Analysis Of Longitudinal Data Research Articles

Longitudinal Analysis of Cancer Family Caregiver Perception of Sleep Difficulty During Home Hospice.

Sleep difficulty in caregivers is associated with poor physical and psychological outcomes. The purpose of this study was to describe family caregivers' perception of sleep difficulty through the hospice trajectory after a cancer diagnosis as predicted by age, sex, self-report of anxiety or depression, and cohabitation. We conducted a secondary analysis of longitudinal data using multilevel modeling with nested model comparisons. Beginning with an unconditional growth model, predictors were added to nested models to test differential impact. Caregivers (n = 164) were predominately white (n = 160; 97%) and female (n = 113, 69%). We hypothesized that age, sex, history of anxiety or depression, and cohabitation would predict sleep difficulty. The cohabitation predictor model was a statistically significant model for caregiver perception of sleep difficulty that worsened throughout hospice caregiving (b = .184, 2 = 7.199, P = 0.027) but age, sex, and history of depression or anxiety did not improve model fit. Our findings indicate that family caregivers who cohabitate exhibit increased perception of sleep difficulty over the course of hospice. Future studies and interventions for hospice family caregivers' sleep should consider cohabitation between the patient and the caregiver as a significant predictor of sleep difficulty to observe and potentially mediate the negative outcomes associated with caregiver sleep difficulty. Further, determining the underlying reasons for sleep difficulty in cohabitation (e.g., patient symptoms or treatments) should be explored.

"It Has Improved My Practice to Be Able to Offer Alternative Treatments": A Longitudinal Qualitative Study of Oregon Medicaid Back Pain Providers.

Introduction: This study aimed to understand health care providers' experiences implementing the Oregon Back Pain Policy (OBPP) over time. The Medicaid OBPP expanded coverage of evidence-based nonpharmacological therapy (NPT) for back pain and restricted access to opioid therapy and interventional approaches. Methods: The study included six online, asynchronous focus groups with providers in February 2020 (Time 1) and August 2022 (Time 2). Analysis was conducted with a longitudinal, recurrent cross-sectional approach. Analysis occurred in three stages: (1) An immersion/crystallization approach was used to analyze Time 1 focus group data, (2) reflexive thematic analysis was used to analyze Time 2 data, and (3) longitudinal analysis was used to integrate the findings across time points. Results: At Time 1, 48 clinicians and 44 NPT providers participated in the study. Time 2 included 63 clinicians and 59 NPT providers. The longitudinal analysis of the focus group data resulted in four themes: (1) general awareness of the policy, (2) providers support the policy and perceive a benefit to their patients, (3) barriers to NPT accessibility, and (4) barriers to referring patients to NPT. Conclusion: The goal of the OBPP was to improve back pain care for Oregon Medicaid members by increasing access to evidence-based NPT and decreasing reliance on opioid medications. This study revealed that, although clinicians and NPT providers supported the policy, they faced persistent implementation challenges related to referrals, prior authorizations, coverage limitations, low reimbursement rates, and a reduced workforce for NPT providers. In some cases, implementation barriers were removed during the COVID-19 pandemic, but other challenges were more prominent during the pandemic.

Demographic factors associated with within-individual variability of lung function for adults with cystic fibrosis: A UK registry study

Background: Lung function is a key outcome used in the evaluation of disease progression in cystic fibrosis. The variability of individual lung function measurements over time (within-individual variability) has been shown to predict subsequent lung function changes. Nevertheless, the association between within-individual lung function variability and demographic and genetic covariates has not been quantified.Methods: We performed a longitudinal analysis of data from a cohort of 7099 adults with cystic fibrosis (between 18 and 49 years old) from the UK cystic fibrosis registry, containing annual review data between 1996 and 2020. A mixed-effects location-scale model is used to quantify mean FEV1 (forced expiratory volume in 1 s) trajectories and FEV1 within-individual variability as a function of sex, age at annual review, diagnosis after first year of life, homozygous F508 genotype and birth cohort.Results: Mean FEV1 decreased with age and lung function variability showed a near-quadratic trend by age. Males showed higher FEV1 mean and variability than females across the whole age range. Earlier diagnosis and homozygous F508 genotype were also associated with higher FEV1 mean and variability. Individuals who died during follow-up showed on average higher lung function variability than those who survived.Conclusions: Key variables known to be linked with mean lung function in cystic fibrosis are also associated with an individual’s lung function variability. This work opens new avenues to understand the role played by lung function variability in disease progression and its utility in predicting key outcomes such as mortality.

Hearing Loss, Hearing Aids, and Functional Status

Hearing loss may contribute to poor functional status via cognitive impairment and social isolation. Hearing aids may play a protective role by attenuating these downstream outcomes. However, population-based evidence is lacking. To examine the association of hearing loss and hearing aids with functional status. This cross-sectional (2016-2017) and longitudinal (2016-2022) analysis of data from the Atherosclerosis Risk in Communities cohort study included older, community-dwelling adults with complete data. Data were analyzed from June to December 2023. The better-hearing ear's pure tone average (BPTA) at speech frequencies (0.5-4 kHz) was modeled categorically (no [BPTA ≤25 dB], mild [26-40 dB], and moderate or greater hearing loss [>40 dB]). Hearing aid use was self-reported. Difficulties in activities of daily living (ADLs; eg, dressing and eating), instrumental activities of daily living (IADLS; eg, household chores and meal preparation), and heavier tasks (eg, walking a quarter of a mile) were self-reported at visit 6. The ability to perform usual activities, walk a half mile, walk up and down stairs, and do heavy housework without help were collected in follow-up surveys. Linear and logistic regression models were used that were adjusted for sociodemographic and health covariates. Among 3142 participants (mean [SD] age, 79.3 [4.6] years; 1828 women [58.2%]), 1013 (32.2%) had no hearing loss, 1220 (38.8%) had mild hearing loss, and 909 (29.0%) had moderate or greater hearing loss. Moderate or greater hearing loss was cross-sectionally associated with difficulty in 1 or more ADLs (odds ratio [OR], 1.27; 95% CI, 1.02-1.58), IADLs (OR, 1.34; 95% CI, 1.05-1.71), and heavier tasks (OR, 1.29; 95% CI, 1.04-1.62) compared with no hearing loss. Over time (mean [SD] follow-up, 1.9 [1.8] years), moderate or greater hearing loss was associated with a faster decline in the number of activities participants were able to do (β = -0.07 per year; 95% CI, -0.09 to -0.06) and greater odds of reporting inability to do 1 or more of the 4 activities (OR, 1.14; 95% CI, 1.05-1.24). Hearing aid users and nonusers did not differ. The results of this study suggest that moderate or greater hearing loss was associated with functional difficulties and may contribute to a faster decline in function longitudinally independent of sociodemographic and health covariates. Hearing aids did not change the association among those with hearing loss.

Individualised prediction of longitudinal change in multimodal brain imaging

Abstract It remains largely unknown whether individualised longitudinal changes of brain imaging features can be predicted based only on the baseline brain images. This would be of great value, for example, for longitudinal data imputation, longitudinal brain-behaviour associations, and early prediction of brain-related diseases. We explore this possibility using longitudinal data of multiple modalities from UK Biobank brain imaging, with around 3,500 subjects. As baseline and follow-up images are generally similar in the case of short follow-up time intervals (e.g., 2 years), a simple copy of the baseline image may have a very good prediction performance. Therefore, for the first time, we propose a new mathematical framework for guiding the longitudinal prediction of brain images, providing answers to fundamental questions: (1) what is a suitable definition of longitudinal change; (2) how to detect the existence of changes; (3) what is the “null” prediction performance; and (4) can we distinguish longitudinal change prediction from simple data denoising. Building on these, we designed a deep U-Net based model for predicting longitudinal changes in multimodal brain images. Our results show that the proposed model can predict to a modest degree individualised longitudinal changes in almost all modalities, and outperforms other potential models. Furthermore, compared with the true longitudinal changes computed from real data, the predicted longitudinal changes have a similar or even improved accuracy in predicting subjects’ non-imaging phenotypes, and have a high between-subject discriminability. Our study contributes a new theoretical framework for longitudinal brain imaging studies, and our results show the potential for longitudinal data imputation, along with highlighting several caveats when performing longitudinal data analysis.

Understanding the conditional media effects: trust, new media exposure, and preventive behaviors during the COVID-19 pandemic

This study analyzed three-wave panel survey data gathered from August 2020 (n = 3,190) to April 2022 (n = 1,153) in Hong Kong to examine the effects of conditional media on preventive behaviors during the COVID-19 (coronavirus disease) pandemic. By using the differential susceptibility to media effects model (DSMM), this study demonstrates the usefulness of trust as an effective cultivator of media exposure, especially with regard to the contradictory effects of interpersonal and institutional trust on the use of new media. Moreover, this study innovatively suggests that the nature of media, specifically new media decentralization, also influences differential media effects in the DSMM. The analysis of longitudinal survey data further revealed a significant mediating role of cognitive risk perception in people’s preventive behaviors during the COVID-19 pandemic. These findings make theoretical contributions to the DSMM and to the understanding of conditional media effects. The practical implications are discussed in this paper.

Understanding the conditional media effects: trust, new media exposure, and preventive behaviors during the COVID-19 pandemic

This study analyzed three-wave panel survey data gathered from August 2020 (n = 3,190) to April 2022 (n = 1,153) in Hong Kong to examine the effects of conditional media on preventive behaviors during the COVID-19 (coronavirus disease) pandemic. By using the differential susceptibility to media effects model (DSMM), this study demonstrates the usefulness of trust as an effective cultivator of media exposure, especially with regard to the contradictory effects of interpersonal and institutional trust on the use of new media. Moreover, this study innovatively suggests that the nature of media, specifically new media decentralization, also influences differential media effects in the DSMM. The analysis of longitudinal survey data further revealed a significant mediating role of cognitive risk perception in people’s preventive behaviors during the COVID-19 pandemic. These findings make theoretical contributions to the DSMM and to the understanding of conditional media effects. The practical implications are discussed in this paper.

특수교육 중재전략 연구에서 베이지안 종단자료 분석모형의 유용성 탐색

Research on the effectiveness of intervention strategies for students with special needs is an important research topic in the field of special education. Until now, the majority of special education research on this topic has been based on the use of frequentist statistics and pre- and post-test designs. However, recent research in the natural and social sciences has criticised the limitations of frequentist statistics and emphasised the importance of reliable longitudinal data. Therefore, the purpose of this study is to introduce a Bayesian longitudinal data analysis model that can overcome the limitations of frequentist statistics in special education situations where longitudinal data are collected. According to the results of this study, when using Bayesian longitudinal data analysis model to test the effectiveness of intervention strategies, it is not only possible to reflect previous studies in parameter estimation, but also to continuously update the effect size of existing intervention strategies. In addition, it is possible to estimate effect sizes with good reliability even in research conditions with a small number of cases, such as in the field of special education. Finally, the limitations of Bayesian theory and future research topics are discussed.

Impaired glymphatic system in genetic frontotemporal dementia: a GENFI study.

The glymphatic system is an emerging target in neurodegenerative disorders. Here, we investigated the activity of the glymphatic system in genetic frontotemporal dementia with a diffusion-based technique called diffusion tensor image analysis along the perivascular space. We investigated 291 subjects with symptomatic or presymptomatic frontotemporal dementia (112 with chromosome 9 open reading frame 72 [C9orf72] expansion, 119 with granulin [GRN] mutations and 60 with microtubule-associated protein tau [MAPT] mutations) and 83 non-carriers (including 50 young and 33 old non-carriers). We computed the diffusion tensor image analysis along the perivascular space index by calculating diffusivities in the x-, y- and z-axes of the plane of the lateral ventricle body. Clinical stage and blood-based markers were considered. A subset of 180 participants underwent cognitive follow-ups for a total of 640 evaluations. The diffusion tensor image analysis along the perivascular space index was lower in symptomatic frontotemporal dementia (estimated marginal mean ± standard error, 1.21 ± 0.02) than in old non-carriers (1.29 ± 0.03, P = 0.009) and presymptomatic mutation carriers (1.30 ± 0.01, P < 0.001). In mutation carriers, lower diffusion tensor image analysis along the perivascular space was associated with worse disease severity (β = -1.16, P < 0.001), and a trend towards a significant association between lower diffusion tensor image analysis along the perivascular space and higher plasma neurofilament light chain was reported (β = -0.28, P = 0.063). Analysis of longitudinal data demonstrated that worsening of disease severity was faster in patients with low diffusion tensor image analysis along the perivascular space at baseline than in those with average (P = 0.009) or high (P = 0.006) diffusion tensor image analysis along the perivascular space index. Using a non-invasive imaging approach as a proxy for glymphatic system function, we demonstrated glymphatic system abnormalities in the symptomatic stages of genetic frontotemporal dementia. Such measures of the glymphatic system may elucidate pathophysiological processes in human frontotemporal dementia and facilitate early phase trials of genetic frontotemporal dementia.

Appendicular lean mass index and motor function in ambulatory patients with Duchenne muscular dystrophy.

Appendicular lean mass index (ALMI) has been linked to motor function in patients with Duchenne muscular dystrophy (DMD). However, quantification of the relationship between ALMI and disease-specific clinical outcome assessment trajectories is needed. The purpose of this study was to determine associations between dual-energy x-ray absorptiometry (DXA) derived estimates of ALMI and motor function in ambulatory patients with DMD. A retrospective analysis of longitudinal clinical visit data from 137 glucocorticoid-treated patients with DMD collected via structured motor assessment protocol evaluated associations between ALMI and motor function indexed by the North Star Ambulatory Assessment (NSAA) and 10 Meter Walk/run Test (10MWT). Body composition was assessed using DXA. ALMI was calculated by dividing arm and leg lean mass by height in m2; fat mass index (FMI) was calculated by dividing whole body fat mass by height in m2. Linear mixed-effects models were used to estimate associations between ALMI and motor function, controlling for age and FMI. The full prediction model (age, age,2 ALMI, and FMI) explained 57% of the variance in NSAA scores and 63% of the variance in 10MWT speed. A 1 kg/m2 higher ALMI value predicted a 5.4-point higher NSAA score (p < .001) and 0.45 m/s faster 10MWT speed (p < .001). A 1 kg/m2 higher FMI value predicted a 1.5-point lower NSAA score (p < .001) and 0.14 meters/second slower 10MWT speed (p < .001). DXA-derived estimates of ALMI and FMI are associated with motor function in DMD and may explain variation in DMD disease progression.

A longitudinal qualitative study on physician experience in managing multimorbidity across the COVID-19 pandemic in Odisha, India

While many studies have documented adverse impact of multiple chronic conditions or multimorbidity on COVID-19 outcomes in patients, there is scarcity of report on how physicians managed these patients. We investigated the experiences and challenges of clinicians in managing patients with multimorbidity throughout the COVID-19 pandemic in Odisha state, India. To understand the factors influencing illness management and the adaptive responses of physicians alongside the evolving pandemic, we followed a longitudinal qualitative study design. Twenty-three physicians comprising general practitioners, specialists, and intensivists, were telephonically interviewed in-depth. Saldana’s longitudinal qualitative data analysis method was employed for data analysis. COVID-19 pandemic initially diverted the attention of health systems, resulting in reduced care. With time, the physicians overcame fear, anxiety, and feelings of vulnerability to COVID-19 and started prioritising patients with multimorbidity for treatment and vaccination. All physicians recommended teleconsultation and digital health records to benefit chronic illness care during future public health crises. The findings underscore the transformative potential of physician resilience and adaptation during the COVID-19 pandemic, emphasizing the importance of prioritizing patients with multimorbidity, incorporating teleconsultation, and implementing digital health records in healthcare systems to enhance chronic illness care and preparedness for future public health crises.

Efficacy and safety of a mineral and vitamin treatment on symptoms of antenatal depression: 12-week fully blinded randomised placebo-controlled trial (NUTRIMUM).

Broad-spectrum micronutrients (minerals and vitamins) have shown benefit for treatment of depressive symptoms. To determine whether additional micronutrients reduce symptoms of antenatal depression. Eighty-eight medication-free pregnant women at 12-24 weeks gestation, who scored ≥13 on the Edinburgh Postnatal Depression Scale (EPDS), were randomised 1:1 to micronutrients or active placebo (containing iodine and riboflavin), for 12 weeks. Micronutrient doses were generally between recommended dietary allowance and tolerable upper level. Primary outcomes (EPDS and Clinical Global Impression - Improvement Scale (CGI-I)) were analysed with constrained longitudinal data analysis. Seventeen (19%) women dropped out, with no group differences, and four (4.5%) gave birth before trial completion. Both groups improved on the EPDS, with no group differences (P = 0.1018); 77.3% taking micronutrients and 72.7% taking placebos were considered recovered. However, the micronutrient group demonstrated significantly greater improvement, based on CGI-I clinician ratings, over time (P = 0.0196). The micronutrient group had significantly greater improvement on sleep and global assessment of functioning, and were more likely to identify themselves as 'much' to 'very much' improved (68.8%) compared with placebo (38.5%) (odds ratio 3.52, P = 0.011; number needed to treat: 3). There were no significant group differences on treatment-emergent adverse events, including suicidal ideation. Homocysteine decreased significantly more in the micronutrient group. Presence of personality difficulties, history of psychiatric medication use and higher social support tended to increase micronutrient response compared with placebo. This study highlights the benefits of active monitoring on antenatal depression, with added efficacy for overall functioning when taking micronutrients, with no evidence of harm. Trial replication with larger samples and clinically diagnosed depression are needed.

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&lt;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&lt;0.001: 95% CI − 15.25 to −12.59). Mexican American individuals consumed 7.47g more protein than Non-Hispanic White individuals (p&lt;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&lt;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&lt;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.

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]

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.