Consensus guidelines advise simultaneous heart kidney transplantation (SHK) in heart candidates with an estimated glomerular filtration rate (eGFR) of <30 mL/min/1.73 m 2 . We hypothesize that a ...significant fraction of such patients would not need an SHK, even though a graded increase in mortality and end-stage kidney disease (ESKD) would be seen with decrements in eGFR.
United Network of Organ Sharing data for isolated heart transplants between 2000 and 2020 were divided into two groups based on eGFR at transplant (≤20 mL/min/1.73 m 2 and 21-29 mL/min/1.73 m 2 ). The primary outcome was mortality and secondary outcome was ESKD posttransplant. Cox regression and cumulative incidence competing risk methods were used to compare risk of mortality and ESKD.
There was no difference in mortality (adjusted hazard ratio aHR 0.82 95% confidence interval, CI: 0.60-1.11, P = 0.21) or ESKD (aHR 1.01 95% CI: 0.49-2.09, P = 0.96) between the two groups (≤20 versus 21-29). The overall incidence of ESKD for the entire cohort at 1, 5, and 10 y were 1.5%, 9.5%, and 20%.
Although risk of ESKD is highest in heart candidates with an eGFR <30 mL/min/1.73 m 2 , <10% of patients reach ESKD within 5 y' and most will recover significant renal function posttransplant. More refined selection criteria are required to identify candidates for SHK.
The aim of this study was to explore the nonlinear relationships between natural amenities and health at the intersection of sociodemographic characteristics among primary care patients with chronic ...conditions.
We used survey data from 3409 adults across 119 US counties. PROMIS-29 mental and physical health summary scores were the primary outcomes. The natural environment (measured using the County USDA Natural Amenities Scale (NAS)) was the primary predictor. Piecewise spline regression models were used to explore the relationships between NAS and health at the intersection of sociodemographic factors.
We identified a nonlinear relationship between NAS and health. Low-income individuals had a negative association with health with each increase in NAS in high-amenity areas only. However, White individuals had a stronger association with health with each increase in NAS in low-amenity areas.
In areas with low natural amenities, more amenities are associated with better physical and mental health, but only for advantaged populations. Meanwhile, for disadvantaged populations, an increase in amenities in high-amenity areas is associated with decreases in mental and physical health. Understanding how traditionally advantaged populations utilize the natural environment could provide insight into the mechanisms driving these disparities.
Destination accessibility is an important measure of the built environment that is associated with active transport and body mass index (BMI). In higher density settings, an inverse association has ...been consistently found, but in lower density settings, findings are limited. We previously found a positive relationship between the density of nonresidential destinations (NRD) and BMI in a low-density state. We sought to test the generalizability of this unexpected finding using data from six other states that include a broader range of settlement densities.
We obtained the address, height, and weight of 16.9 million residents with a driver's license or state identification cards, as well as the location of 3.8 million NRDs in Washington, Oregon, Texas, Illinois, Michigan, and Maine from Dun & Bradstreet. We tested the association between NRDs∙ha−1 within 1 km of the home address, and self-reported BMI (kg∙m−2). Visualization by locally-weighted smoothing curves (LOWESS) revealed an inverted U-shape. A multivariable piecewise regression with a random intercept for state was used to assess the relationship.
After accounting for age, sex, year of issue, and census tract social and economic variables, BMI correlated positively with NRDs in the low-to-mid density stratum (β = +0.005 kg∙m−2/nonresidential building∙ha−1; 95% CI: +0.004,+0.006) and negatively in the mid-to-high density stratum (β = −0.002; 95% CI: −0.004,-0.0003); a significant difference in slopes (P < 0.001).
BMI peaked in the middle density, with lower values in both the low and high-density extremes. These results suggest that the mechanisms by which NRDs are associated with obesity may differ by density level.
•We spatially linked 16.9 million driver's license and state ID records with nonresidential building data and census data.•We found a nonlinear relationship between nonresidential destinations and BMI.•BMI peaked in the mid-density range, with lower values on low and high extremes.•The mechanisms by which nonresidential destinations are associated with obesity likely differ with density.
Summary
Heart transplantation is a viable option for end stage heart disease but long‐term complications such as chronic kidney disease are being increasingly recognized. We sought to investigate the ...effect of change in estimated glomerular filtration rate (eGFR) during the heart transplant waitlist period on post‐transplant mortality and end stage kidney disease (ESKD). We analysed the United Network of Organ Sharing heart transplant database from 2000 to 2017. Multivariable Cox regression with restricted cubic splines and cumulative incidence competing risk (CICR) methods were used to compare the effects of change in eGFR on mortality and ESKD, respectively. A total of 19 412 patients met our inclusion criteria. Mortality increased with increasing loss of eGFR (adjusted hazard ratio increased from 1.02 confidence interval (CI) 1.01–1.04, P = 0.008 for 10% loss to 1.15 (CI 1.06–1.26, P = 0.001) for 50% loss of eGFR. Similarly, risk of ESKD also increased monotonically with increasing loss of renal function subdistribution hazard ratio increased from 1.12 (CI 1.09–1.14, P < 0.001) to 2.0 (CI 1.74–2.3, P < 0.001) as loss of eGFR increased from 10% to 50%. Overall, we found that loss of >10% of eGFR resulted in higher risk of mortality and higher risk of ESKD.
Background and Objective
Previous studies have described the effect of sociodemographic factors on early development. We describe development of a simple cumulative risk index (CRI) based on four ...sociodemographic factors and explore the concurrent and predictive relationship of this index to a measure of the cognitive home environment in early childhood and to later school functioning.
Methods
This was a secondary data analysis of children from an urban pediatrics clinic. Baseline data were collected at 10–23 months (n = 324) with primary follow‐up 6 months later at 18–35 months (n = 179) and secondary follow‐up at 8–10 years (n = 68). A CRI score was derived at baseline using maternal education, marital status, race/ethnicity and child insurance. Baseline and primary follow‐up included three subscales of the STIMQ, a measure of the cognitive home environment. Effectiveness of CRI was examined using analysis of variance (ANOVA) with linear contrasts. Chi‐square examined differences in school function between children from CRI high‐risk (CRI 3–4) and low‐risk (CRI 0–2) families.
Results
CRI had a negative impact in early childhood on STIMQ subscale scores (p < 0.007–0.05) that increased as the number of risk factors increased (p < 0.05). Significantly more children from high‐risk families (CRI 3–4) were rated as having poor school performance than children from low‐risk families (CRI 0–2) (p < 0.05).
Conclusions
We showed that a practice‐friendly CRI, based on characteristics typically available in the medical record, could help identify families less likely to support development concurrently at 1 year of age and predictively at 2–3 years. School functioning at 8 to 10 years was also significantly better in children with a low CRI at 1 year. The CRI could be a useful tool for both clinicians and researchers needing a simple tool for risk assessment.
The effect of donor‐to‐recipient (D‐R) age mismatch in adult heart transplant population is not clearly described, and we undertook this study to determine the impact of age mismatch on mortality. ...Heart transplant recipients from 2000 to 2017 were identified using the United Network of Organ Sharing database. The cohort was divided into three groups: donor age within 5 years of recipient age (Group 1), donors >5 years younger than recipient (group 2), and donors >5 years older than recipients (Group 3). We also evaluated if this finding changed by recipient age. Twenty eight thousand, four hundred and eleven patients met the inclusion criteria. Compared to group 1, the adjusted hazard ratio (aHR) for mortality for group 2 was 0.91 (0.83–0.99, p value <.039) and for group 3 was 1.36 (1.21–1.52, p value <.001); however, when looking at recipient age as continuous variable, receiving a younger heart was protective only for recipients younger than 45 years of age, and receiving a heart transplant from an older donor was detrimental only in recipients aged 25–35.
Purpose
This study was designed to: (1) characterize longitudinal patient-reported outcomes (PROs) between breast cancer patients undergoing lumpectomy and mastectomy and (2) compare return to ...baseline scores at 3 months and 6 months postoperatively.
Methods
Newly diagnosed breast cancer patients seen at an academic breast center between June 2019 and February 2021 were invited to participate in longitudinal PRO surveys at their initial clinic visit. If willing to participate, patients were emailed the validated BREAST-Q™ questionnaire at the initial clinic visit (baseline), 2 weeks after surgery, and then every 3 months for the first year. We used linear mixed models to estimate the differences in slopes over time between lumpectomy and mastectomy for each PRO measure. Pearson’s Chi-square tests with Yates’ continuity correction were used to compare proportions of patients who return to baseline PRO scores.
P
< 0.05 was considered significant.
Results
Of 164 patients invited to participate, 100 (61%) completed a baseline survey and were included in analyses. Mastectomy patients had significantly greater decreases in breast satisfaction (
P
= 0.002), psychosocial well-being (
P
< 0.0001), and sexual well-being (
P
< 0.0001) over time compared with lumpectomy patients. Both surgical groups reported a decrease in physical well-being, although the decline was more significant in lumpectomy patients (
P
= 0.005). At 3 months and 6 months after surgery, significantly larger proportions of lumpectomy patients returned to their baseline breast satisfaction, psychosocial well-being, and physical well-being compared with mastectomy patients.
Conclusions
Understanding how outcomes important to patients change over the care continuum can provide opportunities for early intervention and may prevent debilitating long-term morbidities of treatment.
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