Introduction: Tachycardia caused by sympathetic overactivity impairs myocardial function and raises septic patients’ mortality. This study examined whether tachycardia is associated with acute kidney injury (AKI) period-prevalence among critically ill patients with and without sepsis. Methods: In 328 patients (119 sepsis and 209 non-sepsis) admitted to our intensive care unit (ICU), we assessed heart rate at ICU admission, plasma neutrophil gelatinase-associated lipocalin (NGAL) and N-terminal pro-B-type natriuretic peptide, and urinary L-type fatty acid-binding protein and N-acetyl-β-d-glucosaminidase (NAG) at 0 and 48 h after admission. Tachycardia was defined as a heart rate above 100 beats/min. Results: Tachycardia was independently correlated with AKI prevalence during the first week after ICU admission in the septic patients, but not in the non-septic patients. A dose-dependent increase in AKI period-prevalence was observed across ascending heart rate ranges. Furthermore, we discovered a dose-dependent increase in renal biomarker-positive patients regarding plasma NGAL and urinary NAG over increasing heart rate ranges 48 h after admission. Conclusion: The findings revealed an independent relationship between tachycardia and AKI prevalence during the first week of ICU in septic patients. Heart rate was found to have a dose-dependent effect on AKI prevalence and renal insult monitored by biomarkers.

Sympathetic overactivity in sepsis is characterized by persistent tachycardia even after eliminating other causes including hypovolemia, anemia, pain, and agitation. Tachycardia increases not only myocardial oxygen consumption but also causes coronary malperfusion by shortening diastolic time [1]. The myocardium exposed to tachycardia causes incomplete relaxation, presumably resulting in a decrease in left ventricular end-diastolic volume [2]. Recently, we reported that tachycardia in sepsis was independently associated with high mortality and the increase of the N-terminal of pro-B-type natriuretic peptide (NT-proBNP), which potentially indicates cardiac injury [3]. Another study showed heart rate reduction with short-acting intravenous β1-adrenergic receptor blockers reduced mortality in septic patients while also improving cardiovascular performance [4, 5]. However, the effects of tachycardia on other organs in sepsis are still unknown.

Increasing basic and clinical evidence on cardiorenal syndrome has clarified the complex mechanism of heart-kidney interaction [6]. The onset of myocardial functional depression can regularly aggravate acute kidney injury (AKI), predicting higher mortality [7]. Given this interorgan crosstalk, it is reasonable to presume that tachycardia-induced myocardial dysfunction could impede kidney function, particularly in septic patients. AKI is the most frequent organ dysfunction and is independently associated with high mortality in septic patients [8]. If there is any link between tachycardia and AKI in sepsis, then this would suggest the possible benefit from heart rate control to improve outcomes in septic patients by decreasing AKI development.

Furthermore, the experimental study using septic animal models indicated heart rate control with ivabradine, a selective inhibitor of the funny channel current of cardiac pacemaker cells, improved tissue perfusion, and thus reduced renal, hepatic, and neurological dysfunction [9].

Based on the aforementioned studies, we hypothesized that tachycardia would contribute to AKI onset in septic patients. We undertook this prospective observational study to determine whether heart rate elevation at intensive care unit (ICU) admission is linked with AKI prevalence during the first week in a dose-response manner.

Study Design and Patient Population

We conducted a prospective observational study in the University of Tokyo Hospital’s mixed medical/surgical ICU. All adult patients admitted to the ICU between October 2012 and March 2015 were included consecutively. Patients with end-stage renal disease or a kidney transplant were exempted. The study protocol followed the Declaration of Helsinki and was approved by the Institutional Review Board of the University of Tokyo (#2810-[13]). Each participant or the participant’s legal representative provided informed consent.

Definition

In this study, a heart rate over 100 beats/min was defined as tachycardia based on our previous study [3]. The American College of Chest Physicians/Society for Critical Care Medicine’s definition of sepsis served as the foundation for the diagnosis [10]. The nonrenal sequential organ failure assessment (SOFA) score was determined by subtracting the renal system score from the SOFA score to evaluate the severity of the disease other than AKI [11].

AKI was defined as an elevation in serum creatinine by ≥ 0.3 mg/dL from baseline or an increase in serum creatinine to ≥1.5 times baseline according to the KDIGO Clinical Practice Guideline for Acute Kidney Injury [12]. Baseline serum creatinine was determined as previously reported [13]. Preexisting chronic kidney disease was defined as an estimated glomerular filtration rate (eGFR) < 60 mL/min per 1.73 m2 [14]. The eGFR was calculated using the Modification of Diet in Renal Disease equation and the baseline creatinine value [15]. The primary outcome was AKI period-prevalence, defined as the proportion of patients diagnosed with AKI at ICU admission or during the first 7 days of ICU stay.

Data Collection

The information on the patient characteristics and the agents used at ICU admission was obtained from medical records. Heart rate values of study patients were recorded hourly on the patient monitoring system. Hypovolemia and lack of sedatives and analgesics would contribute to the development of tachycardia. Since appropriate sedation, analgesia, and volume resuscitation were initiated shortly after ICU admission and were anticipated to take effect within 4 h, the average heart rate values during the first 4 h of ICU were recorded as heart rate at admission [3].

Urine and plasma samples were collected at 0 and 48 h after ICU arrival and frozen at −80°C within 1 h of collection. The plasma neutrophil gelatinase-associated lipocalin (NGAL) and NT-proBNP levels were measured using the Triage NGAL and the Triage NT-proBNP devices (Alere Medical, San Diego, CA, USA), respectively. Urinary L-type fatty acid-binding protein (L-FABP) level was measured using commercially available enzyme-linked immunosorbent assay kits (Human L-FABP Assay Kit; CMIC Co. Ltd., Tokyo, Japan). Urinary N-acetyl-b-d-glucosaminidase (NAG) level was determined at the University of Tokyo Hospital Clinical Laboratory using the 4-HP-NAG substrate method (L-Type NAG; Wako Pure Chemical Industries Ltd., Osaka, Japan).

Statistical Analysis

Continuous variables were expressed as means ± standard deviation when normally distributed or median (interquartile range) when nonnormally distributed and compared using the Student’s t test or Wilcoxon rank-sum test, respectively. Categorical variables were expressed as percentages and compared using the χ2 or Fisher’s exact tests. Multiple pairwise comparisons were performed using the Bonferroni test.

To investigate the association of tachycardia with AKI occurrence, we performed multivariate logistic regression analyses with the 1-week prevalence of AKI as the dependent variable. Per previous studies, we chose the established risk factors for AKI and clinical status and treatments impacting heart rate, because they would be confounding factors in the link between tachycardia and AKI [3, 16, 17]. We integrated only the variables that showed significant differences between the tachycardia and non-tachycardia groups in the multivariate logistic regression model. To subsequently assess the dose-dependent relationship between higher heart rate and AKI prevalence, we entered ascending heart rate ranges (i.e., 40−80, 81−100, 101−120, and >120 beats/min) into our constructed model.

Covariate-adjusted logistic regression models were developed to examine the dose-dependent relationship between increasing heart rate ranges and the proportion of patients with elevated cardiorenal biomarkers. In addition to the AKI risk factors and clinical parameters affecting heart rate, we first selected the variables that previously demonstrated the strong link with the biomarkers [18]. These candidate variables were integrated into the models if significantly associated with tachycardia.

The cutoff points of cardiorenal biomarkers for discriminating AKI events within a week of ICU admission were determined using receiver operating characteristic curve analysis. The cutoff values were calculated using the Youden Index (sensitivity + specificity −1) [19]. The JMP® Pro software (version 15.0.0; SAS Institute, Cary, NC, USA) was used for all statistical analyses, and two-tailed p values <0.05 were deemed statistically significant.

Occurrence of Sepsis and Tachycardia

During the study period, 339 patients admitted to the ICU were evaluated for eligibility. Following the exclusion of 11 end-stage renal disease patients, the remaining 328 patients were enrolled in the study. Of those, 119 patients (36.3%) were diagnosed with sepsis at ICU admission and 51 septic patients had tachycardia (>100 beats/min) (Fig. 1). Table 1 shows the study cohort’s baseline patient characteristics and outcomes.

Fig. 1.

Study flow diagram. ESRD, end-stage renal disease.

Fig. 1.

Study flow diagram. ESRD, end-stage renal disease.

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Table 1.

Clinical characteristics of the study cohort

Non-sepsis (n = 209)Sepsis (n = 119)p value
Age, years 64 (50–74) 65 (55–74) 0.16 
Male/female 122/87 84/35 0.027 
APACHE II score 17 (12–21) 21 (14–25) <0.001 
Nonrenal SOFA score 5 (2–7) 7 (4–10) <0.001 
Admission type, n (%) <0.001 
 Medical 104 (49.8) 95 (79.8) 
 Elective surgery 68 (32.5) 5 (4.2) 
 Emergent surgery 37 (17.7) 19 (16.0) 
Heart rate at ICU admission, beats/min 83 (70–95) 96 (80–111) <0.001 
Baseline serum creatinine, mg/dL 0.64 (0.53–0.81) 0.74 (0.57–0.85) 0.049 
Baseline eGFR, mL/min/1.73 m2 75.4 (68.5–96.4) 84.0 (73.9–112.1) 0.056 
CKD, n (%) 29 (13.9) 22 (18.5) 0.27 
AKI stage at ICU admission, n (%) <0.001 
 No AKI 148 (70.8) 51 (42.9) 
 Stage 1 29 (13.9) 25 (21.0) 
 Stage 2 16 (7.7) 20 (16.8) 
 Stage 3 16 (7.7) 23 (19.3) 
AKI stage at 1 week, n (%) <0.001 
 No AKI 121 (57.9) 42 (35.3) 
 Stage 1 43 (20.6) 25 (21.0) 
 Stage 2 23 (11.0) 22 (18.5) 
 Stage 3 22 (10.5) 30 (25.2) 
Need for RRT, n (%) 4 (1.9) 12 (10.1) 0.001 
Length of ICU stay, days 4 (2–8) 6 (3–11) 0.002 
Non-sepsis (n = 209)Sepsis (n = 119)p value
Age, years 64 (50–74) 65 (55–74) 0.16 
Male/female 122/87 84/35 0.027 
APACHE II score 17 (12–21) 21 (14–25) <0.001 
Nonrenal SOFA score 5 (2–7) 7 (4–10) <0.001 
Admission type, n (%) <0.001 
 Medical 104 (49.8) 95 (79.8) 
 Elective surgery 68 (32.5) 5 (4.2) 
 Emergent surgery 37 (17.7) 19 (16.0) 
Heart rate at ICU admission, beats/min 83 (70–95) 96 (80–111) <0.001 
Baseline serum creatinine, mg/dL 0.64 (0.53–0.81) 0.74 (0.57–0.85) 0.049 
Baseline eGFR, mL/min/1.73 m2 75.4 (68.5–96.4) 84.0 (73.9–112.1) 0.056 
CKD, n (%) 29 (13.9) 22 (18.5) 0.27 
AKI stage at ICU admission, n (%) <0.001 
 No AKI 148 (70.8) 51 (42.9) 
 Stage 1 29 (13.9) 25 (21.0) 
 Stage 2 16 (7.7) 20 (16.8) 
 Stage 3 16 (7.7) 23 (19.3) 
AKI stage at 1 week, n (%) <0.001 
 No AKI 121 (57.9) 42 (35.3) 
 Stage 1 43 (20.6) 25 (21.0) 
 Stage 2 23 (11.0) 22 (18.5) 
 Stage 3 22 (10.5) 30 (25.2) 
Need for RRT, n (%) 4 (1.9) 12 (10.1) 0.001 
Length of ICU stay, days 4 (2–8) 6 (3–11) 0.002 

AKI, acute kidney injury; APACHE, acute physiology and chronic health evaluation; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; ICU, intensive care unit; RRT, renal replacement therapy; SOFA, sequential organ failure assessment.

Tachycardia and AKI

We evaluated the relationship between tachycardia at ICU admission and AKI prevalence during a week after admission in septic and non-septic patients. The proportion of AKI events was significantly higher in the tachycardia group than the non-tachycardia group in sepsis, whereas the difference in AKI period-prevalence between the tachycardia and non-tachycardia groups in non-sepsis could not reach statistical significance. Furthermore, septic patients with tachycardia were more likely to require renal replacement therapy than those without tachycardia. However, renal replacement therapy was likewise implemented for AKI in non-septic patients regardless of tachycardia (Table 2).

Table 2.

The effect of tachycardia on the 1-week prevalence of AKI and the need for RRT

Odds ratio (95% confidence interval)p value
AKI prevalence within a week 
 Sepsis 4.40 (1.86–10.43) <0.001 
 Non-sepsis 1.89 (0.98–3.66) 0.059 
AKI requiring RRT 
 Sepsis 4.64 (1.19–18.14) 0.027 
 Non-sepsis 1.19 (0.12–11.67) 0.88 
Odds ratio (95% confidence interval)p value
AKI prevalence within a week 
 Sepsis 4.40 (1.86–10.43) <0.001 
 Non-sepsis 1.89 (0.98–3.66) 0.059 
AKI requiring RRT 
 Sepsis 4.64 (1.19–18.14) 0.027 
 Non-sepsis 1.19 (0.12–11.67) 0.88 

AKI, acute kidney injury; RRT, renal replacement therapy.

Based on these findings, we further explored the effect of heart rate on AKI in septic patients. Table 3 compares the clinical status and treatments influencing heart rate and the possible risk factors for AKI between septic patients with and without tachycardia at ICU admission. The septic patients accompanying tachycardia were more inclined to have a higher nonrenal SOFA score at ICU admission and gain a bigger amount of fluid during the initial 4 h after admission than those without tachycardia. Furthermore, the proportion of risk factors for AKI was comparable except for preexisting chronic kidney disease, which was more prevalent in the tachycardia group. Table 4 displays the results of a multivariate logistic regression analysis for AKI period-prevalence in septic patients integrating prespecified AKI risk factors (eGFR and nonrenal SOFA score) and clinical parameters (fluid administration). Tachycardia was independently associated with AKI prevalence during the first week.

Table 3.

Clinical characteristics of tachycardiac or non-tachycardiac septic patients

Non-tachycardia (n = 68)Tachycardia (n = 51)p value
Age, years 65 (56–73) 65 (53–79) 0.89 
Male/female 52/16 32/19 0.10 
Nonrenal SOFA score 5 (3–10) 9 (6–11) <0.001 
Baseline eGFR, mL/min/1.73 m2 79.2 (70.8–99.9) 75 (57.3–90.3) 0.047 
AKI stage at ICU admission, n (%) 0.047 
 No AKI 36 (52.9) 15 (29.4) 
 Stage 1 10 (14.7) 15 (29.4) 
 Stage 2 9 (13.2) 11 (21.6) 
 Stage 3 13 (19.1) 10 (19.6) 
AKI stage at a week, n (%) 0.003 
 No AKI 33 (48.5) 9 (17.7) 
 Stage 1 14 (20.6) 11 (21.6) 
 Stage 2 10 (14.7) 12 (23.5) 
 Stage 3 11 (16.2) 19 (37.3) 
Fluid volume, mL/4 h 650 (495–1,021) 880 (580–1,400) 0.038 
Hemoglobin, g/dL 9.8 (8.5–12.6) 9.2 (8.1–12.2) 0.22 
Vasopressors and inotropes, n (%) 
 Noradrenaline 32 (47.1) 32 (62.8) 0.089 
 Dopamine 3 (4.4) 5 (9.8) 0.25 
 Dobutamine 3 (4.4) 3 (5.9) 0.72 
 Continuous sedation 34 (50.0) 26 (51.0) 0.92 
 Continuous analgesia 23 (33.8) 21 (41.2) 0.41 
Antiarrhythmics, n (%) 
 Beta-blocker 9 (13.4) 6 (11.8) 0.79 
 Digoxin 3 (4.4) 3 (5.9) 0.72 
 Calcium-channel blocker 0 (0.0) 2 (3.9) 0.10 
Risk factors for AKI, n (%) 
 CHD 16 (23.5) 18 (35.3) 0.16 
 Urinary tract infection 6 (8.8) 3 (5.9) 0.73 
 Nephrotoxic drugs 24 (35.3) 19 (37.3) 0.83 
Non-tachycardia (n = 68)Tachycardia (n = 51)p value
Age, years 65 (56–73) 65 (53–79) 0.89 
Male/female 52/16 32/19 0.10 
Nonrenal SOFA score 5 (3–10) 9 (6–11) <0.001 
Baseline eGFR, mL/min/1.73 m2 79.2 (70.8–99.9) 75 (57.3–90.3) 0.047 
AKI stage at ICU admission, n (%) 0.047 
 No AKI 36 (52.9) 15 (29.4) 
 Stage 1 10 (14.7) 15 (29.4) 
 Stage 2 9 (13.2) 11 (21.6) 
 Stage 3 13 (19.1) 10 (19.6) 
AKI stage at a week, n (%) 0.003 
 No AKI 33 (48.5) 9 (17.7) 
 Stage 1 14 (20.6) 11 (21.6) 
 Stage 2 10 (14.7) 12 (23.5) 
 Stage 3 11 (16.2) 19 (37.3) 
Fluid volume, mL/4 h 650 (495–1,021) 880 (580–1,400) 0.038 
Hemoglobin, g/dL 9.8 (8.5–12.6) 9.2 (8.1–12.2) 0.22 
Vasopressors and inotropes, n (%) 
 Noradrenaline 32 (47.1) 32 (62.8) 0.089 
 Dopamine 3 (4.4) 5 (9.8) 0.25 
 Dobutamine 3 (4.4) 3 (5.9) 0.72 
 Continuous sedation 34 (50.0) 26 (51.0) 0.92 
 Continuous analgesia 23 (33.8) 21 (41.2) 0.41 
Antiarrhythmics, n (%) 
 Beta-blocker 9 (13.4) 6 (11.8) 0.79 
 Digoxin 3 (4.4) 3 (5.9) 0.72 
 Calcium-channel blocker 0 (0.0) 2 (3.9) 0.10 
Risk factors for AKI, n (%) 
 CHD 16 (23.5) 18 (35.3) 0.16 
 Urinary tract infection 6 (8.8) 3 (5.9) 0.73 
 Nephrotoxic drugs 24 (35.3) 19 (37.3) 0.83 

AKI, acute kidney injury; CHD, chronic heart disease; eGFR, estimated glomerular filtration rate; ICU, intensive care unit; SOFA, sequential organ failure assessment.

Table 4.

Multivariate logistic regression model for AKI prevalence within a week

VariableAdjusted odds ratio (95% confidence interval)p value
Nonrenal SOFA score 1.08 (0.97–1.21) 0.15 
Baseline eGFR 1.58 (0.62–4.05) 0.34 
Tachycardia 3.78 (1.51–9.51) 0.005 
Fluid volume 1.35 (0.68–2.66) 0.39 
VariableAdjusted odds ratio (95% confidence interval)p value
Nonrenal SOFA score 1.08 (0.97–1.21) 0.15 
Baseline eGFR 1.58 (0.62–4.05) 0.34 
Tachycardia 3.78 (1.51–9.51) 0.005 
Fluid volume 1.35 (0.68–2.66) 0.39 

AKI, acute kidney injury; eGFR, estimated glomerular filtration rate; SOFA, sequential organ failure assessment.

Figure 2 depicts the proportion of AKI events within a week across ascending heart rate ranges at study entry. After including heart rate as a categorical variable in the original model, there was a dose-dependent increment in the proportion of AKI events among heart rate ranges above 100 beats/min (online suppl. Table S1; for all online suppl. material, see https://doi.org/10.1159/000539808).

Fig. 2.

The prevalence of AKI within a week according to ascending ranges of heart rate at ICU admission among the septic patients. #p < 0.05 versus the reference range of 40–80 beats/min by χ2 test or Fisher’s exact test with Bonferroni post hoc test. AKI, acute kidney injury; ICU, intensive care unit.

Fig. 2.

The prevalence of AKI within a week according to ascending ranges of heart rate at ICU admission among the septic patients. #p < 0.05 versus the reference range of 40–80 beats/min by χ2 test or Fisher’s exact test with Bonferroni post hoc test. AKI, acute kidney injury; ICU, intensive care unit.

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Receiver Operating Characteristic-Derived Criterion Values of Cardiorenal Biomarkers

During ICU admission, the urine samples could not be procured in four cases with anuria. Five cases died, and nine cases were discharged from the ICU by 48 h after ICU admission. We could not obtain the urine samples from 3 anuric patients after 48 h. The performance of four different cardiorenal biomarkers (plasma NGAL and NT-proBNP and urinary NAG and L-FABP) was assessed at 0 and 48 h after ICU admission among the septic patients with complete data (n = 102) regarding the biomarkers. We determined the cutoff values and area under the receiver operating characteristic curve of the biomarkers for differentiating AKI events within a week (Table 5).

Table 5.

Cardiorenal biomarkers’ cutoff values derived from ROC curves for identifying AKI events during the first week following ICU admission

BiomarkersCutoffAUC-ROC95% CI
Plasma NGAL at 0 h, ng/mL 309 0.700 0.584–0.795 
Plasma NGAL at 48 h, ng/mL 221 0.750 0.643–0.833 
Plasma NT-proBNP at 0 h, pg/mL 1,450 0.732 0.622–0.819 
Plasma NT-proBNP at 48 h, pg/mL 2,600 0.775 0.668–0.856 
Urinary NAG at 0 h, U/g Cr 46 0.562 0.437–0.680 
Urinary NAG at 48 h, U/g Cr 72 0.638 0.524–0.738 
Urinary L-FABP at 0 h, µg/g Cr 242 0.637 0.517–0.742 
Urinary L-FABP at 48 h, µg/g Cr 34 0.681 0.566–0.777 
BiomarkersCutoffAUC-ROC95% CI
Plasma NGAL at 0 h, ng/mL 309 0.700 0.584–0.795 
Plasma NGAL at 48 h, ng/mL 221 0.750 0.643–0.833 
Plasma NT-proBNP at 0 h, pg/mL 1,450 0.732 0.622–0.819 
Plasma NT-proBNP at 48 h, pg/mL 2,600 0.775 0.668–0.856 
Urinary NAG at 0 h, U/g Cr 46 0.562 0.437–0.680 
Urinary NAG at 48 h, U/g Cr 72 0.638 0.524–0.738 
Urinary L-FABP at 0 h, µg/g Cr 242 0.637 0.517–0.742 
Urinary L-FABP at 48 h, µg/g Cr 34 0.681 0.566–0.777 

AKI, acute kidney injury; AUC-ROC, area under the receiver operation characteristic curve; CI, confidence interval; L-FABP, L-type fatty acid-binding protein; NAG, N-acetyl-b-d-glucosaminidase; NGAL, neutrophil gelatinase-associated lipocalin; NT-proBNP, N-terminal pro-B-type natriuretic peptide.

Heart Rate and Cardiorenal Biomarkers

Plasma NGAL and NT-proBNP and urinary NAG and L-FABP were transferred as dichotomous variables using the cutoff values shown in Table 5. Figure 3 depicts the proportion of patients with biomarkers above the cutoff points (biomarker-positive) at two points (at ICU admission and 48 h later) according to increasing heart rate ranges at the time of ICU admission. Concerning NGAL and NAG, higher heart rate ranges above 100 beats/min were associated with a dose-dependent increasing proportion of biomarker-positive patients at 48 h. However, NT-proBNP and L-FABP could not show such a trend (online suppl. Table S2).

Fig. 3.

Cardiorenal biomarkers across increasing heart rate ranges in the septic patients with complete data of the biomarkers.#p < 0.05 versus the reference range of 40–80 beats/min by χ2 test or Fisher’s exact test with Bonferroni post hoc test. L-FABP, L-type fatty acid-binding protein; NAG, N-acetyl-b-d-glucosaminidase; NGAL, neutrophil gelatinase-associated lipocalin; NT-proBNP, N-terminal pro-B-type natriuretic peptide.

Fig. 3.

Cardiorenal biomarkers across increasing heart rate ranges in the septic patients with complete data of the biomarkers.#p < 0.05 versus the reference range of 40–80 beats/min by χ2 test or Fisher’s exact test with Bonferroni post hoc test. L-FABP, L-type fatty acid-binding protein; NAG, N-acetyl-b-d-glucosaminidase; NGAL, neutrophil gelatinase-associated lipocalin; NT-proBNP, N-terminal pro-B-type natriuretic peptide.

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This prospective observational study examined the effect of a heart rate over 100 beats/min at ICU admission on AKI prevalence during the first week using a cohort of critically ill patients treated in our mixed ICU. The findings revealed tachycardia was independently associated with the 1-week prevalence of AKI in septic patients, but not in non-septic patients. Additionally, we discovered a significant dose-dependent increase in the proportion of AKI events according to ascending heart rate ranges in septic patients. Furthermore, the proportion of patients with plasma NGAL and urinary NAG elevation indicated a significant dose-dependent increment across heart rate ranges above 100 beats/min at 48 h after admission, whereas such a trend was not observed in plasma NT-proBNP and urinary L-FABP.

Our previous study indicated a heart rate over 100 beats/min at ICU admission was an independent predictor of 28-day mortality in septic patients [3]. Another study demonstrated heart rate control within a target range of 80–94 beats/min using esmolol-enhanced 28-day survival in patients with septic shock [4]. However, the recent randomized controlled trial reported that among patients with septic shock and tachycardia treated with norepinephrine for more than 24 h, an infusion of β-blockade did not reduce organ failure over 14 days from randomization [20]. The association of tachycardia with distant organ injuries has not been clear despite their substantial contribution to worsening outcomes of septic patients.

Focusing on the effects of tachycardia on the kidneys, we found that tachycardia at ICU admission was independently associated with AKI prevalence during the first week. A significant dose-dependency of heart rate was found in AKI period-prevalence. There are two plausible explanations relevant to the obtained results. First, tachycardia-induced myocardial dysfunction may directly affect AKI development, which is suggested by prior experimental studies [2, 9]. Next, sympathetic overactivity in sepsis may involve both the heart and the kidney simultaneously, a condition known as type 5 cardiorenal syndrome [6]. In this context, tachycardia may be an indication of sympathetic overactivity, not the cause of AKI. Further research is required to comprehend the pathophysiological mechanisms underlying the link between tachycardia and AKI during sepsis.

In our study, the impact of tachycardia on AKI occurrence was minor among non-septic patients. This cohort’s heterogeneity may reduce the statistical power to detect a significant association between tachycardia and AKI period-prevalence. Tachycardia in non-septic patients may be caused by more diverse mechanisms than in septic patients. Whether an increased heart rate can impair renal function should be investigated in specific populations without sepsis.

A growing number of biomarkers have been identified for early detection of kidney damage before serum creatinine rises. Plasma NGAL and urinary L-FABP have been the most intensively studied biomarkers for renal tubular cellular injury and showed promising results for early AKI detection [21, 22]. Recently, plasma NT-proBNP was discovered to be an independent predictor of AKI as well as cardiovascular events in ICU patients [17, 23]. Additionally, basic research using nephrotoxic and hepatotoxic models revealed urinary NAG’s ability to predict histological damage in renal tubular cells better than serum creatinine and blood urea nitrogen [24]. Regarding these biomarkers, we assessed the trend of the proportion of biomarker-positive patients across elevating heart rate ranges at two time points (i.e., at the time of ICU admission and 48 h after admission) using the cutoff values for AKI events derived from our sepsis cohort. After adjustment with potential confounding factors per our previous study [18], plasma NGAL and urinary NAG demonstrated a dose-dependent increment in the proportion of biomarker-positive patients across increasing heart ranges at 48 h after admission. The similar trend of different AKI biomarkers suggests the dose-dependent impact of tachycardia on renal tubules is distinct in a delayed manner after tachycardia at ICU admission.

Our study has several limitations possibly affecting the obtained results. First, this study was performed with a small sample size at a single center, which could restrict the generalizability of our results. Numerous confounding factors affecting heart rate, cardiorenal biomarkers, and AKI development may not be sufficiently controlled. Future studies with larger cohorts in multicenter ICUs should be performed to verify and expand our findings. Second, the latest definition of sepsis known as sepsis-3 was not used to stratify the patients with sepsis because this study was conducted before the definition release [25]. Third, this observational cohort study could not determine the causal relationship between tachycardia and AKI. Cumulative AKI incidence was not evaluated in this study because of only 51 septic patients without AKI at ICU admission. Finally, AKI was diagnosed solely through serum creatinine in this study. Although the current definition of AKI on the KDIGO guideline recommends using another criterion based on low urine output, recent studies have frequently used the serum creatinine-based criterion alone [26].

Our study found that tachycardia at ICU admission was independently associated with AKI prevalence in septic patients during the first week. The increase in heart rate may augment the positive signals of renal insult by plasma NGAL and urinary NAG in sepsis in a dose-dependent manner. Heart rate control via suppressing sympathetic overstimulation may prevent septic AKI, thereby improving the outcomes of critically ill patients with sepsis.

The authors would like to appreciate all the staff in the ICU of the University of Tokyo Hospital for collecting the blood and urine samples.

The study protocol was approved by the Institutional Review Board of the University of Tokyo (#2810-[13]). Each participant or the participant’s legal representative provided written informed consent.

The authors have no conflicts of interest to declare.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

N.H. and K.D. conceived this study and participated in its study design and coordination. N.H., M.Y., T.A., and R.I. conducted sample collection, measured biomarkers, and analyzed and interpreted data. N.H. wrote the original manuscript. K.D. critically revised the manuscript for important intellectual content. All authors read and approved the final version of the manuscript.

The data that support the findings of this study are not publicly available due to their containing information that could compromise the privacy of research participants but are available from the corresponding author (K.D.) upon reasonable request.

1.
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