Conectar
Background
Chronic pain is a major cause of distress and disability, and biomarkers may aid in the assessment and treatment of it. Urine metabolites may be valuable bioindicators that can provide biological insight regarding chronic pain.
Objectives
To investigate the relationship between a multimarker composite measure of metabolites and patient-reported outcomes scores in adults with chronic pain, using data from a pragmatic clinical trial with a sequential, multiple-assignment randomized trial design.
Methods
Self-reported measures and urine samples from 169 active-duty service members with chronic pain were collected. Urine was analyzed using a preestablished panel of metabolites, including four previously identified biomarkers of pain: kynurenic acid, pyroglutamic acid, ethylmalonic acid, and methylmalonate. Multivariable linear regression models—adjusted for participant characteristics such as age and sex—were used to cross-sectionally examine the relationship between 11 patient-reported outcomes (fatigue, sleep-related impairment, anxiety, depression, anger, pain catastrophizing, physical function, pain interference, satisfaction with participation with social roles, pain intensity, and pain impact score) and the four urine metabolites both individually and as a composite (urine metabolite pain indicator, or UMPI). Given the study’s small sample size and exploratory nature, a significance threshold of p ≤ .10 was used for all analyses.
Results
The UMPI showed statistically significant associations with five self-reported measures (fatigue, anxiety, depression, physical functioning, and pain impact score); adjusted Pearson correlations ranged from .18 to .25. Individual metabolite analyses supported these findings, with all relationships between individual metabolites and self-reported measures showing positive associations. Kynurenic acid and ethylmalonic acid showed the strongest associations, each having statistically significant relationships with four individual self-reported measures, while pyroglutamic acid had statistically significant relationships with three self-reported measures and methylmalonate with none. The UMPI demonstrated feasible reliability.
Discussion
Our finding of associations between the UMPI and components of the self-reported measures supports the development of the UMPI and these four urine metabolites as biomarkers for chronic pain outcomes. Further research is planned and will be essential for establishing mechanistic insight and guiding biomarker development within the context of pain management. Background
Due to significant gaps in knowledge around women's health, Congress commissioned the National Academies of Sciences, Engineering, and Medicine (National Academies) to conduct a consensus study on funding allocation, workforce needs, and priority research areas for the National Institutes of Health (NIH).
Objectives
This manuscript summarizes the key points of the new National Academies report on women's health research for NIH, presents the relevance and importance for nursing research, and briefly discusses the need for increased representation of nurse scientists on National Academies panels.
Methods
Beginning in the Fall of 2023, a multidisciplinary panel of 17 experts was convened by National Academies to address gaps in women's health research at NIH. The committee was tasked to identify research priorities for NIH-funded research with a focus on conditions that are female specific, are more common in women, or affect women differently. In addition, the committee was asked to make recommendations on NIH training and education to strengthen the women's health research workforce; changes to NIH structural, systems, and review processes; and allocation of funding to more equitably reflect the burden of disease among women.
Results
The committee found that, from 2013 to 2023, only 8.8% of NIH research dollars focused on women's health research and that basic knowledge about women's physiological, hormonal fluctuations, and chromosomal differences is lacking. Data are also needed to better understand diseases that are female specific, are more common in women, or affect women differently. The committee made eight recommendations for transformative change at NIH related to women's health research.
Discussion
Overall, the report describes the need for transformative change at NIH to advance the science on women's health research and improve outcomes. This includes a comprehensive approach and recommendations that would double the NIH's investment in women's health research, enhance accountability, and provide rigorous oversight, prioritization, and integration of women's health research across NIH. Background
Up to 45% of patients report cancer-related cognitive impairment (CRCI). A variety of characteristics are associated with the occurrence and/or severity of CRCI. However, an important gap in knowledge of risk factors for CRCI is the relative contribution of each factor. The multifactorial model of cancer-related cognitive impairment (MMCRCI) is a conceptual model of CRCI that can be used to evaluate the strength of relationships between various factors and CRCI.
Objectives
The purpose of this study was to use structural regression methods to evaluate the MMCRCI using data from a large sample of outpatients receiving chemotherapy (n = 1,343). Specifically, the relationships between self-reported CRCI and four MMCRCI concepts (i.e., social determinants of health, patient-specific factors, treatment factors, and co-occurring symptoms) were examined. The goals were to determine how well the four concepts predicted CRCI and determine the relative contribution of each concept to deficits in perceived cognitive function.
Methods
This study is part of a larger, longitudinal study that evaluated the symptom experience of oncology outpatients receiving chemotherapy. Adult patients were diagnosed with breast, gastrointestinal, gynecological, or lung cancer; had received chemotherapy within the preceding 4 weeks; were scheduled to receive at least two additional cycles of chemotherapy; were able to read, write, and understand English; and gave written informed consent. Self-reported CRCI was assessed using the attentional function index. Available study data were used to define the latent variables.
Results
On average, patients were 57 years of age, college educated, and with a mean Karnofsky Performance Status score of 80. Of the four concepts evaluated, whereas co-occurring symptoms explained the largest amount of variance in CRCI, treatment factors explained the smallest amount of variance. A simultaneous structural regression model that estimated the joint effect of the four exogenous latent variables on the CRCI latent variable was not significant.
Discussion
These findings suggest that testing individual components of the MMCRCI may provide useful information on the relationships among various risk factors, as well as refinements of the model. In terms of risk factors for CRCI, co-occurring symptoms may be more significant than treatment factors, patient-specific factors, and/or social determinants of health in patients receiving chemotherapy. 
FreshRSS 