Article, Cardiology

Plasma bioactive adrenomedullin as a prognostic biomarker in acute heart failure

a b s t r a c t

Objective: The objective was to evaluate the prognostic performance of a new biomarker, plasma bioactive adrenomedullin (bio-ADM), for short-term clinical outcomes in acute heart failure.

Methods: A multicenter prospective cohort study of adult emergency department (ED) patients suspected of hav- ing acute heart failure was conducted to evaluate the association between plasma bio-ADM concentration and clinical outcomes. The primary outcome was a composite of the following within 30 days: death, cardiac arrest with resuscitation, respiratory failure, Emergency dialysis, acute coronary syndrome, hospitalization N 5 days, and repeat ED visit or hospitalization. Prognostic accuracy was evaluated with a nonparametric receiver operat- ing characteristic curve. In addition, a multivariable logistic regression model was constructed to assess the ad- ditive prognostic performance of bio-ADM while adjusting for other biomarkers routinely used clinically, including B-type natriuretic peptide, cardiac troponin I, creatinine, and sodium concentration.

Results: Two hundred forty-six patients were enrolled, including 85 (34.6%) patients with the primary outcome. Plasma bio-ADM concentrations were higher among patients who experienced the primary outcome (median, 80.5 pg/mL; interquartile range [IQR], 53.7-151.5 pg/mL) compared with those who did not (median, 54.4 pg/mL; IQR, 43.4-78.4 pg/mL) (P b .01). Area under the receiver operating characteristic curve was 0.70 (95% con- fidence interval, 0.63-0.75). After adjusting for the other biomarkers, plasma bio-ADM remained a strong predic- tor of the primary outcome (adjusted odds ratio per IQR change, 2.68; 95% confidence interval, 1.60-4.51).

Conclusions: Bioactive adrenomedullin concentrations at the time of ED evaluation for acute heart failure were predictive of clinically important 30-day outcomes, suggesting that bio-ADM is a promising prognostic marker for further study.

(C) 2015

Introduction

Acute heart failure is one of the most common illnesses treated in emergency departments (EDs) in the United States [1]. After establish- ing an AHF diagnosis and initiating treatment, a major clinical decision

? Funding/Support: This work was supported by National Institutes of Health grants K23GM110469 (to WHS) from the National Institute of General Medical Sciences, and 1R01HL088459 (to ABS), K23 HL085387 (to SPC), and K23HL102069 (to TWB) from

the National Heart, Lung, and Blood Institute. Sphingotec GmbH supplied assays for biomarker measurement.

?? Role of the sponsors: The National Institutes of Health had no role in the design and

conduct of the study, or the collection, management, analysis or interpretation of data. Sphingotec GmbH supplied assays for biomarker measurement; in addition, employees of Sphingotec (OH, JS, AB) participated in the study as investigators and authors.

* Corresponding author. Vanderbilt University, 1313 21st Ave S, 703 Oxford House, Nashville, TN 37220. Tel.: +1 615 836 8047; fax: +1 615 936 3754.

E-mail address: [email protected] (W.H. Self).

facing emergency physicians is whether to pursue hospitalization for inpatient management [2]. Approximately 80% of patients diagnosed with AHF in US EDs are hospitalized [1]. Hospitalization allows for close observation and titration of Intravenous medications, but is also associated with substantially higher cost than outpatient management and places patients at risk for nosocomial complications, such as infec- tions, delirium, and falls [2-5]. Ideally, hospitalization would be reserved for patients at high risk for short-term severe complications of AHF, such as respiratory and renal failure, and those needing specific inpatient therapies, such as intravenous Vasoactive medications [2,3]. However, ensuring clinical stability and estimating the risk of severe Short-term outcomes are problematic with existing Prognostic tools. This prognostic uncertainty plays a significant role in the high admission rate for AHF patients [1-3,6].

A Prognostic biomarker that accurately identified AHF patients at high risk for short-term complications would be invaluable for guiding

http://dx.doi.org/10.1016/j.ajem.2015.10.033

0735-6757/(C) 2015

management decisions, particularly decisions regarding hospitalization. Natriuretic peptides, such as B-type Natriuretic Peptide , are widely used as Diagnostic biomarkers for AHF, but their prognostic performance is suboptimal [7,8]. Although patients with an elevated cardiac troponin, renal dysfunction, and hyponatremia are at increased risk for Severe outcomes, a subset of patients without these risk factors also expe- riences adverse events, suggesting that additional biomarkers are needed [9-12].

Adrenomedullin is a vasodilatory peptide that is elevated in patients with chronic heart failure and may also acutely rise in AHF [13-15]. Elevated levels of midregion proadrenomedullin, a stable fragment derived from the same precursor peptide as adrenomedullin, have previously been shown to predict 90-day mortality among patients presenting with acute shortness of breath, including those with AHF [8,16]. Midregion proadrenomedullin measurement does not dis- tinguish between biologically active amidated adrenomedullin and the nonfunctional adrenomedullin variant containing a glycine-extended C-terminal residue. Recently, a sandwich immunoassay has been developed to specifically measure the biologically active form of adrenomedullin–bioactive adrenomedullin (bio-ADM)–making it feasible to use it as a biomarker in clinical medicine [17-19]. Because of the need for better Prognostic markers in AHF and a biologically plausible association between bio-ADM and AHF severity, we evaluated the prognostic accuracy of plasma bio-ADM for predicting severe, short- term clinical outcomes in patients evaluated in the ED for AHF.

Methods

Study design

We conducted a multicenter prospective cohort study to evaluate plasma bio-ADM as a prognostic biomarker in adults presenting to the ED with signs and symptoms consistent with AHF at 2 university- affiliated tertiary care EDs and 2 community EDs in the United States. We studied single measurements of bio-ADM in plasma collected at the time of initial ED presentation. This study used a subset of patients recruited for the STRATIFY and DECIDE studies [20]. Methodological details of patient recruitment and enrollment have been reported previously [20]. The local institutional review boards of the partici- pating sites approved the study. All enrolled patients provided written informed consent for participation.

Study population

We randomly selected 250 patients enrolled in the STRATIFY/DECIDE cohort between July 20, 2007, and February 4, 2011 [20]. Enrolled patients presented to the ED with acute Cardiopulmonary symptoms, met the Modified Framingham Criteria for AHF [20], and were clinically suspected of having AHF. To ascertain if AHF was truly the cause of each patient’s acute symptoms, a panel of 3 cardiologists reviewed the medical record of each enrolled patient’s ED visit and subsequent hospitalization. Each cardiologist classified the primary cause of symptoms as AHF or not AHF. Two cardiologists initially reviewed each case. If the classifications by the initial 2 cardiologists were discordant, a third cardiologist reviewed the case, with the final diagnosis based on majority. Interrater agreement between the initial 2 reviewers was calculated with Cohen ?. The prognostic accuracy of bio-ADM was evaluated both in the full study population (Suspected AHF Population) and separately in the subset of patients who had AHF confirmed based on the cardiologists’ review (Confirmed AHF Population).

Biomarker measurement

Trained research personnel collected and banked plasma from pa- tients in the ED. Samples were frozen within 2 hours and stored at

-80?C. Plasma bio-ADM concentrations were measured by investigators

blinded to clinical data at Sphingotec GmbH (Hennigsdorf, Germany). The bio-ADM assay has been previously described [19]. In brief, it is a 1-step sandwich chemiluminescence immunoassay based on Acridinium NHS-ester labeling for the detection of human ADM in unprocessed, neat plasma. It uses 2 mouse monoclonal antibodies, one directed against the midregion (solid phase) and the other directed against the amidated C-terminal moiety of ADM (labeled antibody). The assay uses 50 uL of plasma samples/calibrators and 200 uL of labeled detection antibody. The analytical assay sensitivity is 2 pg/mL. In prior work [19], the median bio-ADM concentration of 200 Healthy adults was 20.7 pg/mL; the 99th percentile was 43.0 pg/mL.

Patients also had additional, standard-of-care biomarkers measured while in the ED, including BNP, cardiac troponin I, creatinine, and sodium concentration.

Outcomes

Research personnel ascertained outcomes 30 days (+-2 days) after the index ED visit via phone interviews and medical record review. Two categories were evaluated: severe clinical outcomes and health care utilization outcomes. A severe clinical outcome was defined as the occurrence of >= 1 of the following events: death, cardiac arrest with re- turn of spontaneous circulation, respiratory failure with intubation, emergency dialysis, and acute coronary syndrome. [21] Health care utilization outcomes included hospital length of stay greater than 5 days, return ED visit for AHF within 30 days, and repeat hos- pitalization for AHF within 30 days. Five days was chosen to denote Prolonged LOS because this represents the median hospital LOS for AHF in the United States [1].

The primary study outcome was a composite of all severe clinical and health care utilization outcomes. In secondary analyses, we separately evaluated severe clinical outcomes without the health care utilization outcomes.

Data analysis

Unadjusted analyses

In the primary analysis, we evaluated the prognostic accuracy of plasma bio-ADM concentration in the Suspected AHF Population (all enrolled patients) for a composite of all 30-day outcomes. Bioactive adrenomedullin concentrations in patients who experienced >=1 outcome were compared with those who did not experience any outcomes with the Wilcoxon rank sum test. A nonparametric receiver operating charac- teristic (ROC) curve was constructed to display the performance of bio- ADM to discriminate between patients who did and did not experience a 30-day outcome. We also used the 25th, 50th, and 75th percentile of bio-ADM concentration in the study population as cut points and calcu- lated the proportion of patients with bio-ADM levels greater than and less than these cut points who experienced the primary outcome.

Secondary analyses were also performed after limiting study out- comes to the severe clinical outcomes and limiting the study population to the Confirmed AHF Population. Therefore, 3 secondary analyses were conducted: (1) severe clinical outcomes in the Suspected AHF Popula- tion, (2) all 30-day outcomes in the Confirmed AHF Population, and

(3) severe clinical outcomes in the Confirmed AHF Population.

Multivariable biomarker model

A multivariable logistic regression model was constructed to assess the additive prognostic performance of bio-ADM while adjusting for other biomarker results, including BNP, cardiac troponin I, creatinine, and sodium concentration. Data for bio-ADM, BNP, cardiac troponin I, and creatinine were logarithmically transformed (log-10) because of highly skewed distributions. The study population for this model included suspected AHF patients who had nonmissing data for all 5 bio- markers. The dependent variable was a composite of all 30-day out- comes. Independent variables included bio-ADM log-10 transformed,

BNP log-10 transformed, cardiac troponin I log-10 transformed, creati- nine log-10 transformed, and serum sodium concentration. To allow for comparisons of odds ratios (ORs) among the biomarkers, we reported ORs associated with 1 interquartile range (IQR) change in each biomarker level. To quantify the relative strength of association for each of the

Table 1

Patient characteristics

Characteristic Suspected AHF

Population (n = 246)

Confirmed AHF Population (n = 124)

biomarkers with the outcome, we removed 1 biomarker from the full regression model at a time and calculated the added value of each bio- marker based on the likelihood ratio ?2 test for nested models. A higher likelihood ratio ?2 statistic for a particular biomarker indicated greater contribution to the overall model.

Statistical analyses were conducted with STATA 12.0 (College Station, TX).

Results

Patient characteristics

Two hundred fifty patients were randomly selected from the STRATIFY/ DECIDE cohort [20] for this study. Four patients were excluded, in- cluding 3 patients with insufficient data to classify whether their symp- toms were due to AHF and 1 patient who had insufficient plasma for bio-ADM measurement; the remaining 246 patients were included as the Suspected AHF Population (Fig. 1; Table 1). Of these 246 patients, 124 (50.4%) were confirmed to have AHF based on the cardiologist re- view and were considered the Confirmed AHF Population. The initial 2 cardiologists agreed on whether AHF was the cause of symptoms in 224 (91.1%) cases (? = 0.82 [standard error: 0.060]).

Suspected AHF Population

Among the 246 patients in the Suspected AHF Population, 85 (34.6%) met the primary outcome by experiencing at least 1 of the 30-day out- comes; 18 (7.3%) patients had a severe clinical outcome (Table 2).

All 30-day outcomes (primary outcome)

Plasma bio-ADM concentration was higher in patients who experi-

Age, median (IQR), y 62 (53-74) 65 (56-76.5)

Female, n (%) 106 (43.1) 43 (34.7)

Race/ethnicity

White, non-Hispanic 160 (65.0) 72 (58.1)

Hispanic 1 (0.4) 0

Black 84 (35.2) 52 (41.9)

Other 1 (0.4) 0

Medical insurance (primary)

Private insurance 62 (25.2) 32 (25.8)

Medicare 127 (51.6) 66 (53.2)

Medicaid 33 (13.4) 16 (12.9)

None 24 (9.8) 10 (8.1)

Presenting vital signs

Systolic BP, median (IQR) 144 (127-172) 148 (131-179)

Heart rate, median (IQR) 89 (77-104) 94 (78-109)

Respiratory rate, median (IQR) 20 (18-24) 20 (18-24)

Oxygen saturation, median (IQR) 96 (94-98) 96 (92-98) Presenting symptoms

Shortness of breath 147 (59.8) 73 (58.9.)

Chest pain 54 (22.0) 18 (14.5)

Orthopnea 167 (68.2) 83 (67.5)

Fatigue 203 (82.5) 89 (79.0)

Medical history

Body mass index, median (IQR) 30.7 (25.5-38.1) 30.0 (24.9-36.1)

Current smoker, n (%)

41 (16.7)

20 (16.1)

Chronic heart failure, n (%)

145 (58.9)

85 (68.6)

Prior myocardial infarction, n (%)

75 (30.5)

40 (32.3)

Valvular heart disease, n (%)

51 (20.7)

25 (20.2)

Hypertension, n (%)

188 (76.4)

99 (79.8)

Diabetes mellitus, n (%)

106 (43.1)

57 (46.0)

Chronic pulmonary disease, n (%)

79 (32.1)

27 (21.8)

Chronic renal disease, n (%)

45 (18.3)

26 (21.0)

Laboratory results

Sodium, median (IQR) [mEq/L] 139 (137-141) 140 (138-141)

Creatinine, median (IQR) [mg/dL] 1.2 (0.92-1.70) 1.40 (1.13-1.90)

Blood urea nitrogen, median (IQR) [mg/dL] 20 (12-30) 22 (15-34)

Hemoglobin, median (IQR) [g/dL] 12.4 (11.0-13.6) 12.4 (10.8-13.7)

Cardiac troponin I, median (IQR) [ng/mL] 0.01 (0-0.04) 0.03 (0.01-0.06)

enced at least one 30-day outcome (median, 80.5 pg/mL; IQR, 53.7- 151.5 pg/mL) compared with those who did not (median, 54.4 pg/mL;

B-type natriuretic peptide, median (IQR) [pg/mL]

329 (82-1005) 863 (410-1718)

IQR, 43.4-78.4 pg/mL) (P b .01). Area under the ROC curve was 0.70 (95% confidence interval [CI], 0.63-0.75) (Fig. 2A). The 25th, 50th, and 75th percentile of plasma bio-ADM concentration in the Suspected AHF Population was 46.4, 60.7, and 92.5 pg/mL, respectively. Propor- tions of patients with bio-ADM concentrations greater than and less than each of these cut points who experienced the Composite outcome are shown in Table 3.

Severe clinical outcomes

After limiting the outcome of interest to only severe clinical out- comes, plasma bio-ADM concentration was significantly higher in

Fig. 1. Flow diagram of patient enrollment.

Admitted to hospital, n (%) 199 (80.9) 119 (96.0)

BP: blood pressure.

patients who experienced the outcome (median, 89.9; IQR, 53.5-186.6 pg/mL) compared with those who did not (median, 59.5 pg/mL; IQR, 45.8-89.7 pg/mL) (P = .01). Area under the ROC curve was 0.68 (95%

Table 2

Patient outcomes

30-d outcome

Suspected AHF Population

Confirmed AHF Population

(n = 246)

(n = 124)

Severe clinical outcomes

Death

14 (5.7)

10 (8.1)

Cardiac arrest with ROSC

4 (1.6)

4 (3.2)

Respiratory failure

2 (0.8)

1 (0.8)

Emergency dialysis

2 (0.8)

2 (1.6)

Acute coronary syndrome

2 (0.8)

1 (0.8)

>= 1 Severe clinical outcome

18 (7.3)

13 (10.5)

(secondary outcome)

Health care utilization outcomes

Hospital LOS N 5 d

65 (26.4)

54 (43.6)

Return ED visit for AHF

20 (8.1)

19 (15.3)

Return hospitalization for AHF

19 (7.7)

18 (14.5)

>= 1 Health care utilization outcome

78 (31.7)

66 (53.2)

>= 1 Any 30-d outcome (primary outcome)

85 (34.6)

71 (57.3)

ROSC: return of spontaneous circulation.

Fig. 2. Receiver operating characteristic curves showing the Predictive performance of bio-ADM to identify patients with the study outcomes: (A) Suspected AHF Population with a com- posite of all 30-day outcomes; (B) Suspected AHF Population with only severe clinical outcomes; (C) Confirmed AHF Population with a composite of all 30-day outcomes; (D) Confirmed AHF Population with only severe clinical outcomes. The 25th, 50th, and 75th percentiles of bio-ADM concentration for each population are displayed on the ROC plots.

CI, 0.62-0.74) (Fig. 2B). Bioactive adrenomedullin levels for patients with no outcomes, health care utilization outcomes, and severe clinical outcomes are illustrated in Fig. 3.

Confirmed AHF Population

Among the 124 patients in the Confirmed AHF Population, 71 (57.3%) experienced at least 1 of the 30-day outcomes, including 13 (10.5%) with a severe clinical outcome (Table 2). Plasma bio-ADM con- centration was higher in those who experienced at least 1 of the 30-day outcomes (median, 91.8 pg/mL; IQR, 56.0-167.8 pg/mL) than those who did not (median, 69.7 pg/mL; IQR, 46.4-84.6 pg/mL) (P b .01). Area under the ROC curve was 0.67 (95% CI, 0.59-0.76) (Fig. 2C). When only considering severe clinical outcomes, bio-ADM remained a predic- tor of outcomes (Fig. 2D).

Multivariable biomarker model

The multivariable logistic regression model included 151 patients in the Suspected AHF Population who had ED measurements for all 5 bio- markers; 61(40.4%) of these patients experienced the composite 30-day outcome. Both bio-ADM (adjusted odds ratio per 1 IQR change, 2.68; 95% CI, 1.60-4.51) and BNP (adjusted odds ratio per 1 IQR change, 3.06; 95% CI, 1.34-7.00) were significantly associated with the outcome in the multivariable model, with bio-ADM (likelihood ratio ?2: 17.70) contributing more to overall model fit than BNP (likelihood ratio ?2: 7.56) (Table 4).

Discussion

This is the first study to evaluate plasma bio-ADM in patients with AHF and suggests it may be a useful prognostic biomarker. Our study

Table 3

Proportion of patients who experienced a composite of all 30-day outcomes based on bio-ADM concentration cut points

Bio-ADM b cut point

Bio-ADM >= cut point

Bio-ADM cut point

Patients, n

Patients with outcome, n (%)

Patients, n

Patients with outcome, n (%)

Suspected AHF Population (n = 246)

46.4 pg/mL [25th %tile]

61

10 (16.4)

185

75 (40.5)

60.7 pg/mL [50th %tile]

123

32 (26.0)

123

53 (43.1)

92.5 pg/mL [75th %tile]

185

47 (25.4)

61

38 (62.3)

Confirmed AHF Population (n = 124)

53.2 pg/mL [25th %tile]

31

13 (41.9)

93

58 (62.4)

75.0 pg/mL [50th %tile]

62

29 (46.8)

62

42 (67.7)

115.8 pg/mL [75th %tile]

93

45 (48.4)

31

26 (83.9)

Selected bio-ADM cut points represent the 25th, 50th, and 75th percentile of bio-ADM concentration in the study populations.

Fig. 3. Box plots of plasma bio-ADM concentration by outcome category among the

(A) Suspected AHF Population and (B) Confirmed AHF Population. The y-axis of each plot is displayed on a logarithmic scale. The center of each box plot represents the median, with the box denoting the IQR, the upper and lower whiskers representing 1.5 times the IQR greater than and less than the 75th and 25th percentile, respectively, and dots noting outliners beyond the whiskers.

has 2 important findings. First, higher bio-ADM levels were associated with increased risk for important 30-day outcomes. Second, bio-ADM was an independent risk factor for clinical outcomes in a multivariable model including other biomarkers clinicians currently use when evalu- ating AHF patients, including BNP, cardiac troponin I, creatinine, and sodium concentration. This suggests potential complementary roles for bio-ADM and BNP in the risk stratification of AHF patients.

We evaluated the predictive performance of plasma bio-ADM for

several short-term outcomes. Initially, we used a composite of a broad

range of outcomes clinicians find important when deciding on disposi- tion for a patient in the ED [2,3,6,22-24]. These outcomes included mortality, morbidity, and health care utilization, such as Prolonged hospitalization and repeat presentations for AHF. The rationale for in- cluding health care utilization outcomes stems from the concept that ED AHF patients who undergo a prolonged hospitalization or rapidly return to the hospital after an ED visit are likely poor candidates for outpatient management. Acknowledging that hospital LOS and repeat presentations may be driven by factors other than AHF severity, we also evaluated the prognostic performance of bio-ADM for an outcome limited to severe clinical events, including 30-day mortality, cardiac arrest, respiratory failure, emergency dialysis, and acute coronary syndrome. Bioactive adrenomedullin maintained similar prognostic performance both with (ROC area under the curve = 0.70) and without (ROC area under the curve = 0.68) health care utilization end points included in the composite outcome of interest.

Providing clinicians with rapid and accurate prognostic information for AHF patients at the time of ED evaluation has the potential to improve clinical care [2,20,23,24]. Currently, approximately 80% of patients with suspected AHF in US EDs are hospitalized with little atten- tion to an individual patient’s risk for clinical decompensation or poten- tial benefit of hospitalization [1,2,20,23,24]. A reliable prognostic biomarker could help guide clinicians to an aggressive management strategy with intravenous medications and hospitalization selectively for AHF patients most likely to benefit from it.

Because of the heterogeneity of AHF, involvement of multiple organ

systems, and diverse precipitants leading to acute decompensation, no single biomarker provides comprehensive risk stratification [22]. Accounting for this broad range of physiological disturbances with a multibiomarker panel for AHF prognosis may be an approach to improve risk stratification. Bioactive adrenomedullin is a promising new candidate for an AHF biomarker panel. It is a mediator of vascular control and marker of vascular dysregulation, which is a hallmark of AHF exacerbations [10]. Although it has similar biological activity to the natriuretic peptides, bio-ADM responds to different stimuli in the peripheral circulation and therefore likely provides complementary information to BNP [10]. Prior work suggests that cardiac troponin, renal function, and Serum sodium concentration may also help differen- tiate high- and low-risk patients with AHF [9-11]. Initial evaluation in this study suggests that bio-ADM provides predictive information inde- pendent of these other markers. Additional work with larger cohorts is indicated to explore how bio-ADM may be incorporated into a panel of multiple biomarkers for AHF risk stratification.

Limitations

This study was a secondary analysis of the a Multicenter cohort study [20]. This was a relatively small study conducted at a 4 hospitals in the United States. Additional study with larger sample sizes and diverse settings is needed to further adjust for potential confounders and more thoroughly evaluate the additive prognostic information provided by bio-ADM above other markers. Single measurements of bio-ADM were evaluated in this study; evaluation of serial measure- ments is planned.

Conclusions

In this study of 246 ED patients with suspected AHF, single measure- ments of plasma bio-ADM were significantly associated with clinically important 30-day outcomes. Bioactive adrenomedullin is a promising new biomarker that may add important prognostic information for pa- tients with AHF. Further study is indicated to robustly evaluate bio-ADM in larger sample sizes both as a single biomarker and as a component of multimarker panels.

Table 4

Results of univariate and multivariate logistic regression models evaluating 5 biomarkers as predictors of the composite 30-day outcome in patients evaluated for AHF

Variable

df

Univariate

Multivariate

LR ?2

P

OR (95% CI)

Added LR ?2

P

Adjusted OR (95% CI)

Log10 bio-ADM (per IQR change)

1

20.52

b.001

2.62 (1.65-4.17)

17.70

b.001

2.68 (1.60-4.51)

Log10 BNP (per IQR change)

1

12.75

b.001

3.24 (1.62-6.52)

7.56

.006

3.06 (1.34-7.00)

Log10 troponin I (per IQR change)

1

2.20

.138

1.45 (0.88-2.40)

0.15

.70

1.12 (0.63-1.98)

Log10 creatinine (per IQR change)

1

1.73

.188

1.25 (0.89-1.76)

0.42

.52

0.88 (0.58-1.31)

Sodium (per IQR change)

1

0.59

.444

1.16 (0.78-1.74)

1.70

.19

1.34 (0.86-2.08)

Adjusted OR: OR adjusted for all other biomarkers. Added likelihood ratio (LR) ?2: added value analysis based on nested regression models. Log10: data transformed logarithmically using base-10. df: degrees of freedom. LR: likelihood ratio.

Acknowledgments

We would like to thank Karen F. Miller, RN, and Susan K. Roll, RN, for their dedication to this project.

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