Chemotherapy-related symptoms and exercise adherence in older patients with myeloid neoplasms.

PURPOSE: Exercise may ameliorate treatment-related symptoms, but older adults have lower exercise adherence compared to their younger counterparts due to treatment-related symptoms. METHODS: We recruited older patients with myeloid neoplasms receiving chemotherapy to a pilot study of a mobile health exercise intervention. Participants entered their steps and resistance data into the app daily, and symptom data twice a week, over an 8-12 week period. In this proof-of-concept analysis, we used a linear mixed-effects model to assess the association of symptoms from the previous week with exercise adherence in the current week among older adults with myeloid neoplasms. RESULTS: Mean age was 74.3 (SD = 5.0) years (N = 7). At baseline, patients on average walked 2564 daily steps (SD = 1816), which increased to 2967 (SD = 3448) post-intervention. Patients on average performed 3.5 (SD = 2.6) days of resistance training weekly, with mean duration of 21.5 min (SD = 11.6) and rated perceived exertion of 3.68 (SD = 1.78) on a 0-10 scale. Lower average steps in the current week was associated with greater interference with daily activities from pain (ß = - 203.13, p = 0.05), memory (ß = - 492.29, p = 0.09), numbness (ß = - 353.57, p = 0.07), and sadness (ß = - 403.03, p = 0.09) in the previous week. Similarly, lower average resistance minutes in the current week were associated with greater pain, sadness, and anxiety in the previous week. CONCLUSIONS: We found that greater pain, sadness, and anxiety were associated with lower exercise adherence. Symptom monitoring and management in older adults with myeloid neoplasms receiving chemotherapy can promote exercise adherence and in turn improve symptoms. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04035499. Registered 7/29/2019.

Sex-Specific Absolute Delta Thresholds for High-Sensitivity Cardiac Troponin T.

BACKGROUND: Sex differences in high-sensitivity cardiac troponin (hs-cTn) concentrations from healthy populations have led to the establishment of sex-specific upper reference limits for hs-cTn assays. This study assessed the performance of sex-specific delta (i.e., changes in concentrations) thresholds for the hs-cTnT assay for ruling in acute myocardial infarction (AMI) in different emergency department (ED) populations. METHODS: This retrospective study consisted of 2 cohorts (Cohort 1 derivation and Cohort 2 validation). Cohort 1 consisted of 18 056 ED patients who had serial hs-cTnT measured using a 0-h/3-h algorithm at a US medical center, with Cohort 2 consisting of 1137 ED patients with 0-h/3-h sampling at a Canadian medical center. The primary outcome was AMI diagnosis with sex-specific deltas derived based on the Youden index and specificity estimates (i.e., ≥90%) in Cohort 1 and validated in Cohort 2. RESULTS: In Cohort 1, 42% of all patients had 0-h hs-cTnT above the sex-specific 99th percentile. Males had higher 0-h hs-cTnT (median 17 ng/L) and absolute deltas (median 2 ng/L) than females (0-h median 11 ng/L, P < 0.0001; deltas median 1 ng/L, P < 0.0001) in non-AMI patients but not in patients with AMI. For ruling in AMI, the sex-specific delta thresholds based on 90% specificity (14 ng/L for males, 11 ng/L for females) performed best and resulted in 91% diagnostic accuracy in both males and females. The sex-specific delta thresholds yielding high specificity estimates were confirmed in the validation data set. CONCLUSIONS: Sex-specific absolute delta thresholds can be used to rule in AMI and are robust across different study populations.

Neural orientation distribution fields for estimation and uncertainty quantification in diffusion MRI.

Inferring brain connectivity and structure in-vivo requires accurate estimation of the orientation distribution function (ODF), which encodes key local tissue properties. However, estimating the ODF from diffusion MRI (dMRI) signals is a challenging inverse problem due to obstacles such as significant noise, high-dimensional parameter spaces, and sparse angular measurements. In this paper, we address these challenges by proposing a novel deep-learning based methodology for continuous estimation and uncertainty quantification of the spatially varying ODF field. We use a neural field (NF) to parameterize a random series representation of the latent ODFs, implicitly modeling the often ignored but valuable spatial correlation structures in the data, and thereby improving efficiency in sparse and noisy regimes. An analytic approximation to the posterior predictive distribution is derived which can be used to quantify the uncertainty in the ODF estimate at any spatial location, avoiding the need for expensive resampling-based approaches that are typically employed for this purpose. We present empirical evaluations on both synthetic and real in-vivo diffusion data, demonstrating the advantages of our method over existing approaches.

Trajectories of physical well-being among adults with acute myeloid leukemia.

ABSTRACT: Patients with acute myeloid leukemia (AML) often undergo physical decline leading to negative outcomes. Identification of distinct trajectories may help guide clinical decision-making and supportive care interventions. We built group-based trajectory models (GBTM) to find trajectories of change in the Functional Assessment of Cancer Therapy Physical Well-Being (FACT-PWB) subscale (up to 5 time points over 0 to 200 days of follow-up) using data from adults with newly diagnosed AML in 4 supportive care studies. We also estimated the association of baseline characteristics (age, marital status, education, AML risk, baseline FACT-PWB, depression, and anxiety) with group membership. Among 343 patients with ≥2 FACT-PWB scores, mean age was 69.6 years (standard deviation, 12.1); most had intermediate-risk AML (n = 178 [51.8%]), received intensive treatment (n = 244 [71.1%]), and died during follow-up (n = 199 [58.0%]). The GBTM with 4 distinct trajectories showed the best fit. The largest group (n = 153 [45.0%]) showed slight improvement, whereas the smallest (n = 8 [2.4%]) experienced early decline with later improvement. Baseline FACT-PWB was the only characteristic statistically significantly associated with group membership. Adults with AML show distinct trajectories of physical well-being, and many experience some decline. Exploring trajectories of self-reported and objective physical function may inform decision-making and interventions. These trials were registered at www.ClinicalTrials.gov as #NCT02975869, #NCT03310918, and #NCT03372291.

Associations of interleukin-6 with functional trajectories in older adults with cancer: Findings from the Health, Aging, and Body Composition Study.

BACKGROUND: Elevated markers of inflammation, such as interleukin-6 (IL-6), are associated with aging, cancer, and functional decline. We assessed the association of pre-diagnosis IL-6 levels with post-diagnosis functional trajectories among older adults with cancer. Black and White participants experience different social structures, therefore we sought to understand whether these associations differ between Black and White participants. METHODS: We conducted secondary analysis of the Health Aging, Body, and Composition (ABC) prospective longitudinal cohort study. Participants were recruited from 4/1997 to 6/1998. We included 179 participants with a new cancer diagnosis and IL-6 level measured within 2 years before diagnosis. Primary endpoint was functional measures (self-reported ability to walk 1/4, 20-meter gait speed). Nonparametric longitudinal models were used to cluster the trajectories; multinomial and logistic regressions to model associations. FINDINGS: Mean age was 74 (SD 2.9); 36 % identified as Black. For self-reported functional status, we identified 3 clusters: high stable, decline, low stable. For gait speed, we identified 2 clusters: resilient, decline. The relationship between cluster trajectory and IL-6 was different between Black and White participants (p for interaction<0.05). For gait speed, among White participants, a greater log IL-6 level was associated with greater odds of being in the decline vs. resilient cluster [Adjusted Odds Ratio (AOR): 4.31, 95 % CI: 1.43, 17.46]. Among Black participants, a greater log IL-6 levels were associated with lower odds of being in the decline vs. resilient cluster (AOR: 0.49, 95 % CI: 0.10, 2.08). Directionality was similar for self-reported ability to walk » mile (high stable vs. low stable). Among White participants, a higher log IL-6 level was associated numerically with greater odds of being in the low stable vs. high stable cluster (AOR: 1.99, 95 % CI: 0.82, 4.85). Among Black participants, a higher log IL-6 level was associated numerically with lower odds of being in the low stable cluster vs. high stable cluster (AOR: 0.78, 95 % CI: 0.30, 2.00). INTERPRETATION: The association between IL-6 levels and functional trajectories of older adults differed by race. Future analyses exploring stressors faces by other minoritized racial backgrounds are needed to determine the association between IL-6 and functional trajectories. PANEL: RESEARCH IN CONTEXT: Evidence before this study: Previous research has shown that aging is the greatest risk factor for cancer and older adults with cancer experience a higher burden of comorbidities, increasing their risk of functional decline. Race has also been shown to be associated with increased risk for functional decline. Black individuals are exposed to more chronic negative social determinants, compared to White individuals. Previous work has shown that chronic exposure to negative social determinants leads to elevated levels of inflammatory markers, such as IL-6, but studies investigating the relationship between inflammatory markers and functional decline are limited. Added value of this study: Authors of this study sought to understand the association between pre-diagnosis IL-6 levels and functional trajectories post-diagnosis in older adults with cancer, and whether these associations differed between Black and White participants with cancer. Authors decided to utilize the data from the Health, Aging and Body Composition (Health ABC) Study. The Health ACB study was a prospective longitudinal cohort study that has a high representation of Black older adults and collected inflammatory cytokines and physical function data over time. Implications of all available evidence: This work adds to the literature by providing an opportunity to study the difference in the relationships between IL-6 levels and functional trajectories between older Black and White participants with cancer. Identifying factors associated with functional decline and its trajectories may inform treatment decision making and guide development of supportive care interventions to prevent functional decline. Additionally, given the disparities in clinical outcomes for Black individuals, a better understanding of the difference in functional decline based on race will allow more equitable care to be distributed.

Optimized Diffusion Imaging for Brain Structural Connectome Analysis.

High angular resolution diffusion imaging (HARDI) is a type of diffusion magnetic resonance imaging (dMRI) that measures diffusion signals on a sphere in q-space. It has been widely used in data acquisition for human brain structural connectome analysis. To more accurately estimate the structural connectome, dense samples in q-space are often acquired, potentially resulting in long scanning times and logistical challenges. This paper proposes a statistical method to select q-space directions optimally and estimate the local diffusion function from sparse observations. The proposed approach leverages relevant historical dMRI data to calculate a prior distribution to characterize local diffusion variability in each voxel in a template space. For a new subject to be scanned, the priors are mapped into the subject-specific coordinate and used to help select the best q-space samples. Simulation studies demonstrate big advantages over the existing HARDI sampling and analysis framework. We also applied the proposed method to the Human Connectome Project data and a dataset of aging adults with mild cognitive impairment. The results indicate that with very few q-space samples (e.g., 15 or 20), we can recover structural brain networks comparable to the ones estimated from 60 or more diffusion directions with the existing methods.

Does unconscious socioeconomic bias influence tele-evaluation of obstructive sleep apnea? An exploratory analysis.

STUDY OBJECTIVES: We examined the association between a patient's income and a provider's ability to identify risk for obstructive sleep apnea (OSA) when assessed in-person versus via telemedicine. METHODS: We utilized data from a randomized interrater reliability study of 58 patients who were referred to a university sleep center. Participants volunteered their annual income bracket as part of data collection, although raters were blinded to these data. We assessed the inter-method reliability between the clinical impressions of a telemedicine rater and those of an in-person rater for pretest probability of OSA, stratified by income levels. RESULTS: Inter-method reliabilities, assessed using weighted kappa, were 0.83, 0.24, and 0.66 for subjects with low (<$50,000/year), moderate ($50,000-$100,000/year) and high (>$100,000) incomes, respectively. The kappa statistics were significantly different (p = 0.005) between the low and moderate income groups. CONCLUSIONS: There was a significant difference in the reliability values of telemedicine versus in-person assessments between the low and middle income brackets. This is despite the raters being unaware of the patients' income levels. This association might suggest possible unconscious bias in evaluating for OSA. With telemedicine in early development, it is important to create processes that will minimize bias that might result from patients' economic disparities.