CLINICAL RESEARCH: CARDIAC IMAGING
Cardiac Iodine-123 Metaiodobenzylguanidine Imaging Predicts Sudden Cardiac Death Independently of Left Ventricular Ejection Fraction in Patients With Chronic Heart Failure and Left Ventricular Systolic DysfunctionResults From a Comparative Study With Signal-Averaged Electrocardiogram, Heart Rate Variability, and QT Dispersion
Shunsuke Tamaki, MD*,*,
Takahisa Yamada, MD*,
Yuji Okuyama, MD*,
Takashi Morita, MD*,
Shoji Sanada, MD*,
Yasumasa Tsukamoto, MD*,
Masaharu Masuda, MD*,
Keiji Okuda, MD*,
Yusuke Iwasaki, MD*,
Taku Yasui, MD*,
Masatsugu Hori, MD and
Masatake Fukunami, MD*
* Division of Cardiology, Osaka General Medical Center, Osaka, Japan
Department of Cardiovascular Medicine, Osaka University Graduate School of Medicine, Osaka, Japan
Manuscript received April 7, 2008;
revised manuscript received October 20, 2008,
accepted October 26, 2008.
* Reprint requests and correspondence: Dr. Shunsuke Tamaki, Division of Cardiology, Osaka General Medical Center, 3-1-56, Mandai-Higashi, Sumiyoshi-ku, Osaka 558-8558, Japan (Email: tamaki-shunsuke{at}mwc.biglobe.ne.jp).
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Abstract
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Objectives: We prospectively compared the predictive value of cardiac iodine-123 metaiodobenzylguanidine (MIBG) imaging for sudden cardiac death (SCD) with that of the signal-averaged electrocardiogram (SAECG), heart rate variability (HRV), and QT dispersion in patients with chronic heart failure (CHF).
Background: Cardiac MIBG imaging predicts prognosis of CHF patients. However, the long-term predictive value of MIBG imaging for SCD in this population remains to be elucidated.
Methods: At entry, cardiac MIBG imaging, SAECG, 24-h Holter monitoring, and standard 12-lead electrocardiography (ECG) were performed in 106 consecutive stable CHF outpatients with a radionuclide left ventricular ejection fraction (LVEF) <40%. The cardiac MIBG washout rate (WR) was obtained from MIBG imaging. Furthermore, the time and frequency domain HRV parameters were calculated from 24-h Holter recordings, and QT dispersion was measured from the 12-lead ECG.
Results: During a follow-up period of 65 ± 31 months, 18 of 106 patients died suddenly. A multivariate Cox analysis revealed that WR and LVEF were significantly and independently associated with SCD, whereas the SAECG, HRV parameters, or QT dispersion were not. Patients with an abnormal WR (>27%) had a significantly higher risk of SCD (adjusted hazard ratio: 4.79, 95% confidence interval: 1.55 to 14.76). Even when confined to the patients with LVEF >35%, SCD was significantly more frequently observed in the patients with than without an abnormal WR (p = 0.02).
Conclusions: Cardiac MIBG WR, but not SAECG, HRV, or QT dispersion, is a powerful predictor of SCD in patients with mild-to-moderate CHF, independently of LVEF.
Key Words: cardiac I-123 metaiodobenzylguanidine imaging • chronic heart failure • sudden cardiac death
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Abbreviations and Acronyms
| | AUC = area under the curve | | CHF = chronic heart failure | | ECG = electrocardiography/electrocardiogram | | fQRSd = the duration of filtered QRS complex | | H/M = heart-to-mediastinum ratio | | HRV = heart rate variability | | LAS40 = the duration of low-amplitude signals <40 µV in the terminal portion of filtered QRS complex | | LVEF = left ventricular ejection fraction | | MIBG = metaiodobenzylguanidine | | NN = normal-to-normal | | NYHA = New York Heart Association | | QTc = corrected QT interval | | RMS40 = the root mean square voltage for the last 40 ms of filtered QRS complex | | ROI = region-of-interest | | SAECG = signal-averaged electrocardiogram | | SCD = sudden cardiac death | | WR = washout rate |
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Despite advances in pharmacological treatment, mortality in patients with chronic heart failure (CHF) remains high (1). The 2 most common causes of death in patients with CHF are sudden cardiac death (SCD) and pump failure. In CHF patients with mild-to-moderate symptoms, SCD is reported to be the more common event (2).
To date, many efforts have been made to identify patients at high risk for SCD, and several electrocardiographic markers have been proposed. In patients with CHF, sympathetic overactivity and parasympathetic withdrawal are associated with poor outcome (3,4). Heart rate variability (HRV) is a noninvasive tool for the assessment of cardiac autonomic regulation and has been shown to predict SCD (5,6). Furthermore, the signal-averaged electrocardiogram (SAECG) and QT dispersion have prognostic value in patients with CHF (7–9). In addition, cardiac iodine-123 (I-123) metaiodobenzylguanidine (MIBG) imaging, which is useful for the estimation of cardiac adrenergic nerve activity (10,11), has also been reported to predict a poor clinical outcome (12–16). However, little information is available on the comparison of the prognostic value of cardiac MIBG imaging with electrocardiographic parameters such as SAECG, HRV, and QT dispersion. In this study, we sought to prospectively compare the long-term predictive value of cardiac MIBG imaging for SCD with that of SAECG, HRV, and QT dispersion in mild-to-moderate CHF patients.
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Methods
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Patients.
We enrolled 106 consecutive outpatients with CHF whose radionuclide left ventricular ejection fraction (LVEF) was <40%. Chronic heart failure was diagnosed by clinical signs and symptoms according to Framingham criteria (17). Patients were required to be stable for at least 3 months on conventional therapy with angiotensin-converting enzyme inhibitors, diuretics, and digoxin. Patients were excluded from this study if they had significant renal dysfunction, insulin-dependent diabetes mellitus, or autonomic neuropathy. Patients who had been receiving beta-blocker drugs were also excluded. At the time of enrollment, 20 and 10 patients were receiving mexiletine and amiodarone, respectively. At entry, all patients underwent cardiac MIBG imaging, SAECG, 24-h ambulatory electrocardiogram (ECG) monitoring, standard 12-lead ECG, and echocardiography, and a venous blood sample was drawn. All patients gave written, informed consent for their participation in this study, which was approved by the Osaka General Medical Center's Review Committee.
Radionuclide angiography for entry criteria.
Before entry, patients underwent ECG-gated blood-pool scintigraphy with a conventional rotating gamma camera (Prism 2000, Picker, Bedford, Ohio) equipped with a low-energy, high-resolution, parallel-hole collimator. Patients were given 740 MBq of technetium-99m-labeled human serum albumin (Nihon Medi-Physics, Nishinomiya, Japan). The LVEF was calculated with the standard program (18).
Cardiac MIBG imaging.
No patients were taking tricyclic antidepressant drugs, sympathomimetic agents, or other drugs known to interfere with MIBG uptake in the month preceding cardiac MIBG imaging.
Cardiac MIBG Acquisition
All patients underwent myocardial imaging with I-123 MIBG (Daiichi Radioisotope Laboratory, Tokyo, Japan) with the same gamma camera as for the radionuclide angiography. Patients were placed in the supine position. A 111-MBq dose of I-123 MIBG was injected intravenously at rest after an overnight fast. Initial and delayed image acquisitions were performed in the anterior chest view 20 and 200 min after the isotope injection.
Image Analysis
Two independent observers who were unaware of the clinical status of patients assessed cardiac MIBG uptake. Left ventricular activity was recorded with a manually drawn region-of-interest (ROI) over the whole left ventricular myocardium, and the mean heart counts/pixel were calculated. Another 7 x 7 pixel ROI was recorded over the upper mediastinal area, and the mean counts/pixel were calculated. Background subtraction was performed with the upper mediastinal ROI. The heart-to-mediastinum ratio (H/M) was then determined by dividing the mean counts/pixel in the left ventricle by the mean counts/pixel in the mediastinum. After taking radioactive decay of I-123 into consideration, the cardiac MIBG washout rate (WR) was calculated from the initial and delayed images, as previously reported (19). On the basis of our previous study, abnormal WR was defined as >27%, which was the mean control WR + 2 SD (19).
SAECG.
In an electrically shielded room, SAECGs were recorded from a modified X, Y, and Z lead system by the VCM-3000 (Fukuda Denshi, Tokyo, Japan) as previously reported (20).
The duration of filtered QRS complex (fQRSd), the root mean square voltage for the last 40 ms of filtered QRS complex (RMS40), and the duration of low amplitude signals <40 µV in the terminal portion of filtered QRS complex (LAS40) were measured from the vector magnitude by technicians that had no knowledge of the clinical data. Abnormal values for these 3 parameters were defined as fQRSd  130 ms, RMS40  17 µV, and LAS40 40 ms. A late potential was defined by the presence of 2 or more abnormal values.
24-h ambulatory ECG monitoring.
Patients underwent 24-h dual-channel ambulatory ECG recording with a Marquette Electronics (Milwaukee, Wisconsin) 8000 Holter monitoring system. Recordings were analyzed by 2 independent observers who were blinded to the clinical status of the patients. Ventricular arrhythmias were classified according to Lown's grade, and nonsustained ventricular tachycardia was defined as 5 or more consecutive premature ventricular beats lasting <30 s.
Traditional measurements of HRV were analyzed with the DSC-3100; MemCalc/Chiram (Nihon Koden Co. Ltd., Tokyo, Japan), according to the Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (21). Time domain analysis of HRV included the mean duration of all normal-to-normal (NN) intervals (mean RR), standard deviation of all normal-to-normal intervals (SDNN), standard deviation of the averages of NN intervals in all 5-min segments, mean of SDNN in all 5-min segments (SDNN index), square root of the mean of the sum of the squares of differences between adjacent NN intervals, number of NN intervals differing by more than 50 ms from the adjacent interval divided by the total number of NN intervals, and HRV triangular index. Spectral analysis was performed with the maximum entropy method (22). Power spectra were quantified by the area within the following frequency band: total power (0.0001 to 0.5 Hz), ultra-low-frequency power (0.0001 to 0.003 Hz), very-low-frequency power (0.003 to 0.04 Hz), low-frequency power (0.04 to 0.15 Hz), and high-frequency power (0.15 to 0.4 Hz). The low-frequency power/high-frequency power ratio was also calculated. The power within each band was also expressed as the percentage of the total power (normalized ultra-low-frequency power, very-low-frequency power, low-frequency power, and high-frequency power).
QT and corrected QT interval dispersion.
The QT intervals were measured in all 12 leads of a standard ECG. The QT interval in each lead was calculated as the mean of 3 consecutive QT intervals, measuring from the beginning of the QRS complex to the visual return of the T-wave to the TP baseline. The QT dispersion was defined as maximum minus minimum QT interval. Each QT interval was corrected for heart rate with Bazett's formula: QTc = QT/RR1/2(ms), where QTc is the corrected QT interval. The QTc dispersion was determined in the same manner as QT dispersion.
Echocardiography.
Two-dimensional echocardiography was performed with a Toshiba (Tokyo, Japan) SSH-380A recorder equipped with 2.5- or 3.75-MHz transducers. Left ventricular end-diastolic dimension (LVEDD) and left atrial dimension were measured by standard technique (23).
Measurements of plasma noradrenaline concentration and other parameters.
Blood sampling for assessment of the plasma noradrenaline concentration, serum uric acid, sodium, and creatinine levels was done from an intravenous cannula after resting for at least 30 min in the supine position. Plasma noradrenaline concentration was determined in ethylenediaminetetraacetic acid-plasma by high-performance liquid chromatography (24) at Shionogi Biomedical Laboratories (Osaka, Japan). A duplicate determination in the laboratory showed a coefficient of variation of 0.4% to 5.5%.
Follow-up.
All of the study patients were then followed up prospectively in our hospital at least once a month by clinicians who were not aware of the results of cardiac MIBG imaging, SAECG, HRV, or QT dispersion. The primary end point of this study was SCD, defined as witnessed cardiac arrest or death within 1 h after the onset of acute symptoms, or unexpected, unwitnessed death in a patient known to have been well within the previous 24 h. Cardiac death and pump failure death were the other study end points.
Statistical analysis.
Data are presented as mean ± SD. The Student t test and Fisher exact test were used to compare differences in continuous and discrete variables, respectively. In the Cox proportional hazard regression model, the association of the following baseline patient characteristics with survival was assessed: age; sex; underlying causes (ischemic or nonischemic); New York Heart Association (NYHA) functional class; heart rate; systolic and diastolic blood pressure; LVEF; presence of nonsustained ventricular tachycardia on Holter monitoring; echocardiography data; plasma noradrenaline concentration; serum uric acid, sodium, and creatinine levels; and the results of cardiac MIBG imaging, SAECG, HRV, and QT dispersion. The forward stepwise method was used for the multivariate analyses, with entry and removal p values set at 0.05. Patients with sinus rhythm and total study patients were analyzed in separate models, and the results of HRV and QT dispersion, which cannot be measured in the presence of atrial fibrillation, were excluded from the variables assessed in the analysis in total study patients. The Kaplan-Meier method was used to calculate the event-free survival rate in patients with normal and abnormal WR, and the 2 groups were compared with a log-rank test. The diagnostic utility of WR was compared with that of LVEF through the use of the receiver-operating characteristic curves. Results are expressed in terms of the area under the curve (AUC) and 95% confidence interval (CI) for this area. The Fisher exact test was used to compare sensitivity, specificity, positive and negative predictive values, and predictive accuracy, which meant the proportion of all test results—both positive and negative—that were correct among the different criteria for prediction of outcome. Correlations among the various variables were evaluated with Spearman's correlation coefficient. The SPSS (Chicago, Illinois) version 11 statistical software was used to analyze the data, except for the risk-adjusted survival curves calculated by SAS software version 9 (Cary, North Carolina). A p value <0.05 was considered statistically significant.
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Results
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Patient characteristics.
There were 81 men and 25 women (mean age 64 ± 12 years). Chronic heart failure was due to ischemic heart disease in 55 patients and idiopathic dilated cardiomyopathy in 51 patients. The average NYHA functional class was 2.1 ± 0.6, with 16% of patients in class I, 62% in class II, and 22% in class III. The radionuclide LVEF was 30 ± 8%. Of 106 patients, 84 patients were in sinus rhythm.
Follow-up outcome.
All patients were followed up completely. During a mean follow-up of 65 ± 31 months, 38 patients died. A cardiac cause was noted in 30 deaths. In cardiac death, SCD was the most common cause (n = 18), followed by pump failure death (n = 11) and death from myocardial infarction (n = 1).
Comparison of baseline characteristics between patients with and without SCD.
The baseline characteristics of patients with and without SCD are listed in Table 1. There were no differences in age, sex, the proportion of ischemic heart disease, NYHA functional class, heart rate, blood pressure, drug use, serum uric acid, sodium and creatinine levels, Lown's grade, presence of nonsustained ventricular tachycardia, LVEDD, or left atrial dimension between patients with and without SCD. Patients with SCD had a significantly higher plasma concentration of noradrenaline and a significantly lower LVEF.
The results of cardiac MIBG imaging are shown in Figure 1. Patients with SCD had a significantly lower H/M on the early and delayed images and a significantly higher WR than those without SCD, although there were no significant differences in any of SAECG or HRV parameters or QT dispersion in patients with and without SCD (Table 2).
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Figure 1 Results of Cardiac Metaiodobenzylguanidine Imaging
Results of cardiac metaiodobenzylguanidine imaging with and without sudden cardiac death (SCD). H/M(d) = heart-to-mediastinum metaiodobenzylguanidine uptake ratio on the delayed images; H/M(e) = heart-to-mediastinum metaiodobenzylguanidine uptake ratio on the early images; WR = washout rate of cardiac metaiodobenzylguanidine.
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Prognostic analysis.
Univariate and multivariate analysis in total patients is shown in Table 3. In multivariate analysis, both WR and LVEF were the independent predictors for all end points. In addition, LVEDD and serum creatinine level predicted pump failure death, and serum uric acid level predicted cardiac death. The SAECG did not predict any end points.
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Table 3 Univariate and Multivariate Cox Proportional Hazard Analysis for the Identification of CHF Patients at Risk of Sudden, Pump Failure, and Cardiac Death in Total Study Patients
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Sudden cardiac death, pump failure, and cardiac death-free survival curves adjusted for age, sex, and LVEF revealed that the presence of an abnormal WR increases the risk of SCD by 4.79-fold, the risk of pump failure death by 7.00-fold, and the risk of cardiac death by 5.64-fold in total patients (Fig. 2).
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Figure 2 Adjusted Survival Curves
The SCD, pump failure, and cardiac death-free survival curves adjusted for age, sex, and left ventricular ejection fraction in total patients with and without an abnormal WR. CI = confidence interval; other abbreviations as in Figure 1.
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Table 4
shows the results of the univariate and multivariate Cox proportional hazard analysis for SCD, pump failure, and cardiac death in patients with sinus rhythm. In multivariate analysis, WR and LVEF were significantly related to SCD and cardiac death, whereas only LVEDD was significantly related to pump failure death. None of the results of SAECG, HRV, or QT dispersion predicted any end points.
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Table 4 Univariate and Multivariate Cox Proportional Hazard Analysis for the Identification of CHF Patients at Risk of Sudden, Pump Failure, and Cardiac Death in Patients With Sinus Rhythm
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LVEF and WR for the prediction of SCD and cardiac death.
In total patients, the AUC with the WR used to predict SCD was 0.715 (95% CI: 0.587 to 0.843; p = 0.004), which was larger than that with LVEF (0.652, 95% CI: 0.499 to 0.806; p = 0.042).
Prediction of SCD and cardiac death with LVEF and WR is shown in Table 5. Both specificity and predictive accuracy for abnormal WR was significantly higher than that for LVEF 35%. By the combination of LVEF 35% and abnormal WR, both indexes increased further.
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Table 5 Prediction of SCD and Cardiac Death in Patients With Chronic Heart Failure by a Combination of Abnormal WR and LVEF 35% in Total Study Patients
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Relationship between the measured parameters and cardiac MIBG imaging.
In total patients, WR correlated positively with plasma norepinephrine levels, whereas there was no significant correlation between H/M on the delayed images and plasma norepinephrine levels (Table 6).
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Table 6 Correlation Between the Measured Parameters and the Results of Cardiac Metaiodobenzylguanidine Imaging in Total Study Patients
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WR for the prediction of SCD in patients with LVEF >35%.
Figure 3
shows SCD rates in the patients with LVEF >35% and 35% in total patients. Even when confined to the patients with LVEF >35%, a significantly higher rate of SCD was observed in the patients with than without abnormal WR in total patients (Fig. 4).
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Discussion
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The usefulness of MIBG imaging as a prognostic indicator in CHF patients was first advocated by Merlet et al. (12) and has been confirmed in several studies (13–16). Additionally, cardiac MIBG imaging might be useful for predicting SCD in CHF patients (13,16). However, a comparison of cardiac MIBG imaging with other noninvasive markers to predict SCD has not been performed. The information about such a comparison is not available from our previous report (16). Therefore, we prospectively compared the prognostic value of cardiac MIBG imaging with that of SAECG, HRV, and QT dispersion. This study demonstrated that only cardiac MIBG imaging could predict SCD in CHF patients, whereas SAECG, HRV, or QT dispersion did not.
Comparison of prognostic value of cardiac MIBG imaging with HRV.
Because high sympathetic activity in CHF patients is associated with a poor prognosis (3,4), an accurate assessment of cardiac sympathetic nerve activity would be of great importance. In the present study, cardiac MIBG imaging, which provides direct information on the function and integrity of the pre-synaptic sympathetic nerve endings (10,11) and needs only relatively low effective dose (not more than 1.5 mSv) (25), was shown to predict pump failure and cardiac death and, more importantly, SCD. The relationship of cardiac MIBG and SCD would be explained by the previous findings that increased sympathetic activity can modulate basic arrhythmia mechanisms of re-entry, automaticity, and triggered activity to provoke lethal arrhythmias (26–28). In our study, WR seemed to be superior to H/M for the prediction of prognosis, which is consistent with the previous report (15). Considering the better correlation of WR with plasma norepinephrine level than that of H/M in this study, WR might reflect the activation of the adrenergic nervous system better than H/M.
Besides cardiac MIBG imaging, HRV is a noninvasive tool that allows an assessment of autonomic control of the heart (21), and recent studies have revealed a relationship between SCD and HRV (5,6). The HRV reflects the end-organ response of the sinus node to both sympathetic and parasympathetic nerve inputs, whereas cardiac MIBG imaging "directly" reflects only sympathetic nerve function, which might explain the superiority of MIBG imaging in the prediction of SCD.
SAECG and QT dispersion.
The SAECG identifies the presence of slowed conduction within the myocardium, a substrate for re-entrant ventricular tachycardia (29). Although the occurrence of lethal arrhythmias needs both a substrate to maintain re-entry and a trigger to initiate the arrhythmia, an abnormal SAECG reflects only the former, which might in part explain why SAECG failed to predict SCD in our study and previous reports (30).
The QT dispersion represents the inhomogeneity of repolarization (31), and several studies suggested QT dispersion might predict SCD (8,9). However, QT dispersion is low in reproducibility and highly dependent on the method employed to measure the QT intervals. Additionally, the etiology of CHF might affect the prognostic importance of QT dispersion (8). These might explain the discrepancy of our results.
Comparison of prognostic value of cardiac MIBG imaging with LVEF.
To date, LVEF has been the most established marker of the high risk of SCD in CHF patients (32), although our results suggested that cardiac MIBG WR might be a more potent predictor of SCD than LVEF. This discrepancy might derive from differences in patient selection and methods. However, our data did not deny the predictive value of LVEF for SCD, because LVEF was one of the significant multivariate predictors of SCD in both multivariate models. In addition, cardiac MIBG imaging was suggested to be a powerful tool for the prediction of SCD in CHF patients when combined with LVEF, although the sensitivity for SCD fell substantially.
Cardiac MIBG imaging for the prediction of SCD in patients with LVEF >35%.
Because there has been no established method for the prediction of SCD in CHF patients with relatively preserved LVEF (35% to 45%), our findings suggesting the potential usefulness of cardiac MIBG imaging even in this population has great clinical implication. However, a larger prospective study is needed to address this issue, because there were only a few patients in this population, due to our entry criteria.
Noninvasive tests other than cardiac MIBG, SAECG, HRV, or QT dispersion.
Of 84 patients in sinus rhythm, heart rate turbulence and the exercise-induced change of QT dispersion, which also have been previously shown to have association with SCD (33,34), could be measured in 52 and 74 patients, respectively. Although the increase in QTc dispersion by exercise showed significant association with SCD in univariate analysis, it lost significance in multivariate analysis. Moreover, we could not find any association between heart rate turbulence parameters and SCD. The WR independently predicted SCD in these subpopulations as well.
Study limitations.
First, the small and empirically chosen study population sample size and empirically chosen follow-up length are major limitations. Second, no study patient was taking beta-blocker drugs at entry, because most study patients were the participants of our placebo-controlled study (T. Yamada et al., unpublished study, 1995 to 1999), where the efficacy of carvedilol or amlodipine was investigated last century. The medications used during follow-up might affect MIBG uptake and clinical outcome. However, the proportion of the patients treated with beta-blocker drugs and the length of beta-blocker therapy were not significantly different between patients with and without cardiac events. Third, there might have been a problem in quantifying the cardiac MIBG images, because a large decrease in cardiac MIBG activity observed in CHF patients could have introduced an error when drawing the ROI manually. However, although 2 independent observers drew the ROI in this study, the interobserver variation in counts/pixel was within 1.2%. Thus, errors introduced by drawing the ROI manually on the cardiac MIBG images are likely to be subtle. Fourth, because we included only stable outpatients, patients in NYHA functional class IV were not included in this study. Therefore, our results should not be generalized to inpatients with severe CHF. Fifth, because this is a single-center study, one should consider a possible ethnic difference when trying to generalize our results to the non-Japanese population. Sixth, although patients' age is 1 of the known clinical variables associated with increased risk of cardiac death, we could not find any association between them. This would be explained by the relatively young age of our study patients and the fact that the most common cause of cardiac death in this study was SCD, which has been reported not to have a significant association with age (32). Lastly, failure to include data from T-wave alternans testing, which has been recently shown to be useful for the risk stratification of SCD in CHF patients, is a great limitation.
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Conclusions
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To the best of our knowledge, this is the first study comparing the predictive value of cardiac MIBG imaging for SCD with that of SAECG, HRV, and QT dispersion in CHF patients. Cardiac MIBG WR, but not SAECG, HRV, or QT dispersion, is a powerful independent predictor of SCD in patients with mild-to-moderate CHF.
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Acknowledgments
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The authors thank Takashi Sozu, PhD, Osaka University, for expert advice on statistics; Setsuko Ishida and Hiroko Maekawa for technical assistance; and Yumiko Sugie, Yoshie Kimoto, and Yukie Tanesaka for caring for patients.
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