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref032] 32.Politi K, Kaminer K, Nussinovitch U. Reliability of ultrashort electrocardiographic indices in hypertension: The quest for a clinically applicable prognostic marker. Journal of Investigative Medicine. 2020. doi: 10.1136/jim-2019-001106 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref033] 33.Nussinovitch U. Reliability of ultra-short indices for autonomic dysfunction in dyslipidemia. Clinical physiology and functional imaging. 2020;40(6):423–433. doi: 10.1111/cpf.12661 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref034] 34.Nussinovitch U, Cohen O, Kaminer K, Ilani J, Nussinovitch N. Evaluating reliability of ultra-short ECG indices of heart rate variability in diabetes mellitus patients. Journal of Diabetes and its Complications. 2012;26(5):450–453. doi: 10.1016/j.jdiacomp.2012.05.001 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref035] 35.Karp E, Shiyovich A, Zahger D, Gilutz H, Grosbard A, Katz A. Ultra-short-term heart rate variability for early risk stratification following acute st-elevation myocardial infarction. Cardiology. 2009;114(4):275–283. doi: 10.1159/000235568 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref036] 36.Mol MBA, Strous MTA, van Osch FHM, Vogelaar FJ, Barten DG, Farchi M, et al. Heart-rate-variability (HRV), predicts outcomes in COVID-19. PloS one. 2021;16(10):e0258841. doi: 10.1371/journal.pone.0258841 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref037] 37.Perek S, Nussinovitch U, Cohen R, Gidron Y, Raz-Pasteur A. Ultra Short Heart Rate Variability Predicts Clinical Outcomes in Patients with a Clinical Presentation Consistent with Myocarditis: A Derivation Cohort Analysis. Journal of clinical medicine. 2022;12(1). doi: 10.3390/jcm12010089 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref038] 38.Feaktsistava N, Sujayeva V, Sudzhaeva S. The significance of cardiac rhythm variability value assessment in partients with infective endocarditis. E Journal of Cardiovascular Medicine. 2013;1(2):32–35. doi: 10.15511/ejcm.13.00232 [DOI] [Google Scholar]

[pone.0287607.ref039] 39.Li JS, Sexton DJ, Mick N, Nettles R, Fowler VG, Ryan T, et al. Proposed Modifications to the Duke Criteria for the Diagnosis of Infective Endocarditis. Clin Infect Dis. 2000;April(30(4)):633–638. doi: 10.1086/313753 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref040] 40.Liesenborghs L, Meyers S, Lox M, Criel M, Claes J, Peetermans M, et al. Staphylococcus aureus endocarditis: distinct mechanisms of bacterial adhesion to damaged and inflamed heart valves. European heart journal. 2019;40(39):3248–3259. doi: 10.1093/eurheartj/ehz175 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref041] 41.van den Berg ME, Rijnbeek PR, Niemeijer MN, Hofman A, Herpen G van Bots ML, et al. Normal values of corrected heart-rate variability in 10-second electrocardiograms for all ages. Frontiers in Physiology. 2018;9(4):424. doi: 10.3389/fphys.2018.00424 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref042] 42.Shaffer F, McCraty R, Zerr CL. A healthy heart is not a metronome: an integrative review of the heart’s anatomy and heart rate variability. Frontiers in Psychology. 2014;5(September):1–19. doi: 10.3389/fpsyg.2014.01040 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref043] 43.Ahmad S, Tejuja A, Newman KD, Zarychanski R, Seely AJ. Clinical review: a review and analysis of heart rate variability and the diagnosis and prognosis of infection. Critical care (London, England). 2009;13(6):232. doi: 10.1186/cc8132 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref044] 44.Hu S, Lou J, Zhang Y, Chen P. Low heart rate variability relates to the progression of gastric cancer. World Journal of Surgical Oncology. 2018;16(1):1–5. doi: 10.1186/s12957-018-1348-z [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref045] 45.Gidron Y, De Couck M, Schallier D, De Greve J, Van Laethem JL, Maréchal R. The relationship between a new biomarker of vagal neuroimmunomodulation and survival in two fatal cancers. Journal of Immunology Research. 2018;2018. doi: 10.1155/2018/4874193 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref046] 46.Hayano J, Ueda N, Kisohara M, Yuda E, Carney RM, Blumenthal JA. Survival Predictors of Heart Rate Variability After Myocardial Infarction With and Without Low Left Ventricular Ejection Fraction. Frontiers in neuroscience. 2021;15:610955. doi: 10.3389/fnins.2021.610955 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref047] 47.Wee BYH, Lee JH, Mok YH, Chong S-L. A narrative review of heart rate and variability in sepsis. Annals of translational medicine. 2020;8(12):768. doi: 10.21037/atm-20-148 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref048] 48.Kaliyaperumal D, Rk K, Alagesan M, Ramalingam S. Characterization of cardiac autonomic function in COVID-19 using heart rate variability: a hospital based preliminary observational study. Journal of basic and clinical physiology and pharmacology. 2021;32(3):247–253. doi: 10.1515/jbcpp-2020-0378 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref049] 49.Izhaki N, Perek S, Agbaria M, Raz-Pasteur A. Ultrashort Heart Rate Variability for Early Risk Stratification in Pneumonia Patients: Preliminary Analysis. The Israel Medical Association journal: IMAJ. 2022;24(11):741–746. [PubMed] [Google Scholar]

[pone.0287607.ref050] 50.Pei J, Tang W, Li L-X, Su C-Y, Wang T. Heart rate variability predicts mortality in peritoneal dialysis patients. Renal failure. 2015;37(7):1132–1137. doi: 10.3109/0886022X.2015.1061729 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref051] 51.Drawz PE, Babineau DC, Brecklin C, He J, Kallem RR, Soliman EZ, et al. Heart rate variability is a predictor of mortality in chronic kidney disease: a report from the CRIC Study. American journal of nephrology. 2013;38(6):517–528. doi: 10.1159/000357200 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref052] 52.Habib G. Management of infective endocarditis. Heart (British Cardiac Society). 2006;92(1):124–130. doi: 10.1136/hrt.2005.063719 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref053] 53.Ling N, Li CL, Wang ZZ, Zhang HN, Xu H, An XJ. Heart rate variability in children with myocarditis presenting with ventricular arrhythmias. European Review for Medical and Pharmacological Sciences. 2018;22(4):1102–1105. doi: 10.26355/eurrev_201802_14397 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref054] 54.Thuny F, Grisoli D, Collart F, Habib G, Raoult D. Management of infective endocarditis: challenges and perspectives. Lancet (London, England). 2012;379(9819):965–975. doi: 10.1016/S0140-6736(11)60755-1 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref055] 55.Habib G, Badano L, Tribouilloy C, Vilacosta I, Zamorano JL, Galderisi M, et al. Recommendations for the practice of echocardiography in infective endocarditis. European journal of echocardiography: the journal of the Working Group on Echocardiography of the European Society of Cardiology. 2010;11(2):202–219. doi: 10.1093/ejechocard/jeq004 [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref056] 56.Pelletier-Galarneau M, Abikhzer G, Harel F, Dilsizian V. Detection of Native and Prosthetic Valve Endocarditis: Incremental Attributes of Functional FDG PET/CT over Morphologic Imaging. Current cardiology reports. 2020;22(9):93. doi: 10.1007/s11886-020-01334-w [DOI] [PubMed] [Google Scholar]

[pone.0287607.ref057] 57.Krejčí J, Botek M MA. Stabilization period before capturing an ultra- short vagal index can be shortened to 60 s in endurance athletes and to 90 s in university students. PloS one. 2018;Oct 8(13(10)):e0205115. doi: 10.1371/journal.pone.0205115 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0287607.ref058] 58.Kim JW, Seok HS, Shin H. Is Ultra-Short-Term Heart Rate Variability Valid in Non-static Conditions? Frontiers in physiology. 2021;12(3):596060. doi: 10.3389/fphys.2021.596060 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Prognostic implications of ultra-short heart rate variability indices in hospitalized patients with infective endocarditis

Shay Perek

Udi Nussinovitch

Neta Sagi

Yori Gidron

Ayelet Raz-Pasteur

Roles

Abstract

Background

Methods

Results

Conclusion

Introduction

Materials and methods

Study design and population

Data collection

ECG analysis and computation of ultra-short HRV indices

Endpoints and evaluated clinical features

Statistical analysis

Results

Study population

Table 1. Patient clinical, laboratory and electrocardiographic characteristics (native valve IE vs. prosthetic valve IE).

HRV indices compared to published norms

HRV indices and study outcomes

Table 2. HRV indices with relation to study outcomes.

Heart failure with reduced ejection fraction

Table 3. Development of new HFrEF–univariate logistic regression.

Metastatic infection

Table 4. Metastatic infection–univariate logistic regression.

Fig 1. Infective endocarditis metastatic infection–multivariate logistic regression prediction model receiver operating characteristic curve, with 95% confidence interval.

Valve surgery

Staphylococcus IE

Table 5. Staphylococcus IE–univariate logistic regression.

Fig 2. Infective endocarditis Staphylococcus infection–multivariate logistic regression prediction model receiver operating characteristic curve, with 95% confidence interval.

Survival analysis

Table 6. Survival analysis–univariate cox regression.

Discussion

Conclusions

Data Availability

Funding Statement

References

Decision Letter 0

Atnafu Mekonnen Tekleab

Roles

Author response to Decision Letter 0

Decision Letter 1

Atnafu Mekonnen Tekleab

Roles

Acceptance letter

Atnafu Mekonnen Tekleab

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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