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Figure 1. Frequency Distribution of the Ratio Between Mean Nighttime and Daytime Systolic Blood Pressure in the Overall Cohort
Image description not available.

Fifty-six participants exhibited nondipping (a nighttime-daytime systolic blood pressure ratio ≥1). The blue curve is the kernel-density estimate using a bandwidth of 0.03.

Figure 2. Kaplan-Meier Plot for Probability of Heart Failure–Free Survival in the Total Cohort for Nondipping vs Normal Night-Day Blood Pressure Patterns
Image description not available.

Nondipping pattern defined as night-day ambulatory blood pressure ratio of at least 1.

Table 1. Baseline Characteristics of the Cohort by Development of Heart Failure During Follow-up*
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Table 2. Baseline Blood Pressure Measurements of the Total Cohort and by Development of CHF During Follow-Up
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Table 3. Risk of Congestive Heart Failure by Type of Blood Pressure Measurement in the Total Sample and in a Subsample Without Myocardial Infarction
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Table 4. Risk of Congestive Heart Failure by Type of Blood Pressure Measurement in the Total Sample and in a Subsample Without Myocardial Infarction, Adjusted for Previous Factors Plus Office or Ambulatory Blood Pressure
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Original Contribution
June 28, 2006

Diurnal Blood Pressure Pattern and Risk of Congestive Heart Failure

Author Affiliations
 

Author Affiliations: Departments of Public Health and Caring Sciences (Drs Ingelsson, Björklund-Bodegård, Ärnlöv, and Sundström) and Medical Sciences (Drs Lind and Sundström), Uppsala University, Uppsala, Sweden; and AstraZeneca Research and Development, Mölndal, Sweden (Dr Lind).

JAMA. 2006;295(24):2859-2866. doi:10.1001/jama.295.24.2859
Context

Context High blood pressure is the most important risk factor for congestive heart failure (CHF) at a population level, but the relationship of an altered diurnal blood pressure pattern to risk of subsequent CHF is unknown.

Objectives To explore 24-hour ambulatory blood pressure characteristics as predictors of CHF incidence and to investigate whether altered diurnal blood pressure patterns confer any additional risk information beyond that provided by conventional office blood pressure measurements.

Design, Setting, and Participants Prospective, community-based, observational cohort in Uppsala, Sweden, including 951 elderly men free of CHF, valvular disease, and left ventricular hypertrophy at baseline between 1990 and 1995, followed up until the end of 2002. Twenty-four-hour ambulatory blood pressure monitoring was performed at baseline, and the blood pressure variables were analyzed as predictors of subsequent CHF.

Main Outcome Measure First hospitalization for CHF.

Results Seventy men developed heart failure during follow-up, with an incidence rate of 8.6 per 1000 person-years at risk. In multivariable Cox proportional hazards models adjusted for antihypertensive treatment and established risk factors for CHF (myocardial infarction, diabetes, smoking, body mass index, and serum cholesterol level), a 1-SD (9–mm Hg) increase in nighttime ambulatory diastolic blood pressure (hazard ratio [HR], 1.26; 95% confidence interval [CI], 1.02-1.55) and the presence of “nondipping” blood pressure (night-day ambulatory blood pressure ratio ≥1; HR, 2.29; 95% CI, 1.16-4.52) were associated with an increased risk of CHF. After adjusting for office-measured systolic and diastolic blood pressures, nondipping blood pressure remained a significant predictor of CHF (HR, 2.21; 95% CI, 1.12-4.36 vs normal night-day pattern). Nighttime ambulatory diastolic blood pressure and nondipping blood pressure were also significant predictors of CHF after exclusion of all participants who had an acute myocardial infarction before baseline or during follow-up.

Conclusions Nighttime blood pressure appears to convey additional risk information about CHF beyond office-measured blood pressure and other established risk factors for CHF. The clinical value of this association remains to be established in future studies.

Congestive heart failure (CHF) is one of the most common, costly, disabling, and deadly diseases.1 It constitutes a huge burden on health services and accounts for 1% to 2% of the total health care costs in industrialized countries.2 Once diagnosed as having CHF, patients have a 1 in 3 chance of dying within 1 year and a 2 in 3 chance of dying within 5 years.1 The mortality associated with CHF exceeds that of most cancers, although recent reports suggest an improving prognosis.3

The predominant causes of CHF are hypertension and coronary heart disease, and high blood pressure (BP) is suggested to be the most important risk factor for CHF at a population level.4 Ambulatory BP monitoring provides information that is not obtained from conventional office-based BP measurement, such as mean BP over a 24-hour period and night-day patterns. Previous studies have established that 24-hour BP measurements are powerful predictors of cardiovascular morbidity and mortality independent of office-measured BP and other established cardiovascular risk factors.58 However, no previous studies have examined 24-hour ambulatory BP as a predictor of incident CHF in persons free of CHF at baseline.

Thus, the primary aim of the current study was to analyze 24-hour ambulatory BP characteristics as predictors of CHF incidence in a community-based sample of elderly men, adjusting for antihypertensive treatment and traditional risk factors for CHF. The secondary aim was to investigate whether 24-hour ambulatory BP patterns confer any value regarding the risk of future CHF beyond that conveyed by conventional office-measured BP.

METHODS
Study Sample

This study is based on the Uppsala Longitudinal Study of Adult Men cohort (http://www.pubcare.uu.se/ULSAM/), a health investigation focused on identifying metabolic risk factors for cardiovascular disease. All 50-year-old men living in Uppsala in 1970-1973 were invited to join the study, of which 82% (2322 men) participated in the investigation.9 The cohort was reinvestigated 20 years later (baseline of the present study: 1991-1995).

Of the 1681 available 70-year-old men invited to the follow-up investigation, 73% (1221 men) participated. For the present study, 1036 of these men had valid 24-hour ambulatory BP recordings and data on all covariates. Based on the hospital register, 12 further participants were excluded because of a previous diagnosis of CHF and 9 were excluded because of a previous diagnosis of valvular disease; 64 were excluded because of electrocardiographic left ventricular hypertrophy (ECG-LVH) at the baseline examination. Participants with ECG-LVH were excluded because there was evidence of a significant interaction between this variable and 24-hour ambulatory diastolic BP (DBP; P = .03) and nighttime ambulatory DBP (P = .03). Because the number of participants with ECG-LVH was low, the analyses were restricted to participants without it. Thus, 951 men were eligible for the present investigation. A subsample (n = 819) excluding all participants with myocardial infarction at baseline or during follow-up was also examined. All participants provided written informed consent and the ethics committee of Uppsala University approved the study.

Baseline Examinations

Examinations performed when the participants were 70 years old included a medical examination, a questionnaire, blood sampling (after an overnight fast), supine office BP measurement, 24-hour ambulatory BP monitoring, anthropometric measurements, and lipid determinations as previously described.8,10

Office-based BP was measured in the right arm with a sphygmomanometer using the appropriate cuff size. Two recordings were made to the nearest 2 mm Hg after a 10-minute supine rest, and the mean of the 2 measurements was used for the analyses. Systolic and diastolic BP were defined as Korotkoff phases I and V, respectively.

Twenty-four-hour ambulatory systolic BP (SBP) and DBP were recorded using Accutracker II equipment (SunTech Medical Instruments Inc, Raleigh, NC). Blood pressure recordings were made every 20 or 30 minutes between 6 AM and 11 PM and every 20 or 60 minutes between 11 PM and 6 AM. Data were edited by omitting all readings presumed to be erroneous, including readings of 0, DBP readings of more than 170 mm Hg, SBP readings of more than 270 or less than 80 mm Hg, and all readings in which the difference between SBP and DBP was less than 10 mm Hg. The measurements were interpreted and the data edited by skilled laboratory technicians blinded to the study outcome. The Accutracker II device showed satisfactory accuracy and precision according to available documentation at the time of investigation in the early 1990s.11 The coefficients of variation for 24-hour SBP and DBP were 6.8% and 5.5%, respectively, determined in a reproducibility study performed in 22 participants approximately 1 month after the baseline examination. Short, fixed clock time intervals were used, defining daytime as 10 AM to 8 PM and nighttime as midnight to 6 AM. This method is used to eliminate the retiring and rising periods, during which BP is subject to considerable variation; it also helps to diminish variations between different age groups and cultures.12

Pulse pressure was estimated as the difference between SBP and DBP. Sustained hypertension was defined as office BP of 140/90 mm Hg or higher and daytime ambulatory BP of 135/85 mm Hg or higher; isolated ambulatory hypertension (or masked hypertension) was defined as office BP of less than 140/90 mm Hg and daytime ambulatory BP of 135/85 mm Hg or higher; and isolated office hypertension (or white-coat hypertension) was defined as office BP of 140/90 or higher and daytime ambulatory BP of less than 135/85 mm Hg.13

Nocturnal BP decline was assessed by the ratio between mean nighttime and daytime SBP, and “nondipping” was defined as the ratio between nighttime and daytime SBP of 1 or higher; ie, an absence of nocturnal BP reduction, also called inverted dipping. There are several reasons for supporting this definition and the use of night-day BP ratios; first, the ratio depends less on the specific BP level than on the absolute nocturnal BP decrease; second, the ratios are normalized for daytime BP level; and third, a ratio of 1 approximates the 95th percentile of the distribution of night-day ratios in normotensive persons.14 Furthermore, this most extreme form of circadian rhythm disturbance has been previously demonstrated to be associated with the highest risk of cardiovascular mortality.15

The presence of diabetes at baseline was defined as fasting plasma glucose of 7.0 mmol/L (126 mg/dL) or higher or use of oral hypoglycemic agents or insulin.16 The ECG-LVH was defined as high-amplitude R waves according to the revised Minnesota code,17 together with a left ventricular strain pattern.4 Coding of smoking was based on interview reports and medication data were based on questionnaire responses. At baseline, 310 participants were taking antihypertensive medications: 186 with monotherapy, 101 with 2 antihypertensive drugs, and 23 with 3 or more drugs. The presence of valvular disease (International Classification of Diseases, Ninth Revision [ICD-9] codes 394-397 and 424 or International Statistical Classification of Diseases, 10th Revision [ICD-10] codes I05-I08 and I34-I37) and prior myocardial infarction (ICD-9 code 410 or ICD-10 code I21) was assessed from the hospital discharge register. The precision of the myocardial infarction diagnosis in the Swedish hospital discharge register is high.18

Follow-up and Outcomes

Ninety-four men had a hospital discharge register diagnosis of CHF between the 70-year-old baseline and December 31, 2002. The ICD heart failure codes 428 (ICD-9) and I50 (ICD-10) and hypertensive heart disease with congestive heart failure code I11.0 (ICD-10) were considered to be possible CHF. The medical records from the relevant hospitalizations were reviewed by 2 physicians (E.I. and L.L.) who, blinded to the baseline data, classified the cases as definite, questionable, or miscoded. Cases included in the present study were considered definite. The classification relied on the definition proposed by the European Society of Cardiology19 and the review process has been described in detail previously.20 No participants were lost to follow-up.

Statistical Analyses

Analyses were defined a priori. Data are reported as mean (standard deviation) or number (percentage). Logarithmic transformation was performed to achieve normal distribution for the 24-hour pulse pressure, nighttime SBP, and nighttime pulse pressure variables. The prognostic values of a 1-SD increase for the continuous variables, or presence vs absence for the dichotomous variables, for CHF incidence were investigated with Cox proportional hazards analyses. The different hypertension definitions (sustained hypertension, isolated ambulatory hypertension, and isolated office hypertension) were compared with the reference level with lowest CHF risk (ie, no hypertension, office BP <140/90 mm Hg and daytime ambulatory BP <135/85 mm Hg) using Cox proportional hazards analyses. Nonlinear relationships were assessed by examining incidence rates in quintiles of the independent variables, and night-day ratio of SBP was nonlinearly related to CHF incidence, supporting the use of a dichotomous nondipping variable. Proportional hazards assumptions were confirmed by Schoenfeld tests. We investigated the independent variables in 5 sets of models in a hierarchical fashion:

  1. Unadjusted;

  2. Models adjusted for antihypertensive medication (diuretics, β-blockers, angiotensin-converting enzyme inhibitors, calcium antagonists, and α-blockers as separate covariates);

  3. Models adjusted for antihypertensive medication and established risk factors for CHF (prior acute myocardial infarction, diabetes, smoking, body mass index, and serum cholesterol) determined at baseline;

  4. Models adjusted for antihypertensive medication, established risk factors for CHF, and office-measured SBP and DBP; and

  5. Models adjusted for antihypertensive medication, established risk factors for CHF, and 24-hour ambulatory SBP and DBP.

Models 2, 3, and 4 were considered to be primary, whereas models 1 and 5 were considered secondary. All models were repeated in a subsample (n = 819) without myocardial infarction before baseline or during follow-up. To rule out an effect modification by established risk factors on the relation of ambulatory BP variables to CHF, we investigated interaction terms between each of the established risk factors (those listed for model 3, ECG-LVH, and interim myocardial infarction) and the different BP variables. The statistical power was 91% to detect a hazard ratio (HR) of 1.5 for a 1-SD increase in BP level. Two-tailed 95% confidence intervals (CIs) and P values are reported, with P<.05 regarded as statistically significant. PASS 2002 statistical software (NCSS, Kaysville, Utah) was used for power calculations and STATA version 8.2 (Stata Corp, College Station, Tex) for the other analyses.

RESULTS

Participants had a median follow-up time of 9.1 years (range, 0.1-11.4 years), contributing to 8129 person-years at risk. Seventy participants developed CHF during follow-up, with an incidence rate of 8.6 per 1000 person-years at risk. Table 1 shows the clinical characteristics at baseline and Table 2 shows the baseline BP characteristics. The frequency distribution of the ratio between mean nighttime and daytime SBP in the total cohort is shown in Figure 1. The mean (SD) nighttime-daytime SBP ratio was 0.85 (0.10).

In unadjusted Cox proportional hazards analyses (model 1), all office BP measurements, 24-hour ambulatory BP measurements, nighttime ambulatory BP measurements, sustained hypertension, and nondipping were significant predictors of CHF (Table 3). In analyses adjusted for antihypertensive treatment (model 2), nighttime ambulatory SBP and DBP and nondipping were significant predictors of CHF incidence (Table 3). When we also adjusted for established baseline risk factors for CHF (prior acute myocardial infarction, diabetes, smoking, body mass index, and serum cholesterol; model 3), nighttime ambulatory DBP and nondipping remained independent predictors of CHF in separate models (Table 3). A Kaplan-Meier plot for probability of survival free of heart failure for nondipping vs normal night-day BP patterns is presented in Figure 2. When office SBP and DBP were added to the models (model 4), nondipping was a significant predictor of CHF, whereas ambulatory nighttime DBP became nonsignificant (Table 4). In analyses including 24-hour ambulatory SBP and DBP in addition to antihypertensive treatment and established baseline risk factors (model 5), nighttime ambulatory DBP and nondipping were significant predictors of CHF (Table 4).

To facilitate interpretation of the results, we also calculated how much the risk for CHF increased for each 5–mm Hg increment in nighttime ambulatory DBP. In unadjusted models (model 1), each 5–mm Hg increment of nighttime ambulatory DBP was associated with a 21% increased risk of CHF (HR, 1.21; 95% CI, 1.07-1.36). Adjusting for potential confounders in 4 different models, a 5–mm Hg increase in nighttime ambulatory DBP was associated with a 13% to 25% increased risk of CHF (HR, 1.16; 95% CI, 1.02-1.31 in model 2; HR, 1.14; 95% CI, 1.01-1.29 in model 3; HR, 1.13; 95% CI, 0.98-1.30 in model 4; and HR, 1.25; 95% CI, 1.01-1.54 in model 5). An increased nighttime ambulatory DBP, as well as a nondipping BP, were also associated with an increased absolute risk of CHF. The incidence of CHF was 2.7 cases higher per 1000 person-years at risk for each 5–mm Hg increment of nighttime ambulatory DBP (ranging from approximately 6 cases per 1000 person-years at risk in the lowest BP groups [50-65 mm Hg] to approximately 30 cases per 1000 person-years at risk in the highest groups [90-100 mm Hg]) and 15.1 cases higher per 1000 person-years at risk for those with nondipping vs normal night-day BP pattern (22.8 vs 7.7 cases).

In the subsample without myocardial infarction before baseline or during follow-up, several BP variables were significant predictors of CHF in unadjusted analyses (model 1; Table 3). Adjusting for antihypertensive treatment (model 2) in this subsample, office-measured SBP, 24-hour ambulatory DBP, nighttime ambulatory SBP and DBP, and nondipping were significant predictors of CHF incidence (Table 3). After further adjustment for the established risk factors for CHF (model 3), office SBP, nighttime ambulatory DBP, and nondipping remained significant predictors of CHF (Table 3). When adding office SBP and DBP to the models (model 4), nighttime ambulatory DBP and nondipping were significant predictors of CHF (Table 4). In analyses including 24-hour ambulatory SBP and DBP in addition to antihypertensive treatment and established baseline risk factors (model 5), nighttime ambulatory DBP and nondipping were significant predictors of CHF in this subsample (Table 4).

None of the investigated interaction terms was significant in the main analysis sample (excluding men with prevalent CHF, valvular disease, or ECG-LVH) or in the sample without interim myocardial infarction.

COMMENT

In this community-based sample of elderly men free of CHF, valvular disease and ECG-LVH at baseline, a nondipping night-day BP pattern, and increased nighttime diastolic BP predicted CHF incidence independent of antihypertensive treatment and established risk factors for CHF, including myocardial infarction during the follow-up. Furthermore, a nondipping night-day BP pattern increased the risk of CHF even after adjusting for conventional office BP measurement. This indicates that nighttime BP patterns may be important in development of CHF and that a traditional office BP measurement does not capture all of the increased risk that an increased nighttime BP conveys.

Twenty-four-hour ambulatory BP has repeatedly been demonstrated to be a powerful predictor of future cardiovascular morbidity and mortality, even after adjustment for conventional office BP.58 Staessen et al5 demonstrated that a nondipping BP pattern was associated with an increased cardiovascular risk and that nighttime BP more accurately predicted cardiovascular events than daytime BP.5 Other studies also have identified a nondipping pattern as a risk factor for cardiovascular disease.21,22 Previous studies have included CHF as a part of a combined end point but have not examined whether a 24-hour ambulatory BP measurement predicts CHF per se. The pathophysiology of atherosclerotic disease and CHF are not the same, and most new-onset CHF is not preceded by myocardial infarction.4,23,24 Therefore, studies of predictors of CHF, accounting properly for myocardial infarction and risk factors for atherosclerotic disease, are warranted.

A reduced circadian BP variation is a common finding in CHF patients, as reviewed by Goyal et al.25 An increased nighttime ambulatory BP has been related to left ventricular filling impairment in cross-sectional studies with limited samples.26,27 In a recent cross-sectional study of patients with hypertension and type 2 diabetes mellitus, diastolic dysfunction was closely related to increased diastolic BP and nondipping.28 However, to our knowledge, there are no previous studies of 24-hour ambulatory BP patterns as predictors of incident CHF.

Several studies have established that nondipping is associated with endothelial dysfunction and hemostasis.2931 Recent studies indicate that endothelial dysfunction is an important component of the pathophysiological mechanisms of CHF, and it has been associated with the progression and prognosis of CHF.32,33 Thus, it is possible that endothelial dysfunction could be a link between increased nocturnal BP and CHF.

Another possible common pathophysiological mechanism is increased sympathetic activity, which is associated with a nondipping BP pattern34,35 and also is a presumed causal factor in CHF.36

One point of controversy is whether the absence of a nighttime BP decrease per se or an increased 24-hour BP load causes organ damage. To address this possibility, 24-hour ambulatory SBP and DBP were included as covariates in addition to antihypertensive treatment and established risk factors (model 5) in both samples. In these analyses, nondipping and nighttime DBP remained significant predictors of CHF, indicating that the nondipping BP pattern per se is important—or is an indicator of an important trait. An example of such a trait could be sleep apnea, a condition that has been suggested to be associated both with CHF37,38 and a nondipping BP pattern.39 However, since this study was not designed to address the possible involvement of sleep apnea, this needs to be examined in future studies.

A possible explanation for observed importance of nighttime ambulatory BP might be that the intraindividual BP variation is lower than that for daytime BP. This may be due to high BP consistency during sleep compared with daytime BP, which is influenced more by physical and psychological activity. However, it should be noted that this study did not primarily address the pathophysiological mechanisms behind the association between nighttime BP pattern and CHF. That has to be examined in other settings.

The strengths of this study include the large, community-based population and the long follow-up period. Furthermore, all CHF cases were validated, limiting the inclusion of false-positive cases. However, there are some limitations to this study. Because we only examined men of the same age with a similar ethnic background, this study has unknown generalizability to women or other age and ethnic groups. However, we did circumvent the powerful effects of age on CHF incidence. Moreover, due to limitations in sample size, men using antihypertensive medications were included in the study population, which may have affected the results through residual confounding, despite the adjustment for specific antihypertensive treatment. Another possible limitation is that multiple statistical testing is present to some degree. However, all analyses were specified a priori and the findings were consistent in all models and in the subsample.

Since evidence of effect modification between some of the BP variables and ECG-LVH was found, the study sample had to be stratified into 2 parts: one stratum with participants with ECG-LVH at baseline and the other without these participants. The stratum consisting of participants with ECG-LVH was unfortunately too small (64 participants, of whom 11 developed CHF during the follow-up) to be analyzed. Thus, the analyses were restricted to the stratum with participants without ECG-LVH, which also might be considered to be a limitation of the study.

Milder, nonhospitalized cases of CHF were not included in our end point, which may be considered a limitation but would tend to bias the results toward the null hypothesis. Since the CHF diagnosis was based on a review of medical records, it was not possible to differentiate between systolic and diastolic heart failure because echocardiography was not available at the time of diagnosis for many of the cases. Thus, we could not examine whether the impact of BP pattern is different for systolic vs diastolic heart failure. Finally, the diagnosis of prevalent CHF at baseline was defined as previous hospitalization for CHF. Since nondipping is associated with prevalent CHF, it is plausible that part of the association between nondipping and incident CHF identified in this study could be a result of undiagnosed prevalent CHF at baseline that only later was severe enough to require hospitalization. However, in a substudy of 343 participants without prevalent CHF, only 5 (1.5%) had an ejection fraction less than 0.40 on echocardiography; only 1 of these 5 had nondipping BP, and 3 developed CHF. Therefore, even if CHF were not diagnosed, it would have been uncommon.

CONCLUSION

In conclusion, a nondipping night-day BP pattern and an increased nighttime BP predicted CHF incidence independent of established risk factors in our large, community-based sample of elderly men. Nondipping was also a risk factor for CHF even when taking conventional office BP measurement into account. Nighttime BP appears to convey additive risk information about CHF, but its clinical value remains to be established in future studies.

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Article Information

Corresponding Author: Erik Ingelsson, MD, PhD, Department of Public Health and Caring Sciences, Geriatrics, Uppsala University, Uppsala Science Park, SE-751 85 Uppsala, Sweden (erik.ingelsson@pubcare.uu.se).

Author Contributions: Dr Ingelsson had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Ingelsson, Björklund-Bodegård, Lind, Ärnlöv, Sundström.

Acquisition of data: Ingelsson, Björklund-Bodegård.

Analysis and interpretation of data: Ingelsson, Björklund-Bodegård, Lind, Ärnlöv, Sundström.

Drafting of the manuscript: Ingelsson, Björklund-Bodegård.

Critical revision of the manuscript for important intellectual content: Björklund-Bodegård, Lind, Ärnlöv, Sundström.

Statistical analysis: Ingelsson, Björklund-Bodegård, Ärnlöv, Sundström.

Obtained funding: Ingelsson.

Administrative, technical, or material support: Björklund-Bodegård.

Study supervision: Lind, Sundström.

Financial Disclosures: Dr Lind is a part-time employee at AstraZeneca Research and Development, Mölndal, Sweden, and a part-time employee at Uppsala University (AstraZeneca has no interests in this project and has not provided any financial support). No other disclosures were reported.

Funding/Support: Funding was provided by Primary Health Care in Uppsala County, the Swedish Heart Lung Foundation (Hjärt-Lungfonden), and the Thuréus Foundation.

Role of the Sponsors: The funding sources had no role in the design and conduct of the study, in the collection, analysis, and interpretation of the data, or in the preparation, review, or approval of the manuscript.

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