Tool For Disease Assessment Research Articles

Implementation of an algorithm for predicting exacerbations in telemonitoring: A multimethod study of patients’ and clinicians’ experiences

BackgroundPrediction algorithms may improve the ability of telehealth solutions to assess the risk of future exacerbations in patients with chronic obstructive pulmonary disease. Learning from patients’ and clinicians’ evaluations and experiences about the use of such algorithms is essential to evaluate its potential and examine factors that could potentially influence the implementation and sustained use. ObjectiveTo investigate the patients’ and clinicians’ perceptions and satisfaction with an algorithm for predicting exacerbations in patients with chronic obstructive pulmonary disease. DesignMultimethod study. SettingThree community nursing sites in Aalborg Municipality, Denmark. ParticipantsOne hundred and eleven adults with chronic obstructive pulmonary disease and four clinicians (three nurses and one physiotherapist) specialized in telehealth monitoring of the disease. MethodsThe study was performed from November 2021 to November 2022 alongside a clinical trial in which a prediction algorithm was integrated into an existing telehealth system. The patients’ perspectives were investigated using a self-constructed questionnaire. The clinicians’ perspective was explored using semistructured individual interviews. ResultsMost patients (84.0%–90.8%) were satisfied with the algorithm and the additional measurements required by the algorithm. Approximately 71.7%–75.9% found that the algorithm could be a useful tool for disease assessment. Patients elaborated that they could see an exacerbation prevention potential in the algorithm. Patients trusted the algorithm and found an increased sense of security. The clinicians showed a positive response toward the algorithm and its user-friendliness. However, they were concerned that the additional measurements could be too demanding for some patients and questioned the accuracy of the measurements. Some felt that the algorithm could risk being time-consuming and harm the overall assessment of the individual patient. They expressed a need for continuous information about the algorithm to understand its functions and alarms. ConclusionsOptimal use of the algorithm would require that patients perform additional pulse and oxygen saturation measurements. Furthermore, it will require in-depth insight among clinicians regarding the algorithm's functions and alarms. RegistrationThe study was performed alongside a clinical trial, which was first registered September 9, 2021, at clinicaltrials.gov (registration number NCT05218525). Date of first recruitment was September 28, 2021.

Assessing Atherosclerosis by Super-Resolution Imaging of HClO in Foam Cells Using a Ratiometric Fluorescent Probe.

Atherosclerosis (AS) is the leading cause of cardiovascular disease. Foam cells, with elevated lipid droplets (LDs) and HClO levels, are the main components of the atherosclerotic plaques that are characteristic of AS. Super-resolution imaging can be used to visualize the distribution of LDs in foam cells at the nanometer level, facilitating the identification of LDs and HClO. In the present study, we report the development of a ratiometric fluorescent probe, SFL-HClO, for super-resolution imaging of LDs and HClO. Super-resolution imaging with this probe revealed the precise structure of LDs at the suborganelle level. Moreover, the fluorescence behavior of SFL-HClO on the surface of LDs verified its excellent performance in detecting HClO in the foam cells. SFL-HClO can sequentially and specifically respond to LDs and HClO via "turn-on" and ratiometric signal output, respectively, thus contributing to precise imaging of foam cells. Importantly, we demonstrate that SFL-HClO can be used to report on upregulated HClO in atherosclerotic plaques in the aorta of AS mice, providing a suitable fluorescent tool for early atherosclerotic disease assessment.

Disease Activity and Bone Microarchitectural Phenotype in Patients With Axial Spondyloarthritis

Background: Axial spondyloarthritis (AxSpA) is a chronic rheumatic disease characterized by spine inflammation, abnormal bone growth, and paradoxically osteoporosis and vertebral fractures. The pathogenesis of skeletal deficits in this disease is poorly understood. Purpose: We sought to evaluate volumetric bone mineral density (vBMD) and bone microarchitecture in patients with AxSpA and to identify disease-related factors associated with skeletal abnormalities. Methods: We enrolled patients between 2018 and 2021 as part of a 2-year prospective study at a single institution investigating skeletal health and the skeletal effects of interleukin-17 (IL-17) treatment. Patients with AxSpA who met Assessment in SpondyloArthritis International Society (ASAS) classification criteria by X-ray or had evidence of active inflammation on magnetic resonance imaging suggestive of sacroiliitis were referred to the study by their rheumatologists. We excluded those with a history of fragility fracture, multiple myeloma, Cushing’s disease, primary hyperparathyroidism, osteomalacia, untreated vitamin D deficiency, secondary osteoporosis, or other systemic rheumatic diseases, as well as use of oral steroids for 2 or more weeks in the 6 months prior or current use of hormone replacement therapy, current oral bisphosphonate, past or current intravenous bisphosphonate, teriparatide, or denosumab therapies. A total of 1606 patients were screened for eligibility. Of these, 30 participants were enrolled (mean age 43 years, 50% male). Patients with AxSpA had dual-energy X-ray absorptiometry (DXA) measurements of areal BMD (aBMD) and high-resolution peripheral quantitative computed tomography (HR-pQCT) measurements of vBMD microarchitecture and failure load by finite element analysis. Standardized disease assessment tools used included the Bath Ankylosing Spondylitis Disease Activity (BASDAI), Metrology Index (BASMI), and Functional Index (BASFI). Results: In the 30 included patients, mean DXA and HR-pQCT Z-scores were within 1 standard deviation (SD) of normal for all indices, except for total vBMD in males (–1.2 SD below mean). Mean symptom duration was 11.7 years and mean scores for BASDAI, BASFI, and BASMI were 4.6, 3.6, and 2.7, respectively (range 1–10, 10 = severe limitation). Longer disease duration was associated with more severe skeletal deficits at the hip and tibia—specifically, lower hip aBMD, lower meta- and inner-trabecular vBMD, lower trabecular number, and higher trabecular separation and heterogeneity. Conclusion: This study of 30 patients with AxSpA found that abnormalities in bone density and microarchitecture at weightbearing sites were associated with longer disease duration. Because of its small sample size, larger studies are needed to better characterize the pathogenic disease factors that govern skeletal damage in AxSpA.

Circulating tumor DNA as a predictor of treatment response to neoadjuvant chemotherapy in stage 2/3 rectal cancer without high risks: Subset analysis from the COPEC trial.

e15623 Background: Circulating tumor DNA (ctDNA) serves as a valuable tool for minimal residual disease (MRD) assessment. It has been reported as a promising noninvasive biomarker for the dynamic monitoring of treatment response of metastatic colorectal cancers to chemotherapy and locally advanced rectal cancers (LARC) to neoadjuvant chemoradiotherapy. However, the potential role of ctDNA in neoadjuvant chemotherapy (NCT) in LARC remains unexplored. The present study aims to investigate the value of ctDNA in NCT based on a prospective, multicentered, non-inferior, randomized, controlled trial (ClinicalTrials.gov ID, NCT04922853). The COPEC trial enrolls stage 2/3 LARC with low or intermediate and is designed to determine the optimal time (after 2 or 4 cycles of CAPOX) to evaluate treatment response based on pathological regression grades. Methods: Colonoscopy biopsy was taken before neoadjuvant therapy. Peripheral blood samples were collected before neoadjuvant (baseline, BL), one cycle (C1) and two cycles (4-cycle group, C2) after NCT, before surgery (BS), and within one month after surgery (postoperative, OP). All tissue biopsy and plasma specimens were analyzed by NGS assays using the MinerVA platform (Genecast Biotechnology Co., Ltd). MRI tumor regression grade (mrTRG) was assessed after 2 and 4 cycles (4-cycle group) of NCT. The primary outcome was the accuracy of ctDNA in the prediction of pathological tumor regression grade (pTRG). Results: A total of 151 LARC patients were enrolled, including 82 in the 2-cycle group and 69 in the 4-cycle group. The ctDNA was detectable in 87.4% (132/151), 39.6% (55/139), 29.0% (18/62), 38.4% (58/151), and 4.4% (6/138) at BL, C1, C2, BS and OP, respectively. The ctDNApositivity rates were significantly lower in good responders determined by mrTRG (mrTRG 1-3) compared to mrTRG 4-5 group at C1 (29% vs. 63.89%, p < 0.001), C2 (20% vs.56.25%, p = 0.011), and BS time points (23.85% vs. 74.36%, p < 0.001). Furthermore, the ctDNA-positivity rates at C1 in the good response group determined by TRG (pTRG 0-1) were 6.25%, significantly lower than that in the pTRG 2-3 group (49.53%). At neither C2 nor BS time point, patients in the pTRG 0-1 subgroup were detected as ctDNA positive while the ctDNA positivity rates for patients in pTRG 2-3 subgroup were 39.13% and 50%, respectively. Additionally, the mean of hGE/ml was 0.045 in pTRG 0-1 group at C1, significantly lower comparing to 1.337 in pTRG 2-3 group (p < 0.001). Conclusions: We find that dynamic monitoring of ctDNA status was a useful tool in early predicting the effect of (treatment response to) NCT in LARC patients with low/intermediate risks. The monitoring of ctDNA status can supplement MRI in determining the NCT response and could potentially help identify poor responders to discontinue the treatment with inadequate efficacy. Clinical trial information: NCT04922853 .

SWIGH-SCORE: A translational light-weight approach in computational detection of rearranged immunoglobulin heavy chain to be used in monoclonal lymphoproliferative disorders

We present a lightweight tool for clonotyping and measurable residual disease (MRD) assessment in monoclonal lymphoproliferative disorders. It is a translational method that enables computational detection of rearranged immunoglobulin heavy chain gene sequences.•The swigh-score clonotyping tool emphasizes parallelization and applicability across sequencing platforms.•The algorithm is based on an adaptation of the Smith-Waterman algorithm for local alignment of reads generated by 2nd and 3rd generation of sequencers.For method validation, we demonstrate the targeted sequences of immunoglobulin heavy chain genes from diagnostic bone marrow using serial dilutions of CD138+ plasma cells from a patient with multiple myeloma. Sequencing libraries from diagnostic samples were prepared for the three sequencing platforms, Ion S5 (Thermo Fisher Scientific), MiSeq (Illumina), and MinION (Oxford Nanopore), using the LymphoTrack assay. Basic quality filtering was performed, and a Smith-Waterman-based swigh-score algorithm was developed in shell and C for clonotyping and MRD assessment using FASTQ data files. Performance is demonstrated across the three different sequencing platforms.

Management of Ocular Surface Inflammation with Persistent Epithelial Defects Using a Sutureless Human Amniotic Membrane Dehydrated Matrix: A Prospective Study Utilizing a Digital Ocular Surface Assessment Tool.

To report the outcomes of using a sutureless human amniotic membrane dehydrated matrix (HAMDM) in the management of a range of ocular surface conditions utilizing a digital ocular surface disease assessment tool. Two UK NHS Trusts - Queen Victoria Hospital Foundation Trust (East Grinstead and Maidstone) and Tunbridge Wells Trust (Kent) - prospectively treated patients with ocular surface disease with sutureless HAMDM. The patient cohort was assessed for resolution of epithelial defects, ocular surface inflammation, and best-corrected visual acuity pre- and posttreatment. Measurements of ocular surface inflammation and epithelial defect size were assessed using AOS digital imaging software, a validated tool for objective grading of bulbar conjunctival redness and measurement of corneal epithelial defects. A total of 47 applications of sutureless HAMDM on 46 eyes of 46 patients (25 male, 21 female, age 9-94 years) were assessed across various etiologies for an average of 24.0±14.1 days. Patients with limbal stem-cell deficiency (n=17), persistent epithelial defects (n=16), neurotrophic corneal disease (n=7), filamentary keratitis (n=2), corneal erosion (n=1), corneal thinning (n=1), ocular surface inflammation (n=1), and traumatic corneal laceration (n=1) were included in the study. Across all patents, 63% of eyes showed complete healing of epithelial defects and 32.6% of eyes showed partial resolution. The average rate of healing (wound closure) was 0.36 mm2 per day across the overall patient cohort, and the rate of healing in cases with complete resolution of epithelial defects was 0.41 mm2 per day. Inflammation across all four quadrants of the ocular surface remained stable. Visual acuity across the patient cohort remained stable (61%) and improved in 26% of patients (0.06±0.51 logMAR). Sutureless HAMDM application can be accomplished in just a few minutes and effectively treat a range of ocular surface disease in a clinical, nonsurgical setting. The AOS imaging software offered a quantitative methodology for measuring epithelial defect size and inflammation state.

P153 Exploring the relationships between objective and subjective clinical measures in Sjogren's Syndrome

Abstract Background/Aims Patient Reported Outcome Measures (PROMs) are standardised, validated questionnaires designed to measure the patient’s perception of their disease. Discordance between the patient’s perspective and objective clinical measures (clinical scores, laboratory data) has led to increased interest in PROMs in Sjogren’s syndrome (SS). Initial concern about the subjectivity of PROMs has given way to methodological rigour and clear guidance for the development of PROMs. Several studies have now used PROMs for symptom-based stratification, and recently researchers have developed composite disease assessment tools incorporating PROMs and objective clinical measures to create more clinically meaningful endpoints for SS trials. With the advent of PROM-based stratification tools and composite endpoints, it is vital to better understand the relationship between clinical measures in SS. In this project we performed network analysis with data from a large cohort of well-characterised SS patient to improve our understanding of the relationship between objectively measured parameters and PROMs. Methods The UK Primary Sjogren’s Syndrome Registry (UKPSSR) is a nationwide observational cohort of primary SS patients who fulfil the 2002 American European Consensus Group classification criteria. The UKPSSR holds detailed clinical and laboratory data that is collected prospectively, including patient-reported outcomes collected using standardized questionnaires. To assess concordance between clinical measures we used the ARACNE algorithm, which calculates mutual information between the variables of a multidimensional dataset to construct a network of shared information. Statistical analysis was performed in R-v4.1.3 and JMP Pro-v15 and network visualisation in Cytoscape-v3.8.2. Results The ARACNE network highlights key areas of concordance and discordance between PROMs, clinician-based and laboratory-based measurements. Providing assurance to this approach, multi-domain PROMs and ESSDAI (EULAR Sjögren's syndrome disease activity index) subdomains are strongly associated with their component scores and different PROMs measuring the same symptoms were also correlated. In contrast, there is a clear separation between PROMs, clinician-based and laboratory-based measurements each forming their own sub-networks. Furthermore, most laboratory measurements do not have strong relationship with clinician-based disease activity score or PROMs. EQ-5D utility and HADS (Hospital Anxiety and Depression Scale) values provide the primary link between ESSPRI (EULAR Sjogren's Syndrome Patient Reported Index) and ESSDAI subdomain scores and both ESSDAI and ESSPRI are important contributors to quality-of-life. Conclusion The dissociation between PROMs and objective clinical measures is important for clinical management and trial design. Whilst it complicates clinical management of SS including any treat-to-target strategy; it highlights the importance of PROMs in supporting clinician assessment and laboratory measurements to better capture all aspects of SS and give a more individualised, meaningful assessment. Finally, it supports the dual-target strategy of systemically pursuing two targets in the design of clinical trials: one focused on the disease activity and another focused on the symptoms and impact. Disclosure J.S. Berry: None. J. Tarn: None. D. Lendrem: None. J. Casement: None. W. Ng: Consultancies; Expert advice in the area of Sjogren’s syndrome to GlaxoSmithKline, MedImmune, UCB, Abbvie, Roche, Eli Lilly, Takeda, Resolves Therapeutics, Sanofi, Novartis and BMS.

Combined Unet and CNN image classification model for COVID disease detection using CXR/CT imaging

Accurate SARS-CoV-2 screening is made possible by automated Computer-Aided Diagnosis (CAD) which reduces the stress on healthcare systems. Since Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is highly contagious, the transition chain can be broken through an early diagnosis by clinical knowledge and Artificial Intelligence (AI). Manual findings are time and labor-intensive. Even if Reverse Transcription-Polymerase Chain Reaction (RT-PCR) delivers quick findings, Chest X-ray (CXR) imaging is still a more trustworthy tool for disease classification and assessment. Several studies have been conducted using Deep Learning (DL) algorithms for COVID-19 detection. One of the biggest challenges in modernizing healthcare is extracting useful data from high-dimensional, heterogeneous, and complex biological data. Intending to introduce an automated COVID-19 diagnosis model, this paper develops a proficient optimization model that enhances the classification performance with better accuracy. The input images are initially pre-processed with an image filtering approach for noise removal and data augmentation to extend the dataset. Secondly, the images are segmented via U-Net and are given to classification using the Fused U-Net Convolutional Neural Network (FUCNN) model. Here, the performance of U-Net is enhanced through the modified Moth Flame Optimization (MFO) algorithm named Chaotic System-based MFO (CSMFO) by optimizing the weights of U-Net. The significance of the implemented model is confirmed over a comparative evaluation with the state-of-the-art models. Specifically, the proposed CSMFO-FUCNN attained 98.45% of accuracy, 98.63% of sensitivity, 98.98% of specificity, and 98.98% of precision.

Correlation between neutrophil to lymphocyte ratio and disease activity in patients with rheumatoid arthritis.

Objective: To figure out correlation between neutrophils to lymphocyte ratio in rheumatoid arthritis and its relationship with the disease severity. Study Design: Prospective study. Setting: Department of Rheumatology Fauji Foundation Hospital, Rawalpindi, Pakistan. Period: July 1st to December 31st, 2021. Material & Methods: Study population included rheumatoid arthritis patients fulfilling American college for rheumatology criteria. On the basis of disease activity score-28 (DAS-28), the subjects were categorised into active and remission groups. The control group consisted of healthy age and gender matched subjects. Relationship between neutrophils to lymphocytes ratio with disease activity was analyzed. Data was analysed using SPSS 21. Results: 140 patients with RA were evaluated along with 70 healthy control subjects. NLR was higher in active RA (1.99±0.84) as compared to RA with remission (1.76±0.41) and controls (1.77±0.79). p value<0.05 was obtained which was statistically significant. NLR is significantly correlated with CDAI and SDAI (r=0.24, p=0.04 each). CRP and ESR were also significantly higher in active RA patients compared to those in remission (p<0.005 and p<0.00 respectively) and control group. Conclusion: The neutrophil to lymphocyte ratio is a measure derived from a simple blood test. An elevated NLR is often considered an indicator of systemic inflammation. High NLR values may suggest increased inflammation and immune system activation, which are key features of RA. NLR may serve as a less expensive and easily accessible marker to detect inflammation in RA. It can be utilized in future as disease assessment tool.

P388 Eliakim score performance among patients with active Crohn’s disease

Abstract Background Pan-enteric capsule endoscopy [PEC] (PillCam Crohn’s, Medtronic, USA) is a useful tool for disease assessment and monitoring in Crohn’s disease (CD). We have previously demonstrated the reliability and accuracy of Eliakim score (ES) in the assessment of CD-activity among patients with quiescent disease. We aimed to examine the performance of ES among patients who experienced clinical flare, as well as its responsiveness and sensitivity to change during follow-up (≤52weeks). Methods Patients with CD who have been started on biologics were included. They were prospectively followed with clinical visits, biomarkers and PEC at baseline, and after 14 and 52 weeks. At each time-point Crohn’s disease activity index (CDAI), C-reactive protein (CRP) and fecal-calprotectin (FC) levels were collected, and Lewis score (LS) and ES were calculated (independently reviewed by two experienced readers). Inter-class classification (ICC) was used to asses for agreement between readers. Baseline correlations were obtained using the Spearman's correlation. Repeated-measures correlation (RMC) was calculated using the rmcorr package in R (version 3.3-1). William's test was used to assess difference between correlations. Results Seventy-four patients were included (median age of 31.0 [22.5-46.5] years, male–50%). 142 PEC procedures were performed (Baseline– 62, week 14– 58, week 52– 22). Inter-rater agreement between both readers was high for both the LS and ES (ICC of 0.872 [p<0.001] and 0.925 [<0.001], respectively). At baseline, the correlations between FC and ES (r=0.509 [p<0.001]) and FC and LS (r=0.467 [p<0.001]) were comparable (p=0.68). RMC between biomarkers and ES were higher than between biomarkers and LS (CRP: r=0.376 [p=0.005] vs. r=0.204 [p=0.138], FC: r=0.549 [p<0.001] vs. r=0.412 [p=0.003], for ES and LS, [p=0.034/0.021], respectively), while no difference was observed (p=0.77) with regard to CDAI score (r=0.381 [p=0.007] vs. r=0.346 [p=0.015]). Performing sub-group analysis restricted to procedures which were confined to the small bowel (n=88), RMC was numerically higher (p=0.12) between FC and ES (r=0.590 [p=0.001]) than between FC and LS (r=0.470 [p=0.010]). Conclusion ES is a reliable and accurate scoring system in assessing mucosal inflammation in patients with active CD, and might have a higher sensitivity to clinical/inflammatory biomarker changes over time compared to LS.

P921 Maintenance of clinical, biochemical and transmural remission in inflammatory bowel disease patients switching from intravenous to subcutaneous infliximab

Abstract Background Subcutaneous (SC) infliximab (IFX) effectively maintains biochemical, clinical and endoscopic remission in inflammatory bowel disease (IBD) with a comparable safety profile to intravenous (IV) formulation. Transmural healing is considered a desirable long-term treatment endpoint in IBD, especially in Crohn’s disease (CD). Whether switching from intravenous to SC-IFX effectively maintains transmural remission in IBD is still unknown. Methods This is a preliminary report from a prospective multicentre cohort study on IBD patients in clinical and endoscopic remission on IV-IFX treatment switched to SC-IFX. Enrolled patients were followed-up for 12 months, with fecal calprotectin (FC), C-reactive protein (CRP), infliximab trough levels and anti-drug antibodies (ADAs) measured at baseline, at 3, 6 and 12 months. Intestinal ultrasound (IUS) was performed at baseline and every six months. At month 12 a full colonoscopy was performed for mucosal healing assessment. Remission rates and safety profile were subsequently recorded. T-Test and ANOVA for mean comparisons and Kaplan-Meier estimates were used for survival curves. Results 43 IBD patients (69% males) were enrolled, 58% with CD, of whom 52% reported a history of perianal disease. Median disease duration and IFX therapy were 6 (IQR 3-12) and 5 (IQR 2-9) years, respectively. During a median follow-up of 311 (range 122-489) days, clinical remission rate was 98% (Harvey-Bradshaw Index <5 and Mayo score <2). No reactivation of perianal disease was reported. FC and CRP remained stable at each time point (p> 0.05). The median baseline infliximab level was 10.02 ( range 0.1- 41.84) ug/ml. Undetectable infliximab levels (<1 ug/ml) and positive ADAs were found in 6 and 14 patients, respectively; at 3 months, a significant increase in infliximab levels (mean increase 27.5 ng/ml; ± 12.5 SD; p< 0.001) and a progressive decrease of ADAs titer were observed, despite unchanged SC-IFX dose. At baseline, all patients had normal bowel wall thickness (i.e. ileum ≤ 3mm, colon≤4 mm) and a Limberg score ≤1at IUS; reactive lymphadenopathies were reported in 5 patients and a mild abdominal effusion in 1. No significant changes were shown during follow-up. Mild endoscopic activity was found in 2 out 30 patients who performed follow-up endoscopy. Regarding safety profile 12 mild infectious events, 2 mild cutaneous injection site reaction and 1 non-IBD related hospital admission were observed. Conclusion Switching from IV to SC infliximab in a selected cohort of IBD patients confirmed to be safe and effective in maintaining clinical, biochemical, and transmural remission. IUS is a useful, non-invasive and low-cost tool for periodic disease assessment in this subset of patients.

Clinical effects of traditional Chinese herbal medicine management in patients with COVID-19 sequelae: A hospital-based retrospective cohort study in Taiwan.

Introduction: An estimated 43% of COVID-19 patients showed sequelae, including fatigue, neurocognitive impairment, respiratory symptoms, and smell or taste disorders. These sequelae significantly affect an individual's health, work capacity, healthcare systems, and socioeconomic aspects. Traditional Chinese herbal medicine (TCHM) management showed clinical benefits in treating patients with COVID-19 sequelae. This study aimed to analyze the effects of personalized TCHM management in patients with COVID-19 sequelae. Methods: After the COVID-19 outbreak in Taiwan, we recorded Chronic Obstructive Pulmonary Disease Assessment Tool (CAT), Chalder Fatigue Questionnaire (CFQ-11), and Brief Symptom Rating Scale (BSRS-5) to assess post-COVID respiratory, fatigue, and emotional distress symptoms, respectively. In this study, we retrospectively reviewed the medical records between July 2022 and March 2023. We analyzed the effects of TCHM administration after 14- and 28-days of treatment. Results: 47 patients were included in this study. The results demonstrated that personalized TCHM treatment significantly improved the CAT, CFQ-11, and BSRS-5 scores after 14 and 28 days. TCHM alleviated physical and psychological fatigue. In logistic regression analysis, there was no statistically significant differences in the severity of the baseline symptoms and TCHM administration effects concerning the duration since the initial confirmation of COVID-19, sex, age, or dietary preference (non-vegetarian or vegetarian). Conclusions: Our study suggested that personalized TCHM treatment notably reduced fatigue, respiratory and emotional distress symptoms after 14- and 28-days of treatment in patients with COVID-19 sequelae. We propose that TCHM should be considered as an effective intervention for patients with COVID-19 sequelae.

Unraveling the potential clinical utility of circulating tumor DNA detection in colorectal cancer—evaluation in a nationwide Danish cohort

Increasingly, circulating tumor DNA (ctDNA) is proposed as a tool for minimal residual disease (MRD) assessment. Digital PCR (dPCR) offers low analysis costs and turnaround times of less than a day, making it ripe for clinical implementation. Here, we used tumor-informed dPCR for ctDNA detection in a large colorectal cancer (CRC) cohort to evaluate the potential for post-operative risk assessment and serial monitoring, and how the metastatic site may impact ctDNA detection. Additionally, we assessed how altering the ctDNA-calling algorithm could customize performance for different clinical settings. Stage II-III CRC patients (N= 851) treated with a curative intent were recruited. Based on whole-exome sequencing on matched tumor and germline DNA, a mutational target was selected for dPCR analysis. Plasma samples (8 ml) were collected within 60 days after operation and-for a patient subset (n= 246)-every 3-4 months for up to 36 months. Single-target dPCR was used for ctDNA detection. Both post-operative and serial ctDNA detection were prognostic of recurrence [hazard ratio (HR)= 11.3, 95% confidence interval (CI) 7.8-16.4, P < 0.001; HR= 30.7, 95% CI 20.2-46.7, P < 0.001], with a cumulative ctDNA detection rate of 87% at the end of sample collection in recurrence patients. The ctDNA growth rate was prognostic of survival (HR= 2.6, 95% CI 1.5-4.4, P= 0.001). In recurrence patients, post-operative ctDNA detection was challenging for lung metastases (4/21 detected) and peritoneal metastases (2/10 detected). By modifying the cut-off for calling a sample ctDNA positive, we were able to adjust the sensitivity and specificity of our test for different clinical contexts. The presented results from 851 stage II-III CRC patients demonstrate that our personalized dPCR approach effectively detects MRD after operation and shows promise for serial ctDNA detection for recurrence surveillance. The ability to adjust sensitivity and specificity shows exciting potential to customize the ctDNA caller for specific clinical settings.

Occupational exposure to fine particulate matter in the reinforced concrete production and its association with respiratory symptoms and lung function

BackgroundReinforced concrete production is widespread, but little is known about the occupational exposure to fine particulate matter (PM) in such workplaces, including from metalworking and concrete processing. Therefore, the aim was to characterize exposure to fine PM in the typical workplaces of the whole production cycle and to quantify the risk of respiratory symptoms and lung function in a cohort of reinforced concrete parts production industry.MethodsAt a reinforced concrete parts producing facility in Almaty, we collected 50 personal PM2.5 samples from the main exposure sites and the measured mass concentrations using gravimetric method. Workers also completed questionnaires on a detailed working history, respiratory symptoms (chronic obstructive pulmonary disease (COPD) Assessment Tool (CAT)), followed by spirometry. The association of cumulative dose with CAT score and forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) was tested with multiple regression.ResultsThe highest PM2.5 concentrations were found in the concrete-mixing unit (median 1180 µg/m3), followed by metalworking (510 µg/m3), armature workshop (375 µg/m3) and molding site (245 µg/m3), different from the concentrations in the office (29.5 µg/m3), Kruskall-Wallis p < 0.001. Cumulative PM2.5 dose, mg/m3-year (beta 0.10 (95% confidence interval (CI) 0.05; 0.15)) was strongly associated with CAT score, whereas production with FEV1/FVC (beta -4.96 (-8.31; -1.61)), independent of smoking and chronic bronchitis and sex.ConclusionsMixing concrete and metalworks pose the greatest risk for worker’s health in the reinforced concrete production from the inhalational exposure to aerosol, adversely affecting respiratory health.

Oculomotor analysis to assess brain health: preliminary findings from a longitudinal study of multiple sclerosis using novel tablet-based eye-tracking software.

A growing body of evidence supports the link between eye movement anomalies and brain health. Indeed, the oculomotor system is composed of a diverse network of cortical and subcortical structures and circuits that are susceptible to a variety of degenerative processes. Here we show preliminary findings from the baseline measurements of an ongoing longitudinal cohort study in MS participants, designed to determine if disease and cognitive status can be estimated and tracked with high accuracy based on eye movement parameters alone. Using a novel gaze-tracking technology that can reliably and accurately track eye movements with good precision without the need for infrared cameras, using only an iPad Pro embedded camera, we show in this cross-sectional study that several eye movement parameters significantly correlated with clinical outcome measures of interest. Eye movement parameters were extracted from fixation, pro-saccade, anti-saccade, and smooth pursuit visual tasks, whereas the clinical outcome measures were the scores of several disease assessment tools and standard cognitive tests such as the Expanded Disability Status Scale (EDSS), Brief International Cognitive Assessment for MS (BICAMS), the Multiple Sclerosis Functional Composite (MSFC) and the Symbol Digit Modalities Test (SDMT). Furthermore, partial least squares regression analyses show that a small set of oculomotor parameters can explain up to 84% of the variance of the clinical outcome measures. Taken together, these findings not only replicate previously known associations between eye movement parameters and clinical scores, this time using a novel mobile-based technology, but also the notion that interrogating the oculomotor system with a novel eye-tracking technology can inform us of disease severity, as well as the cognitive status of MS participants.

E33 Identifying and understanding JDM in Africa: a survey of rheumatology care providers from Africa

Abstract Background It is estimated that millions of children in Africa suffer from pediatric rheumatic diseases (PRD). Despite this, as of 2021, there were just 28 pediatric rheumatologists in only 10 of the 54 African countries. With ∼700 million children living in Africa, this number falls far short of the recommended minimum 1750 pediatric rheumatologists needed for ideal care. Rheumatic and musculoskeletal diseases are the second leading cause of disability globally. However, there is a paucity of data on PRD in low and middle-income countries (LMIC) due to limited diagnostic capacities, scarcity of pediatric rheumatologists, and limited awareness of PRD. We have much to learn about the prevalence of PRD as well as clinical manifestations, optimal treatments, and outcomes in African children with PRD. Juvenile dermatomyositis (JDM) can cause significant morbidity and irreversible damage when inadequately treated, resulting in medical, social, and economic burden on patients, families, and healthcare systems, particularly in LMIC. The few studies of JDM in Africa suggest high rates of severe manifestations, including calcinosis, vasculitis, and pulmonary involvement. The objective of this survey is to better understand the scope of JDM burden in Africa by obtaining an overview of JDM and comparing this to data in previously published work. Methods A survey was distributed to members of the African League of Associations for Rheumatology (AFLAR; n = 233) and Paediatric Society of the African League Against Rheumatism (PAFLAR; n = 130) via WhatsApp groups. Respondents were queried about the total number of JDM patients seen currently or within the last 10 years; morbidities and clinical outcomes, including calcinosis, interstitial lung disease (ILD), clinically inactive disease, remission, and death; and availability and accessibility of diagnostic tools and medications. Results A total of 43 (12%) individuals started the survey, with 4 (9%) partially and 16 (37%) fully completing it, describing 216 JDM patients. One general pediatrician participated; the remainder were adult (n = 10; 50%), pediatric (n = 7; 35%), or adult/pediatric (n = 2; 10%) rheumatologists. Respondents represented the 5 regions of Africa, primarily Northern Africa (n = 12; 60%). Mortality was reported at 14% and 29% in Kenya and Zambia, respectively (Table 1). Many respondents identified limited availability of medications (56%), unfamiliarity with JDM by caregivers (69%) and other medical providers (44%), and delayed presentation to care (75%). Access and/or cost limited use of diagnostic tools and medications. Of the 27 queried diagnostic tools and medications, 13 were reported to be accessible to only 50% or fewer of respondents, the majority (69%) of whom were from Northern or Southern African countries. Despite the lack of cost or other apparent access barriers, disease assessment tools are used by only 53% of respondents. Conclusion This is the first study to explore JDM on a broad scale across the African continent. We identified 216 African children with JDM within the past 10 years, exceeding the previously published reports of 196 JDM patients seen in the last 25 years and likely still underestimating prevalence. Our results suggest substantially higher rates of severe disease, with mortality rates in some countries vastly different from the 1–3% reported in high-income countries. Many respondents were limited in their capacity to diagnose and treat JDM, but there was a wide range across African regions that seemed to parallel known disparities in healthcare resource availability in Africa. This survey highlighted important possible differences in disease manifestations and outcomes that warrant further study. Future collaboration with our African colleagues is critical to raise awareness of JDM to ultimately improve disease severity and outcomes. Ethics Institutional review board approval was obtained with waiver of informed consent.

Use of disease assessment tools to increase the value of case reports on Susac syndrome: two case reports

BackgroundSusac syndrome is an immune-mediated, ischemia-producing, occlusive microvascular endotheliopathy that threatens the brain, retina, and inner ear. There is a need for disease assessment tools that can help clinicians and patients to more easily, accurately, and uniformly track the clinical course and outcome of Susac syndrome. Ideally, such tools should simultaneously facilitate the clinical care and study of Susac syndrome and improve the value of future case reports. To meet this need, two novel clinical assessment tools were developed: the Susac Symptoms Form and the Susac Disease Damage Score. The former is a comprehensive self-report form that is completed by patients/families to serially document the clinical status of a patient. The latter documents the extent of damage perceived by individual patients/families and their physicians. Both forms were initially trialed with two particularly representative and instructive patients. The results of this trial are shared in this report.Case presentationPatient 1 is a 21-year-old Caucasian female who presented with an acute onset of headache, paresthesias, cognitive dysfunction, and emotional lability. Patient 2 is a 14-year-old Caucasian female who presented with an acute onset of headache, cognitive dysfunction, urinary incontinence, ataxia, and personality change. Both patients fulfilled criteria for a definite diagnosis of Susac syndrome: both eventually developed brain, retinal, and inner ear involvement, and both had typical “snowball lesions” on magnetic resonance imaging. The Susac Symptoms Form documented initial improvement in both patients, was sufficiently sensitive in detecting a subsequent relapse in the second patient, and succinctly documented the long-term clinical course in both patients. The Disease Damage Score documented minimal disease damage in the first patient and more significant damage in the second.ConclusionsThe Susac Symptoms Form and the Disease Damage Score are useful disease assessment tools, both for clinical care and research purposes. Their use could enhance the value of future case reports on Susac syndrome and could improve opportunities to learn from a series of such reports.

Abstract 2306: Potential clinical utility of circulating tumor DNA detected by digital PCR in a nationwide Danish cohort of high-risk colorectal cancer patients

Abstract Introduction: Increasingly, circulating tumor DNA (ctDNA) is proposed as a tool for minimal residual disease (MRD) assessment, with the potential to guide postoperative treatment decisions. Low ctDNA levels immediately after surgery necessitate extremely sensitive detection methods. Additionally, for potential clinical implementation, detection methods should ideally feature short turnaround times (TATs) and low analysis costs. Compared to sequencing-based detection methods, digital PCR is low-cost, and features TATs of less than a day. Consequently, digital PCR is a good candidate for clinical implementation. Here, we present ctDNA detection results from a highly optimized, tumor-informed digital PCR strategy in a large cohort of stage II-III colorectal cancer (CRC) patients. Methods: Stage II-III CRC patients (n=864) treated with curative intent were recruited from Danish surgical centers from 2014 to 2021. Whole exome sequencing was conducted on matched tumor and buffy coat from all patients. After thorough clonality assessment, a mutational target was chosen for digital PCR analysis. Plasma samples (8mL) collected before and within 60 days after surgery, were investigated for ctDNA using digital PCR. Additionally, a subset of patients (n=229) had serial samples collected every three months analyzed for ctDNA. Results: Before surgery, ctDNA was detected in 569/828 (69%) analyzed blood samples. A minimum of 12 months of radiological follow-up was available for 598/864 patients at time of writing, enabling prognostic evaluation of ctDNA detection in these patients. Postoperative ctDNA detection was highly correlated to future recurrence (HR=9.6, 95%CI 6.3-15, P&amp;lt;0.001). The median time to recurrence was significantly shorter for postoperatively ctDNA positive patients (10 months, interquartile range (IQR) 3.8-12 months) compared to ctDNA negative patients (18 months, IQR 12-26 months, P&amp;lt;0.001), indicating a higher disease burden postoperatively in ctDNA positive patients. In a subset of patients with samples collected immediately after adjuvant treatment (n=95) and serially (n=186), ctDNA was also prognostic of recurrence (HR=6.4, CI95% 2.9-14, P&amp;lt;0.001; HR=27, 95%CI 14-52, P&amp;lt;0.001). A minimum of 12 months of follow-up is expected to be available for 700 patients before the AACR meeting 2023. Conclusion: These results from one of the largest ctDNA detection cohorts of stage II-III CRC patients demonstrate that our personalized digital PCR approach effectively detects MRD immediately after surgery. Additionally, our approach shows promise for serial ctDNA detection for recurrence surveillance applications. With digital PCR being a widespread and cost-effective method with low TATs, clinical implementation of ctDNA analysis may be more forthright using this method over cost-intensive sequencing-based methods. Citation Format: Tenna V. Henriksen, Christina Demuth, Amanda Frydendahl, Marijana Nesic, Mads H. Rasmussen, Thomas Reinert, Ole H. Larsen, Anders H. Madsen, Uffe S. Løve, Per V. Andersen, Ole Thorlacius-Ussing, Ismail Gögenur, Jakob Lykke, Allan G. Pedersen, Peter Bondeven, Nis H. Schlesinger, Lene H. Iversen, Kåre A. Gotschalck, Claus L. Andersen. Potential clinical utility of circulating tumor DNA detected by digital PCR in a nationwide Danish cohort of high-risk colorectal cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2306.

An All-in-One Tool for 2D Atherosclerotic Disease Assessment and 3D Coronary Artery Reconstruction.

Diagnosis of coronary artery disease is mainly based on invasive imaging modalities such as X-ray angiography, intravascular ultrasound (IVUS) and optical coherence tomography (OCT). Computed tomography coronary angiography (CTCA) is also used as a non-invasive imaging alternative. In this work, we present a novel and unique tool for 3D coronary artery reconstruction and plaque characterization using the abovementioned imaging modalities or their combination. In particular, image processing and deep learning algorithms were employed and validated for the lumen and adventitia borders and plaque characterization at the IVUS and OCT frames. Strut detection is also achieved from the OCT images. Quantitative analysis of the X-ray angiography enables the 3D reconstruction of the lumen geometry and arterial centerline extraction. The fusion of the generated centerline with the results of the OCT or IVUS analysis enables hybrid coronary artery 3D reconstruction, including the plaques and the stent geometry. CTCA image processing using a 3D level set approach allows the reconstruction of the coronary arterial tree, the calcified and non-calcified plaques as well as the detection of the stent location. The modules of the tool were evaluated for efficiency with over 90% agreement of the 3D models with the manual annotations, while a usability assessment using external evaluators demonstrated high usability resulting in a mean System Usability Scale (SUS) score equal to 0.89, classifying the tool as "excellent".

Statistical and topological summaries aid disease detection for segmented retinal vascular images.

Disease complications can alter vascular network morphology and disrupt tissue functioning. Microvascular diseases of the retina are assessed by visual inspection of retinal images, but this can be challenging when diseases exhibit silent symptoms or patients cannot attend in-person meetings. We examine the performance of machine learning algorithms in detecting microvascular disease when trained on statistical and topological summaries of segmented retinal vascular images. We compute 13 separate descriptor vectors (5 statistical, 8 topological) to summarize the morphology of retinal vessel segmentation images and train support vector machines to predict each image's disease classification from the summary vectors. We assess the performance of each descriptor vector, using five-fold cross validation to estimate their accuracy. We apply these methods to four datasets that were assembled from four existing data repositories; three datasets contain segmented retinal vascular images from one of the repositories, whereas the fourth "All" dataset combines images from four repositories. Among the 13 total descriptor vectors considered, either a statistical Box-counting descriptor vector or a topological Flooding descriptor vector achieves the highest accuracy levels. On the combined "All" dataset, the Box-counting vector outperforms all other descriptors, including the topological Flooding vector which is sensitive to differences in the annotation styles between the different datasets. Our work represents a first step to establishing which computational methods are most suitable for identifying microvascular disease and assessing their current limitations. These methods could be incorporated into automated disease assessment tools.