Trajectories Of Progression Research Articles

A robust and interpretable machine learning approach using multimodal biological data to predict future pathological tau accumulation

The early stages of Alzheimer’s disease (AD) involve interactions between multiple pathophysiological processes. Although these processes are well studied, we still lack robust tools to predict individualised trajectories of disease progression. Here, we employ a robust and interpretable machine learning approach to combine multimodal biological data and predict future pathological tau accumulation. In particular, we use machine learning to quantify interactions between key pathological markers (β-amyloid, medial temporal lobe atrophy, tau and APOE 4) at mildly impaired and asymptomatic stages of AD. Using baseline non-tau markers we derive a prognostic index that: (a) stratifies patients based on future pathological tau accumulation, (b) predicts individualised regional future rate of tau accumulation, and (c) translates predictions from deep phenotyping patient cohorts to cognitively normal individuals. Our results propose a robust approach for fine scale stratification and prognostication with translation impact for clinical trial design targeting the earliest stages of AD.

Identification and Characterization of Trajectories of Renal Function Decline After Heart Transplantation

<h3>Purpose</h3> Renal function in heart transplant (HT) recipients usually decreases progressively over time. However, the rate of decline may be highly variable among patients. A variety of mechanisms may be involved with the different progression patterns, with modifiable factors associated with the evolution of the disease. We aimed to identify subgroups of renal function trajectories in HT recipients. <h3>Methods</h3> Glomerular filtration rate was estimated (eGFR) using the CKD-EPI equation, from immediate post HT. The latent class linear mixed model was used to identify subgroups of eGFR trajectories, and patient characteristics were compared between these subgroups. <h3>Results</h3> We identified six distinct trajectories of eGFR among 166 cohort members over 9 [6,14] years follow up (Fig. 1A). The model adequately separated the trajectories, showing a discrimination probability of 0.82 -0.97. Most patients had persistently low levels of eGFR<50 ml/min/1.73m² (34%, Group 5) or experienced a slow decline of eGFR from levels of ∼70 ml/min/1.73m², within the first year, followed by eGFR stabilization (35%, Group 3). Two groups had a strong decline of eGFR within the first year, from different levels of eGFR (80 vs 120 ml/min/1.73m²; Group 4 vs 1), followed either by a progressive slow decline (13%, Group 4) or by eGFR stabilization (5%, Group 1). A further 8% of patients had accelerated loss of eGFR from ∼60 ml/min/1.73m² (Group 6). Finally, 5% experienced an accelerated increase in eGFR from levels of ∼50 ml/min/1.73m² (Group 2). Patients with progressive loss of eGFR (Groups 4,5 & 6) were older with frequent comorbidities. Multivariable analysis showed older recipient age as the stronger independent predictor for progressive loss of eGFR over time (OR 1.29, p=0.01; Fig. 1B). <h3>Conclusion</h3> We identified six clinically relevant subgroups of renal function trajectories. These different progression trajectories of eGFR among HT recipients can serve to investigate modifiable risk factors for renal function deterioration.

Progression Trajectories of Glomerular Filtration Rate Are Associated with Heart Transplantation Outcomes

<h3>Purpose</h3> The patterns of kidney function deterioration after heart transplantation (HT) are diverse; some patients have non-progressive or slowly progressive kidney disease while other progress rapidly to end-stage renal disease (ESRD). Little is known about the impact of renal function decline pattern, rather than the development of renal dysfunction per se, on HT outcomes. We aimed to test the hypotheses that progression trajectories of estimated glomerular filtration rate (eGFR) would be associated with varying risks of HT outcomes. <h3>Methods</h3> We used the latent class linear mixed model to identify patients with similar trajectories of eGFR deterioration after HT. Each pattern was served as the exposure variable. Outcomes included mortality, ESRD, and cardiac allograft vasculopathy (CAV). <h3>Results</h3> Using a median of 122 [91,206] serum creatinine measurements per patient, during 9 [6,14] years of follow up, a total of 166 patients were grouped into six distinct eGFR trajectories (Fig. 1A). We found an association between the distinct profiles of eGFR trajectories and HT outcomes. eGFR trajectories 4 and 6 were associated with higher post-transplant mortality rates (5-year mortality 18% [95% CI, 0-35] and 57% [95% CI, 23-79], respectively), in comparison with trajectories 1 and 2 that were characterized by 5-year survival of 100% (log-rank <i>P</i><0.0001; Fig. 1B). Similarly, Kaplan-Meier survival analysis showed that, at 5 years after HT, ESRD rate was 100% for group 6, 18% for group 5, and 36 % for group 4, in comparison with 0% for groups 1-3 (log-rank <i>P</i><0.0001; Fig. 1C). Rate of CAV at 5-year was significantly higher for trajectories 2,5 and 6 (34%, 20% and 47%) in comparison with groups 1,3,4 (0%, 8%, 12%), respectively (log-rank <i>P</i>=0.038; Fig. 1D). <h3>Conclusion</h3> Understanding the progression trajectory of eGFR following HT can guide clinical decision-making. Transition to a calcineurin inhibitors-free regimen, as a disease-modifying intervention, should be considered for patients with trajectories 4-6.

Eight-year trajectories of malalignment progression in symptomatic knee osteoarthritis.

Although various therapies have been developed to treat malalignment in osteoarthritic knees, the pattern of malalignment progression is still unclear. This study aimed to identify homogeneous subgroups with distinct trajectories of malalignment progression in subjects with symptomatic knee osteoarthritis (KOA) and to determine corresponding risk factors. Eight-year follow-up (from 2004 to 2012) data on 1252 participants with symptomatic KOA from the Osteoarthritis Initiative were included. Varus/valgus angle progression was characterized by group-based trajectory models. Time-varying covariates were introduced into the model to investigate how they affected trajectories. Multinomial logistic regression for trajectory group membership was applied to ascertain risk factors. Five subgroups were identified. Participants in the varus worsening trajectory (n = 166) or valgus worsening trajectory (n = 118) proceeded to worsen malalignment over time. The neutral trajectory (n = 378), varus stable trajectory (n = 328), and valgus stable trajectory (n = 262) maintained close to the initial varus/valgus angle over 8 years. Higher baseline Kellgren and Lawrence grade (odds ratio [OR] = 4.35, P < 0.001 for varus; OR = 3.85, P < 0.001 for valgus) and "severe" baseline malalignment (OR = 13.57, P < 0.001 for varus; OR = 23.04, P < 0.001 for valgus) were risk factors for worsening trajectories. The cutoff point of the baseline varus/valgus angle to discriminate between stable or worsening trajectory was -4.5° for varus and 3.6° for valgus. This study identified the malalignment progression pattern - minor malalignment (-4.5° to +3.6°) tends to remain stable, while major baseline malalignment is likely to progress. This provides a reference for therapy to prevent malalignment from deteriorating and emphasizes the necessity of determining the trigger factors for malalignment onset.

How do factors of sociodemographic, health literacy and dementia experience influence carers' knowledge of dementia?

BackgroundDementia is a life limiting disease following a progressive trajectory. As carers often become key decision makers, their knowledge of dementia will have health implications for the person living with dementia as well as carer’s psychological wellbeing.AimTo explore how sociodemographic factors, health literacy and dementia experience influence family carers knowledge about dementia.MethodIn this cross-sectional, mixed methods study, we interviewed 150 family carers and assessed their dementia knowledge using the Dementia Knowledge Assessment Scale (DKAS). Linear regression analyses were used to examine whether health literacy, previous experiences of dementia, support group attendance and sociodemographic characteristics predicted knowledge. Sixteen carers also completed qualitative interviews which explored unmet information needs. Transcripts and field notes were thematically analysed.ResultsMost participants were partners (47%) or adult children (48%) and cared for someone with severe (32%) or moderate (43%) dementia. Mean DKAS scores were 34.8/50 (SD = 7.0, range = 17–48) reflecting 8/25 incorrect answers. Backwards elimination regression found greater dementia knowledge was associated with greater health literacy for appraising information (coef 3.48, 95% CI (1.38, 5.58); p = 0.001) and more years of education (coef 0.39, 95% CI (0.12, 0.65); p = 0.004). Although not significant, knowledge was slightly lower in those who attended a support group, and a trend was found between ability to understand health information and knowledge. Only 39% accurately identified dementia as life shortening, indicating notable gaps in knowledge. Four qualitative themes were identified; arm yourself with information, ability to steer through information, other experience of dementia can be helpful and the importance of relationships with health care professionals.ConclusionsIn an information age, vast amounts of information are available, but this can bring difficulties. Carers with more years of education and higher health literacy knew more about dementia. Professionals should consider how carers with lower health literacy can be supported through provision of timely, relevant information.

Progression patterns of range of motion progression after open release for post-traumatic elbow stiffness.

Background & HypothesisPost-traumatic stiffness of the elbow may be treated surgically with open osteocapsular release. This study investigated postoperative range of motion (ROM) improvements after this procedure. We hypothesized that there would be predictable recovery patterns and significant progress up to 6 months after surgery.MethodsA retrospective chart review of patients who underwent open elbow release for post-traumatic stiffness (PTS) was performed. Demographic information and surgical approach were recorded. Patients with ipsilateral primary elbow osteoarthritis were excluded. Range of motion (ROM) data were collected at preoperative, intraoperative, and postoperative intervals of 2 weeks, 6 weeks, 3 months, and 6 months. Growth mixture modeling (GMM) and latent class growth analysis (LCGA) were performed to identify motion recovery trajectory groups, and Student's t-tests were performed to compare ROM data between intervals.ResultsOne hundred and eighty-seven patients who underwent open elbow release for PTS were included (112 with a medial approach, 50 lateral, and 25 both). The mean preoperative arc was 84° ± 31, and the arc of motion at final follow-up was 119° ± 19 (P < .05). The mean time to the final follow-up arc of motion was 16 weeks, with 56% of patients achieving their final arc by their 3-month follow-up visit. The largest improvement was seen with extension between 6 weeks and 3 months, where 26% of the extension at final follow-up was gained. Most of the recovery occurred within the first 3 months postoperatively, with small improvements thereafter. GMM and LCGA did not identify statistically significant groups for postoperative ROM progression trajectories. Arc of motion preoperatively, intraoperatively, and at 2 weeks postoperatively did not correlate with the final arc of motion. There were no demographic or historical characteristics, or thresholds of motion, which conferred a higher likelihood of achieving a better result postoperatively.ConclusionsROM recovery after surgical release for post-traumatic elbow stiffness did not depend on the preoperative, intraoperative, or 2-week postoperative arcs of motion. Most ROM recovery occurs early after surgery, and maximal arc of motion can be expected by approximately 16 weeks postoperatively. This knowledge may inform patients about their expected rehabilitation and splinting time and reduce the total costs of therapy.

Mixture regression for longitudinal data based on joint mean–covariance model

In the process of modeling longitudinal data, we focus on the case that the studied population is comprised of different groups of individuals and individuals within the same group share the similar kind of mean progression trajectories, where finite mixture models (FMM) are often used to address this kind of unobserved heterogeneity in terms of mean. Existing methods, such as parametric and semiparametric mixture regression, usually model the mean in each subpopulation with assumption that observations sharing a common trajectory are independent or their covariance structure is pre-specified, but less research considers modeling of covariance structures while accounting for heterogeneity. In this paper, we introduce a joint model which models the mean and covariance structures simultaneously in a finite normal mixture regression, demonstrating how important the within-subject correlation is in clustering longitudinal data. Model parameters are estimated with an iteratively re-weighted least squares EM (IRLS-EM) algorithm. Our estimators are shown to be consistent and asymptotically normal. We can identify different mean trajectories and covariance structures in all clusters. Simulations show that the proposed method performs well and gives more accurate clustering results by introducing covariance modeling. Real data analysis is also used to illustrate the usefulness of the proposed method, and it presents good performance in clustering COVID-19 deaths for European countries in terms of progression trajectory.

Longitudinal clustering analysis and prediction of Parkinson's disease progression using radiomics and hybrid machine learning.

We employed machine learning approaches to (I) determine distinct progression trajectories in Parkinson's disease (PD) (unsupervised clustering task), and (II) predict progression trajectories (supervised prediction task), from early (years 0 and 1) data, making use of clinical and imaging features. We studied PD-subjects derived from longitudinal datasets (years 0, 1, 2 & 4; Parkinson's Progressive Marker Initiative). We extracted and analyzed 981 features, including motor, non-motor, and radiomics features extracted for each region-of-interest (ROIs: left/right caudate and putamen) using our standardized standardized environment for radiomics analysis (SERA) radiomics software. Segmentation of ROIs on dopamine transposer - single photon emission computed tomography (DAT SPECT) images were performed via magnetic resonance images (MRI). After performing cross-sectional clustering on 885 subjects (original dataset) to identify disease subtypes, we identified optimal longitudinal trajectories using hybrid machine learning systems (HMLS), including principal component analysis (PCA) + K-Means algorithms (KMA) followed by Bayesian information criterion (BIC), Calinski-Harabatz criterion (CHC), and elbow criterion (EC). Subsequently, prediction of the identified trajectories from early year data was performed using multiple HMLSs including 16 Dimension Reduction Algorithms (DRA) and 10 classification algorithms. We identified 3 distinct progression trajectories. Hotelling's t squared test (HTST) showed that the identified trajectories were distinct. The trajectories included those with (I, II) disease escalation (2 trajectories, 27% and 38% of patients) and (III) stable disease (1 trajectory, 35% of patients). For trajectory prediction from early year data, HMLSs including the stochastic neighbor embedding algorithm (SNEA, as a DRA) as well as locally linear embedding algorithm (LLEA, as a DRA), linked with the new probabilistic neural network classifier (NPNNC, as a classifier), resulted in accuracies of 78.4% and 79.2% respectively, while other HMLSs such as SNEA + Lib_SVM (library for support vector machines) and t_SNE (t-distributed stochastic neighbor embedding) + NPNNC resulted in 76.5% and 76.1% respectively. This study moves beyond cross-sectional PD subtyping to clustering of longitudinal disease trajectories. We conclude that combining medical information with SPECT-based radiomics features, and optimal utilization of HMLSs, can identify distinct disease trajectories in PD patients, and enable effective prediction of disease trajectories from early year data.

Y-Mat: an improved hybrid finite-discrete element code for addressing geotechnical and geological engineering problems

PurposeContinua and discontinua coexist in natural rock materials. This paper aims to present an improved approach for addressing the mechanical response of rock masses based on the combined finite-discrete element method (FDEM) proposed by Munjiza.Design/methodology/approachSeveral algorithms have been programmed in the new approach. The algorithms include (1) a simpler and more efficient algorithm to calculate the contact force; (2) An algorithm for tangential contact force closer to the actual physical process; (3) a plastic yielding criterion (e.g. Mohr-Coulomb) to modify the elastic stress for fitting the mechanical behavior of elastoplastic materials; and (4) a complete code for the mechanical calculation to be implemented in Matrix Laboratory (MATLAB).FindingsThree case studies, including two standard laboratory experiments (uniaxial compression and Brazilian split test) and one engineering-scale anti-dip slop model, are presented to illustrate the feasibility of the Y-Mat code and its ability to deal with multi-scale rock mechanics problems. The results, including the progressive failure process, failure mode and trajectory of each case, are acceptable compared to other corresponding studies. It is shown that, the code is capable of modeling geotechnical and geological engineering problems.Originality/valueThis article gives an improved FDEM-based numerical calculation code. And, feasibility of the code is verified through three cases. It can effectively solve the geotechnical and geological engineering problems.

Early palliative interventions for improving outcomes in people with a primary malignant brain tumour and their carers.

Primary malignant brain tumours can have an unpredictable course, but high-grade gliomas typically have a relentlessly progressive disease trajectory. They can cause profound symptom burden, affecting physical, neurocognitive, and social functioning from an early stage in the illness. This can significantly impact on role function and on the experiences and needs of informal caregivers. Access to specialist palliative and supportive care early in the disease trajectory, for those with high-grade tumours in particular, has the potential to improve patients' and caregivers' quality of life. However, provision of palliative and supportive care for people with primary brain tumours - and their informal caregivers - is historically ill-defined and ad hoc, and the benefits of early palliative interventions have not been confirmed. It is therefore important to define the role and effectiveness of early referral to specialist palliative care services and/or the effectiveness of other interventions focused on palliating disease impact on people and their informal caregivers. This would help guide improvement to service provision, by defining those interventions which are effective across a range of domains, and developing an evidence-based model of integrated supportive and palliative care for this population. To assess the evidence base for early palliative care interventions, including referral to specialist palliative care services compared to usual care, for improving outcomes in adults diagnosed with a primary brain tumour and their carers. We conducted searches of electronic databases, CENTRAL, MEDLINE, CINAHL, Web of Science, and PsycINFO (last searched 16 November 2021). We conducted searches to incorporate both qualitative and quantitative search terms. In addition to this, we searched for any currently recruiting trials in ClinicalTrials.gov and in the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) search portal, and undertook citation tracking via Scopus. We also handsearched reference lists of potentially eligible systematic review articles to identify any other relevant studies, contacted experts in the field and searched key authors via Web of Science and searched SIGLE (System of Information on Grey Literature in Europe). We included studies looking at early referral to specialist palliative care services - or early targeted palliative interventions by other healthcare professionals - for improving quality of life, symptom control, psychological outcomes, or overall survival as a primary or secondary outcome measure. Studies included randomised controlled trials (RCTs), non-randomised studies (NRS), as well as qualitative and mixed-methods studies where both qualitative and quantitative data were included. Participants were adults with a confirmed radiological and/or histological diagnosis of a primary malignant brain tumour, and/or informal adult carers (either at individual or family level) of people with a primary malignant brain tumour. We followed standard Cochrane methodological procedures for data extraction, management, and analysis. We used GRADE to assess the certainty of the evidence for symptom control, i.e. cognitive function. We identified 9748 references from the searches, with 8337 remaining after duplicates were removed. After full-text review, we included one trial. There were no studies of early specialist palliative care interventions or of early, co-ordinated generalist palliative care approaches. The included randomised trial addressed a single symptom area, focusing on early cognitive rehabilitation, administered within two weeks of surgery in a mixed brain tumour population, of whom approximately half had a high-grade glioma. The intervention was administered individually as therapist-led computerised exercises over 16 one-hour sessions, four times/week for four weeks. Sessions addressed several cognitive domains including time orientation, spatial orientation, visual attention, logical reasoning, memory, and executive function. There were no between-group differences in outcome for tests of logical-executive function, but differences were observed in the domains of visual attention and verbal memory. Risk of bias was assessed and stated as high for performance bias and attrition bias but for selective reporting it was unclear whether all outcomes were reported. We considered the certainty of the evidence, as assessed by GRADE, to be very low. Currently there is a lack of research focusing on the introduction of early palliative interventions specifically for people with primary brain tumours, either as co-ordinated specialist palliative care approaches or interventions focusing on a specific aspect of palliation. Future research should address the methodological shortcomings described in early palliative intervention studies in other cancers and chronic conditions. In particular, the specific population under investigation, the timing and the setting of the intervention should be clearly described and the standardised palliative care-specific components of the intervention should be defined in detail.

Atopic dermatitis: clinical phenotypes, persistence and comorbidity

Background. Atopic dermatitis is the most common skin disease among children. Its natural history is heterogeneous with a difference in age of manifestation, localization of lesions, severity, sensitization profiles, presence of comorbid atopic conditions, and longitudinal trajectories of disease progression. The study aimed to assess the impact of factors such as the onset of the disease, atopic family history, presence of concomitant allergic pathology, duration of breastfeeding on the course of the disease and the development of respiratory allergies, and the impact of environmental factors that aggravate the disease. Materials and methods. Children with atopic dermatitis (n = 88) were included in the study from September 2020 to April 2021 in Kyiv, Ukraine. Symptoms of respiratory allergy in the history of patients have been documented as comorbidity. Results. Total of 88 patients at the time of examination presented with manifestations of atopic dermatitis in the form of a rash, dry skin, scaling, itching, lichenization. The disease severity was significantly related to the age of onset: children with early phenotype had more severe disease (OR = 16.261; 2.056–127.911). There was no statistically significant association of early phenotype of atopic dermatitis with the development of concomitant allergic diseases (OR = 1.813; 0.415–7.916). A severe course was observed in the group of children with atopic family history (OR = 2.750; 1.123–6.735). Children with severe atopic dermatitis had a high risk of concomitant respiratory allergy (OR = 5.604; 1.863–16.863). The duration of breastfeeding did not impact the severity of atopic dermatitis (OR = 0.778; 0.119–5.100) and the risk of concomitant atopic diseases (OR = 1.417; 0.444–4.521). The course of atopic dermatitis was influenced by seasonality in 76 children (86.4 %): the condition of the skin deteriorated in the winter. Contact with the animal was associated with exacerbation of atopic dermatitis in 4 (4.5 %) children, food ingestion — in 20 children (25 %), pollen trees and grasses caused exacerbation in 5 children (5.7 %). Conclusions. Children with a severe phenotype of atopic dermatitis are at risk of developing respiratory allergies. Patients with atopic dermatitis who develop symptoms at the age of under 2 years, as well as those with an atopic family history, are at high risk of developing a severe disease phenotype.

Is Amyloid Burden Measured by 18F-Flutemetamol PET Associated with Progression in Clinical Alzheimer's Disease?

Background:Patients with Alzheimer’s disease (AD) show heterogeneity in clinical progression rate, and we have limited tools to predict prognosis. Amyloid burden from 18F-Flutemetamol positron emission tomography (PET), as measured by standardized uptake value ratios (SUVR), might provide prognostic information.Objective:We investigate whether 18F-Flutemetamol PET composite or regional SUVRs are associated with trajectories of clinical progression.Methods:This observational longitudinal study included 94 patients with clinical AD. PET images were semi-quantified with normalization to pons. Group-based trajectory modeling was applied to identify trajectory groups according to change in the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) over time. Multinomial logistic regression models assessed the association of SUVRs with trajectory group membership.Results:Three trajectory groups were identified. In the regression models, neither composite nor regional SUVRs were associated with trajectory group membership.Conclusion: There were no associations between CDR progression and 18F-Flutemetamol PET-derived composite SUVRs or regional SUVRs in clinical AD.

Risk of Cardiovascular Disease after Common Psychiatric Disorders: Analyses of Disease Susceptibility and Progression Trajectory in the UK Biobank

Risk of Cardiovascular Disease after Common Psychiatric Disorders: Analyses of Disease Susceptibility and Progression Trajectory in the UK Biobank

Эпохальные открытия Николая Кондратьева и их место в современной экономической науке

The article describes 130th years since the birth of outstanding Russian economist Nikolai Kondratiev (1892–1938) and the 100th anniversary of the publication of his main scientific work “World Economy and its conjunctures ...”. The article presents three his great discoveries: the long waves of innovation in economic growth ranging from forty to sixty years; the second, the dynamism and instability of the market economy, which was explained only later, at the end of the 20th century, by synergistic economics; and the third, the need for the government’s active response to crises in economy by stimulating the self-regulation mechanisms inherent in market relationships. Kondratiev’s theory predated Keynesianism, which appeared during the Great Depression in the 1930s. The long wave theory was taken further by Joseph A. Schumpeter in his famous theory of economic development in the 1930s. In addition, the article outlines the prospects of development of the ‘Schumpeterian synthesis’ combining contemporary economic theory with Kondratiev– Schumpeter’s theory of innovative cyclical economic development. The key principles of the long-term forecasting of socio-economic development from the perspective of Kondratiev’s long wave theory are highlighted. The study proposes an information model of technological progress suitable for long-term forecasting of economic and technological development in the 21st century. The most suitable modes of production of technological information for the development of the information (1982–2018) and digital (2018–2050) economies are described. A special focus is made on the case of the US economic development. Forecasts are calculated to describe the future trajectories of technological progress and economic growth in the digital era (2018–2042) in the upward phase of the 6th K-wave.

A three-range approach enhances the prognostic utility of CSF biomarkers in Alzheimer's disease.

IntroductionAlzheimer's disease consensus recommends biomarker dichotomization, a practice with well‐described clinical strengths and methodological limitations. Although neuroimaging studies have explored alternative biomarker interpretation strategies, a formally defined three‐range approach and its prognostic impact remains under‐explored for cerebrospinal fluid (CSF) biomarkers .MethodsWith two‐graph receiver‐operating characteristics based on different reference schemes, we derived three‐range cut‐points for CSF Elecsys biomarkers. According to baseline CSF status, we assessed the prognostic utility of this in predicting risk of clinical progression and longitudinal trajectories of cognitive decline and amyloid–beta (Aβ) positron emission tomography (PET) accumulation in non‐demented individuals (Alzheimer's Disease Neuroimaging Initiative [ADNI]; n = 1246). In all analyses, we compared herein‐derived three‐range CSF cut‐points to previously described binary ones.ResultsIn our main longitudinal analyses, we highlight CSF p‐tau181/Aβ1‐42 three‐range cut‐points derived based on the cognitively normal Aβ‐PET negative versus dementia Aβ‐PET positive reference scheme for best depicting a prognostically relevant biomarker abnormality range. Longitudinally, our approach revealed a divergent intermediate cognitive trajectory undetected by dichotomization and a clearly abnormal group at higher risk for cognitive decline, with power analyses suggesting the latter group as potential trial enrichment candidates. Furthermore, we demonstrate that individuals with intermediate‐range CSF status have similar rates of Aβ deposition to those in the clearly abnormal group.DiscussionThe proposed approach can refine clinico‐biological prognostic assessment and potentially enhance trial recruitment, as it captures faster biomarker‐related cognitive decline in comparison to binary cut‐points. Although this approach has implications for trial recruitment and observational studies, further discussion is needed regarding clinical practice applications.

The Crafts and Capitalism: Handloom Weaving Industry in Colonial India by Tirthankar Roy (review).

Reviewed by: The Crafts and Capitalism: Handloom Weaving Industry in Colonial India by Tirthankar Roy Annapurna Mamidipudi (bio) and Vivek S. Oak (bio) The Crafts and Capitalism: Handloom Weaving Industry in Colonial India By Tirthankar Roy. New York: Routledge, 2020. Pp. 200. Global economic history has long studied and established that cotton as commodity has been one of the major engines of world capitalism at least since the sixteenth century. Along with scholars like Giorgio Riello, Prasannan Parthasarathi, and Sven Beckert, who highlighted big politics and the transmission of key-technologies, Tirthankar Roy has for the past three decades foregrounded the role of artisanal cotton handloom weavers in Colonial India. He posits a technological trajectory of craft industrialization from hand weaving to powered looms for the handmade textile industry that expanded through innovation and entrepreneurship. Roy's new book The Crafts and Capitalism is therefore of interest to scholars wanting to understand craft producers' and women consumers' diverse regional responses to industrialization in the nineteenth and twentieth centuries. In particular, it reverses the commonly held history of technology thesis, of the growing insignificance of human-powered craft work vis-à-vis mechanical production. Roy argues that it was the handloom weavers' ability to adapt to new efficient European technologies that advanced their growth. Rather than the patriarchal, nationalistic discourse that valorizes Gandhian ideas of hand spinning, Roy suggests that the role of women customers was crucial for creating growth in hand weaving markets. They liberated themselves from hidebound tradition by demanding designs suited to the rapidly urbanizing context of modernizing India. Roy then looks at the emergence of power loom weaving in the textile towns of South and West India post-independence, ending with the power loom segment breaking from its history and roots in handloom weaving. As capital-rich actors came to dominate power loom weaving, the technological trajectories of handloom and power loom weaving diverged, though both continue to this day. This book ensures that crafts' key role in the [End Page 259] modernization and industrialization of Indian textiles—and in the establishment of power loom weaving—is not lost. The Crafts and Capitalism is the most recent iteration of Roy's provocative thesis: that many handloom weavers were not oppressed by, but in fact benefited from, the industrial revolution and imperial trade policy. He provides a two-fold explanation. While some entrepreneurial weavers progressed from handloom to power loom weaving, others adopted progressive capitalist imperatives of growth in handloom weaving, using technological innovations from the West. Secondly, as evidence, Roy uses quantitative data to show the increasing handloom cloth production in the first half of the twentieth century, and cites the expanding progressive section of the handloom industry well into the second half of that century. This makes Roy's argument that crafts had been successfully mobilized in a capitalistic mode convincing, but raises other questions. What happened to weaving communities deemed "inefficient" or "obsolete"? How can we grasp the trajectories of progress of handloom weavers who did not become capitalistic? In that context, this book is a rich resource for tracing the replacement of local craft knowledge and material diversity with capitalist obligations of growth and productivity. This is especially relevant because the iconic weaving locations that Roy highlights are sites of labor exploitation and ecological devastation today. Skilled weaving households have been replaced by precarious, migrant, working men as producers in these towns. We could ask then whether using capitalist frameworks obscures other inequities—such as the distribution of wealth generated through economic growth, as Thomas Piketty argues, and the exclusion of specific communities from the handloom weaving profession and the destabilization of rural women producers' livelihoods, as Karuna Dietrich Wielenga shows. In that sense, the book does not engage with the lived experience of producers: cotton farmers, spinners, and handloom weavers, phenomena outside the frame of capitalist development. As an example, Roy's sources show that the weight of handspun yarn produced went from 170 million pounds in 1795 to zero in 1920; while mill-spun yarn went from zero to 660 million pounds in the same period. Roy argues that the fall in hand-spinning "was more than offset" by the large-scale development...

Co-occurring Hearing Loss and Cognitive Decline in Older Adults: A Dual Group-Based Trajectory Modeling Approach.

Hearing loss and cognitive impairments are both highly prevalent neurological complications for older adults. While there is growing evidence to suggest that these two conditions are interrelated, little research has been conducted that directly examines the progression and developmental trajectories of these complications contemporaneously. The aim of the study is to identify the distinct trajectory profiles for hearing loss and cognitive function in an older population over a 10-year period. Through dual trajectory modeling, the interrelationship, co-occurring movements, and overlaps between these two complications were examined. We also investigated the influence of hearing aid ownership on cognitive function trajectories. We utilized longitudinal data from 1,445 participants in the Blue Mountains Hearing Study (aged 55+ years) involving repeated measures from a population-based survey with audiometric hearing assessments. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). The group-based trajectory modeling (GBTM) identified three trajectory profiles for both hearing loss and cognitive function in two older age groups (55–69 years and 70+ years). The outputs from the dual trajectories models showed the conditional probability for “no hearing loss” trajectories to be around 90% more likely to have “high-normal” cognitive function, demonstrating co-occurring overlap. In contrast, for “moderate to severe hearing loss” trajectories, the conditional probability drops to 65% and 79% for the 55–69 age group and 70+ age group respectively. There was also an increasing probability for “cognitive decline” conditional on the severity of hearing loss with 6.7%, 7.5%, and 8.7% for no hearing loss, mild hearing loss, and moderate to severe hearing loss trajectory groups. While we did not find any statistically significant difference in the influence of hearing aid use in the cognitive function trajectories, there was a consistent greater representation of non-hearing aid users in the trajectories with poorer cognitive function. This study found GBTM to identify trajectories that were in agreement with our current understanding of hearing loss and cognitive impairment in older adults. This study also adds to the existing evidence-base as dual trajectories demonstrated co-occurrence in developmental changes in these two common neurological complications for the older population.

Trajectories of neighbourhood inequality in Britain: Unpacking inter‐regional socioeconomic imbalances, 1971−2011

AbstractPersistent spatial inequalities represent a menace to economic progress, social cohesion and political stability. The UK stands out as one of the most unequal countries in the industrialised world. This paper investigates intra‐regional and inter‐urban inequalities at the neighbourhood level in Britain during a 40‐year period, 1971−2011. Using a novel dataset containing a temporal classification of neighbourhoods, we analysed seven representative trajectories of neighbourhood persistence and change unveiling pathways of socioeconomic progress, decline, persistent affluence and disadvantage. Results highlight the extent of geographic unbalance in the distribution of these trajectories. Socioeconomic progress trajectories have been widespread across British cities. Yet a small handful of cities have concentrated persistent affluent neighbourhoods, and persistent struggling neighbourhoods have prevailed in northern cities.

Evaluation of Albumin Kinetics in Critically Ill Patients With Coronavirus Disease 2019 Compared to Those With Sepsis-Induced Acute Respiratory Distress Syndrome.

This report aims to characterize the kinetics of serum albumin in critically ill patients with coronavirus disease 2019 compared with critically ill patients with sepsis-induced acute respiratory distress syndrome. Retrospective analysis. We analyzed two critically ill cohorts, one with coronavirus disease 2019 and another with sepsis-induced acute respiratory distress syndrome, treated in the New York Presbyterian Hospital-Weill Cornell Medical Center. Adult patients in the coronavirus disease 2019 cohort, diagnosed through reverse transcriptase-polymerase chain reaction assays performed on nasopharyngeal swabs, were admitted from March 3, 2020, to July 10, 2020. Adult patients in the sepsis-induced acute respiratory distress syndrome cohort, defined by Sepsis III criteria receipt of invasive mechanical ventilation and a Pao2/Fio2 ratio less than 300 were admitted from December 12, 2006, to February 26, 2019. None. We evaluated serial serum albumin levels within 30 days after ICU admission in each cohort. We then examined the albumin progression trajectories, aligned at ICU admission time to test the relationship at a similar point in disease progression, in survivors and nonsurvivors. Albumin trajectory in all critically ill coronavirus disease 2019 patients show two distinct phases: phase I (deterioration) showing rapid albumin loss and phase II (recovery) showing albumin stabilization or improvement. Meanwhile, albumin recovery predicted clinical improvement in critical coronavirus disease 2019. In addition, we found a deterioration and recovery trends in survivors in the sepsis-induced acute respiratory distress syndrome cohort but did not find such two-phase trend in nonsurvivors. The changes in albumin associated with coronavirus disease 2019 associated respiratory failure are transient compared with sepsis-associated acute respiratory distress syndrome and highlight the potential for recovery following a protracted course of severe coronavirus disease 2019.

Longitudinal motor decline in dementia with Lewy bodies and Parkinson’s disease dementia in a community autopsy cohort

AbstractBackgroundAlthough parkinsonism is a core feature of Parkinson’s Disease Dementia (PDD) and Dementia with Lewy bodies (DLB), its evolution is less delineated. We aimed to assess differences in severity and progression of parkinsonian motor symptoms and signs in a community autopsy cohort with clinicopathologic diagnosis of DLB, PDD or Alzheimer’s Disease (AD).MethodData included were from 194 participants in the Arizona study of Aging and Neurodegenerative Disorders with clinicopathologic diagnosis of DLB (n=48), PDD (n=98) (±AD co‐pathology) or pure AD (n=48), and at least two movement exams performed by movement disorders subspecialists who classified PD and parkinsonism according to MDS‐UPDRS criteria. DLB was subgrouped by presence or absence of parkinsonism at final exam (DLB+Park and DLB–Park). Between group trajectory of UPDRS‐II and UPDRS‐III scores were explored using piecewise‐linear and non‐linear MMRM multivariate analysis.ResultOver 1435 participant‐years of longitudinal data were included in the analyses (Figure 1). Mean±SD age at baseline movement exam and death were 76.0±7.5 and 83.4±6.8 years, respectively. At baseline, most participants did not have dementia or substantial motor abnormalities (except motor abnormalities in PDD). DLB (73.9%) and PDD (69.2%) groups had more males than AD (33.3%). Parkinsonism was present in 65.6% of DLB at last exam. Piecewise‐linear MMRM analysis showed baseline UPDRS‐II and UPDRS‐III scores were highest (p&lt;0.001) for PDD (mean±SE: 14.3±0.78 and 27.4±1.64), followed by DLB+Park (5.0±1.05 and 17.4±3.10), DLB‐Park (3.7±2.54 and 3.8±1.35) and AD (3.2±0.88 and 8.0±1.94). Annual rate of increase in UPDRS‐II was greatest for DLB+Park (1.44±0.20) and PDD (1.04±0.08), followed by DLB‐Park (0.89±0.18) and AD (0.30±0.11). Annual rate of increase in UPDRS‐III was highest for PDD and DLB+Park (2.12±0.20 vs 2.64±0.42), followed by DLB‐Park and AD (1.31 ± 0.38 and 0.64 ± 0.22). Preliminary non‐linear MMRM models (Figure 2) further supported substantial between group/subgroup differences in motor trajectories, and progression in DLB‐Park.ConclusionThese preliminary results in a large, well‐characterized clinicopathological community‐based autopsy cohort support that DLB+Park experience comparable, or greater, parkinsonian motor progression to PDD. Future modeling/sensitivity analyses will better delineate expected trajectories of motor progression to add prognostication value in clinic and design of DLB clinical trials.