Muscle Mass and Serum Creatinine Concentration by Race and Ethnicity among Hemodialysis Patients

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Abstract

Significance Statement

Serum creatinine is a product of skeletal muscle metabolism. Differences in serum creatinine concentration between Black and non-Black individuals have been attributed to differences in muscle mass but have not been thoroughly examined. Furthermore, other race and ethnic groups have not been considered. If differences in body composition explain differences in serum concentration by race or ethnicity, then estimates of body composition could be used in eGFR equations rather than race. Adjustment for intracellular water (ICW) as a proxy of muscle mass among patients with kidney failure in whom creatinine clearance should minimally influence serum concentration does not explain race- and ethnicity-dependent differences.

Background

Differences in serum creatinine concentration among groups defined by race and ethnicity have been ascribed to differences in muscle mass. We examined differences in serum creatinine by race and ethnicity in a cohort of patients receiving hemodialysis in whom creatinine elimination by the kidney should have little or no effect on serum creatinine concentration and considered whether these differences persisted after adjustment for proxies of muscle mass.

Methods

We analyzed data from 501 participants in the A Cohort Study to Investigate the Value of Exercise in ESKD/Analyses Designed to Investigate the Paradox of Obesity and Survival in ESKD study who had been receiving hemodialysis for >1 year. We examined the independent associations among race and ethnicity (Black, Asian, non-Hispanic White, and Hispanic), serum creatinine, and ICW (L/m²), a proxy for muscle mass, derived by whole-body multifrequency bioimpedance spectroscopy, using multivariable linear regression with adjustment for several demographic, clinical, and laboratory characteristics. We examined the association of race and ethnicity with serum creatinine concentration with and without adjustment for ICW.

Results

Black, Asian, and Hispanic patients had higher serum creatinine concentrations (+1.68 mg/dl [95% confidence interval (CI), 1.09 to 2.27], +1.61 mg/dl [95% CI, 0.90 to 2.32], and +0.83 [95% CI, 0.08 to 1.57], respectively) than non-Hispanic White patients. Overall, ICW was associated with serum creatinine concentration (0.26 mg/dl per L/m² ICW; 95% CI, 0.006 to 0.51) but was not statistically significantly different by race and ethnicity. Black, Asian, and Hispanic race and ethnicity remained significantly associated with serum creatinine concentration after adjustment for ICW.

Conclusion

Among patients receiving dialysis, serum creatinine was higher in Black, Asian, and Hispanic patients than in non-Hispanic White patients. Differences in ICW did not explain the differences in serum creatinine concentration across race groups.

Introduction

Use of equations to estimate GFR has facilitated and standardized the detection and management of kidney disease. Estimates of GFR (eGFR) commonly used in clinical practice are typically derived from equations that rely on the serum creatinine concentration and include adjustment for age, sex, and, in some cases, for Black (versus non-Black) race.^1,2 Until recently, equations included an adjustment for Black race because serum creatinine concentrations are higher among Black than among White persons at a given GFR measured using exogenous filtration markers.³ Differences in serum creatinine concentrations by race have been attributed by some to differences in muscle mass and creatinine generation (without evidence thereof), and this difference provided a rationale for the use of a race coefficient in GFR estimating equations.

GFR estimating equations for Japanese, Chinese, and Thai cohorts have also required race adjustments, suggesting that the question of whether differences in serum creatinine concentrations are related to differences in muscle mass may be relevant for persons of races other than Black and White.^4–6 On the other hand, serum creatinine-based GFR estimating equations used in the United Kingdom, Brazil, parts of Africa, and Australia have not typically adjusted for race.^7–13 Racial and ethnic diversity is increasing in the United States. Furthermore, there is increasing recognition that race is a social rather than a biological construct and that considering race in estimation of GFR may introduce or exacerbate disparities in recognition and treatment of CKD.^14,15 Therefore, understanding the reason(s) for differences in serum creatinine and/or eGFR by race could help to improve diagnosis and management of kidney disease and other conditions for which therapeutic strategies might be influenced by kidney function. Serum creatinine is a product of skeletal muscle metabolism; differences in serum concentration among Black and non-Black individuals have been attributed to muscle mass. These assumptions have not been thoroughly examined. Furthermore, other race and ethnic groups have not been considered. If differences in body composition were to explain differences in serum concentration by race or ethnicity, then including estimates of body composition in eGFR equations rather than race would be a logical and more equitable solution. We hypothesized that, among patients with kidney failure in whom the serum creatinine concentration should be minimally influenced by creatinine clearance, adjustment for proxies of muscle mass would not adequately explain race- and ethnicity-dependent differences in serum creatinine.

Methods

Study Design and Participants

This study examined participants enrolled in the A Cohort Study to Investigate the Value of Exercise in ESKD/Analyses Designed to Investigate the Paradox of Obesity and Survival in ESKD study. To be eligible, participants had to have received maintenance hemodialysis for more than 3 months at one of seven centers in the San Francisco Bay Area or seven centers in the Atlanta, Georgia, metropolitan area from 2009 to 2011,¹⁶ be older than 18 years, and be able to provide consent in English or Spanish. For this analysis, we included only participants (N=501) who had been on dialysis for more than 1 year to reduce residual creatinine clearance as a potential confounder. The study was approved by the University of California San Francisco Committee on Human Research and the Emory University Institutional Review Board.

Data Collection

Study coordinators conducted an interview with participants, performed measurements of body composition, and abstracted clinical and laboratory data from medical records. Laboratory data reported were from a single time point. Participants were asked to identify their race and ethnicity. We obtained demographic and medical history information through chart review and linkage with the ESKD Medical Evidence Report (Form Centers for Medicare and Medicaid Services-2728). At the time of this study, all major global manufacturers have standardized creatinine calibration to be traceable to an isotope dilution mass spectrometry reference. Most creatinine-based eGFR equations used isotope dilution mass spectrometry–traceable creatinine.¹⁷

Body Composition

Study coordinators measured height using a stadiometer and weight in kilograms.¹⁶ We used the ImpediMed SFB7 multifrequency bioimpedance spectroscopy (BIS) device (ImpediMed, San Diego, CA), which scans 256 frequencies between 4 and 1000 HkHz, to examine body composition. We obtained ten body composition measurements in rapid succession for each assessment, and we assessed the reproducibility of measurements by Cole–Cole resistance and reactance plots.^18,19 The Cole–Cole plots are a visual representation of the data across the full spectrum of frequency. Each measurement generates a plot that we visually inspected and the software automatically evaluated. Measures were only accepted when the plots indicated good quality.

BIS uses differences in tissue-specific conductivity to estimate intracellular water (ICW) and extracellular water (ECW) compartments, with ICW largely housed in skeletal muscle. We performed whole-body BIS immediately before a midweek dialysis session, minimizing the risk of wide variations in interdialytic weight gain as previously described.²⁰ Multifrequency BIS determines intracellular and extracellular volumes independently, allowing for its use as a valid method for assessing volume status and muscle mass among hemodialysis patients.^21–27 Previous studies have shown direct correlation between ICW and serum creatinine concentration.^28–31

Analysis

We compared characteristics of participants by race and ethnicity using Kruskal–Wallis tests for continuous variables and chi-squared tests for categorical variables. We used multivariable linear regression modeling to determine whether race and ethnicity (Black, Asian, Non-Hispanic White, and Hispanic) were associated with serum creatinine concentration. We used linear regression modeling to examine the association of BIS-derived ICW indexed to height in meters squared, our proxy for muscle mass, with serum creatinine concentration. We then examined whether race and ethnicity (Black, Asian, Non-Hispanic White, and Hispanic) were associated with differences in BIS-derived ICW, adjusting for factors known to influence muscle mass including age and sex. Finally, we used multivariable linear regression modeling to determine whether race and ethnicity (Black, Asian, Non-Hispanic White, and Hispanic) were associated with serum creatinine concentration after adjusting for ICW. These models were adjusted for factors known to influence serum creatinine concentration including age, sex, diabetes mellitus, vintage (time since starting maintenance dialysis), and also used urea-based Daugirdas II formula as an indicator of the efficiency of solute clearance (expressed as Daugirdas II, Kt/V_urea).³² For all models, we compared patients of Black, Asian, and Hispanic race and ethnicity with Non-Hispanic White patients. To test for differences among patients in all race and ethnicity categories, we then conducted least squares means analysis with Tukey–Kramer multiple comparisons tests on fully adjusted models to examine differences in estimated muscle mass by race and ethnicity and then to examine differences in serum creatinine by race and ethnicity adjusting for muscle mass.

We conducted sensitivity analysis of final models. We examined the contribution of vascular disease and dialysis adequacy (Daugirdas II, spKt/V_urea) to final models. We examined the interaction of age×race and ethnicity to explore the contribution of differences in body mass throughout the age span. We also examined the interaction of dialysis vintage×race and ethnicity to explore potential difference related to time on dialysis in our final models. We used SAS version 9.4 (SAS institute, Cary, NC) for all analyses, and two-tailed nominal P values <0.05 were considered to indicate statistical significance.

Results

Participant Characteristics

The cohort comprised 501 participants: 318 Black (63%), 70 Asian (14%), 55 Non-Hispanic White (11%), and 58 Hispanic (12%) individuals. The majority were men (58%); the mean age was 57±14 years, and the mean vintage was 5.2 years (Table 1). Black and Hispanic participants were younger than their Non-Hispanic White and Asian counterparts. Dialysis vintage was similar among groups except that Black participants had been on dialysis for a longer period. All participants exceeded minimum targets for dialysis solute clearance (adequacy) as recommended by the Kidney Disease Outcomes Quality Initiative with mean Daugirdas II, spKt/V_urea of 1.60±0.34, and serum albumin concentrations were similar for all groups. Black patients had higher serum creatinine concentrations than their Asian, non-Hispanic White, and Hispanic counterparts (Table 1).

Table 1.

Participant characteristics, overall and by race and ethnicity

Characteristic	All N=501	Non-Hispanic White N=55	Black N=318	Hispanic N=58	Asian N=70	P Value
Demographic
Age, yr, mean±SD	57±14	63±15	55±13	57±17	60±14	<0.0001
Men, n (%)	295 (58)	37 (67)	179 (56.3)	38 (65.5)	37 (53)	0.22
Clinical and laboratory
Diabetes, n (%)	250 (50%)	28 (51%)	151 (47.5%)	28 (57%)	38 (54.3%)	0.49
Dialysis duration, yr, mean±SD	5.16±4	3.72±2.36	5.85±4.60	3.98±2.71	4.14±3.3	0.0002
Daugirdas II, spKt/Vurea	1.60±0.34	1.60±0.35	1.52±0.25	1.74±0.57	1.76±0.39	<0.0001
Serum creatinine, mg/dl, mean±SD	8.81±2.62	7.09±2.26	9.18±2.56	8.32±2.39	8.92±2.76	<0.0001
Serum phos, g/dl, mean±SD	5.60±1.8	5.43±1.9	5.52±1.4	5.48±1.66	5.70±2.1	0.57
Serum albumin, g/dl, mean±SD	4.02±0.3	3.97±0.3	4.01±0.3	4.07±0.3	4.10±0.3	0.02
Body composition
BMI, kg/m2, mean±SD	28±7	28±7	28±7	28±5	26±6	0.007
≤25 kg/m2, n (%)	196 (39)	20 (36)	116 (36.5)	20 (35)	40 (57)	0.008
>25 to <30 kg/m2, n (%)	149 (30)	17 (31)	91 (28.6)	25 (43)	16 (23)
≥30 kg/m2, n (%)	156 (31.0)	18 (33)	111 (35)	13 (22)	14 (20)
ICW, L/m2, mean±SD	22±5.2	21±4	22.5±5.4	20±4	19.5±5	<0.0001
ECW, L/m2, mean±SD	19±4.6	19.4±4.0	19.8±4.6	17.7±4.0	16.8±4.6	<0.0001
Fat mass, kg/m2, mean±SD	0.30±0.10	0.32±0.09	0.29±0.11	0.31±0.08	0.28±0.09	0.11

ICW, intracellular water; ECW, extracellular water.

Association of Race and Ethnicity with Serum Creatinine

Black, Asian, and Hispanic patients had higher adjusted serum creatinine concentrations (+1.68 mg/dl [95% confidence interval (CI), 1.09 to 2.27], +1.61 mg/dl [95% CI, 0.90 to 2.32], and +0.83 [95% CI, 0.08 to 1.57], respectively) compared with their non-Hispanic White counterparts in multivariable linear regression analysis after adjusting for clinical characteristics and laboratory parameters (Figure 1). Male sex and higher serum albumin and phosphate concentrations (proxies of dietary intake and nutritional status) were associated with higher serum creatinine concentrations, whereas older age and history of diabetes mellitus were associated with lower serum creatinine concentrations. History of peripheral vascular disease was not associated with serum creatinine concentrations.

Figure 1.

Mean differences in serum creatinine by race and ethnicity (N=501). *Adjusted for age, sex, serum phosphorus, serum albumin, Daugirdas II, spKt/V_urea, history of diabetes, and dialysis duration using multivariable linear regression. ICW, intracellular water (muscle mass proxy). Figure 1 can be viewed in color online at www.jasn.org.

Association of Race and Ethnicity with ICW

Unadjusted estimated muscle mass was higher among Black participants (22.0±5.4 L/m²) than among Asian (19.5±5.0 L/m²), non-Hispanic White (21±4.0 L/m²), and Hispanic participants (20.0±4.0 L/m²) (Table 1). After adjusting for covariates (including age and sex), estimated muscle mass did not significantly differ by race and ethnicity (Table 2). As expected, male sex and younger age were associated with higher estimated muscle mass.

Table 2.

Mean differences in intracellular water by race and ethnicity (N=501)

	Difference in ICW, L/m2 (95% CI)a
	Referent Group
Race and Ethnicity	Non-Hispanic White	Black	Hispanic
Black	+0.2 (−0.2 to 0.7)
Hispanic	−0.05 (−0.6 to 0.5)	−0.3 (−0.7 to 0.1)
Asian	−0.1 (−0.6 to 0.4)	−0.3 (−0.7 to 0.0)	−0.1 (−0.6 to 0.5)

ICW, intracellular water (muscle mass proxy); CI, confidence interval.

^aAdjusted for age and sex using multivariable linear regression.

Association of Race and Ethnicity with Serum Creatinine after Adjustment for Body Composition

Serum creatinine correlated directly with ICW in adjusted analysis (+0.26 mg/dl per L/m² ICW; 95% CI, 0.006 to 0.51). Race and ethnicity remained associated with serum creatinine concentration after adjustment for ICW (Figure 1). Differences among race and ethnicity groups were not substantially attenuated by addition of ICW/m² to the models, with Black participants having serum creatinine concentrations that were similar to Asian participants (0.03 mg/dl; 95% CI, 0.6 to −0.50) and higher than that of their Non-Hispanic White (+1.65 mg/dl; 95% CI, 1.06 to 2.23) and Hispanic (+0.83 mg/dl; 95% CI, 0.26 to 1.40) counterparts. In sensitivity analysis, interaction terms for either age with race and ethnicity and dialysis vintage with race and ethnicity did not alter the associations observed.

Discussion

Among persons receiving dialysis for 1 year or more in whom serum creatinine concentration would not be expected to be affected by glomerular filtration or tubular secretion, Black, Asian, and Hispanic participants had higher serum creatinine concentrations than non-Hispanic White participants. After further adjusting for ICW as an indicator of muscle mass, these differences persisted. Thus, it is unlikely that muscle mass explains the observed differences in serum creatinine among members of different race and ethnicity groups.

In addition to confirming that Black patients receiving dialysis had higher serum creatinine concentrations than non-Hispanics White patients, we also observed higher serum creatinine concentrations among Asian and Hispanic patients. Several previous studies examining differences in serum creatinine by race solely focused on differences among Black and White patients. Such observations led to the use of kidney function estimating equations that included adjustments for Black race. However, combining members of other racial and ethnic groups into a single non-Black category may have masked differences among other racial and ethnic groups. Differences in kidney function estimation among non-Black racial ethnic groups have also been observed among persons not receiving dialysis.³³ These findings support the need for population diversity in future studies of existing and/or novel endogenous markers of kidney function.³⁴

After controlling for younger age, Black patients in our study did not have substantially higher ICW than non-Hispanic White patients. Previous studies examining differences in muscle mass by race have largely focused on healthy individuals. In one study comparing 8810 National Health and Nutrition Examination Survey participants (1999–2004), appendicular muscle mass derived by dual-energy x-ray absorptiometry was higher among non-Hispanic Black than non-Hispanic White individuals, and a larger proportion of non-Hispanic White individuals were classified as having low muscle mass compared with non-Hispanic Black individuals.³⁵ Even among 3075 generally healthy individuals of advanced age (70–79 years), lean muscle mass was higher among Black than non-Hispanic White Americans.³⁶ However, in the setting of CKD, there is a high prevalence of muscle wasting, particularly among individuals with ESKD.^37–39 The absence of significantly higher ICW among Black participants and the persistently higher serum creatinine concentration among Black participants even after adjustment for ICW suggest that the observed differences in serum creatinine concentration may be related to factors other than what we studied.

Previous studies examining the contribution of muscle mass to differences in serum creatinine concentration have used anthropometric measurement or single frequency bioimpedance analysis (BIA) to estimate muscle mass.^31,40 In a study among 170 healthy Brazilian individuals, anthropometric measures were used as an estimate of muscle mass to examine the relation with serum creatinine concentrations. However, anthropometric measures, which include midarm circumference, midarm muscle circumference, and calf circumference measurements, are imprecise and may vary by hydration status.⁴¹ Thus, it is difficult to generalize study results to chronic disease cohorts in which overhydration may be misclassified as preserved or greater muscle mass on the basis of having excess ECW.⁴² Among a diverse cohort of 3009 individuals with ESKD in the United States, differences in serum creatinine concentration by race were linked to BIA-derived surrogates of muscle mass after adjusting for markers of nutrition, chronic disease burden, and sex.³¹ In this analysis, higher serum creatinine concentration among Black individuals was not explained by higher estimated muscle mass. Some clinicians argued that on the basis of the known limitations of single frequency BIA (50 Hz) in separating ICW from ECW, the results should be interpreted with caution.⁴³ However, the primary analysis of that study used phase angle as a proxy of muscle mass, which may minimize those limitations.

Previous studies among non-US cohorts have cited differences in body composition as the reason for needing a race coefficient for Asian adults. In a cohort of 763 Japanese adults, inulin clearance, creatinine clearance, and serum creatinine were used to examine the need for a race coefficient.⁴ In that study, both the mean serum creatinine concentration and the estimated creatinine excretion rate were lower for Japanese adults compared with estimates for North American White adults, and a race adjustment was found to better approximate measured kidney function. Similarly, Ma and colleagues examined plasma creatinine concentrations and GFR measured using ¹²⁵I-iothlamate among 684 Chinese individuals with CKD to improve the diagnostic performance of the Modification of Diet for Renal Disease equations for estimating kidney function.⁵ Again, study investigators found improved accuracy when a coefficient for Chinese race and ethnicity was added to the Modification of Diet for Renal Disease equations, and they presumed that the need for such a correction related to differences in muscle mass. However, they did not directly examine this possibility. Although our study showed that serum creatinine concentration was higher among Asian than among non-Hispanic White and Hispanic patients, muscle mass did not entirely explain the observed difference. Apart from examining the role of muscle mass as a predictor of serum creatinine concentration, there are other factors related to creatinine generation/metabolism (e.g., diet) and elimination (e.g., tubular secretion), particularly in the setting of chronic disease, that may affect serum creatinine concentration.

A key strength of this study was the inclusion of participants without substantial creatinine clearance by the kidneys. Our study findings raise questions about whether variations in creatine content and rate of conversion to creatinine relative to muscle size (or quality) exist or whether other extra-renal routes of elimination of creatinine may be more important determinants of differences in creatinine concentration. It is plausible that CKD may affect creatinine synthesis, leading to differences in creatine stores, but studies that have directly examined this possibility are limited.⁴⁴ Disturbances in creatine metabolism have been associated with other diseases affecting skeletal muscle.⁴⁵ On the other hand, creatinine is not completely eliminated by the kidneys, and the degree to which creatinine is metabolized or eliminated by other organ systems is not well understood. In a study of eight patients with kidney failure, three of whom were anephric, investigators found that radiolabeled plasma creatinine concentration declined in the absence of any appreciable kidney function and concluded that 16%–66% of creatinine produced was metabolized or excreted through extra-kidney routes.⁴⁶ Mitch and colleagues further examined creatinine metabolism in nine patients with steady-state CKD and found that creatinine metabolism correlated directly with creatinine production, but the rate of creatinine metabolism varied widely (0–76 µmol/d per kg). Study investigators posited that differences in clearance by the liver and gut contributed to variability in serum creatinine concentrations.⁴⁷

Our study had several limitations. Our Northern California and Atlanta cohorts do not mimic the racial distribution across the US dialysis population nor the 2020 US Census, which may limit the generalizability of our findings.^48,49 Studies have estimated muscle mass in different ways with anthropometric measures, dual-energy x-ray absorptiometry, or single frequency BIA.^31,40,50 With advanced CKD, fluctuations in hydration status may influence estimates.^{23,26,27,42,51,52} We used whole-body multifrequency BIS, a measure of body composition that is less sensitive to hydration status, to examine whether differences in muscle mass by race and ethnicity might explain racial and ethnic differences in serum creatinine concentrations. We did not exclude patients receiving nutritional supplements. The nutritional status of the A Cohort Study to Investigate the Value of Exercise in ESKD/Analyses Designed to Investigate the Paradox of Obesity and Survival in ESKD study participants may not be reflective of the general US dialysis population. Although we adjusted for comorbid conditions that we expect to most strongly influence muscle mass, our sample size and data sources limited inclusion of all potential comorbidities. We did not measure residual kidney function, although we specifically chose patients with dialysis vintage of at least 1 year to reduce confounding by residual kidney function. Nevertheless, our results do show muscle mass is not the sole determinant of differences in serum creatinine by race and ethnicity. Differences in dietary intake and extra-renal elimination/metabolism of creatinine across race and ethnicity groups may be a potential alternative explanation for differences in serum creatinine by race and ethnicity; future investigation should explore these possibilities.

In summary, among a prevalent cohort of patients receiving maintenance dialysis in whom residual kidney function should contribute very little to serum creatinine concentration, we observed higher serum creatinine concentrations among members of all non-White race and ethnicity categories compared with Non-Hispanic White patients in pairwise comparisons. The results of this work address recent calls by the National Kidney Foundation and American Society of Nephrology Task Force to include diversity in studies and to examine non-GFR determinants of serum concentration of endogenous kidney filtration markers.⁵³

Disclosures

G.M. Chertow reports consultancy: Akebia, Ardelyx, AstraZeneca, Calico, Gilead, Miromatrix, Reata, Sanifit, Unicycive, and Vertex; ownership interest: Ardelyx, CloudCath, Durect, DxNow, Eliaz Therapeutics, Outset, Physiowave, PuraCath, Renibus, and Unicycive; research funding: CSL Behring, NIAID, and NIDDK; advisory or leadership role: Board of Directors, Satellite Healthcare, Co-Editor, Brenner & Rector's The Kidney (Elsevier); and other interests or relationships: DSMB service—Bayer, Gilead, Mineralys, NIDDK, and ReCor. C. Delgado reports membership of the GUIDE-US Anemia Council Scientific; advisory board for Glaxo Smith Kline; and serves on the editorial board for the American Journal of Kidney Disease. B. Grimes reports ownership interest: Abbot and Amgen. K.L. Johansen reports membership of the Steering Committee for the GSK ASCEND studies; consultancy for Akebia and Vifor Pharma; and serves as an Associate Editor for the JASN. N.R. Powe reports honoraria from Hennepin Healthcare Research Institute, Patient Centered Outcomes Research Institute, Robert Wood Johnson Foundation, and Vanderbilt University and scientific advisor or membership with Hennepin Healthcare Research Institute, Patient Centered Outcomes Research Institute, Robert Wood Johnson Foundation, the JASN as an Associate Editor, and Vanderbilt University. Because K.L. Johansen and N.R. Powe are editors of the JASN, they were not involved in the peer review process for this manuscript. A guest editor oversaw the peer review and decision-making process for this manuscript.

Funding

C. Delgado's work is supported with the resources and the use of facilities at the San Francisco VA Medical Center. K.L. Johansen is supported by K24DK085153 from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK).

Author Contributions

Conceptualization: Glenn M. Chertow, Cynthia Delgado, Barbara Grimes, Kirsten L. Johansen, Neil R. Powe.

Data curation: Barbara Grimes.

Formal analysis: Cynthia Delgado, Barbara Grimes, Kirsten L. Johansen.

Investigation: Cynthia Delgado.

Methodology: Cynthia Delgado, Kirsten L. Johansen.

Supervision: Kirsten L. Johansen.

Writing – original draft: Cynthia Delgado.

Writing – review & editing: Glenn M. Chertow, Kirsten L. Johansen, Neil R. Powe.

Data Sharing Statement

All data are included in the manuscript and/or supporting information.