Patterns Of Progression Research Articles

Clinical characteristics, progression patterns and treatment outcomes in microsporidial keratoconjunctivitis: a prospective study in Thailand.

To assess the clinical characteristics, progression patterns, and treatment outcomes of microbiologically confirmed microsporidial keratoconjunctivitis (MKC). This prospective cross-sectional study included patients with superficial punctate epithelial keratitis clinically suspected of MKC. Comprehensive slit-lamp examinations were conducted, and corneal scraping was performed for Gram-chromotrope staining and polymerase chain reaction (PCR) analysis. A standardized questionnaire gathered demographic data, clinical features, and risk behaviors. Treatment regimens and corneal findings, including medication and frequency, were documented at each visit. PCR confirmed the diagnosis of MKC in 96 out of 117 eyes (82.1%), identifying Vittaforma corneae in 93.7% of cases, Microsporidium sp. in 4.2%, and Encephalitozoon hellem in 2.1%. All cases exhibited similar characteristics and pattern of progression, including elevated epithelial lesions in diffused distribution (34.1%), typical target lesions (31.3%), and subepithelial infiltrations (41.7%). Treatment with topical moxifloxacin, with or without oral albendazole, followed by topical steroids for subepithelial infiltrates, led to clinical improvement within approximately two weeks, with 52% of patients achieving complete recovery. This study identifies key clinical features and progression patterns in MKC. Topical fluoroquinolone monotherapy, or its combination with topical steroids or oral albendazole, results in favorable visual outcomes without corneal scarring. These insights may inform and enhance clinical management of MKC.

A Discourse Analysis Perspective of Thematic Structure and Thematic Progression in Students’ Written Narrative Texts: A Case of Mjimpya Secondary School Students in Morogoro Municipality

The study investigated the thematic structure and thematic progression in students’ written narrative texts. Specifically, it analysed types of themes and identified types of thematic progression patterns employed in students’ written narrative texts. It also examined the implications of the theme and thematic progression pattern’s predominance in students’ written narrative texts. 85 participants were selected from among Form Three and Form Four students. Data was collected using the closed test and documentary reviews. Data was coded and analysed using Systemic Functional Linguistics (SFL) and Thematic Progression (TP) theories by Halliday, Mathiessen, and Danes respectively. The findings indicated that students employed the taxonomy of four types of themes in their narrative texts: topical theme, textual theme, interpersonal theme, and macro theme. The topical theme was predominantly used followed by textual theme and interpersonal theme. The findings also revealed the taxonomy of seven types of thematic progression patterns in students’ written narrative texts, namely: constant pattern, zigzag pattern, and multiple patterns, constant-zigzag or zigzag-constant, constant-zigzag-multiple, zigzag-multiple, and constant macro pattern. The constant pattern was predominantly used followed by a zigzag pattern and then multiple patterns. The predominance of topical themes and constant thematic progression patterns implied that students tended to rely on thematic selections like topical themes and constant which seem simpler to use rather than textual themes, interpersonal themes, zigzag patterns and multiple patterns, all of which seem complex for students since they need advanced and sophisticated knowledge and skills to apply these thematic structures and progression patterns in their texts. Thus, students’ dependence on simple thematic selections indicates a lack of knowledge or ability to use complex thematic structures and thematic progression patterns in their written narrative texts while these thematic structures have a crucial role in their writing. Therefore, a systematic approach to teaching thematic selections is crucial. The findings of the current study contribute to the body of knowledge on thematic structure and progression in academic writing due to the detailed taxonomy of thematic structure and progression patterns revealed in this study. The study recommends that educational planners and implementers ensure that the theory of thematic structure and thematic progression are systematically integrated into the teaching and learning of writing activities from lower levels of education, specifically secondary education. Further, the study recommends further research in this area to use different approaches, genres and respondents from different settings such as advanced-level secondary school students

Pathogenetic and clinical signifcance of EpCАM expression features in tumors and circulating tumor cells

Purpose of the study: to summarize the available data on the structure and function of EpCAM and its domains, their roles in promoting proliferation and epithelial-mesenchymal transition (EMT), contributing to cell stemness, and facilitating interactions with cell adhesion and invasion molecules.Material and Methods. A comprehensive search was conducted for articles in Russian and English within the scientifc databases PubMed, Scopus, Web of Science, and E-library. A total of seventy-nine articles ranging from 1996 to 2024 were utilized to compile this review.Results. This review summarized the pathogenetic and clinical signifcance of various EpCAM expression variants: EpCAM^high, EpCAM^low, and EpCAM^loss. It described the causes and mechanisms behind the loss of membrane EpCAM expression, each holding distinct biological and clinical implications. Features of EpCAM expression in normal epithelial tissues, during regeneration, and in dysplasia/ neoplasia as well as carcinomas were carefully outlined. The clinical implications of EpCAM expression remain a subject of debate; overexpression of EpCAM has been linked to both unfavorable and favorable prognoses. Special emphasis was placed on the expression variants of EpCAM in circulating tumor cells, disseminated cells, and carcinoma metastases.Conclusion. The pathogenetic and clinical signifcance of EpCAM expression in various nosological forms of carcinoma is complex and multifaceted. Weak expression or absence of EpCAM acts as independent factors infuencing the unique progression patterns of these diseases. Achieving a deeper understanding of the role of EpCAM in disease progression necessitates the simultaneous examination of both its extracellular and intracellular domains.

Validation of an interactive process mining methodology for clinical epidemiology through a cohort study on chronic kidney disease progression.

Process mining holds promise for analysing longitudinal data in clinical epidemiology, yet its application remains limited. The objective of this study was to propose and evaluate a methodology for applying process mining techniques in observational clinical epidemiology. We propose a methodology that integrates a cohort study design with data-driven process mining, with an eight-step approach, including data collection, data extraction and curation, event-log generation, process discovery, process abstraction, hypothesis generation, statistical testing, and prediction. These steps facilitate the discovery of disease progression patterns. We implemented our proposed methodology in a cohort study comparing new users of proton pump inhibitors (PPI) and H2 blockers (H2B). PPI usage was associated with a higher risk of disease progression compared to H2B usage, including a greater than 30% decline in estimated Glomerular Filtration Rate (eGFR) (Hazard Ratio [HR] 1.6, 95% Confidence Interval [CI] 1.4-1.8), as well as increased all-cause mortality (HR 3.0, 95% CI 2.1-4.4). Furthermore, we investigated the associations between each transition and covariates such as age, gender, and comorbidities, offering deeper insights into disease progression dynamics. Additionally, a risk prediction tool was developed to estimate the transition probability for an individual at a future time. The proposed methodology bridges the gap between process mining and epidemiological studies, providing a useful approach to investigating disease progression and risk factors. The synergy between these fields enhances the depth of study findings and fosters the discovery of new insights and ideas.

Comprehensive analysis of radiologic cancer-free (rCF) status through various treatment approaches in advanced-stage hepatocellular carcinoma

Introduction In the realm of oncology, the pinnacle of therapeutic success is achieving a state where the patient is entirely free of cancer, i.e. ‘cancer-free’. This benchmark should not only apply to early-stage malignancies but should also be the standard aim for advanced-stage diseases, including hepatocellular carcinoma (HCC). However, there is a glaring gap in the research landscape concerning the understanding of what cancer-free status truly means for advanced-stage HCC. Our study sheds light on the profound implications of reaching a cancer-free by radiological assessments in patients with advanced-stage HCC. Methods We established a database tracking the full clinical course of all patients with HCC (from 2003–2022). We identified the initial instances of macrovascular invasion or extrahepatic spread. We defined radiologic cancer-free (rCF) as cases in which no recurrence was observed for at least 2 months following curative treatment or complete response to systemic therapies. The frequency of achieving rCF status was investigated, categorised by patients’ background. Results We identified 795 patients with advanced-stage HCC. The rCF rate was 8.7%. Patients who achieved rCF status had significantly better prognoses compared to those who did not (p < 0.001). In the decision tree analysis, the number of tumors ≥8 was the strongest factor making it difficult to achieve rCF status. Analysis of stage progression patterns revealed varying background characteristics at the time of advanced-stage diagnosis, with discrepancies in rCF rates. Conclusions Despite the low rate of achieving rCF status, the prognostic impact was significant. Patients with certain tumor characteristics had a higher likelihood of achieving rCF status. The distribution of tumor conditions varies based on the pattern of progression, which affects the likelihood of achieving a rCF status.

Retinopathy in Mucopolysaccharidoses.

To determine the pattern(s) of onset, variation, and progression of retinopathy in patients with Mucopolysaccharidosis (MPS). Prospective, longitudinal, observational study. Between November 2015 and March 2023, individuals with MPS were recruited from Ophthalmology clinics at the Manchester Royal Eye Hospital, United Kingdom. Participants underwent assessment of visual acuity, corneal clouding, intraocular pressure, along with fundoscopy, ultra-widefield (UWF) colour fundus photography, fundus autofluorescence (FAF) imaging, optical coherence tomography (OCT), and electroretinography (ERG), where feasible. Evaluation of findings from clinical examination, retinal imaging, and electroretinogram studies, to ascertain the presence and patterns of retinopathy. Data was collected for 75 patients, including 45 MPS I, 9 MPS II, 13 MPS IVA, and 8 MPS VI, aged 3-58 years. Fundus photography was conducted in 65 patients, FAF in 61, OCT in 58, and electrodiagnostic studies in 36 participants. Retinopathy was defined as signs of retinal disease evident through retinal examination or fundus photography such as depigmentation, bone-spicule pigmentation, vascular tortuosity, retinal pigment epithelium (RPE) mottling/other changes, macular atrophy/puckering/epiretinal membranes, FAF findings such as a central hyperautofluorescent dot, hyperautofluorescent parafoveal ring, hypoautofluorescent lesions around fovea (double bull's eye), areas of hyper/hypoautofluorescence, and extrafoveal changes, OCT imaging features such as central external limiting membrane (ELM) thickening, RPE disturbance, photoreceptor layer loss, parafoveal retinal atrophy, and outer retinal/intrachoroidal cavities, or electroretinogram studies revealing rod-mediated retinopathy or rod-cone dystrophy. Retinopathy was confirmed in 32 patients, including 25 MPS I, 4 MPS II, 1 MPS IVA, and 2 MPS VI. Five participants were first diagnosed with retinopathy with clinical examination, while 31 participants were identified on UWF colour fundus photography supported by FAF and OCT. 21 patients exhibited ERG abnormalities consistent with retinopathy. Fifteen of the total 32 participants described symptoms of nyctalopia. The onset of retinopathy varied substantially, with initial detection between 2 and 53 years of age. MPS patients as young as 2 may develop retinopathy, diagnosed through fundus examination, ophthalmic imaging, or ERG. Emerging treatments, including gene therapy, may prevent or stabilise retinopathy. Phenotypic data and natural history of MPS-related retinopathy are thus of paramount importance.

Comorbidity Pattern and Autonomic Nervous System Dysfunction in Patients with Chronic Vulvar Discomfort

This study examines novel concepts of comorbidity in patients with chronic vulvar discomfort using data from the DATRIV (Diagnostic Accuracy of Three Rings Vulvoscopy) study, which involved 328 participants categorized into four groups: asymptomatic individuals with normal or impaired vulvar skin and patients with chronic vulvar discomfort, classified as either vulvodynia or vulvar dermatosis. Clinical data were collected through a structured questionnaire and analyzed using statistical software, including StatSoft (Dell, Austin, TX, USA), Statistica 12 (TIBCO®, Palo Alto, CA, USA), and SPSS 20 (IBM, Armonk, NY, USA). The study received approval from the Institutional Review Board of Polyclinic Harni, and all participants provided written informed consent. The findings reveal significantly higher comorbidity rates in patients with chronic vulvar discomfort compared to other groups (p = 0.0000). A substantial percentage of asymptomatic participants with both normal (63.4%) and impaired (70.7%) vulvar skin also reported comorbid conditions. Analysis of comorbidity curves revealed distinct patterns of symptom progression, with a gradual increase in frequency from asymptomatic individuals to patients with vulvodynia, followed by a decline in vulvar dermatosis cases. These patterns highlight the central role of autonomic nervous system (ANS) dysfunction, where sympathetic hyperactivity and parasympathetic depression contribute to separate comorbidity chains. These dysfunctions may act independently or concurrently, leading to various health issues. The elevated comorbidity rates and overlapping symptomatology suggest complex pathophysiology driven by ANS dysregulation. Further research on comorbidity clusters may unveil new therapeutic targets and guide the development of multifaceted treatment strategies.

CTNI-41. LONG-TERM SURVIVAL AND PATTERNS OF PROGRESSION IN PATIENTS WITH NEWLY DIAGNOSED GLIOBLASTOMA TREATED WITH OR WITHOUT TUMOR TREATING FIELDS (TTFIELDS) IN A REAL-WORLD SETTING

Abstract BACKGROUND Tumor Treating Fields therapy (TTFields) is an FDA-approved locoregional treatment for patients with newly diagnosed glioblastoma (ndGBM). Previous trial data showed the addition of TTFields to standard TMZ-based therapy to significantly improve overall survival (OS), but real-world data is lacking, particularly with long follow-up duration. Here, we report real-world survival and patterns of progression for patients with ndGBM treated with or without TTFields. METHODS Patients diagnosed with GBM and treated with standard of care therapy at the Medical College of Wisconsin between March 2015–March 2023 were included. Progression-free survival (PFS) and OS outcomes were assessed, and compared across groups who received or did not receive TTFields therapy during maintenance treatment. Patterns of disease progression were analyzed via anatomic assessment. Patients were followed through March 1, 2024. RESULTS A total of 210 patients (TTFields: n=110/52.4%; No-TTFields: n=100/47.6%) were included for analysis. Median age was 60 and 63 years for the TTFields and No-TTFields groups, respectively, with each group 43% female. Other baseline characteristics were consistent across groups. Median TTFields duration was 6.8 months (range: 1–94). OS was significantly improved for the TTFields group vs No-TTFields group (median OS: 21.6 months [18.4–24.8] vs 17.7 months [15.0–20.8]; HR 0.73 [95% CI: 0.54–0.99, P=0.042]). Median PFS was 12.1 months (10.3–14.4) vs 9.6 months (8.5–12.8) with HR 0.77 (95% CI: 0.58–1.02; P=0.071). 5-year OS was 17% (10–28) for the TTFields group, and 11% (5–22) for No-TTFields group. Patients treated with TTFields exhibited a higher rate of non-local progression compared with the No-TTFields group (28% vs 15%, [P=0.044]). CONCLUSIONS Analysis of patients from a large institutional dataset reveals an association between TTFields use and long-term survival benefit. Higher incidence of non-local patterns of progression among TTFields users is consistent with pivotal trial findings.

INNV-33. ADVANCING PRECISION TREATMENT FOR DIFFUSE MIDLINE GLIOMA: THE DMG LEARNING HUB INITIATIVE

Abstract Diffuse Midline Glioma (DMG) poses a significant challenge in neuro-oncology due to its heterogeneous presentation and limited therapeutic options. Clinical trials often serve as the primary avenue for treatment, yet families encounter numerous barriers in navigating and selecting appropriate trials. Health disparities, including disparities in medical literacy and access to specialized medical centers, further complicate decision-making processes. Existing registries lack comprehensive data integration, focusing on isolated perspectives of either research or clinical data, neglecting the holistic patient profile. Evaluation of treatment endpoints beyond Progression-Free Survival (PFS) and Overall Survival (OS) remain inconsistent, despite being a priority for families. The DMG Learning Hub emerges as a transformative platform designed to empower families by offering informed options and guidance while fostering a collaborative environment where patient families actively contribute to shaping the landscape of clinical trials. Leveraging AI-assisted matching, the platform assists families in navigating the complex decision-making process surrounding clinical trial participation. The inclusion of a patient-reported outcome journal feature enables families to track vital information such as symptom changes and supplement usage, with autonomy over the timing of shared data. Using real-time data sharing facilitates invaluable insights for researchers, bridging gaps that would otherwise be overlooked and enriching the collective understanding of DMG. Harmonizing molecular, imaging, and clinical data within the platform equips care teams with comprehensive, near-real-time information crucial for personalized treatment strategies. This integrated approach not only supports the inclusion of n-of-1 arms in current trials but also extends therapeutic opportunities to patients previously ineligible for studies due to specific disease markers or progression patterns. The DMG Learning Hub represents a significant stride towards precision oncology by synergizing patient-centric priorities with cutting-edge technology, integrating harmonized data, and fostering collaborative efforts, the initiative heralds a promising era of personalized treatment for DMG and beyond the neuro-oncology community.

SURG-14. PATTERNS OF PROGRESSION OF TEMPORAL LOBE GLIOBLASTOMAS: EVIDENCE FOR THE ROLE OF TEMPORAL LOBECTOMY

Abstract Glioblastomas extend beyond the contrast-enhancing tumor, and supramaximal resections into non-enhancing (NE) tumor improves survival. Yet, supramaximal resection is difficult to achieve in most cases. For temporal lobe tumors, supramaximal anterior temporal lobe resection is feasible and safe. Case series have shown a survival advantage by resecting the anterior temporal lobe. This study aims to explore patterns of tumor progression in temporal lobe glioblastomas and whether the presence of NE tumor in the temporal tip could be used as a biomarker to predict the site of progression. We searched a single institution tumor database looking for patients who had glioblastomas in the temporal lobe, who underwent complete resection of enhancing tumor, and went on to have chemoradiotherapy. Patients needed to have imaging demonstrating first progression. We determined pre-operatively if NE tumor had extended into the temporal tip. At progression, the direction of tumor progression was recorded and assessed if it would have been resected should a lobectomy have been performed. We identified 55 patients that fulfilled our entry criteria (mean age 57.7 years, range 19.6-72.9; 37 male). In 16 cases, the anterior temporal lobe was resected; these patients were not used in further assessments. In 25 cases (64.1%), the tumor progressed into the residual anterior temporal lobe. In 16 cases (41.0%), a lobectomy would have encompassed the area of progression. NE tumor was seen in the tip in 28 cases (71.8%). This could predict progression into the anterior temporal lobe with a sensitivity of 76.2% (95%CI: 54.9-90.6%) and specificity of 33.1% (95%CI: 11.8-61.6%). The likelihood ratio of tumor progression was 1.14 (95%CI: 0.75-1.74). We conclude that temporal lobe glioblastomas most commonly progress into the anterior temporal lobe, but NE tumor is not a suitable predictive biomarker. Developing suitable biomarkers and biomarker-driven trials of temporal lobectomy for glioblastomas are needed.

Prediction and clustering of Alzheimer’s disease by race and sex: a multi-head deep-learning approach to analyze irregular and heterogeneous data

Early detection of Alzheimer’s disease (AD) is crucial to maximize clinical outcomes. Most disease progression analyses include people with diagnoses of cognitive impairment, limiting understanding of AD risk among those with normal cognition. The objective was to establish AD progression models through a deep learning approach to analyze heterogeneous, multi-modal datasets, including clustering analyses of population subsets. A multi-head deep-learning architecture was built to process and learn from biomedical and imaging data from the National Alzheimer’s Coordinating Center. Shapley additive explanation algorithms for feature importance ranking and pairwise correlation analysis were used to identify predictors of disease progression. Four primary disease progression clusters (slow, moderate and rapid converters or non-converters) were subdivided into groups by race and sex, yielding 16 sub-clusters of participants with distinct progression patterns. A multi-head and early-fusion convolutional neural network achieved the most competitive performance and demonstrated superiority over a single-head deep learning architecture and conventional tree-based machine-learning methods, with 97% test accuracy, 96% F1 score and 0.19 root mean square error. From 447 features, 2 sets of 100 predictors of disease progression were extracted. Feature importance ranking, correlation analysis and descriptive statistics further enriched cluster analysis and validation of the heterogeneity of risk factors.

Patterns of loco-regional progression and patient outcomes after definitive-dose radiation therapy for anaplastic thyroid cancer

BackgroundThe aim of this study is to characterize the patterns of loco-regional progression (LRP) and outcomes after definitive-dose intensity modulated radiation therapy (IMRT) for anaplastic thyroid cancer (ATC) with macroscopic neck disease at the time of IMRT. MethodsDisease/treatment characteristics and outcomes for patients with unresected or incompletely resected ATC who received IMRT (≥45 Gy) were retrospectively reviewed. For those with LRP after IMRT, progressive/recurrent gross tumor volumes (rGTV) were contoured on diagnostic CTs and co-registered with initial planning CTs using deformable image registration. rGTVs were classified based on established spatial/dosimetric criteria. ResultsForty patients treated between 2010–2020 formed the cohort. Median IMRT dose was 66 Gy (45–70 Gy); altered fractionation (AF) was used in 24 (60 %). All received concurrent chemotherapy. In addition to areas of gross disease, target volumes (TVs) commonly included: central compartment/upper mediastinum (levels VI/VII), neck levels II-V in an involved, and levels III-IV in an uninvolved lateral neck. Median overall survival was 7.1 m. Median progression free survival was 7.4 m for patients with locoregional disease and 1.8 m for patients with distant metastasis at the time of IMRT. Twenty-one patients (53 %) developed LRP at median of 10.9 m; freedom from LRP at 3 m and 12 m was 71 % (95 %CI 58–87 %) and 47 % (95 %CI 32–68 %). Forty-one individual rGTVs were identified and most occurred within the high dose (HD) TVs: Type A/central HD (n = 29, 71 %) and B/peripheral HD (n = 3, 7 %). ConclusionsDespite an intensive treatment schedule, including AF and concurrent chemotherapy, classic radio-resistant and rapid Type A failures predominated; isolated extraneous dose failures were rare. While these findings support the IMRT and TV delineation strategies described herein, they highlight the importance of identifying novel strategies to further improve LRC for patients with unresectable disease without targetable mutations for contemporary neo-adjuvant strategies.

P179 Lenvatinib plus Pembrolizumab (L+P) vs. Sunitinib (S) in advanced Renal Cell Carcinoma (aRCC): Patterns of progression and subsequent therapy in the CLEAR trial

P179 Lenvatinib plus Pembrolizumab (L+P) vs. Sunitinib (S) in advanced Renal Cell Carcinoma (aRCC): Patterns of progression and subsequent therapy in the CLEAR trial

Latent factors underlying the symptoms of adult-onset myotonic dystrophy type 1 during the clinical course

BackgroundMyotonic dystrophy type 1 (DM1) is a multisystem genetic disorder that classically presents with symptoms associated with myotonia, early onset cataracts, and muscular weakness, although the presentation and pattern of disease progression is quite varied. Presenting symptoms are well documented among adults with DM1. However, less is known about the co-occurrence of symptoms over time. We aimed to use factor analysis to explore the correlation pattern of signs and symptoms (S/S) that emerged during the clinical course.ResultsClinical records of 228 individuals with adult onset DM1 were abstracted using the Muscular Dystrophy Surveillance, Tracking, and Research Network (MD STARnet) from a six-site cohort in the United States during an eight-year study period. Factor analysis was used to group the correlated S/S into latent factors. Three factors were identified. Group 1: ‘Facial Weakness/Myotonia’ includes the two most common S/S, as indicated by its name. Group 2: ‘Skeletal Muscle Weakness’ includes eight muscular S/S and is more frequently reported by males and those with older age at onset. Group 3: ‘Gastrointestinal distress/Sleepiness’ includes four non-muscular S/S and hand stiffness. The abstracted medical records reported that over 63% of individuals had S/S from all three groups. Associations of covariates with factor scores were also examined using linear regression. CTG repeat length was significantly positively associated with higher factor scores for all three factors.ConclusionsThis study identified three latent factors of S/S which accumulated during the clinical course of adult onset DM1.

A Good Diagnosis Saves Lives: The Importance of Teledermatology: Case Report

Chromoblastomycosis (CBM) is one of the most prevalent subcutaneous mycoses, caused by melanized or pigmented fungi. Considered a tropical or subtropical disease, commonly seen in rural areas after traumatic inoculation, mostly associated with agriculture. The lesions tend to present on the limbs and follow a chronic and progressive pattern, which if left untreated or misdiagnosed can lead to loss of functionality and lower quality of life. Teledermatology (TD) has been used mainly to diagnose, monitor and treat patients at distance in neglected areas. Guatemala has a vast rural area and despite the efforts from both private and public sectors, we still cannot reach all the patients and not all the patients can reach us. We present a case report on how with the aid of teledermatology a life was changed for the good.

The Progression of Symptoms in Post COVID-19 Patients: A Multicentre, Prospective, Observational Cohort Study

Background: Although the coronavirus disease 2019 (COVID-19) pandemic is no longer a public health emergency of international concern, 30% of COVID-19 patients still have long-term complaints. A better understanding of the progression of symptoms after COVID-19 is needed to reduce the burden of the post COVID-19 condition. Objective: This study aims to investigate the progression of symptoms, identify patterns of symptom progression, and assess their associations with patient characteristics. Methods: Within the P4O2 COVID-19 study, patients aged 40–65 years were recruited from five Dutch hospitals. At 3–6 and 12–18 months post COVID-19, medical data were collected, and pulmonary function tests were performed. In between, symptoms were assessed monthly with a questionnaire. Latent class mixed modelling was used to identify symptom progression patterns over time, with multinomial logistic regression to examine associations with patient characteristics. Results: Eighty-eight patients (aged 54.4 years, 48.9% males) were included. Three trajectories were identified for fatigue and dyspnoea: decreasing, high persistent, and low persistent. The odds of “decreasing fatigue” was higher for never smokers and participants in the lifestyle intervention and lower for those having a comorbidity. The odds of “decreasing dyspnoea” was higher for moderate COVID-19 patients and lifestyle intervention participants and lower for males, mild COVID-19 patients, and those with a higher age. Conclusions: Three distinct trajectories were identified for fatigue and dyspnoea, delineating patterns of symptom persistence following COVID-19. Sex, age, smoking status, participation in lifestyle interventions and COVID-19 severity were associated with the likelihood of belonging to different trajectories. These findings highlight the heterogeneity of the long-term symptoms experienced by post COVID-19 patients and emphasise the importance of personalised treatment strategies.

Exploring the developmental changes in and the relationship between resilience and anxiety and depression in older gastric cancer survivors: A latent growth mixture model and random intercept cross-lagged panel model analysis.

This study aims to investigate the independent and joint trajectories of resilience, anxiety, and depression symptoms and research the interaction between older gastric cancer survivors' resilience and anxiety-depression during the period of 1 year after surgery. The participants were 381 older gastric cancer survivors, with a mean age of 69 years. Resilience, anxiety, and depression symptoms were assessed immediately after surgery, and at 3, 6, and 12 months post-surgery, respectively. A longitudinal design was employed to capture the dynamic changes in resilience, anxiety, and depression levels among older gastric cancer survivors post-surgery. Latent growth mixture model and random intercept cross-lagged panel model were used to analyse the trajectories of resilience and anxiety-depression and the interaction between them. Two latent trajectories were identified for the resilience, four latent trajectories were identified for the anxiety, and five latent trajectories were identified for the depression, respectively, with three joint trajectories identified: gradual-increasing resilience, gradual-decreasing anxiety, and depression group (10.0%); gradual-decreasing resilience, gradual-increasing anxiety, and depression group (21.2%); and rapid-growth resilience, rapid-decline anxiety, and depression group (68.8%). Resilience among older gastric cancer survivors exhibits significant bidirectional and negative predictive effects on anxiety and depression. Individual differences in resilience, anxiety, and depression trajectories exist among older gastric cancer survivors, with heterogeneous joint progression patterns, and the relationship between resilience and anxiety-depression appears bidirectional. More sophisticated intervention programmes tailored to the unique characteristics of the relevant trajectories are necessary to enhance resilience and mitigate the risk of anxiety and depression.

Development of the Unbiased Disease Network Using Health Insurance Claims Big Data in South Korea

Abstract Background Research on the overall relationship between disease is needed. The disease network model can comprehensively show the complex relationships between diseases and progression patterns. Existing disease network studies were estimated by univariate relative risks. We aim to develop the unbiased disease network. Methods We used NHIS national data of 50 million patients, collected from 2008 to 2022. We used only the primary diagnosis codes (three-digit codes) and defined 603 disease categories based on the special tabulation list for morbidity in the detailed subcategories of ICD-10, prior research, and the frequency of diseases in the dataset. To develop a more unbiased disease network, we first adjusted for age, sex, period, season, and encounter type, then added the confounding disease exposure according to the Directed Acyclic Graph (DAG) and performed Poisson regression to estimate relative risk (RR) applying Inverse Probability Weighting (IPW). We identified statistically significant disease pairs (RR > 1.10, p < 0.001) and repeated the IPW analysis up to the third round because the network would be updated every round. The significant disease pairs identified in the last round were connected to develop the overall network and subnetworks by age and sex. Results We repeated the process up to the third round for all 346,948 disease pairs and fitted 9,024 pairs as significant. We identified general population disease network and subnetwork per age and sex subgroups. Conclusions These disease networks represented the overall progression relationship between diagnosis codes. Key messages • We developed the unbiased disease network that shows progression patterns by adjusting for confounders and using IPW. • The disease network can be used to extract features from various diagnosis codes in EHR/Claims data, analyze causal effects, and predict disease or healthcare usage using RR or graph embedding.

Diffusion capacity and static hyperinflation as markers of disease progression predict 3-year mortality in COPD: Results from COSYCONET.

Chronic obstructive pulmonary disease (COPD) exhibits diverse patterns of disease progression, due to underlying disease activity. We hypothesized that changes in static hyperinflation or KCO % predicted would reveal subgroups with disease progression unidentified by preestablished markers (FEV1, SGRQ, exacerbation history) and associated with unique baseline biomarker profiles. We explored 18-month measures of disease progression associated with 18-54-month mortality, including changes in hyperinflation parameters and transfer factor, in a large German COPD cohort. Analysing data of 1364 patients from the German observational COSYCONET-cohort, disease progression and improvement patterns were assessed for their impact on mortality via Cox hazard regression models. Association of biomarkers and COPD Assessment test items with phenotypes of disease progression or improvement were evaluated using logistic regression and random forest models. Increased risk of 18-54-month mortality was linked to decrease in KCO % predicted (7.5% increments) and FEV1 (20 mL increments), increase in RV/TLC (2% increments) and SGRQ (≥6 points), and an exacerbation grade of 2 at 18 months. Decrease in KCO % predicted ≥7.5% and an increase of RV/TLC ≥2% were the most frequent measures of 18-month disease progression occurring in ~52% and ~46% of patients, respectively. IL-6 and CRP thresholds exhibited significant associations with medium- and long-term disease measures. In a multicentric cohort of COPD, new markers of current disease activity predicted mid-term mortality and could not be anticipated by baseline biomarkers.

Cystitis glandularis: MR imaging characteristics in 27 patients.

To explore the diagnostic characteristics of cystitis glandularis (CG) using magnetic resonance imaging (MRI). A retrospective study was conducted on pathologically confirmed patients who underwent bladder MRI examination between January 2019 and November 2023. Image analysis was jointly conducted, with emphasis on lesion location, morphology, size, signal intensity, and pattern of enhancement, by two genitourinary radiologists with 22 and 15 years of experience, respectively. A total of 27 patients with 27 lesions were included (median age 47 years, 24 males). The lesions were mostly located in the bladder trigone area (18/27). The lesions could be categorized as focal thickening (17/27), nodular (8/27), and diffuse thickening of the entire bladder (2/27) in morphological terms. On T2-weighted imaging (T2WI), 15 of 17 focal thickening lesions appeared as a slightly hyperintense thickened inner layer, with a higher signal in the center of the thickened inner layer, resembling a sandwich sign, and 6 of 8 nodular lesions were slightly hyperintense. On T1-weighted imaging (T1WI), 19 patients showed slight hypointensity. The lesions on DWI showed mainly high (5/27) and slightly high signal (21/27), with an average mean apparent diffusion coefficient (mADC) value of 2.171 ± 0.052 × 10-3mm2/s. Among the 23 patients who underwent dynamic contrast-enhanced (DCE) scanning, 18 lesions showed mild enhancement in the arterial phase (average 1.7 times comparing to unenhanced phase), and the degree of enhancement gradually increased in the venous and delayed phases (average 2.2 and 2.3 times compared to the unenhanced phase, respectively), showing a progressive enhancement pattern. On MRI, the majority of CG manifest as focal thickening or nodules in the bladder trigone area, showing slight hyperintensity on T2WI, slight hypointensity on T1WI, and a progressive enhancement pattern, without significant restriction on DWI. Focal thickening lesions may exhibit a special sandwich sign.