Analysis Of Longitudinal Data Research Articles

Nursing researchers'concern about research activities during the COVID-19 pandemic: A secondary analysis of longitudinal survey data in Japan.

The coronavirus disease(COVID-19) pandemic has negatively affected research activities across various fields. This study aimed to determine nursing researchers'concerns about research activities during the COVID-19 pandemic in Japan and subsequent changes brought on by it. For this study, we conducted descriptive statistics and text mining analyses using data from two surveys conducted by the Japan Academy of Nursing Science (JANS) in the early days of the pandemic (first survey: mid-2020) and after 2 years (second survey: early 2022). Concerns about research activities were observed in 89% and 80% of the nursing researchers in the first and second surveys, respectively. Furthermore, concerns about "Difficulty in collecting research data" and "Content and quality of your research" were stronger in the second survey. Text mining analyses revealed that in the first survey, they were concerned about environmental changes and restrictions when proceeding with research during the COVID-19 pandemic, which was unfamiliar at the time. In the second survey, after overcoming environmental changes in the early stages of the pandemic, nursing researchers'concerns shifted to anxiety about the future, such as concerns about degree acquisition, employment and career advancement, and research results. The current study highlights various concerns among nursing researchers regarding research activities that have evolved over time during the pandemic. Academic societies must flexibly construct support measures for nursing researchers when a new infectious disease occurs. Such measures should be sensitive to the prevailing social circumstances and the evolving needs of researchers.

Clinical nSights: A software platform to accelerate real world oncology analyses.

e23316 Background: Real world data analyses are critical to assess drug safety and effectiveness, including in patient populations underrepresented in clinical trials. Significant barriers to performing such analyses remain, including: (1) incomplete access to electronic health record (EHR) data due to patient privacy concerns, (2) lack of data harmonization within and across EHRs, (3) requirements for time- and labor-intensive data curation efforts, and (4) necessity of coding or data science expertise given the absence of user-friendly platforms. We present Clinical nSights, a software platform that addresses these challenges to enable researchers and clinicians to perform rapid, robust, and scalable real world oncology analyses. Methods: With input EHR data from multiple health systems, we developed intuitive user interfaces and a scalable researcher friendly programming environment for real world clinical analytics. We used (1) nCognito, a previously described HIPAA-compliant de-identification algorithm, to de-identify EHRs across data modalities; (2) the combination of a de novo knowledge graph, vector and distribution similarity metrics, and manual review to harmonize data types including but not limited to laboratory tests, disease codes, and drugs; and (3) a series of Bidirectional Encoder Representations from Transformers (BERT) models to perform augmented curation of variables of interest (e.g., cancer staging, tumor biomarkers) from unstructured clinical records. We developed a user interface for users to create and analyze defined patient cohorts. Results: Clinical nSights facilitates intuitive cohort creation via flexible specification of inclusion and exclusion criteria, including options to perform temporal linking between criteria and propensity score matching. The ability to specify criteria documented in de-identified clinical notes expands the repertoire of available features for cohort creation beyond those captured in structured EHR fields, including but not limited to cancer stage and tumor biomarker status (e.g., HER2 status, microsatellite instability). Data harmonization enables scalable longitudinal analyses of laboratory test data across cancer types, including changes in measurements in the years leading up to and following initial cancer diagnosis. Augmented curation improves the coverage of phenotypes including immune-related toxicities of checkpoint inhibitors and symptoms experienced by patients prior to a cancer diagnosis. Using the no-code interface, users can easily quantify and visualize outcomes such as overall survival and hospitalization rates. Conclusions: Clinical nSights addresses important challenges in the collection, curation, and analysis of real world oncology data. By enabling a broad range of users to rapidly generate and test hypotheses, this platform has the potential to significantly improve care delivery and patient outcomes.

Investigating predictors of protein intake in an adult population utilising the National Health and Nutrition Examination (NHANES) Survey in the United States

It is widely accepted that meeting recommended protein intake is protective of muscle mass(1). Insufficient intake is related to accelerated sarcopenia and impaired physical function, contributing to increased mortality and morbidity. The recommended target set by the American dietary guidelines is 0.8 g of protein per kg of body weight, based on data collated by the National Academies published in 2005(2). Currently approximately 50% of women and 30% of men do not meet these targets(3). It is of public interest to analyse current patterns of intake to allow for improved strategy through awareness of factors that impact protein intake.To investigate the factors which determine an individual’s protein intake and how they can be used to predict daily intake.A secondary data analysis of longitudinal data collected in the National Health and Nutrition Examination Survey (NHANES) between 2011 and 2020 has been carried out(4). Data was accessed from the public domain on the Centers for Disease Control and Prevention (CDC) website. The study protocol received approval from the research ethics review board of the National Center for Health Statistics (NCHS) of the CDC. Average protein intake has been calculated and participant demographics reported. STATA software has been used to carry out a bivariate regression of factors associated with protein intake, an adjusted multivariate regression analysis and a parsimonious model.19601 participants (52.4% women) aged 20 and over had valid protein data. Adjusted regression analysis generated three model fits, with the parsimonious model excluding BMI categories and household income had a statistically insignificant impact on protein intake. Men consumed 23.99g more protein per day compared to women (p<0.001: 95% CI 23.09 to 24.89). Individuals over 65 consumed 13.92g less protein per day compared to those aged 20-35 years old (p<0.001: 95% CI − 15.25 to −12.59). Mexican American individuals consumed 7.47g more protein than Non-Hispanic White individuals (p<0.001: 95% CI 5.89 to 9.04) and Non-Hispanic White individuals consumed 2.95g more protein compared to non-Hispanic Black individuals (p<0.001: 95% CI 4.13 to 1.77). Those with the lowest educational attainment consumed 10.77g less protein compared to individuals with a college degree (p<0.001: 95% CI −12.79 to −8.74). From 2011 to 2020, there was a gradual decline in protein intake which is statistically significant when comparing 2011/12 with 2015/16 and 2017/2020.Protein intake can be predicted by an individual’s gender, age, ethnicity, level of education attainment and time period. This study informs policymakers that individuals aged 65 and above are at risk of insufficient protein intake and there has been a general decrease in protein consumption over time. This provides evidence to support initiatives focused on this age category to maximise change and reduce rates of sarcopenia.

The effects of parent-child dysfunctional interactions on early childhood weight: A serial mediation model through emotional feeding and child appetite traits

Parent-child dysfunctional interactions (PCDI) are known to contribute to children's weight status. However, the underlying mechanisms in how dysfunctional interactions between parent and child influence child weight are not clear. This study investigates the impact of PCDI on toddlers' weight, focusing on the potential serial mediation by maternal emotional feeding and child appetite traits. We conducted a secondary analysis of longitudinal data from a larger intervention trial to prevent childhood obesity in low-income Hispanic families. A total of 241 mother-child dyads were included in these analyses. Measurements were taken at various stages: PCDI at child age 19 months, maternal emotional feeding at 28 months, and both child appetite traits and weight-for-age z-score (WFAz) at 36 months. Serial mediation analyses revealed a significant indirect effect of early PCDI on later child WFAz through maternal emotional feeding and two child food approach traits (food responsiveness, emotional overeating) out of the eight child appetite traits assessed. PCDI at 19 months was associated with increased use of emotional feeding in mothers at 28 months, which was associated with heightened food responsiveness and emotional overeating in children at 36 months, which in turn was linked to greater child WFAz at 36 months. The findings of this study expand the understanding of the mechanisms underlying PCDI and child weight, emphasizing the interplay between maternal feeding practices and child appetite in the context of adverse parent-child interactions during early childhood.

Prolonged Early Food Insecurity and Child Feeding Practices among a Low-Income Hispanic Population: Role of Parenting Stress

ObjectiveTo examine associations between prolonged early household food insecurity (FI) during pregnancy, infancy, and toddlerhood, and child feeding practices, and the mediating role of dysfunctional parent-child interactions. MethodsWe conducted secondary longitudinal analyses of data from the Starting Early Program (StEP) randomized controlled trial, which studied a primary care-based child obesity prevention program for low-income Hispanic families. Our independent variable was FI, using the USDA Food Security Module, during the third trimester of pregnancy and at child ages 10- and 19-months. Frequency of reported FI was defined by the number of periods with FI (0, 1, 2, or 3). Our dependent variables were feeding practices at child age 28-months using the Comprehensive Feeding Practices Questionnaire. Our mediating variable was dysfunctional parent-child interactions using the Parenting Stress Index subscale at age 19-months. We used linear regression to determine associations between frequency of reported FI and feeding practices adjusting for covariates, and mediation analyses to determine if dysfunctional parent-child interactions mediate these associations. ResultsThree hundred and forty four mothers completed assessments at child age 28-months. Of the 12 feeding practices examined, higher frequency of reported FI was positively associated with using food as a reward, restriction of food for weight control, and using food for emotional regulation, and was negatively associated with monitoring of less healthy foods. There was a significant indirect effect of frequency of reported FI on these practices through dysfunctional parent-child interactions. ConclusionHigher frequency of reported FI was associated with four feeding practices, through dysfunctional parent-child interactions. Understanding these pathways can inform preventive interventions.

Impact of care–recipient relationship type on quality of life in caregivers of older adults with dementia over time

Abstract Background Dementia caregiving is a dynamic and multidimensional process. To gain a comprehensive understanding of informal caregiving for people living with dementia (PLWD), it is pivotal to assess the quality of life (QoL) of informal caregivers. Objective To evaluate whether the care–recipient relationship type predicts changes in the QoL of informal caregivers of PLWD over a two-year period. Methods This was a secondary analysis of longitudinal data. The data were drawn from two waves of linked data from the National Health and Aging Trends Study (NHATS) and the National Study of Caregiving (NSOC) (2015: NHATS R5 & NSOC II; 2017: NHATS R7 & NSOC III). Caregivers were categorized into spousal, adult–child, “other” caregiver and “multiple” caregivers. QoL was assessed through negative emotional burden (NEB), positive emotional benefits and social strain (SS). Generalized estimating equation modelling was used to examine changes in caregivers’ QoL outcomes across types of relationship over time. Results About, 882 caregivers were included who linked to 601 PLWD. After adjusting caregivers’ socio-demographics, “other” caregivers had lower risk of NEB and SS than spousal caregivers (OR = 0.34, P = 0.003, 95%CI [0.17, 0.70]; OR = 0.37, P = 0.019, 95%CI 0.16, 0.85], respectively), and PLWD’s dementia status would not change these significance (OR = 0.33, P = 0.003, 95%CI [0.16, 0.68]; OR = 0.31, P = 0.005, 95%CI [0.14, 0.71], respectively). Conclusions The study demonstrates that spousal caregivers face a higher risk of NEB and SS over time, underscoring the pressing need to offer accessible and effective support for informal caregivers of PLWD, especially those caring for their spouses.

Health-related quality of life (HRQoL) outcomes from the randomized, double-blind phase 3 KEYNOTE-671 study of perioperative pembrolizumab for early-stage non-small-cell lung cancer (NSCLC).

8012 Background: Neoadjuvant pembrolizumab + cisplatin-based chemotherapy (neoadj pembro + chemo), resection, and adjuvant (adj) pembro (pembro arm; n=397) significantly improved EFS, OS, pCR, and mPR and had an expected safety profile versus neoadj placebo (pbo) + chemo, resection, and adj pbo (pbo arm; n=400) in patients (pts) with resectable stage II, IIIA, or IIIB (N2) NSCLC. We present prespecified pt-reported outcome (PRO) endpoints from KEYNOTE-671. Methods: Pts completed EORTC QLQ-C30 and QLQ-LC13 questionnaires at baseline (BL), the last scheduled presurgery visit, adj cycles 1-4, 7, 10, and 13, and each post treatment visit. A constrained longitudinal data analysis model was used to estimate least squares mean (LSM) score changes from BL to neoadj wk 11 and adj wk 10 (latest time of ≥60% completion and ≥80% compliance) in QLQ-C30 global health status (GHS)/QoL, physical functioning (PF), role functioning (RF), and dyspnea and QLC-LC13 cough and chest pain in all treated pts who completed ≥1 PRO assessment. Data are from interim analysis 2 (10 Jul 2023 cutoff). Results: Across arms, questionnaire completion was ≥87% at neoadj wk 11 and ≥62% at adj wk 10; compliance was ≥87% and ≥92%, respectively. There were no differences in LSM change from BL in the neoadj or adj phase for any PRO score (Table). Conclusions: Adding perioperative pembro maintained HRQoL in both the neoadj and adj settings versus neoadj chemo and surgery alone in pts with resectable early-stage NSCLC. Together with the significant efficacy improvements and absence of new safety signals, HRQoL data support the perioperative pembro regimen as a new standard of care. Clinical trial information: NCT03425643 . [Table: see text]

Health-related quality of life (HRQoL) with nivolumab (NIVO) subcutaneous (SC) or intravenous (IV) in patients (pts) with advanced or metastatic clear cell renal cell carcinoma (ccRCC) who have received prior therapy in the phase 3 CheckMate 67T trial.

4535 Background: NIVO IV has improved outcomes in multiple tumor types. Evolving treatment paradigms have created a need for administration options that address treatment burden and improve efficiencies of healthcare systems. In a phase 1/2 study (CheckMate 8KX), pts were highly satisfied with NIVO SC and preferred it over NIVO IV [Lonardi et al, ESMO 2022; Lonardi et al, SITC 2023]. CheckMate 67T (NCT04810078) is a multicenter, randomized, open-label, phase 3 study that demonstrated pharmacokinetic and objective response rate noninferiority of NIVO SC vs IV in pts with locally advanced or metastatic ccRCC [George et al, ASCO-GU 2024]. This exploratory analysis assessed non-inferiority of HRQoL between pts randomized to NIVO SC (n=248) vs NIVO IV (n=247) in CheckMate 67T. Methods: HRQoL was measured using patient-reported outcomes (PROs), FKSI-19 (kidney cancer-related HRQoL) and the EQ-5D-5L (pt’s health status). FKSI-19 total score (range 0-76, higher score better HRQoL)and EQ-5D-5L visual analogue scale (VAS) (range 0-100, higher score better health HRQoL) scores were evaluated longitudinally on-treatment visits with ≥10 pts per arm included in model [week 57]) using linear mixed models (constrained longitudinal data analysis), with least squares (LS) mean changes from baseline and differences in the LS mean between NIVO SC and NIVO IV assessed; non-inferiority of NIVO SC vs NIVO IV was evaluated by examining overall treatment differences for on-treatment visits relative to prespecified thresholds. Results: PRO data were available for 247 pts (99.6%) for NIVO SC and 245 pts (99.2%) for NIVO IV, with completion rates >87% across instruments up to week 57 for both treatment arms. HRQoL was maintained over time for both NIVO arms for FKSI-19 total score and subscales and EQ-5D-5L VAS. NIVO SC was non-inferior to NIVO IV across FKSI-19 total score and subscales and EQ-5D-5L VAS (Table). Conclusions: These results demonstrate maintenance of HRQoL for pts with advanced or metastatic ccRCC while on treatment with NIVO, regardless of the mode of administration (SC or IV), supporting the use of NIVO SC as a new option to align with patient preferences. Clinical trial information: NCT04810078 . [Table: see text]

At-home, telehealth-supported ketamine treatment for depression: Findings from longitudinal, machine learning and symptom network analysis of real-world data

BackgroundImproving safe and effective access to ketamine therapy is of high priority given the growing burden of mental illness. Telehealth-supported administration of sublingual ketamine is being explored toward this goal. MethodsIn this longitudinal study, moderately-to-severely depressed patients received four doses of ketamine at home over four weeks within a supportive digital health context. Treatment was structured to resemble methods of therapeutic psychedelic trials. Patients receiving a second course of treatment were also examined. Symptoms were assessed using the Patient Health Questionnaire (PHQ-9) for depression. We conducted preregistered machine learning and symptom network analyses to investigate outcomes (osf.io/v2rpx). ResultsA sample of 11,441 patients was analyzed, demonstrating a modal antidepressant response from both non-severe (n = 6384, 55.8 %) and severe (n = 2070, 18.1 %) baseline depression levels. Adverse events were detected in 3.0–4.8 % of participants and predominantly neurologic or psychiatric in nature. A second course of treatment helped extend improvements in patients who responded favorably to initial treatment. Improvement was most strongly predicted by lower depression scores and age at baseline. Symptoms of Depressed mood and Anhedonia sustained depression despite ongoing treatment. LimitationsThis study was limited by the absence of comparison or control groups and lack of a fixed-dose procedure for ketamine administration. ConclusionsAt-home, telehealth-supported ketamine administration was largely safe, well-tolerated, and associated with improvement in patients with depression. Strategies for combining psychedelic-oriented therapies with rigorous telehealth models, as explored here, may uniquely address barriers to mental health treatment.

Persisting exercise ventilatory inefficiency in subjects recovering from COVID-19. Longitudinal data analysis 34 months post-discharge

BackgroundSARS-CoV-2 infection has raised concerns about long-term health repercussions. Exercise ventilatory inefficiency (EVin) has emerged as a notable long-term sequela, potentially impacting respiratory and cardiovascular health. This study aims to assess the long-term presence of EVin after 34 months and its association with cardiorespiratory health in post-COVID patients.MethodsIn a longitudinal study on 32 selected post-COVID subjects, we performed two cardiopulmonary exercise tests (CPETs) at 6 months (T0) and 34 months (T1) after hospital discharge. The study sought to explore the long-term persistence of EVin and its correlation with respiratory and cardiovascular responses during exercise. Measurements included also V̇O2peak, end-tidal pressure of CO2 (PETCO2) levels, oxygen uptake efficiency slope (OUES) and other cardiorespiratory parameters, with statistical significance set at p < 0.05. The presence of EVin at both T0 and T1 defines a persisting EVin (pEVin).ResultsOut of the cohort, five subjects (16%) have pEVin at 34 months. Subjects with pEVin, compared to those with ventilatory efficiency (Evef) have lower values of PETCO2 throughout exercise, showing hyperventilation. Evef subjects demonstrated selective improvements in DLCO and oxygen pulse, suggesting a recovery in cardiorespiratory function over time. In contrast, those with pEvin did not exhibit these improvements. Notably, significant correlations were found between hyperventilation (measured by PETCO2), oxygen pulse and OUES, indicating the potential prognostic value of OUES and Evin in post-COVID follow-ups.ConclusionsThe study highlights the clinical importance of long-term follow-up for post-COVID patients, as a significant group exhibit persistent EVin, which correlates with altered and potentially unfavorable cardiovascular responses to exercise. These findings advocate for the continued investigation into the long-term health impacts of COVID-19, especially regarding persistent ventilatory inefficiencies and their implications on patient health outcomes.

DeepIDA-GRU: a deep learning pipeline for integrative discriminant analysis of cross-sectional and longitudinal multiview data with applications to inflammatory bowel disease classification.

Biomedical research now commonly integrates diverse data types or views from the same individuals to better understand the pathobiology of complex diseases, but the challenge lies in meaningfully integrating these diverse views. Existing methods often require the same type of data from all views (cross-sectional data only or longitudinal data only) or do not consider any class outcome in the integration method, which presents limitations. To overcome these limitations, we have developed a pipeline that harnesses the power of statistical and deep learning methods to integrate cross-sectional and longitudinal data from multiple sources. In addition, it identifies key variables that contribute to the association between views and the separation between classes, providing deeper biological insights. This pipeline includes variable selection/ranking using linear and nonlinear methods, feature extraction using functional principal component analysis and Euler characteristics, and joint integration and classification using dense feed-forward networks for cross-sectional data and recurrent neural networks for longitudinal data. We applied this pipeline to cross-sectional and longitudinal multiomics data (metagenomics, transcriptomics and metabolomics) from an inflammatory bowel disease (IBD) study and identified microbial pathways, metabolites and genes that discriminate by IBD status, providing information on the etiology of IBD. We conducted simulations to compare the two feature extraction methods.

Evaluating a nurse-led narrative interview intervention with cancer patients with a first diagnosis: A feasibility study

Narrative Medicine and Nursing are clinical-supporting intervention methodologies that aim to enhance professionals’ communication skills and place patients at the heart of their therapeutic path. A narrative interview (NI) is a communication tool between practitioner and patient. The role of NI is debated extensively in the literature, but no studies focus on its use by nurses responsible for first-diagnosed cancer patients.This study aimed to evaluate the feasibility and utility of NI, carried out by Nurses, in managing people recently diagnosed with cancer.A pilot mixed-methods study with before-and-after-intervention evaluation, qualitative longitudinal data analysis, and concurrent data triangulation was conducted. The Mini-Mental Adjustment to Cancer assessed disease adaptation, while the Psychological Distress Inventory investigated psychological distress. The qualitative analysis of the narrative interviews assessed the usefulness of this intervention.13 out of 14 eligible patients took voluntary part in the study. Of those, 9 (69 %) completed T1 and T2 questionnaires and NI. The following five themes emerged from thematic analysis: reaction to the disease, feelings related to the new condition of life, changes, importance of relationships and perception of care. Patients reported being highly stressed and recognized the importance of a supporting social network for better coping with the condition.The adoption of an NI approach at the time of cancer diagnosis is feasible. Due to the limited sample size, it is unclear if NI may positively impact psychological distress in this patient population. Further studies would benefit from the integration of an additional investigation tool aiming to clarify whether NI promotes disease awareness in cancer patients. Furthermore, the recruitment of a larger sample is equally recommended.

Prevalence, incidence, mortality, and healthcare resource use for generalised pustular psoriasis, palmoplantar pustulosis, and plaque psoriasis in England: a population-based cohort study.

Generalised pustular psoriasis (GPP) and palmoplantar pustulosis (PPP) are chronic, inflammatory skin conditions. Accumulating evidence shows that GPP and PPP have different characteristics compared with plaque psoriasis and are distinct clinical entities. To assess the epidemiology, comorbidities, mortality and healthcare use for patients with GPP and PPP compared with those with plaque psoriasis in England. A cohort study involving analyses of longitudinal electronic health record data in the Clinical Practice Research Datalink Aurum database and linked hospital and mortality data between 2008 and 2019. The primary study outcome was the incidence and prevalence rates for GPP, PPP and plaque psoriasis in England. Secondary outcomes included survival rates and healthcare resource use (HCRU) by disease type. We identified 373 patients with GPP, 1,828 with PPP and 224,223 with plaque psoriasis. The mean age was 55.9 years (standard deviation [SD]: 18.6) for patients with GPP, 51.5 years (SD: 16.4) for those with PPP, and 48.5 years (SD: 19.1) for those with plaque psoriasis; 62.5% and 65.9% of patients with GPP and PPP, respectively, were women, compared with 49.4% of those with plaque psoriasis. About half of the patients were overweight or obese at baseline (GPP, 48.6%; PPP, 56.0%; and plaque psoriasis, 45.9%). The incidence rates for GPP, PPP and plaque psoriasis were 0.25 (95% CI: 0.21-0.28), 2.01 (95% CI: 1.92-2.11) and 103.2 (95% CI: 102.5-103.9) per 100,000 person-years, respectively. From 2008 to 2019, the prevalence rates per 100,000 persons ranged from 1.61 to 3.0 for GPP, 1.1 to 18.7 for PPP and 1771.0 to 1903.8 for plaque psoriasis. Survival rates were lower for patients with GPP, particularly those who were over 55 years old and those with a history of ≥1 comorbidity in each cohort. HCRU was lower in the plaque psoriasis cohort and highest in the GPP cohort, particularly among those who had ≥1 GPP flare. Our results provide further evidence that GPP is a distinct disease with different epidemiology, lower survival and higher HCRU than plaque psoriasis in England.

Methionine as a regulator of bone remodeling with fasting.

Caloric restriction improves metabolic health but is often complicated by bone loss. We studied bone parameters in humans during a 10-day fast and identified candidate metabolic regulators of bone turnover. Pro-collagen 1 intact N-terminal pro-peptide (P1NP), a bone formation marker, decreased within 3 days of fasting. Whereas dual-energy x-ray absorptiometry measures of bone mineral density were unchanged after 10 days of fasting, high-resolution peripheral quantitative CT demonstrated remodeling of bone microarchitecture. Pathway analysis of longitudinal metabolomics data identified one-carbon metabolism as fasting dependent. In cultured osteoblasts, we tested the functional significance of one-carbon metabolites modulated by fasting, finding that methionine - which surged after 3 days of fasting - affected markers of osteoblast cell state in a concentration-dependent manner, in some instances exhibiting a U-shaped response with both low and high concentrations driving putative antibone responses. Administration of methionine to mice for 5 days recapitulated some fasting effects on bone, including a reduction in serum P1NP. In conclusion, a 10-day fast in humans led to remodeling of bone microarchitecture, potentially mediated by a surge in circulating methionine. These data support an emerging model that points to a window of optimal methionine exposure for bone health.

Recommendations on Methods for Assessing Multimorbidity Changes Over Time: Aligning the Method to the Purpose.

The rapidly growing field of multimorbidity research demonstrates that changes in multimorbidity in mid- and late-life have far reaching effects on important person-centered outcomes, such as health-related quality of life. However, there are few organizing frameworks and comparatively little work weighing the merits and limitations of various quantitative methods applied to the longitudinal study of multimorbidity. We identify and discuss methods aligned to specific research objectives with the goals of (i) establishing a common language for assessing longitudinal changes in multimorbidity, (ii) illuminating gaps in our knowledge regarding multimorbidity progression and critical periods of change, and (iii) informing research to identify groups that experience different rates and divergent etiological pathways of disease progression linked to deterioration in important health-related outcomes. We review practical issues in the measurement of multimorbidity, longitudinal analysis of health-related data, operationalizing change over time, and discuss methods that align with 4 general typologies for research objectives in the longitudinal study of multimorbidity: (i) examine individual change in multimorbidity, (ii) identify subgroups that follow similar trajectories of multimorbidity progression, (iii) understand when, how, and why individuals or groups shift to more advanced stages of multimorbidity, and (iv) examine the coprogression of multimorbidity with key health domains. This work encourages a systematic approach to the quantitative study of change in multimorbidity and provides a valuable resource for researchers working to measure and minimize the deleterious effects of multimorbidity on aging populations.

Challenges and directions for digital twin implementation in otorhinolaryngology.

Digital twin technology heralds a transformative era in Otorhinolaryngology (ORL), merging the physical and digital worlds to offer dynamic, virtual models of physical entities or processes. These models, capable of simulating, predicting, and optimizing real-world counterparts, are evolving from static replicas to intelligent, adaptive systems. Fueled by advancements in communication, sensor technology, big data analytics, Internet of Things (IoT), and simulation technologies, artificial intelligence (AI), digital twins in ORL promise personalized treatment planning, virtual experimentation, and therapeutic intervention optimization. Despite their potential, the integration of digital twins in ORL faces challenges including data privacy and security, data integration and interoperability, computational demands, model validation and accuracy, ethical and regulatory considerations, patient engagement, and cost and accessibility issues. Overcoming these challenges requires robust data protection measures, seamless data integration, substantial computational resources, rigorous validation studies, ethical transparency, patient education, and making the technology accessible and affordable. Looking ahead, the future of digital twins in ORL is bright, with advancements in AI and machine learning, omics data integration, real-time monitoring, virtual clinical trials, patient empowerment, seamless healthcare integration, longitudinal data analysis, and collaborative research. These developments promise to refine diagnostic and treatment strategies, enhance patient care, and facilitate more efficient and tailored ORL research, ultimately leading to more effective and personalized ORL management.

MD3F: Multivariate Distance Drift Diffusion Framework for High-Dimensional Datasets.

High-dimensional biomedical datasets have become easier to collect in the last two decades with the advent of multi-omic and single-cell experiments. These can generate over 1000 measurements per sample or per cell. More recently, focus has been drawn toward the need for longitudinal datasets, with the appreciation that important dynamic changes occur along transitions between health and disease. Analysis of longitudinal omics data comes with many challenges, including type I error inflation and corresponding loss in power when thousands of hypothesis tests are needed. Multivariate analysis can yield approaches with higher statistical power; however, multivariate methods for longitudinal data are currently limited. We propose a multivariate distance-based drift-diffusion framework (MD3F) to tackle the need for a multivariate approach to longitudinal, high-throughput datasets. We show that MD3F can result in surprisingly simple yet valid and powerful hypothesis testing and estimation approaches using generalized linear models. Through simulation and application studies, we show that MD3F is robust and can offer a broadly applicable method for assessing multivariate dynamics in omics data.

The well-being equation: How inner fulfilment drives the impact of older persons on the Ghanaian society.

Understanding and managing the complex processes of ageing is a critical function of gerontological nursing, especially when it comes to older people's well-being and their contributions to society. Globally, older persons contribute in many ways to families and communities. However, the relationship between older person's overall well-being and their propensity to contribute to society remains an important gap in research. The study examined the association between well-being and the impact of older persons on Ghanaian society. A secondary analysis of longitudinal survey data of the 2014/15 Study on Global Ageing and Adult Health (SAGE Wave 2) conducted by the World Health Organization was used. The multilevel logistic regression technique was used to examine four dimensions of well-being and their associations with high social contribution among older persons. The output was reported as odds ratios (OR). The results show that older persons who had high physical and psychological well-being were more likely to contribute to society (OR = 1.25, 95% CI = 0.93, 1.68), (OR = 1.75, 95% CI = 1.32, 2.33). However, those with high levels of emotional and spiritual well-being were less likely to make social contributions (OR = 0.66, 95% CI = 0.49, 0.88), (OR = 0.88, 95% CI = 0.66, 1.18). This study shows a positive association between well-being and older persons' societal impact. Good mental and physical health encourage societal involvement among older persons, while high emotional and spiritual well-being may lead to less societal contribution. These findings are important for nursing policies promoting social contribution and well-being among older persons 60 years and over in Ghana.

Interventional analytics in skilled nursing facilities associated with reduced readmissions.

To assess differences in longitudinal profiles for 30-day risk-adjusted readmission rates in skilled nursing facilities (SNFs) associated with Penn Medicine's Lancaster General Hospital (LGH) that implemented an interventional analytics (IA) platform vs other LGH facilities lacking IA vs other SNFs in Pennsylvania vs facilities in all other states. Retrospective longitudinal analysis of CMS readmissions data from 2017 through 2022, and cross-sectional analysis using CMS quality metrics data. CMS SNF quality performance data were aggregated and compared with risk-adjusted readmissions by facility and time period. Each SNF was assigned to a cohort based on location, referral relationship with LGH, and whether it had implemented IA. Multivariable mixed effects modeling was used to compare readmissions by cohort, whereas quality measures from the fourth quarter of 2022 were compared descriptively. LGH profiles differed significantly from both state and national profiles, with LGH facilities leveraging IA demonstrating an even greater divergence. In the most recent 12 months ending in the fourth quarter of 2022, LGH SNFs with IA had estimated readmission rates that were 15.24, 12.30, and 13.06 percentage points lower than the LGH SNFs without IA, Pennsylvania, and national cohorts, respectively (all pairwise P < .0001). SNFs with IA also demonstrated superior CMS claims-based quality metric outcomes for the 12 months ending in the fourth quarter of 2022. SNFs implementing the studied IA platform demonstrated statistically and clinically significant superior risk-adjusted readmission rate profiles compared with peers nationally, statewide, and within the same SNF referral network (P < .0001). A more detailed study on the use of IA in this setting is warranted.

Disease Course of Clinically Isolated Optic Neuritis.

Optic neuritis is the most common optic neuropathy in young adults and a frequent manifestation of multiple sclerosis. Its clinical course is pertinent to the design of visual pathway neuroprotection trials. This is a secondary analysis of longitudinal data from the TONE trial, which included 103 patients from 12 German academic tertiary centers with acute unilateral optic neuritis as a clinically isolated syndrome and baseline high-contrast visual acuity <0.5 decimal. Patients were randomized to 1,000 mg methylprednisolone i.v./d plus either erythropoietin (33,000 IU/d) or placebo (saline solution) for 3 days. They were followed up at standardized intervals with a battery of tests including high-contrast visual acuity, low-contrast letter acuity, contrast sensitivity, visual fields, visual evoked potentials, and retinal optical coherence tomography. At 6 months, participants answered a standardized questionnaire on vision-related quality of life (NEI-VFQ 25). We describe the disease course with mixed-effects piecewise linear models and calculate structure-function correlations using Pearson r. Because erythropoietin had no effect on the visual system, we use pooled (treatment-agnostic) data. Patients experienced initial rapid and then decelerating improvements of visual function with thinning of inner and thickening of outer retinal layers. At 6 months, visual parameters were positively correlated with inner and negatively correlated with outer retinal thickness changes. Peripapillary retinal nerve fiber layer thinning predominantly occurred in sectors without previous swelling. At 6 months, macular ganglion cell and inner plexiform layer thinning was weakly correlated with the P100 peak time (r = -0.11) and moderately correlated with the amplitude of visual evoked potentials (r = 0.35). Only functional outcomes were at least moderately correlated with vision-related quality of life. The longitudinal data from this large study cohort may serve as a reference for the clinical course of acute optic neuritis. The pattern of correlation between visual evoked potentials and inner retinal thinning may argue that the latter is mostly due to ganglion cell loss, rather than dysfunction. Visual pathway neuroprotection trials with functional outcomes are needed to confirm that candidate drugs will benefit patients' vision-related quality of life. ClinicalTrials.gov, NCT01962571.