Increasingly, dementia caregiver interventions are informed by acceptance-based approaches such as Acceptance and Commitment Therapy. These interventions promote psychological skills like psychological flexibility and value-based living. Less is known how these constructs interact within well-established caregiver stress processes. We examined a moderated mediation model (N = 161 dementia caregivers; PROCESS Procedure; SPSS Release 4.1), with BPSD frequency (Revised Memory and Behavior Problems Checklist) predicting depressive symptoms (10-item CES-D), mediated via caregiver burden (short Burden inventory). The moderator was the Values Questionnaire, and we controlled for gender, caregiver duration, age, income, and education. Results: revealed that the indirect effect of BPSD on depressive symptoms through caregiver burden was weakened through higher progress toward values (moderated mediation significant at p < .05). Committed action toward values signify caregivers' success at balancing care-related stress with other priorities. Interventions that build skills in values-based living have promise for caregivers, offering healthier ways to adjust to being a caregiver.
NARRATIVE SUMMARY: The formation of a patient-reported outcomes registry to provide information about functional changes and pain among adults with cerebral palsy (CP) was identified as a priority to address the gap in knowledge and practice about aging and CP. The Cerebral Palsy Research Network collaborated with consumers, clinicians, and researchers to create an interactive internet platform, MyCP, to host a Community Registry. MyCP also provides educational programming, access to webinars and community forums, and fitness opportunities. The registry hosts surveys on function and pain for adults with CP, which provide cross-sectional and longitudinal data about these important issues. Surveys include previously validated measures with normative values that have been used with other populations and investigator developed questions. Enrollment in the registry is growing but needs to reflect the population of adults with CP, which limits generalizability. Future initiatives involve strategies to increase consumer engagement and enrollment.
BACKGROUND AND AIMS: A cardiovascular disease polygenic risk score (CVD-PRS) can stratify individuals into different categories of cardiovascular risk, but whether the addition of a CVD-PRS to clinical risk scores improves the identification of individuals at increased risk in a real-world clinical setting is unknown. METHODS: The Genetics and the Vascular Health Check Study (GENVASC) was embedded within the UK National Health Service Health Check (NHSHC) programme which invites individuals between 40-74 years of age without known CVD to attend an assessment in a UK general practice where CVD risk factors are measured and a CVD risk score (QRISK2) is calculated. Between 2012-2020, 44,141 individuals (55.7% females, 15.8% non-white) who attended an NHSHC in 147 participating practices across two counties in England were recruited and followed. When 195 individuals (cases) had suffered a major CVD event (CVD death, myocardial infarction or acute coronary syndrome, coronary revascularisation, stroke), 396 propensity-matched controls with a similar risk profile were identified, and a nested case-control genetic study undertaken to see if the addition of a CVD-PRS to QRISK2 in the form of an integrated risk tool (IRT) combined with QRISK2 would have identified more individuals at the time of their NHSHC as at high risk (QRISK2 10-year CVD risk of ≥10%), compared with QRISK2 alone. RESULTS: The distribution of the standardised CVD-PRS was significantly different in cases compared with controls (cases mean score .32; controls, -.18, P = 8.28×10-9). QRISK2 identified 61.5% (95% confidence interval [CI]: 54.3%-68.4%) of individuals who subsequently developed a major CVD event as being at high risk at their NHSHC, while the combination of QRISK2 and IRT identified 68.7% (95% CI: 61.7%-75.2%), a relative increase of 11.7% (P = 1×10-4). The odds ratio (OR) of being up-classified was 2.41 (95% CI: 1.03-5.64, P = .031) for cases compared with controls. In individuals aged 40-54 years, QRISK2 identified 26.0% (95% CI: 16.5%-37.6%) of those who developed a major CVD event, while the combination of QRISK2 and IRT identified 38.4% (95% CI: 27.2%-50.5%), indicating a stronger relative increase of 47.7% in the younger age group (P = .001). The combination of QRISK2 and IRT increased the proportion of additional cases identified similarly in women as in men, and in non-white ethnicities compared with white ethnicity. The findings were similar when the CVD-PRS was added to the atherosclerotic cardiovascular disease pooled cohort equations (ASCVD-PCE) or SCORE2 clinical scores. CONCLUSIONS: In a clinical setting, the addition of genetic information to clinical risk assessment significantly improved the identification of individuals who went on to have a major CVD event as being at high risk, especially among younger individuals. The findings provide important real-world evidence of the potential value of implementing a CVD-PRS into health systems.
This paper employs the Analytical Hierarchy Process (AHP) to enhance the accuracy of differential diagnosis for febrile diseases, particularly prevalent in tropical regions where misdiagnosis may have severe consequences. The migration of health workers from developing countries has resulted in frontline health workers (FHWs) using inadequate protocols for the diagnosis of complex health conditions. The study introduces an innovative AHP-based Medical Decision Support System (MDSS) incorporating disease risk factors derived from physicians' experiential knowledge to address this challenge. The system's aggregate diagnostic factor index determines the likelihood of febrile illnesses. Compared to existing literature, AHP models with risk factors demonstrate superior prediction accuracy, closely aligning with physicians' suspected diagnoses. The model's accuracy ranges from 85.4% to 96.9% for various diseases, surpassing physicians' predictions for Lassa, Dengue, and Yellow Fevers. The MDSS is recommended for use by FHWs in communities lacking medical experts, facilitating timely and precise diagnoses, efficient application of diagnostic test kits, and reducing overhead expenses for administrators.
Fever , Humans , Diagnosis, Differential , Fever/diagnosis , Decision Support Techniques , Tropical Medicine/methods , Decision Support Systems, Clinical
Hexagonal boron nitride (h-BN) hosts pure single-photon emitters that have shown evidence of optically detected electronic spin dynamics. However, the electrical and chemical structures of these optically addressable spins are unknown, and the nature of their spin-optical interactions remains mysterious. Here, we use time-domain optical and microwave experiments to characterize a single emitter in h-BN exhibiting room temperature optically detected magnetic resonance. Using dynamical simulations, we constrain and quantify transition rates in the model, and we design optical control protocols that optimize the signal-to-noise ratio for spin readout. This constitutes a necessary step toward quantum control of spin states in h-BN.
Extensive efforts have been dedicated to developing cell-specific targeting ligands that can be conjugated to therapeutic cargo, offering a promising yet still challenging strategy to deliver oligonucleotide therapeutics beyond the liver. Indeed, while the cargo and the ligand are crucial, the third component, the linker, is integral but is often overlooked. Here, we present strain-promoted sydnone-alkyne cycloaddition as a versatile linker chemistry for oligonucleotide synthesis, expanding the choices for bioconjugation of therapeutics while enabling subcellular detection of the linker and payload using nanoscale secondary ion mass spectrometry (NanoSIMS) imaging. This strategy was successfully applied to peptide and lipid ligands and profiled using the well characterized N-acetylgalactosamine (GalNAc) targeting ligand. The linker did not affect the expected activity of the conjugate and was detectable and distinguishable from the labeled cargo. Finally, this work not only offers a practical bioconjugation method but also enables the assessment of the linker's subcellular behavior, facilitating NanoSIMS imaging to monitor the three key components of therapeutic conjugates.
INTRODUCTION: Treatment guideline revision introduced by the National Comprehensive Cancer Network (NCCN) is referred to by about 95% of the United States (US) oncologists in treatment decision-making for stage 1A non-small cell lung cancer. It is vital to account for this factor that affects the standard treatment receipt among stage 1A patients, with about a 75% survival rate if treated on time. The first choice for medically fit patients is lobectomy; however, over the decades since the initial guidelines were published, several medical advances have introduced trends in treatment receipt along with other sociodemographic factors that could help identify survival outcomes associated with treatment receipt. Establishing the role of treatment guideline revision years is important to determine a close to true causal relationship in racial treatment disparities. METHODS: US national cancer registry data for all US counties and historical Area Health Resource Files for the study period 1988-2015 were utilized. Logistic regression analysis was adjusted for clustering of standard errors at the state level and for time-invariant unobserved factors for the year of diagnosis and county. The time-invariant unobservable for each year of diagnosis and county specificity were accounted for by including their dummy variables in the regression model with standard errors clustered at the state level. RESULTS: Black patients, Medicaid beneficiaries, large fringe metropolitan residents, and those diagnosed post-2007 treatment revisions years are less likely to receive lobectomy, which is the standard treatment guideline for medically fit patients. CONCLUSION: The study concludes that there exists a difference in treatment type received among stage 1A NSCLC patients in the US by race, socioeconomic status, and treatment guideline revisions.
BACKGROUND: Relationships of midlife inflammation with late-life mobility and influences of chronic health conditions, race, and social determinants of health (SDoH) on these relationships are poorly understood. METHODS: Among 4758 community-dwelling participants (41% men, 20% Black), high-sensitivity C-reactive protein (hsCRP) was measured over 20+ years: in midlife at study visit 2 (V2: 1990-1992, 47-68 years); at V4 (1996-1998, 53-74 years); and with concurrent late-life 4-m gait speed at V5 (2011-2013, 67-88 years, mean 75 years). SDoH measures included race, the national-rank area deprivation index, education, and income. We examined associations of late-life gait speed with midlife hsCRP (V2 continuous and clinically high ≥3 mg/L), with 20-year hsCRP history from midlife (V2-V5 average continuous hsCRP and clinically high ≥3 mg/L) and with inflammation accumulation (visits and years with high hsCRP). Regression models adjusted for demographic, cardiovascular, and SDoH measures; effect modification by the presence of other common chronic conditions (obesity, diabetes, hypertension) and race were examined, with and without accounting for SDoH. RESULTS: High midlife hsCRP was associated with slower late-life gait speed, even among those without chronic conditions in midlife: -4.6 cm/s (95% CI: -6.4, -2.8). Importantly, sustained high hsCRP was associated with a 20-year slowing of -10.0 cm/s (-14.9, -5.1) among those who never experienced obesity, diabetes, or hypertension over the 20-year period. Associations were similar between Black participants, -3.8 cm/s (-6.9, -0.7) and White participants -3.3 (-4.5, -2.2) per interquartile range of midlife hsCRP; effect modifications by chronic conditions and race were unsupported throughout. Results were robust to accounting for SDoH or otherwise; however, worse SDoH was associated with higher inflammation and slower gait speed in both Black and White participants. CONCLUSIONS: Inflammation in midlife may contribute to clinically meaningful late-life slowing of gait speed, even among otherwise healthy-appearing adults and regardless of race and socioeconomic disadvantage. Regular monitoring and interventions for inflammation may be warranted from midlife.
BACKGROUND: Quantifying the economic burden of cardiovascular disease and stroke over the coming decades may inform policy, health system, and community-level interventions for prevention and treatment. METHODS: We used nationally representative health, economic, and demographic data to project health care costs attributable to key cardiovascular risk factors (hypertension, diabetes, hypercholesterolemia) and conditions (coronary heart disease, stroke, heart failure, atrial fibrillation) through 2050. The human capital approach was used to estimate productivity losses from morbidity and premature mortality due to cardiovascular conditions. RESULTS: One in 3 US adults received care for a cardiovascular risk factor or condition in 2020. Annual inflation-adjusted (2022 US dollars) health care costs of cardiovascular risk factors are projected to triple between 2020 and 2050, from $400 billion to $1344 billion. For cardiovascular conditions, annual health care costs are projected to almost quadruple, from $393 billion to $1490 billion, and productivity losses are projected to increase by 54%, from $234 billion to $361 billion. Stroke is projected to account for the largest absolute increase in costs. Large relative increases among the Asian American population (497%) and Hispanic American population (489%) reflect the projected increases in the size of these populations. CONCLUSIONS: The economic burden of cardiovascular risk factors and overt cardiovascular disease in the United States is projected to increase substantially in the coming decades. Development and deployment of cost-effective programs and policies to promote cardiovascular health are urgently needed to rein in costs and to equitably enhance population health.
Background: Evidence regarding the frequency and timing of treatment for lumbar spinal stenosis (LSS) fails to offer clear consensus. We describe the LSS care journey from initial diagnosis to first surgical intervention. Methods: Using Medicare claims database from 2009 through 2020, we identified patients who were diagnosed with LSS. The use and timing of conservative and surgical treatments during the entire follow-up from the initial diagnosis were reported. Results: Of the 143,849 patients identified, 68% received conservative care within 8.4 months and 25.3% received a surgical or minimally invasive intervention over 5.7 years following initial diagnosis, with 12.6% undergoing open decompression alone, 10.2% undergoing open decompression with fusion, and 5.1% undergoing fusion surgery alone. Fewer than 1% were provided with interspinous spacers or a percutaneous image-guided lumbar decompression. Conclusion: Approximately three-quarters of patients in the study received no surgical or non-invasive interventions for approximately six years following diagnosis with LSS.
The selection of renewable energy technologies is widely based on the economic index levelized cost of electricity (LCOE). However, the LCOE ignores the potential temporal mismatch between electricity generation and actual grid demand: this aspect is accounted for in the new index named actual cost of electricity (ACOE), here proposed. This index provides a more accurate economic assessment of renewable energy, minimizing the number of assumptions to be made and outlining the benefits of including a storage. The proposed index is tested across ten cases encompassing three renewable technologies: wind, photovoltaic, and concentrated solar power. The outcomes show that the actual renewable electricity generation of a plant can be reduced by 40%-50% when accounting for the actual electricity demand, resulting in an ACOE exceeding the LCOE by up to 100/150 $/MWh. In addition, the ACOE enables the identification of breakthrough conditions that make storage adoption economically feasible.
Mental disorders are among the leading causes of global disease burden. To respond effectively, a strong understanding of the structure of psychopathology is critical. We empirically compared two competing frameworks, dynamic-mutualism theory and common-cause theory, that vie to explain the development of psychopathology. We formalized these theories in statistical models and applied them to explain change in the general factor of psychopathology (p factor) from early to late adolescence (N = 1,482) and major depression in middle adulthood and old age (N = 6,443). Change in the p factor was better explained by mutualism according to model-fit indices. However, a core prediction of mutualism was not supported (i.e., predominantly positive causal interactions among distinct domains). The evidence for change in depression was more ambiguous. Our results support a multicausal approach to understanding psychopathology and showcase the value of translating theories into testable statistical models for understanding developmental processes in clinical sciences.
Survivors of adolescent and young adult (AYA, age 15-39 years at diagnosis) cancer are a growing population with the potential to live for many decades after treatment completion. Survivors of AYA cancer are at risk for adverse long-term outcomes including chronic conditions, secondary cancers, impaired fertility, poor psychosocial health and health behaviors, and financial toxicity. Further, survivors of AYA cancer from racially minoritized and low socio-economic status populations experience disparities in these outcomes, including lower long-term survival. Despite these known risks, most survivors of AYA cancer do not receive routine survivorship follow-up care, and research on delivering high-quality, evidence-based survivorship care to these patients is lacking. The need for survivorship care was initially advanced in 2006 by the Institute of Medicine. In 2019, the Quality of Cancer Survivorship Care Framework (QCSCF) was developed to provide an evidence-based framework to define key components of optimal survivorship care. In this commentary focused on survivors of AYA cancer, we apply the QCSCF framework to describe models of care that can be adapted for their unique needs, multi-level factors limiting equitable access to care, and opportunities to address these factors to improve short- and long-term outcomes in this vulnerable population.
The manufacturing of autologous chimaeric antigen receptor (CAR) T cells largely relies either on fed-batch and manual processes that often lack environmental monitoring and control or on bioreactors that cannot be easily scaled out to meet patient demands. Here we show that human primary T cells can be activated, transduced and expanded to high densities in a 2 ml automated closed-system microfluidic bioreactor to produce viable anti-CD19 CAR T cells (specifically, more than 60 million CAR T cells from donor cells derived from patients with lymphoma and more than 200 million CAR T cells from healthy donors). The in vitro secretion of cytokines, the short-term cytotoxic activity and the long-term persistence and proliferation of the cell products, as well as their in vivo anti-leukaemic activity, were comparable to those of T cells produced in a gas-permeable well. The manufacturing-process intensification enabled by the miniaturized perfusable bioreactor may facilitate the analysis of the growth and metabolic states of CAR T cells during ex vivo culture, the high-throughput optimization of cell-manufacturing processes and the scale out of cell-therapy manufacturing.
BACKGROUND: Genetics plays an important role in several medical domains, however, the influence of human leukocyte antigen (HLA) genotype on the development of periprosthetic joint infection (PJI) in total hip arthroplasty (THA) remains unknown. The primary aim of this study was to determine if HLA genotype is associated with the development of bacterial PJI in THA. Secondarily, we evaluated the association between HLA genotype and PJI treatment success. METHODS: A retrospective, matched, case-control study was performed using prospectively collected data from a single institution. A total of 49 patients who underwent primary THA were included, with a mean follow-up of 8.5 years (range, 4.2 to 12.9). The 23 cases (PJI) and 26 controls (no PJI) were matched for age, sex, follow-up, body mass index (BMI), primary diagnosis, and comorbidities (P > 0.05). High-resolution genetic analysis targeting 11 separate HLA loci was performed in all patients using serum samples. The HLA gene frequencies and carriage rates were determined and compared between cohorts. A subgroup analysis of PJI treatment success (18) and failure (5) was performed. Statistical significance was set at P = 0.10 for genetic analysis and at 0.05 for all other analyses. RESULTS: There were four HLA alleles that were significantly associated with the development of PJI. The 3 at-risk alleles included HLA-C*06:02 (OR [odds ratio] 5.25, 95% CI [confidence interval] 0.96 to 28.6, P = 0.064), HLA-DQA1*04:01 (P = 0.096), and HLA-DQB1*04:02 (P = 0.096). The single protective allele was HLA-C*03:04 (OR 0.12, 95% CI 0.01 to 1.10, P = 0.052). There were no specific HLA alleles that were associated with treatment success or failure. CONCLUSION: This study suggests that there are at-risk and protective HLA alleles associated with the development of PJI in THA. To our knowledge, this is the first study to demonstrate an association between patient HLA genotype and the development of PJI. A larger study of the subject matter is necessary and warranted.
BACKGROUND: Neoadjuvant chemotherapy (NAC) use for pancreatic ductal adenocarcinoma (PDAC) has increased, but some patients never get resection following NAC. METHODS: Data from January 2012 to December 2019 for all clinically resectable patients across two health networks were utilized, as well as data from the ACS NCDB registry. Univariate testing, multivariable logistic regression, and survival analyses were employed to evaluate failure to resection after neo-adjuvant chemotherapy. RESULTS: Of the 10 007 registry patients eligible for resection, the resected group was younger (64.6 vs. 69.5 years; p < 0.001) and had a slightly lower mean comorbidity index (0.41 vs. 0.45; p < 0.001) than the nonsurgical group. The nonsurgical group was composed of a higher percentage of Black and Hispanic patients (17.5 vs. 13.1%; p < 0.001). After adjusting for age and comorbidities, the factors associated with decreased probability of resection after NAC were evaluation at a community hospital (OR 2.4), Black or Hispanic race (OR 1.6), areas of increased high school drop-out rates (OR 1.4), and lack of private health insurance (OR 1.3). The median overall survival for nonsurgery was markedly worse than the surgical cohort (10.6 vs. 26.6 months; p < 0.001). The most frequent reasons for a lack of definitive resection were operative upstaging to unresectable (39.6%), patient preference (14.5%), progression on NAC (13.2%), deconditioning or comorbidity severity (12.5%), and nonreferral to a surgeon (8.8%). CONCLUSIONS: Racial, economic, and educational disparities have a considerable influence on the successful completion of a neoadjuvant approach for resectable PDAC. A comprehensive closed or highly collaborative/communicative multidisciplinary neoadjuvant program is optimal for treatment success and completion.
Empirical evidence for a low normal or reference interval for serum prolactin (PRL) is lacking for men, while the implications of very low PRL levels for human health have never been studied. A clinical state of "PRL deficiency" has not been defined except in relation to lactation. Using data from the European Male Ageing Study (EMAS), we analyzed the distribution of PRL in 3,369 community-dwelling European men, aged 40-80 years at phase-1 and free from acute illnesses. In total, 2,948 and 2,644 PRL samples were collected during phase-1 and phase-2 (3 to 5.7 years later). All samples were analysed in the same centre with the same assay. After excluding individuals with known pituitary diseases, PRL ≥ 35 ng/ml, and PRL-altering drugs including antipsychotic agents, selective serotonin reuptake inhibitors, or dopamine agonists, 5,086 data points (2,845 in phase-1 and 2,241 in phase-2) were available for analysis. The results showed that PRL declined minimally with age (slope = -0.02) and did not correlate with BMI. The positively skewed PRL distribution was log-transformed to a symmetrical distribution (skewness reduced from 13.3 to 0.015). Using two-sigma empirical rule (2[]SD about the mean), a threshold at 2.5% of the lower end of the distribution was shown to correspond to a PRL value of 2.98ng/ml. With reference to individuals with PRL levels of 5-34.9 ng/ml (event rate = 6.3%), the adjusted risk of developing type 2 diabetes increased progressively in those with PRL levels of 3-4.9 ng/ml: event rate = 9.3%, OR (95% CI) 1.59 (0.93-2.71), and more so with PRL levels of 0.3-2.9 ng/ml: event rate = 22.7%, OR 5.45 (1.78-16.62). There was also an increasing trend in prediabetes and diabetes based on fasting blood glucose levels was observed with lower categories of PRL. However, PRL levels were not associated with cancer, cardiovascular diseases, depressive symptoms or mortality. Our findings suggest that a PRL level below 3 ng/ml (64 mlU/l) significantly identifies European men with a clinically-important outcome (of type 2 diabetes), offering a lower reference-value for research and clinical practice.
PURPOSE OF REVIEW: This review provides an overview of the current and future role of artificial intelligence (AI) and virtual reality (VR) in addressing the complexities inherent to the diagnosis, classification, and management of headache disorders. RECENT FINDINGS: Through machine learning and natural language processing approaches, AI offers unprecedented opportunities to identify patterns within complex and voluminous datasets, including brain imaging data. This technology has demonstrated promise in optimizing diagnostic approaches to headache disorders and automating their classification, an attribute particularly beneficial for non-specialist providers. Furthermore, AI can enhance headache disorder management by enabling the forecasting of acute events of interest, such as migraine headaches or medication overuse, and by guiding treatment selection based on insights from predictive modeling. Additionally, AI may facilitate the streamlining of treatment efficacy monitoring and enable the automation of real-time treatment parameter adjustments. VR technology, on the other hand, offers controllable and immersive experiences, thus providing a unique avenue for the investigation of the sensory-perceptual symptomatology associated with certain headache disorders. Moreover, recent studies suggest that VR, combined with biofeedback, may serve as a viable adjunct to conventional treatment. Addressing challenges to the widespread adoption of AI and VR in headache medicine, including reimbursement policies and data privacy concerns, mandates collaborative efforts from stakeholders to enable the equitable, safe, and effective utilization of these technologies in advancing headache disorder care. This review highlights the potential of AI and VR to support precise diagnostics, automate classification, and enhance management strategies for headache disorders.
